No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Dynamic causal modeling suggests serial processing of tactile vibratory stimuli in the human somatosensory cortex—An fMRI study
Abstract
Sensitivity to location and frequency of tactile stimuli is a characterizing feature of human primary (S1), and secondary (S2) somatosensory cortices. Recent evidence suggests that S1 is predominantly receptive to stimulus location, while S2 is attuned to stimulus frequency. Although it is well established in humans that tactile frequency information is relayed serially from S1 to S2, a recent study, using functional magnetic resonance imaging (fMRI) in combination with dynamic causal modeling (DCM), suggested that somatosensory inputs are processed in parallel in S1 and S2. In the present fMRI/DCM study, we revisited this controversy and investigated the specialization of the human somatosensory cortical areas with regard to tactile stimulus representations, as well as their effective connectivity. During brain imaging, 14 participants performed a somatosensory discrimination task on vibrotactile stimuli. Importantly, the model space for DCM was chosen to allow for direct inference on the question of interest by systematically varying the information transmission from pure parallel to pure serial implementations. Bayesian model comparison on the level of model families strongly favors a serial, instead of a parallel processing route for tactile stimulus information along the somatosensory pathway. Our fMRI/DCM data thus support previous suggestions of a sequential information transmission from S1 to S2 in humans.
... Animal studies using electrophysiological and anatomical tracing approaches found extensive cortico-cortical projections between SI and SII (Burton and Carlson, 1986;Friedman et al., 1980;Pons and Kaas, 1986). In humans, a small number of studies using dynamic causal modeling (DCM) with functional magnetic resonance imaging (fMRI) data have suggested that both innocuous and noxious tactile stimuli are processed in serial mode (from SI to SII) (Kalberlah et al., 2013;Khoshnejad et al., 2014). In contrast, the parallel processing theory proposes that somatosensory stimulation is directly transmitted to both contralateral SI and SII. ...
... The pneumotactile stimuli are received through the cutaneous mechanoreceptors in the facial skin to the brainstem and then to the thalamus. Our DCM results provide strong evidence for a network able to parallel process of low velocity (5 cm/s) orofacial pneumotactile stimuli, which is in agreement with some studies (Klingner et al., 2015;Liang et al., 2011;Song et al., 2021) and also contrasts other findings (Disbrow et al., 2001;Kalberlah et al., 2013;Khoshnejad et al., 2014). Liang et al. has reported that non-nociceptive and nociceptive somatosensory inputs (electrical pulses to the right ankle that activate all subpopulation of fast-conducting myelinated Aβ fibers) are processed in parallel from the thalamus to Fig. 6. ...
... The present study used pneumotactile stimuli to the right lower face area and found parallel processing of orofacial pneumotactile stimuli using DCM, which has not been reported previously. Contrary to our findings, two DCM studies supported serial processing from the contralateral SI to SII in response to innocuous and noxious electrical stimuli to the right sural nerve (Khoshnejad et al., 2014), as well as tactile vibratory stimuli to the left middle and index fingers (Kalberlah et al., 2013). The contradicting findings could result from various experimental settings (i.e., electrical versus tactile vibratory stimuli, stimulation to fingers/medial nerve versus foot/ankle). ...
The effective connectivity of neuronal networks during orofacial pneumotactile stimulation with different velocities is still unknown. The present study aims to characterize the effectivity connectivity elicited by three different saltatory velocities (5, 25, and 65 cm/s) over the lower face using dynamic causal modeling on functional magnetic resonance imaging data of twenty neurotypical adults. Our results revealed the contralateral SI and SII as the most likely sources of the driving inputs within the sensorimotor network for the pneumotactile stimuli, suggesting parallel processing of the orofacial pneumotactile stimuli. The 25 cm/s pneumotactile stimuli modulated forward interhemispheric connection from the contralateral SII to the ipsilateral SII, suggesting a serial interhemispheric connection between the bilateral SII. Moreover, the velocity pneumotactile stimuli influenced the contralateral M1 through contralateral SI and SII, indicating that passive pneumotactile stimulation may positively impact motor function rehabilitation. Furthermore, the medium velocity 25 cm/s pneumotactile stimuli modulated both forward and backward connections between the right cerebellar lobule VI and the contralateral left SI and M1. This result suggests that the right cerebellar lobule VI plays a role in the sensorimotor network through feedforward and feedback neuronal pathways. This study is the first to map similarities and differences of effective connectivity across the three-velocity orofacial pneumotactile stimulation. Our findings shed light on the potential therapeutic use of passive orofacial pneumotactile stimuli using the Galileo system.
... These MRI-based studies provide an essential theoretical basis for decoding tactile processing. However, investigating tactile processing from the time-series dimension, such as serial processing model, 21,22 is relatively tricky due to fMRI's low temporal resolution. ...
... In neurophysiology, the serial processing model is the commonly believed model of tactile processing, which as follows 21,22 : (1) When the peripheral nerve receives tactile stimulation, it produces action potentials encoded tactile information, transmitted along the sensory nerves to the thalamus; (2) the bulk of the tactile information from thalamocortical was preliminarily integrated and identified in SI, 53,54 initially identify the location of tactile stimulation, 22 the type of tactile stimulation, 55 the vibration frequency of tactile stimulation, 56,57 and prepares for the extraction of higher-order features 58 ; ...
... In neurophysiology, the serial processing model is the commonly believed model of tactile processing, which as follows 21,22 : (1) When the peripheral nerve receives tactile stimulation, it produces action potentials encoded tactile information, transmitted along the sensory nerves to the thalamus; (2) the bulk of the tactile information from thalamocortical was preliminarily integrated and identified in SI, 53,54 initially identify the location of tactile stimulation, 22 the type of tactile stimulation, 55 the vibration frequency of tactile stimulation, 56,57 and prepares for the extraction of higher-order features 58 ; ...
Humans obtain characteristic information such as texture and weight of external objects, relying on the brain's integration and classification of tactile information; however, the decoding mechanism of multi-level tactile information is relatively elusive from the temporal sequence. In this paper, nonvariant frequency, along with the variant pulse width of electrotactile stimulus, was performed to generate multi-level pressure sensation. Event-related potentials (ERPs) were measured to investigate the mechanism of whole temporal tactile processing. Five ERP components, containing P100-N140-P200-N200-P300, were observed. By establishing the relationship between stimulation parameters and ERP component amplitudes, we found the following: (1) P200 is the most significant component for distinguishing multi-level tactile sensations; (2) P300 is correlated well with the subjective judgment of tactile sensation. The temporal sequence of brain topographies was implemented to clarify the spatiotemporal characteristics of the tactile process, which conformed to the serial processing model in neurophysiology and cortical network response area described by fMRI. Our results can help further clarify the mechanism of tactile sequential processing, which can be applied to improve the tactile BCI performance, sensory enhancement, and clinical diagnosis for doctors to evaluate the tactile process disorders by examining the temporal ERP components.
... Animal studies using electrophysiological and anatomical tracing approaches found extensive corticocortical projections between SI and SII (Burton & Carlson, 1986;Friedman, Jones, & Burton, 1980;Pons & Kaas, 1986). In humans, a small number of studies using dynamic causal modeling (DCM) with functional magnetic resonance imaging (fMRI) data have suggested that both innocuous and noxious tactile stimuli are processed in serial mode (from SI to SII) (Kalberlah, Villringer, & Pleger, 2013;Khoshnejad, Piché, Saleh, Duncan, & Rainville, 2014). In contrast, the parallel processing theory proposes that somatosensory stimulation is directly transmitted to both contralateral SI and SII. ...
... The pneumotactile stimuli are received through the cutaneous mechanoreceptors in the facial skin to the brain stem and then to the thalamus. Our DCM results provide strong evidence for a network able to parallel process of low velocity (5 cm/s) orofacial pneumotactile stimuli, which is in agreement with some studies (Klingner et al., 2015;Liang et al., 2011;Song et al., 2021) and also contrasts other findings (Disbrow et al., 2001;Kalberlah et al., 2013;Khoshnejad et al., 2014). Liang et al. has reported that non-nociceptive and nociceptive somatosensory inputs (electrical pulses to the right ankle that activate all subpopulation of fast-conducting myelinated Aß fibers) are processed in parallel from the thalamus to S1 and from the thalamus to S2 using DCM of fMRI data (Liang et al., 2011). ...
... The copyright holder for this preprint (which this version posted April 14, 2021. ; findings, two DCM studies supported serial processing from the contralateral SI to SII in response to innocuous and noxious electrical stimuli to the right sural nerve (Khoshnejad et al., 2014), as well as tactile vibratory stimuli to the left middle and index fingers (Kalberlah et al., 2013). The contradicting findings could result from various experimental settings (i.e., electrical versus tactile vibratory stimuli, stimulation to fingers/medial nerve versus foot/ankle). ...
The effective connectivity of neuronal networks during orofacial pneumotactile stimulation with different velocities is still unknown. The present study aims to characterize the effectivity connectivity elicited by three different saltatory velocities (5, 25, and 65 cm/s) over the lower face using dynamic causal modeling on functional magnetic resonance imaging data of twenty neurotypical adults. Our results revealed the contralateral SI and SII as the most likely sources of the driving inputs within the sensorimotor network for the pneumotactile stimuli, suggesting parallel processing of the orofacial pneumotactile stimuli. The 25 cm/s pneumotactile stimuli modulated forward interhemispheric connection from the contralateral SII to the ipsilateral SII, suggesting a serial interhemispheric connection between the bilateral SII. Moreover, the velocity pneumotactile stimuli influenced the contralateral M1 through both contralateral SI and SII, indicating that passive pneumotactile stimulation may positively impact motor function rehabilitation. Furthermore, the slow velocity 5 cm/s pneumotactile stimuli modulated both forward and backward connections between the right cerebellar lobule VI and the contralateral left SI, SII, and M1, while the medium velocity 25 cm/s pneumotactile stimuli modulated both forward and backward connections between the right cerebellar lobule VI and the contralateral left SI and M1. Our findings suggest that the right cerebellar lobule VI plays a role in the sensorimotor network through feedforward and feedback neuronal pathways.
... This is because adolescents seem to encounter problems while integrating motor and tactile information whenever the sensory information is processed via SI (Bodmer et al., 2018). Areas SI and SII differ in the kind of vibro-tactile stimulus features being processed (Chung et al., 2013;Francis et al., 2000;Hämäläinen, Kekoni, Sams, Reinikainen, & Näätänen, 1990;Harrington & Hunter Downs III, 2001;Kalberlah, Villringer, & Pleger, 2013). Especially the SII region has been shown to encode more cognitive aspects of tactile processing like modulations with attention, discrimination learning and stimuli comparisons (Ackerley & Kavounoudias, 2015). ...
... In the SI condition, a low frequency known to predominantly activate the SI cortex (Chung et al., 2013;Francis et al., 2000;Harrington & Hunter Downs III, 2001) was used as Nogo stimulus whereas a high frequency served as Go stimulus. In the SII condition, a high frequency stimulus known to be processed in the SII cortical area (Chung et al., 2013;Francis et al., 2000;Hämäläinen et al., 1990;Harrington & Hunter Downs III, 2001;Kalberlah et al., 2013) constituted the Nogo stimulus and the low frequency the Go stimulus. In the SI condition, 150 Hz vibration of 100 ms duration served as Go stimulus and the 40 Hz of equal duration as Nogo stimulus. ...
... 40 Hz was chosen since it is not the upper limit of this approximated range but produces sufficient vibratory sensation in the short 100 ms period. The high 150 Hz frequency is in the range from 100 to 400 Hz which is assumed to predominantly activate the SII cortex (Chung et al., 2013;Francis et al., 2000;Hämäläinen et al., 1990;Harrington & Hunter Downs III, 2001;Kalberlah et al., 2013). The short 100 ms stimulation duration was chosen to produce a strong reaction tendency making it more difficult to withhold responses. ...
We ask whether actions of the norepinephrine (NE) system during response inhibition are affected by properties of lower level sensory stimulus processing. We used a somato-sensory Go/Nogo task and combined ERP recordings with pupil diameter recordings as an index of NE system activity. The Go/Nogo task was designed to achieve processing of tactile stimuli predominantly over primary somatosensory (SI) and secondary somatosensory (SII) areas. The data show that response inhibition was better when stimuli were processed via SII, compared to SI areas. This was reflected by variations in the Nogo-N2/P3 associated with anterior cingulate structures. Correlations with the pupil diameter data, indicting modulations of the NE system during inhibitory control processes, were only evident when SI sensory areas were involved. These dissociable modulatory effects were associated with activations in the superior frontal gyrus. Actions of the NE system during response inhibition are modulated by properties of lower level processing.
... The visual cortex, however, merely exhibits indirect pathways to target frontal regions involved in response inhibition via areas in the parietal cortex (Hagmann et al., 2008). The primary and secondary somatosensory cortices are connected with inferior as well as motor areas of the frontal cortex (Kaas, 1993;Yeterian et al., 2012;Kalberlah et al., 2013;Borich et al., 2015). ...
... Different frequencies of 40 and 150 Hz (100 ms duration) were used for GO and NO-GO stimuli in order to distinguish them clearly. As frequencies in the range from 10 to 50 Hz have been demonstrated to be predominantly processed in the primary sensory cortex (Hämäläinen et al., 1990;Francis et al., 2000;Chung et al., 2013) and frequencies ranging from 100 to 400 Hz in the secondary somatosensory cortex (Hämäläinen et al., 1990;Francis et al., 2000;Kalberlah et al., 2013) both frequencies were used as GO or NO-GO stimuli. This means that whether the slow or the fast frequency constituted the GO or NO-GO stimuli was counterbalanced across experimental blocks. ...
... SMA) and somatosensory association cortices (Fang et al., 2005;Borich et al., 2015). Moreover, the primary and secondary somatosensory cortices form connections with inferior and motor regions of the frontal cortex (Kaas, 1993;Yeterian et al., 2012;Kalberlah et al., 2013;Borich et al., 2015). Interestingly, the visual modality is lacking such a straight connection to functional neuroanatomical structures crucial for inhibitory processes. ...
Response inhibition is a central aspect of cognitive control. Usually, response inhibition is examined using information from a single sensory modality. Yet, evidence suggests that conflicts between information from different modalities affect response inhibition. It is, however, crucial to consider that there are modality differences in the efficiency to trigger response inhibition that may also modulate the impact of conflicts between different sensory modalities. In the current study, we compared an auditory-tactile to an auditory-visual Go/Nogo task. We recorded EEG data and performed signal decomposition and source localization. On the behavioral level, we show stronger interference effects in the visual than the tactile modality. Despite sensory processes were experimentally varied, temporally decomposed EEG data show that response selection mechanisms are associated with these effects and not the sensory processing stage. These modulations of response selection processes occur in the temporo-parietal junction (TPJ, BA40) and inferior frontal structures (IFG, BA47). The smaller activity in the TPJ during auditory-tactile, compared to auditory-visual conflicts suggests that task representations are less affected by interfering auditory information when the tactile modality informs response inhibition processes. This also explains why less intense braking processes (reflected by IFG activity) are still able to maintain a reasonable response inhibition performance level. It can be concluded that the tactile and visual domains do not only differ in regard to their efficiency to trigger response inhibition processes but also in their susceptibility to interference while informing inhibitory control. Clinical implications are discussed.
... Classically, the contralateral primary somatosensory cortex (SI), bilateral secondary somatosensory areas (SII) and the contralateral posterior parietal cortex (PPC) are activated by tactile stimuli (Penfield and Boldrey 1937;Rasmussen and Penfield 1947;Disbrow et al. 2000;Francis et al. 2000;Ackerley et al. 2012). The SI can be subdivided into different Brodmann areas (BAs), i.e., 3a, 3b, 1 and 2. Both SI and SII areas have been shown to be directly connected to the inferior and orbitofrontal areas (Yeterian et al. 2012) and motor areas of the frontal lobe (Kaas 1993;Kalberlah et al. 2013;Borich et al. 2015), but the SI area shows more and straighter connections to the prefrontal areas (Kaas 1993). Since somatosensory cortices and the SI, in particular, show close and strong neuroanatomical connections to motor cortices (Luppino et al. 1993;Fang et al. 2005;Borich et al. 2015), the tactile modality has been shown to be more powerful to control the execution and inhibition of motor responses than the visual modality (Bodmer and Beste 2017). ...
... There has been a long debate on whether tactile stimuli are processed serially from SI to SII or in parallel, but in humans and other primates there is strong evidence that parallel connections exist (Ackerley and Kavounoudias 2015). Interestingly, SI and SII differ with regard to the processing of vibrotactile stimuli: while the SI rather processes slow-frequency vibratory stimuli (Francis et al. 2000;Harrington and Hunter Downs 2001;Chung et al. 2013), the SII seems to be predominantly engaged in highfrequency vibratory stimuli (Chung et al. 2013;Francis et al. 2000;Hämäläinen et al. 1990;Harrington and Hunter Downs 2001;Kalberlah et al. 2013). Besides differences in stimulus features that are predominantly processed in SI or SII, the SII region has moreover been shown to encode cognitive aspects of tactile processing (Ackerley and Kavounoudias 2015) being also important for behavioral decisions (Romo et al. 2002a, b). ...
... However, opposed to the SII area, it is already known that SI shows more and straighter connections to motor areas (Borich et al. 2015), which makes it possible that the SI is particularly potent to modulate inhibitory control over motor responses. Moreover, aside strong connections to motor areas, there are strong connections to areas in the inferior and orbital frontal cortex (Kaas 1993;Yeterian et al. 2012;Kalberlah et al. 2013;Borich et al. 2015). Since these latter prefrontal cortical areas belong to a network important in inhibitory motor control (Aron et al. 2004(Aron et al. , 2014Bari and Robbins 2013), they may be modulated by variations of sensory processing between the SI and SII areas. ...
Sensorimotor integration is essential for successful motor control and the somatosensory modality has been shown to have strong effects on the execution of motor plans. The primary (SI) and the secondary somatosensory (SII) cortices are known to differ in their neuroanatomical connections to prefrontal areas, as well as in their involvement to encode cognitive aspects of tactile processing. Here we ask whether the area specific processing architecture or the structural neuroanatomical connections with prefrontal areas determine the efficacy of sensorimotor integration processes for motor control. In a system neurophysiological study including EEG signal decomposition (i.e. residue iteration decomposition, RIDE) and source localization we investigated this question using vibro-tactile stimuli optimized for SI or SII processing. The behavioral data shows that when being triggered via the SI area, inhibitory control of motor processes is stronger as when being triggered via the SII area. On a neurophysiological level, these effects were reflected in the C-cluster as the result of a temporal decomposition of EEG data, indicating that the sensory processes affecting motor inhibition modulate the response selection level. These modulations were associated with a stronger activation of the right inferior frontal gyrus (rIFG) extending to the right middle frontal gyrus (rMFG) as parts of a network known to be involved in inhibitory motor control when response inhibition is triggered over SI. In addition, areas important for sensorimotor integration like the postcentral gyrus and superior parietal cortex (BA7) showed activation differences. The data suggests that connection patterns are more important for sensorimotor integration and control than the more restricted area-specific processing architecture.
... However, these studies reached different conclusions regarding whether somatosensory information is processed in parallel or in series. Two of these studies reported evidence supporting parallel processing of somatosensory information (Liang et al., 2011;Chung et al., 2014), while the other two studies reported evidence supporting serial processing of somatosensory information (Kalberlah et al., 2013;Khoshnejad et al., 2014). A recent study that applied DCM analysis to magnetoencephalographic (MEG) data suggested that somatosensory data are processed in parallel during the early stage (within the first 100 ms; Klingner et al., 2015). ...
... We used a DCM analysis to clarify whether somatosensory information is processed in parallel (directly entering the SII; Liang et al., 2011;Chung et al., 2014) or in series (entering only the SI and then further transmitted from the SI to the SII; Kalberlah et al., 2013;Khoshnejad et al., 2014). Specifically, we were interested in whether the processing route of somatosensory information changes over time. ...
... The current observation of a change in the processing mode may explain recent conflicting results from fMRI-DCM analyses (Liang et al., 2011;Kalberlah et al., 2013;Chung et al., 2014;Khoshnejad et al., 2014). The parallel processing of information should be found to be the prominent mode based on analyses that focus mainly on the perception of a change in the somatosensory environment, e.g., analyses based on data acquired shortly after stimulus onset or perhaps based on the use of only stimuli. ...
The question regarding whether somatosensory inputs are processed in parallel or in series has not been clearly answered. Several studies that have applied dynamic causal modeling (DCM) to fMRI data have arrived at seemingly divergent conclusions. However, these divergent results could be explained by the hypothesis that the processing route of somatosensory information changes with time. Specifically, we suggest that somatosensory stimuli are processed in parallel only during the early stage, whereas the processing is later dominated by serial processing. This hypothesis was revisited in the present study based on fMRI analyses of tactile stimuli and the application of DCM to magnetoencephalographic (MEG) data collected during sustained (260 ms) tactile stimulation. Bayesian model comparisons were used to infer the processing stream. We demonstrated that the favored processing stream changes over time. We found that the neural activity elicited in the first 100 ms following somatosensory stimuli is best explained by models that support a parallel processing route, whereas a serial processing route is subsequently favored. These results suggest that the secondary somatosensory area (SII) receives information regarding a new stimulus in parallel with the primary somatosensory area (SI), whereas later processing in the SII is dominated by the preprocessed input from the SI.
... However, human neuroimaging studies on vibrotactile WM have revealed mixed results as 26 to whether S1 is activated during the delay period of information storage: Several studies have 27 shown that the average activity level of S1 (as detected by a "mass-univariate" statistical approach) 28 is not significantly larger during the WM delay period than during a control condition (for reviews 29 see (Christophel et al., 2017). Dynamical causal modelling (DCM) estimates of interactions between serially processed from S1 to secondary somatosensory cortex (S2; (Kalberlah et al., 2013), which 1 matches findings in non-human primates (for review (Romo & Rossi-Pool, 2020). ...
... 24relayed to S2(Kalberlah et al., 2013), which possesses a reciprocal connection with S1 and 25 disseminates information via insular projections to frontal and parietal regions(Wang et al., 2013). ...
It is well-established that several cortical areas represent vibrotactile stimuli in somatotopic maps. However, whether such somatotopic representations remain active during the delay period of working memory (WM) tasks, i.e. in the absence of any tactile stimulation, is unknown. In our experiment, participants had to compare two tactile stimuli with different vibration frequencies that were separated by a delay period (memory condition) or they were exposed to identical stimuli but did not have to solve a WM task (no memory condition). Importantly, both vibrotactile stimuli were either applied to the right index or little finger. Analyzing the delay period, we identified a well-known fronto-parietal network of brain regions involved in WM but we did not find WM specific activity in S1. However, using multi-voxel pattern analysis (MVPA) and representational similarity analysis (RSA), we found that S1 finger representations were more dissimilar during the delay period of the WM condition than during the control condition. These results indicate that WM processes modulate the representational geometry of S1 suggesting that some aspects of the tactile WM content are represented in a somatotopic fashion.
HIGHLIGHTS
Multivariate approaches were used to identify finger specific representational changes during vibrotactile frequency discrimination.
Vibrotactile working memory modulates somatotopic finger representations in contralateral S1 during the delay period, i.e. in the absence of any tactile stimuli
... Studies have been also conducted to observe the level of neural activation in the S1 and BA3 areas when the fingers are presented with high-frequency (>100 Hz) vibrational stimuli sensitive to the Pacinian corpuscle. Namely, one study compared activation characteristics of these areas when presenting the high-frequency vibration stimulus to all phalanges of the index finger [15], and another study compared the degree of activation when applying the high-frequency vibration stimulus to the first phalange of the index finger and the little finger [16]. In these previous studies, the activation area of the little finger was larger than that of other fingers, and the activation area of the second finger was larger than that of the first and third nodes. ...
... Several studies have reported the brain activation associated with low-frequency vibration stimulation of each finger; the highest levels of activation have frequently been found in the S1 and BA3 regions on stimulation of the index finger [2,6,9,12,16], and a few studies have reported similar results after stimulation of the little finger [1,7]. Generally, the greatest level of activation has been reported to occur for stimulation of the index finger, which has a large distribution of sensory receptors. ...
In this study, we measured neuronal activation in the primary somatosensory area (S1) and Brodmann area 3 (BA3) using 3T functional magnetic resonance imaging (fMRI) while presenting a 250-Hz high-frequency vibrational stimulus to each of three phalanges (distal, intermediate, and proximal) of four fingers of the right hand (index, middle, ring, and little). We compared the nerve activation area between each finger and each phalange. Ten healthy male college students (26.6 ± 2.5 years old) participated in this study. One session consisted of three blocks: a rest (30 s), stimulation (30 s), and response phase (9 s). In the rest phase, the vibrational stimulus was not presented. In the stimulation phase, the vibrational stimulation was presented at any one of the three phalanges of the selected finger. In the response phase, subjects were instructed to press a button corresponding to the phalange that they thought had received the vibration. The subtraction method was used to extract the activation area. The activation area in the S1 was the largest when the little finger was stimulated (for the finger comparison), and largest when the second phalange was stimulated (for the phalange comparison). The BA3 showed similar trends, and there was no statistically significant difference.
... The stimulator was attached to the right thumb to avoid contact with the table and the response device. Participants were asked to respond by button press with their right index finger to the GO stimulation stimulation range activates the secondary somatosensory cortex (Chung et al., 2013;Francis et al., 2000;Kalberlah, Villringer, & Pleger, 2013). The experiment consisted of four blocks and participants received 204 trials per block (i.e., 832 trials in total). ...
... It was considered the methodologically most appropriate alternative to have exact the same set up for both groups except of varying the administration of the stimulation protocol. A control stimulation at the same hand was excluded since it could still have interfered with the relevant stimulation site due to potentially overlapping cortical representations (Ackerley & Kavounoudias, 2015;Kalberlah et al., 2013;Sanchez Panchuelo, Besle, Schluppeck, Humberstone, & Francis, 2018). Conducting the control stimulation on the other hand was also not an option because transcallosal connections between homologous somatosensory regions as well as nonhomologous regions (Tamè, Braun, Holmes, Farnè, & Pavani, 2016) could have a potential effect on the results. ...
Response inhibition is of vital importance in the context of controlling inappropriate responses. The role of perceptual processes during inhibitory control has attracted increased interest. Yet, we are far from an understanding of the mechanisms. One candidate mechanism by which perceptual processes may affect response inhibition refers to ‘gain control’ that is closely linked to the signal-to-noise ratio of incoming information. A means to modulate the signal-to-noise ratio and gain control mechanisms is perceptual learning.
In the current study, we examine the impact of perceptual learning (i.e. passive repetitive sensory stimulation) on response inhibition combining EEG signal decomposition with source localization analyses. A tactile Go/Nogo paradigm was conducted to measure action restraint as one subcomponent of response inhibition. We show that passive perceptual learning modulates response inhibition processes. In particular, perceptual learning attenuates the detrimental effect of response automation during inhibitory control. Temporally decomposed EEG data show that stimulus-related and not response selection processes during conflict monitoring are linked to these effects. The superior and middle frontal gyrus (BA6), as well as the motor cortex (BA4), are associated with the effects of perceptual learning on response inhibition. Reliable neurophysiological effects were not evident on the basis of standard ERPs, which has important methodological implications for perceptual learning research. The results detail how lower level sensory plasticity protocols affect higher-order cognitive control functions in frontal cortical structures.
... The rIFG is part of the response inhibition network [50][51][52][53][54] which is also assumed to fulfill a "braking function" in the context of response inhibition [52,[55][56][57]. Importantly, there are structural connections between the somatosensory cortex and the rIFG [58][59][60][61], which have previously been suggested to be the reason why response inhibition is very efficient when being triggered using somatosensory stimuli [13,14]. We hypothesize that the reference stimulation condition results in a stronger activation of rIFG as compared to the objective or subjective stimulation condition because of a stronger binding of the stimulus feature and the associated response due to the higher intensity of the stimulus in the reference condition. ...
... Before each block, the participants were informed which frequencies served a GO and NOGO stimuli. Frequencies of 160 and 240 Hz were used, because these frequencies have been shown to be predominantly processed in the secondary somatosensory cortex (SII) [59,62,63] whereas frequencies ranging from 10 to 50 Hz are predominantly processed in the primary somatosensory cortex (SI) [62,64,65]. Hence, the range of vibratory stimuli predominantly processed in one cortical area is larger for SII so that the space between both frequencies could be defined large enough to ensure sufficient discriminability between GO and NOGO stimuli. ...
Response inhibition is a central aspect of cognitive control. Yet, only recently the role of sensory mechanisms for response inhibition has been addressed and neurophysiological mechanisms are far from being understood. Here we ask in how far the physical intensity of stimuli is a relevant perceptual factor modulating motor inhibitory control. We investigated how different physical (objective) stimulus and the subjectively perceived stimulus magnitude modulated response inhibition and its neurophysiological correlates. To this end we used a somatosensory GO/NOGO task in combination with EEG recordings and applied temporal signal decomposition and source localization methods. The behavioral (false alarm) data clearly demonstrated that response inhibition performance was worse in the subjective and objective stimulation condition as compared to the reference stimulation condition with higher stimulus magnitude. Despite primary perceptual aspects were manipulated, neurophysiological correlates of lower-level perceptual and attentional selection processes did not explain effects on overt response inhibition behavior. Rather, neurophysiological processes at the response selection level were modulated. These were associated with activation differences in the right inferior frontal gyrus and suggest that “braking processes” enabling the inhibition of a to-be-executed motor response are modulated. The modulation of these braking processes depends on objective physical magnitude of incoming sensory information and not the subjectively perceived stimulus magnitude.
... It is well-known that slow frequencies predominantly activate the SI cortex B. Bodmer et al. Developmental Cognitive Neuroscience 31 (2018) (Chung et al., 2013;Francis et al., 2000;Harrington and Hunter Downs, 2001) and that high frequent stimuli are processed in the SII cortical area (Chung et al., 2013;Francis et al., 2000;Hämäläinen et al., 1990;Harrington and Hunter Downs, 2001;Kalberlah et al., 2013). The vibrotactile stimuli were delivered via small electromagnetic stimulators (Dancer Design; for more detailed information see http://www. ...
... 40 Hz was chosen since it is not the upper limit of this approximated range but produces sufficient vibratory sensation in the short 100 ms period. The high 150 Hz frequency is in the range from 100 to 400 Hz which is assumed to predominantly activate the SII area (Chung et al., 2013;Francis et al., 2000;Hämäläinen et al., 1990;Harrington and Hunter Downs, 2001;Kalberlah et al., 2013). The short 100 ms stimulation duration was chosen to produce a strong reaction tendency making it more difficult to withhold responses. ...
Response inhibition processes undergo strong developmental changes. The same is true for sensory processes, and recent evidence shows that there also within-modality differences in the efficacy to trigger motor response inhibition. Yet, modulatory effects of within-modality differences during age-related changes in response inhibition between adolescence and adulthood are still indeterminate. We investigated this question in a system neurophysiological approach combining analysis of event-related potentials (ERPs) with temporal EEG signal decomposition and source localization processes. We used the somatosensory system to examine possible within-modality differences. The study shows that differences in response inhibition processes between adolescents and adults are modulated by sensory processes. Adolescents show deficient response inhibition when stimuli triggering these mechanisms are processed via SI somatosensory areas, compared to SII somatosensory areas. Opposed to this, no differences between adolescents and adults are evident, when response inhibition processes are triggered via SII cortical regions. The EEG data suggests that specific neurophysiological subprocesses are associated with this. Adolescents seem to encounter problems assigning processing resources to integrate motor with tactile information in posterior parietal areas when this information is processed via SI. Thus, basic perceptual and age-related processes interactively modulate response inhibition as an important instance of cognitive control.
... Let us note that similar compromises were made by several authors in their DCM analysis, e.g. (Hillebrandt et al., 2013;Kalberlah et al., 2013;Sevel et al., 2015;Dowlati et al., 2016). (ii) Group-mean baseline activation peaks, which are not part of the somatosensory circuit and showed no significant condition-dependent changes in the voxel-wise GLM model, were excluded from the DCM network model (e.g. ...
... Similar compromises were made by several authors in their DCM analysis, e.g. (Hillebrandt et al., 2013;Kalberlah et al., 2013;Sevel et al., 2015;Dowlati et al., 2016). On the other hand, interhemispheric connectivity might also be an important feature in pain processing (Sevel et al., 2016). ...
Central sensitization is a key mechanism in the pathology of several neuropathic pain disorders. We aimed to investigate the underlying brain connectivity changes in a rat model of chronic pain. Non-noxious whisker stimulation was used to evoke BOLD responses in a block-design fMRI experiment on 9.4T. Measurements were repeated two days and one week after injecting complete Freund's adjuvant into the rats' whisker pad. We found that acute pain reduced activation in the barrel cortex, most probably due to a plateau effect. After one week, increased activation of the anterior cingulate cortex was found. Analyses of effective connectivity driven by stimulus-related activation revealed that chronic pain related central sensitization manifested as a widespread alteration in the activity of the somatosensory network. Changes were mainly mediated by the anterior cingulate cortex and the striatum and affected the somatosensory and motor cortices and the superior colliculus. Functional connectivity analysis of nested BOLD oscillations justified that the anterior cingular-somatosensory interplay is a key element of network changes. Additionally, a decreased cingulo-motor functional connectivity implies that alterations also involve the output tract of the network. Our results extend the knowledge about the role of the cingulate cortex in the chronification of pain and indicate that integration of multiple connectivity analysis could be fruitful in studying the central sensitization in the pain matrix.
... Vibratory stimuli, such as those used in our protocol, are relayed by the lemniscal pathway from the cutaneous mechanoreceptors to the somatosensory cortical areas (Patestas and Gartner 2006;Cruccu et al. 2008). Previous somatosensory evoked magnetic fields studies on healthy subjects suggest that epicritic inputs from the lemniscal system are transmitted from the ventroposteriolateral nucleus of the thalamus to several cortical areas; Information is thought to be transformed in a hierarchical way from area 3b, in the posterior wall of the central sulcus to areas 1 and 2 on the surface and area SII in the upper bank of the Sylvian fissure (Inui et al. 2004;Kalberlah et al. 2013). After pneumatic activation of mechanoreceptors, a strong response is first observed in the contralateral SI, followed by a bilateral response in SII (Simões et al. 2001). ...
... The volume of cortical representation of the digits shows some relative correlation to the receptor density of the fingers, and is larger for the thumb than the index, and ring fingers (Overduin and Servos 2004). Electrical, vibrotactile and mechanical stimulation studies suggest that SII does not seem to follow a topological organization of the fingers (Kalberlah et al. 2013) or show a strong spatial overlap (Ruben et al. 2001;Simões et al. 2001), and may be involved in bimanual tasks (Simões et al. 2001). ...
Background
In surgical planning for epileptic focus resection, functional mapping of eloquent cortex is attained through direct electrical stimulation of the brain. This procedure is uncomfortable, can trigger seizures or nausea, and relies on subjective evaluation. We hypothesize that a method combining vibrotactile stimulation and statistical clustering may provide improved somatosensory mapping.Methods
Seven pediatric candidates for surgical resection underwent a task in which their fingers were independently stimulated using a custom designed finger pad, during electrocorticographic monitoring. A cluster-based statistical analysis was then performed to localize the elicited activity on the recording grids.ResultsMid-Gamma clusters (65–115 Hz) arose in areas consistent with anatomical predictions as well as clinical findings, with five subjects presenting a somatotopic organization of the fingers. This process allowed us to delineate finger representation even in patients who were sleeping, with strong interictal activity, or when electrical stimulation did not successfully locate eloquent areas.Conclusions
We suggest that this scheme, relying on the endogenous neural response rather than exogenous electrical activation, could eventually be extended to map other sensory areas and provide a faster and more objective map to better anticipate outcomes of surgical resection.
... Studies using DCM on fMRI data have reached different conclusions regarding the two processing theories. Two studies have found evidence for the serial processing theory (Kalberlah et al., 2013;Khoshnejad et al., 2014), and another two studies found evidence for the parallel processing theory (Chung et al., 2014;Liang et al., 2011). ...
... With this DCM analysis, we aimed to clarify whether somatosensory stimulus information may directly enter SII (Chung et al., 2014;Liang et al., 2011) or is transmitted serially from SI to SII (Kalberlah et al., 2013;Khoshnejad et al., 2014). We used DCM for evoked responses (David et al., 2006) and sensory evoked potentials (SEP) as a neuronal model. ...
... As the predominant somatosensory cortex, the S1 is particularly sensitive to the frequency of stimuli (Kalberlah et al., 2013) and processes multiple sensory factors influencing the perception of somatosensory stimuli such as the intensity (Chen et al., 2002), location (Beauchamp et al., 2009), and modality . The alternations in functional connectivity between region of interest (ROIs) and other 36 channels during each reinforcing-reducing manipulation. ...
Introduction:
Traditional acupuncture with reinforcing-reducing manipulation is essential for clinical effectiveness, whereas the underlying central mechanism of it remains unknown. This study with multiple-channels functional near-infrared spectroscopy (fNIRS) aims to explore cerebral-response modes during acupuncture with reinforcing-reducing manipulations.
Materials and methods:
Functional near-infrared spectroscopy data were recorded from 35 healthy participants during the lifting-thrusting reinforcing manipulation, the lifting-thrusting reducing manipulation, and the even reinforcing-reducing manipulation with lifting-thrusting. The general linear model based (GLM) cortical activation analysis and the functional connectivity (FC) based on region of interest (ROI) analysis were combined to be conducted.
Results:
In comparison with the baseline, the results showed that three acupuncture with reinforcing-reducing manipulations similarly induced the hemodynamic responses in the bilateral dorsolateral prefrontal cortex (DLPFC) and increased FC between the DLPFC and primary somatosensory cortex (S1). Specifically, the even reinforcing-reducing manipulation deactivated the bilateral DLPFC, the frontopolar area (FP), the right primary motor cortex (M1), the bilateral S1, and the bilateral secondary somatosensory cortex (S2); The reducing manipulation deactivated the bilateral DLPFC; The reinforcing manipulation activated the bilateral DLPFC, the left S1, and the right S2. The between-group comparisons indicated that the reinforcing-reducing manipulation induced opposite hemodynamic responses in the bilateral DLPFC and the left S1 and exhibited different FC patterns in the left DLPFC-S1, within the right DLPFC, and between the left S1 and the left orbitofrontal cortex (OFC).
Conclusion:
These findings verified the feasibility of fNIRS for investigating cerebral functional activities of acupuncture manipulations, suggesting that the regulations on the DLPFC-S1 cortex may be the potential central mechanism for the realization of acupuncture with reinforcing-reducing manipulation's effect.
Clinical trial registration:
ClinicalTrials.gov, identifier, ChiCTR2100051893.
... Several groups have demonstrated that tactile irritation leads to a reliable activation of PSC using fMRI (Stippich et al. 1999;Kalberlah et al. 2013;Schweizer et al. 2008;Chen et al. 2002;Disbrow et al. 1998). Indeed, we observed a good visual correlation between IOI and the preoperative fMRI with tactile irritation. ...
The determination of exact tumor boundaries within eloquent brain regions is essential to maximize the extent of resection. Recent studies showed that intraoperative optical imaging (IOI) combined with median nerve stimulation is a helpful tool for visualization of the primary sensory cortex (PSC). In this technical note, we describe a novel approach of using IOI with painless tactile irritation to demonstrate the feasibility of topographic mapping of different body regions within the PSC. In addition, we compared the IOI results with preoperative functional MRI (fMRI) findings. In five patients with tumors located near the PSC who received tumor removal, IOI with tactile irritation of different body parts and fMRI was applied. We showed that tactile irritation of the hand in local and general anesthesia leads to reliable changes of cerebral blood volume during IOI. Hereby, we observed comparable IOI activation maps regarding the median nerve stimulation, fMRI and tactile irritation of the hand. The tactile irritation of different body areas revealed a plausible topographic distribution along the PSC. With this approach, IOI is also suitable for awake surgeries, since the tactile irritation is painless compared with median nerve stimulation and is congruent to fMRI findings. Further studies are ongoing to standardize this method to enable a broad application within the neurosurgical community.
... This discrepancy may be since the patients in this study mainly had stroke lesions in the posterior IC, which is more involved in the processing of non-nociceptive stimuli rather than nociceptive stimuli (67,68). With respect to light touch perception, there has been emerging evidence that it causally involves the SI (69,70). To investigate which brain areas downstream of the SI are specifically responsible for touch perception, Preusser et al. (18) identified 61 patients (mainly suffered from a chronic ischemic stroke) without lesions in the SI and then compared patients with impaired touch perception (i.e., hypoesthesia) to patients without such impairments. ...
Somatosensory deficits after stroke are a major health problem, which can impair patients' health status and quality of life. With the developments in human brain mapping techniques, particularly magnetic resonance imaging (MRI), many studies have applied those techniques to unravel neural substrates linked to apoplexy sequelae. Multi-parametric MRI is a vital method for the measurement of stroke and has been applied to diagnose stroke severity, predict outcome and visualize changes in activation patterns during stroke recovery. However, relatively little is known about the somatosensory deficits after stroke and their recovery. This review aims to highlight the utility and importance of MRI techniques in the field of somatosensory deficits and synthesizes corresponding articles to elucidate the mechanisms underlying the occurrence and recovery of somatosensory symptoms. Here, we start by reviewing the anatomic and functional features of the somatosensory system. And then, we provide a discussion of MRI techniques and analysis methods. Meanwhile, we present the application of those techniques and methods in clinical studies, focusing on recent research advances and the potential for clinical translation. Finally, we identify some limitations and open questions of current imaging studies that need to be addressed in future research.
... High frequency activates more Pacinian than Meissner as Pacinian corpuscles possess low field density and wide receptive field [1]. High frequency predominantly activates SII compared to SI region [2,4,8]. Therefore, Pacinian is known to poorly localized the SI area compared to SII area [4]. ...
Vibratory (e.g., piezoelectric) devices can stimulate cortical responses from the somatosensory area during functional magnetic resonance imaging. Twelve healthy, right-handed subjects (7 males and 5 females) were scanned with a 3.0 T magnetic resonance imaging scanner and stimulated at 30-240 Hz using a piezoelectric vibrator attached to the subjects’ index fingers. The functional images were analysed to determine the brain activation region by performing random effects analyses at the group level. One-way analysis of variance was used to measure changes in frequency on brain activity. The activated regions were identified with WFU PickAtlas software, and the images were thresholded at Puncorrected < 0.001 for multiple comparisons. The average effect of frequency revealed significant activations in the right insula and right middle frontal gyrus; the corresponding region in the somatosensory area may act as a top-down control signal to improve sensory targets. Results revealed significant differences between frequencies; 90 Hz > 120 Hz activated right inferior parietal gyrus, 120 Hz > 150 Hz activated right cerebellum, and 60 Hz > 90 Hz activated right supramarginal gyrus and bilateral inferior frontal gyrus pars triangularis. Findings indicated the role of secondary somatosensory areas and the cerebellum in performing higher-order functions and discriminating various frequencies during vibratory stimulation. Increasing the patient sample size and testing higher frequencies in future experiments will contribute to furthering brain mapping of somatosensory areas.
... It is unclear whether somatosensory information is processed from S1 to S2 in a serial or parallel manner. Human studies using fMRI have been inconclusive, with some supporting parallel processing [17,18] and others supporting serial processing [19,20]. By contrast, in nonprimate and lower primate mammals, tactile somatosensory processing is dominated by parallel processing through the networks between the thalamus and somatosensory cortices [21,22]. ...
Studies using functional magnetic resonance imaging assume that hemodynamic responses have roughly linear relationships with underlying neural activity. However, to accurately investigate the neurovascular transfer function and compare its variability across brain regions, it is necessary to obtain full-field imaging of both electrophysiological and hemodynamic responses under various stimulus conditions with superior spatiotemporal resolution. Optical imaging combined with voltage-sensitive dye (VSD) and intrinsic signals (IS) is a powerful tool to address this issue. We performed VSD and IS imaging in the primary (S1) and secondary (S2) somatosensory cortices of rats to obtain optical maps of whisker-evoked responses. There were characteristic differences in sensory responses between the S1 and S2 cortices: VSD imaging revealed more localized excitatory and stronger inhibitory neural activity in S1 than in S2. IS imaging revealed stronger metabolic responses in S1 than in S2. We calculated the degree of response to compare the sensory responses between cortical regions and found that the ratio of the degree of response of S2 to S1 was similar, irrespective of whether the ratio was determined by VSD or IS imaging. These results suggest that neurovascular coupling does not vary between the S1 and S2 cortices.
... It has been suggested that vibrotactile frequency discrimination is not solely driven by mechanoreceptive afferents (Kuroki et al. 2017;Birznieks et al. 2019). There may be an additional system for vibrotactile frequency processing, possibly involving horizontal connections (Schwark and Jones 1989) or the secondary somatosensory cortex (Nelson et al. 2004;Chung et al. 2013;Kalberlah et al. 2013). Further research is needed to fully characterize S1 pRF properties as a function of frequency of vibrotactile stimulation. ...
Several neuroimaging studies have shown the somatotopy of body part representations in primary somatosensory cortex (S1), but the functional hierarchy of distinct subregions in human S1 has not been adequately addressed. The current study investigates the functional hierarchy of cyto-architectonically distinct regions, Brodmann areas BA3, BA1, and BA2, in human S1. During functional MRI experiments, we presented participants with vibrotactile stimulation of the fingertips at three different vibration frequencies. Using population Receptive Field (pRF) modeling of the fMRI BOLD activity, we identified the hand region in S1 and the somatotopy of the fingertips. For each voxel, the pRF center indicates the finger that most effectively drives the BOLD signal, and the pRF size measures the spatial somatic pooling of fingertips. We find a systematic relationship of pRF sizes from lower-order areas to higher-order areas. Specifically, we found that pRF sizes are smallest in BA3, increase slightly towards BA1, and are largest in BA2, paralleling the increase in visual receptive field size as one ascends the visual hierarchy. Additionally, we find that the time-to-peak of the hemodynamic response in BA3 is roughly 0.5 s earlier compared to BA1 and BA2, further supporting the notion of a functional hierarchy of subregions in S1. These results were obtained during stimulation of different mechanoreceptors, suggesting that different afferent fibers leading up to S1 feed into the same cortical hierarchy.
... Effective connectivity provides a causal basis of integration across neuronal populations; it defines whether neural activity in one population of neurons causes activity in another population. Such methods are being used to decipher the causal propagation of neural activity through cortical regions during global cortical integration associated with pain (Liang et al., 2011;Kalberlah et al., 2013;Khoshnejad et al., 2014). ...
... However, not all patients with lesions in BA 3b, as the assumed main entry site of thalamic projections (i.e., SI proper 10 ), also presented hypoesthesia. This suggests that thalamic projections do not exclusively target 3b 19 , but probably also neighbouring BAs, such as BA 1, 2, or 3a. ...
Which brain regions contribute to the perceptual awareness of touch remains largely unclear. We collected structural magnetic resonance imaging scans and neurological examination reports of 70 patients with brain injuries or stroke in S1 extending into adjacent parietal, temporal or pre-/frontal regions. We applied voxel-based lesion-symptom mapping to identify brain areas that overlap with an impaired touch perception (i.e., hypoesthesia). As expected, patients with hypoesthesia (n = 43) presented lesions in all Brodmann areas in S1 on postcentral gyrus (BA 1, 2, 3a, 3b). At the anterior border to BA 3b, we additionally identified motor area BA 4p in association with hypoesthesia, as well as further ventrally the ventral premotor cortex (BA 6, BA 44), assumed to be involved in whole-body perception. At the posterior border to S1, we found hypoesthesia associated effects in attention-related areas such as the inferior parietal lobe and intraparietal sulcus. Downstream to S1, we replicated previously reported lesion-hypoesthesia associations in the parietal operculum and insular cortex (i.e., ventral pathway of somatosensory processing). The present findings extend this pathway from S1 to the insular cortex by prefrontal and posterior parietal areas involved in multisensory integration and attention processes.
... [4] Human studies using electrocorticography (ECoG), electroencephalography (EEG) and functional magnetic resonance imaging(fMRI) also found out that the neuronal representation varies along different vibrotactile stimuli. [3,5] Moreover, tactile perception is subjective in individual and it is closely related to encoding sensory features. In one previous study, monkeys categorized the vibrotactile stimuli consisting of different features(frequency, amplitude and duration) and the responses of primary somatosensory neurons showed correlation with the animals' categorization behavior. ...
Perceiving and processing sensory stimuli are essential to generate motor action. Previous studies suggested features of vibrotactile stimulus such as amplitude and frequency are differently represented onto somatosensory cortices so that the stimulus can be discriminated. In the present study, we aimed to demonstrate the effect of transcranial magnetic stimulation (TMS) triplet pulses over primary somatosensory cortex (S1) or secondary somatosensory cortex (S2) on a tactile discrimination task. In two alternative forced choice task, TMS over S1 or S2 significantly interfered with the discrimination performance. This disruptive influence was mostly shown when the vibrotactile stimulus was close to high frequency (320 Hz). Therefore we concluded the inhibitory effect of TMS is selective with tactile frequency.
... In addition, lack of controlled delivery of stimulation intraoperatively with precise temporal resolution limits our capability to explore the related neural correlates. Devices such as a planar-coil-type actuator or piezoelectric-ceramic stimulator 11,12 have been developed to also provide haptic stimulus but require complex and cumbersome circuitry that are usually costly. ...
... DCM is a model-based technique to infer network dynamics that has found explanatory utility in cognitive neuroscience, including language (Leff et al., 2008;Noppeney et al., 2008), motor processes (Grefkes et al., 2008), vision (Mechelli et al., 2003;Fairhall and Ishai, 2007) and memory (Smith et al., 2006). DCM has been employed to study perceptual decision-making tasks (Summerfield et al., 2006;Stephan et al., 2007;Summerfield and Koechlin, 2008) including vibrotactile discrimination tasks, focussing on the exchange of information from primary to secondary somatosensory cortex (Kalberlah et al., 2013). Here, we use DCM to disambiguate between candidate serial, parallel or hierarchical engagement of the PFC in the representation and manipulation of perceptual precision. ...
Actions are shaped not only by the content of our percepts but also by our confidence in them. To study the cortical representation of perceptual precision in decision making, we acquired functional imaging data whilst participants performed two vibrotactile forced-choice discrimination tasks: a fast-slow judgment, and a same-different judgment. The first task requires a comparison of the perceived vibrotactile frequencies to decide which one is faster. However, the second task requires that the estimated difference between those frequencies is weighed against the precision of each percept—if both stimuli are very precisely perceived, then any slight difference is more likely to be identified than if the percepts are uncertain. We additionally presented either pure sinusoidal or temporally degraded “noisy” stimuli, whose frequency/period differed slightly from cycle to cycle. In this way, we were able to manipulate the perceptual precision. We report a constellation of cortical regions in the rostral prefrontal cortex (PFC), dorsolateral PFC (DLPFC) and superior frontal gyrus (SFG) associated with the perception of stimulus difference, the presence of stimulus noise and the interaction between these factors. Dynamic causal modeling (DCM) of these data suggested a nonlinear, hierarchical model, whereby activity in the rostral PFC (evoked by the presence of stimulus noise) mutually interacts with activity in the DLPFC (evoked by stimulus differences). This model of effective connectivity outperformed competing models with serial and parallel interactions, hence providing a unique insight into the hierarchical architecture underlying the representation and appraisal of perceptual belief and precision in the PFC.
... Our results may provide some insight into the ongoing debate about the serial versus parallel processing of S1 and S2 during vibrotactile stimulation 27,28 . Although we could not investigate the causal relationship between them, it is unlikely that the HG activation in S2 (the posterior part of the upper bank of the Sylvian fissure) directly represents the primary response for a high-frequency stimulus. ...
Humans can easily detect vibrotactile stimuli up to several hundred hertz, but underlying large-scale neuronal processing mechanisms in the cortex are largely unknown. Here, we investigated the macroscopic neural correlates of various vibrotactile stimuli including artificial and naturalistic ones in human primary and secondary somatosensory cortices (S1 and S2, respectively) using electrocorticography (ECoG). We found that tactile frequency-specific high-gamma (HG, 50–140 Hz) activities are seen in both S1 and S2 with different temporal dynamics during vibration (>100 Hz). Stimulus-evoked S1 HG power, which exhibited short-delayed peaks (50–100 ms), was attenuated more quickly in vibration than in flutter (<50 Hz), and their attenuation patterns were frequency-specific within vibration range. In contrast, S2 HG power, which was activated much later than that of S1 (150–250 ms), strikingly increased with increasing stimulus frequencies in vibration range, and their changes were much greater than those in S1. Furthermore, these S1-S2 HG patterns were preserved in naturalistic stimuli such as coarse/fine textures. Our results provide persuasive evidence that S2 is critically involved in neural processing for high-frequency vibrotaction. Therefore, we propose that S1-S2 neuronal co-operation is crucial for full-range, complex vibrotactile perception in human.
... There is a well-established body of literature examining the functional neuroanatomy of brain regions underlying 2ptD, with SI serving as the main sensory entry site and sequentially aligned upstream areas, such as the SII, the posterior parietal cortex, the supramarginal gyrus and the IC being involved in higher-level processing as well as multimodal integration (Kalberlah et al., 2013;Lucan et al., 2010;Makin et al., 2007;Preusser et al., 2015;Sathian, 2016;Stilla et al., 2007;Zhang et al., 2005). Lesions of the SI, for example, have been shown to affect the detection of tactile stimuli while lesions of the posterior parietal cortex are associated with impairments of more complex functions such as shape recognition. ...
There is a growing interest in identifying the neural mechanisms by which the human brain allows for improving performance. Tactile perceptual measurements, e.g. two-point discrimination (2ptD), can be used to investigate neural mechanisms of perception as well as perceptual improvement. Improvement can be induced in a practice-independent manner, e.g. in the tactile domain through repetitive somatosensory stimulation (rSS). With respect to tactile perception, the role of cortical excitability and activation within the somatosensory cortex has been investigated extensively. However, the role of structural properties, such as regional gray matter (GM) volume, is unknown. Using high resolution imaging and voxel-based morphometry (VBM), we sought to investigate how regional GM volume relates to individual 2ptD performance. Furthermore, we wanted to determine if electrical rSS has an influence on regional GM volume. 2ptD thresholds of the index fingers were assessed bilaterally. High-resolution (1 mm³), T1-weighted images were obtained using a 3T scanner pre-and post-stimulation. RSS was applied for 45 min to the dominant right hand, specifically to the fingertips of all fingers. At baseline, performance in the 2ptD task was associated with regional GM volume in the thalamus, primary somatosensory cortex, and primary visual cortex (negative association). After 45 min of rSS, we observed an improvement in 2ptD of the stimulated hand, whereas no improvement in tactile performance was seen on the non-stimulated side. These perceptual changes were accompanied by an increase in GM volume in the left somatosensory cortex and the degree of improvement correlated with GM volume changes in the insular cortex. Our results show that structural changes in the brain, specifically in regions receiving afferent input from the stimulated body site can be induced via a short-term intervention lasting only 45 min. However, the neurobiological correlates of these changes and the dynamics need to be further elucidated.
... Since we previously showed that rTMS deactivation of S1 worsened tactile spatial discrimination, while paradoxically increasing the perceived intensity of a tactile stimulus, the current findings suggest a very different role for S2 in tactile perception. We previously suggested that the increased intensity perception following S1 rTMS [17] may have resulted from S1 inhibition leading to S2 disinhibition. The current findings of S2 involvement in perceived touch intensity support that idea. ...
Research suggests that the discriminative and affective aspects of touch are processed differently in the brain. Primary somatosensory cortex is strongly implicated in touch discrimination, whereas insular and prefronal regions have been associated with pleasantness aspects of touch. However, the role of secondary somatosensory cortex (S2) is less clear. In the current study we used inhibitory repetitive transcranial magnetic stimulation (rTMS) to temporarily deactivate S2 and probe its role in touch perception. Nineteen healthy adults received two sessions of 1-Hz rTMS on separate days, one targeting right S2 and the other targeting the vertex (control). Before and after rTMS, subjects rated the intensity and pleasantness of slow and fast gentle brushing of the hand and performed a 2-point tactile discrimination task, followed by fMRI during additional brushing. rTMS to S2 (but not vertex) decreased intensity ratings of fast brushing, without altering touch pleasantness or spatial discrimination. MRI showed a reduced response to brushing in S2 (but not in S1 or insula) after S2 rTMS. Together, our results show that reducing touch-evoked activity in S2 decreases perceived touch intensity, suggesting a causal role of S2 in touch intensity perception.
... The extent threshold of activation was P < 0.05, FDR corrected for multiple comparisons over the whole brain with height threshold set at P < 0.005 uncorrected (one-tailed). Regions surrounded by red lines indicate the speed-related regions depicted in Fig. 4 Participants in the present study may have been able to use this temporal frequency cue in order to infer the speed of moving surfaces, a notion consistent with previous findings that activity in the parietal operculum is related to the frequency of vibration [34][35][36] . In addition to the parietal operculum, we also observed speed-related activation in other brain regions, including the inferior and superior frontal gyrus. ...
Humans are able to judge the speed of an object's motion by touch. Research has suggested that tactile judgment of speed is influenced by physical properties of the moving object, though the neural mechanisms underlying this process remain poorly understood. In the present study, functional magnetic resonance imaging was used to investigate brain networks that may be involved in tactile speed classification and how such networks may be affected by an object's texture. Participants were asked to classify the speed of 2-D raised dot patterns passing under their right middle finger. Activity in the parietal operculum, insula, and inferior and superior frontal gyri was positively related to the motion speed of dot patterns. Activity in the postcentral gyrus and superior parietal lobule was sensitive to dot periodicity. Psycho-physiological interaction (PPI) analysis revealed that dot periodicity modulated functional connectivity between the parietal operculum (related to speed) and postcentral gyrus (related to dot periodicity). These results suggest that texture-sensitive activity in the primary somatosensory cortex and superior parietal lobule influences brain networks associated with tactually-extracted motion speed. Such effects may be related to the influence of surface texture on tactile speed judgment.
... (53) andKhoshnejad et al. (54) supported serial processing, whereas Chung et al. (55) and Liang et al. (56) the parallel model. Even intracranial studies yielded conflicting results. ...
Significance
Here, we show how anatomical and functional data recorded from patients undergoing stereo-EEG can be combined to generate highly resolved four-dimensional maps of human cortical processing. We used this technique, which provides spatial maps of the active cortical nodes at a millisecond scale, to depict the somatosensory processing following electrical stimulation of the median nerve in nearly 100 patients. The results showed that human somatosensory system encompasses a widespread cortical network including a phasic component, centered on primary somatosensory cortex and neighboring motor, premotor, and inferior parietal regions, as well as a tonic component, centered on the opercular and insular areas, lasting more than 200 ms.
... The response rate of the contralateral SII was much lower (τ of cBA40 = 20.99 s) than that of the contralateral SI. In terms of a hierarchical somatosensory network for tactile information processing from SI (low-level) to SII (highlevel) [41], it is likely that these adaptive changes in the degrees of activation occurs in the contralateral SI earlier than in the contralateral SII. Other regions beyond the contralateral SII including the ipsilateral SII, bilateral PPC and insula showed no significant adaptive change in the degree of activation. ...
Background
Tactile adaptation is a phenomenon of the sensory system that results in temporal desensitization after an exposure to sustained or repetitive tactile stimuli. Previous studies reported psychophysical and physiological adaptation where perceived intensity and mechanoreceptive afferent signals exponentially decreased during tactile adaptation. Along with these studies, we hypothesized that somatosensory cortical activity in the human brain also exponentially decreased during tactile adaptation. The present neuroimaging study specifically investigated temporal changes in the human cortical responses to sustained pressure stimuli mediated by slow-adapting type I afferents.
Methods
We applied pressure stimulation for up to 15 s to the right index fingertip in 21 healthy participants and acquired functional magnetic resonance imaging (fMRI) data using a 3T MRI system. We analyzed cortical responses in terms of the degrees of cortical activation and inter-regional connectivity during sustained pressure stimulation.
Results
Our results revealed that the degrees of activation in the contralateral primary and secondary somatosensory cortices exponentially decreased over time and that intra- and inter-hemispheric inter-regional functional connectivity over the regions associated with tactile perception also linearly decreased or increased over time, during pressure stimulation.
Conclusion
These results indicate that cortical activity dynamically adapts to sustained pressure stimulation mediated by SA-I afferents, involving changes in the degrees of activation on the cortical regions for tactile perception as well as in inter-regional functional connectivity among them. We speculate that these adaptive cortical activity may represent an efficient cortical processing of tactile information.
... It has long been debated for somatosensory information processing at earlier sensory stages, whether serial or parallel processing dominates within SI and SII (Pons et al., 1987(Pons et al., , 1992Zhang et al., 1996;Iwamura, 1998;Karhu & Tesche, 1999;Ploner et al., 1999;Inui et al., 2004;Liang et al., 2011;Kalberlah et al., 2013). Meanwhile, PPC has been widely accepted as a later stage of somatosensory processing and WM (Iwamura, 1998;Fuster, 2001;Fuster & Bressler, 2012). ...
In the present study, we investigated causal roles of both the primary somatosensory cortex (SI) and the posterior parietal cortex (PPC) in a tactile unimodal working memory (WM) task. Individual MRI-based single-pulse transcranial magnetic stimulation (spTMS) was applied respectively to left SI (ipsilateral to tactile stimuli), right SI (contralateral to tactile stimuli) and right PPC (contralateral to tactile stimuli), while human participants were performing a tactile-tactile unimodal delayed matching-to-sample task. Time points of spTMS were 300ms, 600ms, and 900ms after the onset of the tactile sample stimulus (duration: 200ms). Compared with ipsilateral SI, application of spTMS over either contralateral SI or contralateral PPC at those time points significantly impaired the accuracy of task performance. Meanwhile, the deterioration in accuracy did not vary with the stimulating time points. Together, these results indicate that the tactile information is processed cooperatively by SI and PPC in the same hemisphere, starting from the early delay of the tactile unimodal WM task. This pattern of processing of tactile information is different from the pattern in tactile-visual crossmodal WM. In a tactile-visual crossmodal WM task, SI and PPC contribute to the processing sequentially, suggesting a process of sensory information transfer during the early delay between modalities. This article is protected by copyright. All rights reserved.
This article is protected by copyright. All rights reserved.
The aim of the work has been to report on the effects of vibrostimulation, administered through wearable technology, on stereotyped behaviour of a child in middle childhood, with autism, intellectual disability and severe behaviour in the ‘stereotypic behaviour’ subscale of the Restricted and Repetitive Behaviour Revised Scale. He received vibrostimulation (210 Hz, 2.8 µm), with a continuous pattern of vibration: three vibrations of 700 ms, each separated by a rest period of 500 ms and a pause of 8000 ms. Vibration was delivered bilaterally by two devices, repeating the vibration pattern for 3 min. The measures were repeated four times alternately, with the device turned off and on. The outcome measure was frequency of stereotyed behaviour, which was evaluated for 3 min with and without vibrostimulation. The results and observations, over 3 min of stimulation, showed the disappearance of stereotyped movements during vibrostimulation and better precision in intentional hand movements. Subjectively, the child enjoyed vibrostimulation.
Background and purpose:
The effective connectivity of neuronal networks during passive saltatory pneumotactile velocity stimulation to the glabrous hand with different velocities is still unknown. The present study investigated the effectivity connectivity elicited by saltatory pneumotactile velocity arrays placed on the glabrous hand at three velocities (5, 25, and 65 cm/second).
Methods:
Dynamic causal modeling (DCM) was used on functional MRI data sampled from 20 neurotypical adults. Five brain regions, including the left primary somatosensory (SI) and motor (M1) cortices, bilateral secondary somatosensory (SII) cortices, and right cerebellar lobule VI, were used to build model space.
Results:
Three velocities (5, 25, and 65 cm/second) of saltatory pneumotactile stimuli were processed in both serial and parallel modes within the sensorimotor networks. The medium velocity of 25 cm/second modulated forward interhemispheric connection from the contralateral SII to the ipsilateral SII. Pneumotactile stimulation at the medium velocity of 25 cm/second also influenced contralateral M1 through contralateral SI. Finally, the right cerebellar lobule VI was involved in the sensorimotor networks.
Conclusions:
Our DCM results suggest the coexistence of both serial and parallel processing for saltatory pneumotactile velocity stimulation. Significant contralateral M1 modulation promotes the prospect that the passive saltatory pneumotactile velocity arrays can be used to design sensorimotor rehabilitation protocols to activate M1. The effective connectivity from the right cerebellar lobule VI to other cortical regions demonstrates the cerebellum's role in the sensorimotor networks through feedforward and feedback neuronal pathways.
Dynamic causal modeling (DCM) has long been used to characterize effective connectivity within networks of distributed neuronal responses. Previous reviews have highlighted the understanding of the conceptual basis behind DCM and its variants from different aspects. However, no detailed summary or classification research on the task-related effective connectivity of various brain regions has been made formally available so far, and there is also a lack of application analysis of DCM for hemodynamic and electrophysiological measurements. This review aims to analyze the effective connectivity of different brain regions using DCM for different measurement data. We found that, in general, most studies focused on the networks between different cortical regions, and the research on the networks between other deep subcortical nuclei or between them and the cerebral cortex are receiving increasing attention, but far from the same scale. Our analysis also reveals a clear bias towards some task types. Based on these results, we identify and discuss several promising research directions that may help the community to attain a clear understanding of the brain network interactions under different tasks.
Nociceptive and tactile information is processed in the somatosensory system via reciprocal (i.e., feedforward and feedback) projections between the thalamus, the primary (S1) and secondary (S2) somatosensory cortices. The exact hierarchy of nociceptive and tactile information processing within this ‘thalamus-S1-S2’ network and whether the processing hierarchy differs between the two somatosensory submodalities remains unclear. In particular, two questions related to the ascending and descending pathways have not been addressed. For the ascending pathways, whether tactile or nociceptive information is processed in parallel (i.e., 'thalamus-S1′ and 'thalamus-S2′) or in serial (i.e., 'thalamus-S1-S2′) remains controversial. For the descending pathways, how corticothalamic feedback regulates nociceptive and tactile processing also remains elusive. Here, we aimed to investigate the hierarchical organization for the processing of nociceptive and tactile information in the ‘thalamus-S1-S2’ network using dynamic causal modelling (DCM) combined with high-temporal-resolution fMRI. We found that, for both nociceptive and tactile information processing, both S1 and S2 received inputs from thalamus, indicating a parallel structure of ascending pathways for nociceptive and tactile information processing. Furthermore, we observed distinct corticothalamic feedback regulations from S1 and S2, showing that S1 generally exerts inhibitory feedback regulation independent of external stimulation whereas S2 provides additional inhibition to the thalamic activity during nociceptive and tactile information processing in humans. These findings revealed that nociceptive and tactile information processing have similar hierarchical organization within the somatosensory system in the human brain.
Several neuroimaging studies have shown the somatotopy of body part representations in primary somatosensory cortex (S1), but the functional hierarchy of distinct subregions in human S1 has not been adequately addressed. The current study investigates the functional hierarchy of cyto-architectonically distinct regions, Brodmann areas BA3, BA1, and BA2, in human S1. During functional MRI experiments, we presented participants with vibrotactile stimulation of the fingertips at 3 different vibration frequencies. Using population Receptive Field (pRF) modeling of the fMRI BOLD activity, we identified the hand region in S1 and the somatotopy of the fingertips. For each voxel, the pRF center indicates the finger that most effectively drives the BOLD signal, and the pRF size measures the spatial somatic pooling of fingertips. We find a systematic relationship of pRF sizes from lower-order areas to higher-order areas. Specifically, we found that pRF sizes are smallest in BA3, increase slightly towards BA1, and are largest in BA2, paralleling the increase in visual receptive field size as one ascends the visual hierarchy. Additionally, we find that the time-to-peak of the hemodynamic response in BA3 is roughly 0.5s earlier compared to BA1 and BA2, further supporting the notion of a functional hierarchy of subregions in S1. These results were obtained during stimulation of different mechanoreceptors, suggesting that different afferent fibers leading up to S1 feed into the same cortical hierarchy.
In this report, we used biotinylated dextran amine to anterogradely label individual axons projecting from primary somatosensory cortex (S1) to four cortical areas in rats, namely the secondary somatosensory (S2), the parietal ventral (PV), the perirhinal (PR), and the contralateral S1 (S1c). A major goal was to determine whether axon terminals could be classified on the basis of morphological criteria, such as the shape and density of boutons, and the shape and size of individual terminal arbors. Evidence from reconstruction of isolated axon terminal fragments (n=111) supported a degree of morphological heterogeneity. In particular, morphological parameters associated with the complexity of terminal arbors and the proportion of beaded, en passant boutons (Bp) vs. stalked boutons terminaux (Bt) were found to differ significantly. Two broad groups could be established following a discriminant function analysis across axon fragments. Both groups occurred in all four target areas, possibly consistent with a commonality of presynaptic processing of tactile information in these areas. However, more work is needed to investigate synaptic function at the single bouton level and see how this might be associated with emerging properties in the postsynaptic targets.
In this report, we used biotinylated dextran amine to anterogradely label individual axons projecting from primary somatosensory cortex (S1) to four cortical areas in rats, namely the secondary somatosensory (S2), the parietal ventral (PV), the perirhinal (PR), and the contralateral S1 (S1c). A major goal was to determine whether axon terminals could be classified on the basis of morphological criteria, such as the shape and density of boutons, and the shape and size of individual terminal arbors. Evidence from reconstruction of isolated axon terminal fragments (n=111) supported a degree of morphological heterogeneity. In particular, morphological parameters associated with the complexity of terminal arbors and the proportion of beaded, en passant boutons (Bp) vs. stalked boutons terminaux (Bt) were found to differ significantly. Two broad groups could be established following a discriminant function analysis across axon fragments. Both groups occurred in all four target areas, possibly consistent with a commonality of presynaptic processing of tactile information in these areas. However, more work is needed to investigate synaptic function at the single bouton level and see how this might be associated with emerging properties in the postsynaptic targets.
Response inhibition as a central facet of executive functioning is no homogeneous construct. Interference inhibition constitutes a subcomponent of response inhibition and refers to inhibitory control over responses that are automatically triggered by irrelevant stimulus dimensions as measured by the Simon task. While there is evidence that the area-specific modulation of tactile information affects the act of action withholding, effects in the context of interference inhibition remain elusive. We conducted a tactile version of the Simon task with stimuli designed to be predominantly processed in the primary (40 Hz) or secondary (150 Hz) somatosensory cortex. On the basis of EEG recordings, we performed signal decomposition and source localization. Behavioral results reveal that response execution is more efficient when sensory information is mainly processed via SII, compared to SI sensory areas during non-conflicting trials. When accounting for intermingled coding levels by temporally decomposing EEG data, the results show that experimental variations depending on sensory area-specific processing differences specifically affect motor and not sensory processes. Modulations of motor-related processes are linked to activation differences in the superior parietal cortex (BA7). It is concluded that the SII cortical area supporting cognitive preprocessing of tactile input fosters automatic tactile information processing by facilitating stimulus-response mapping in posterior parietal regions.
Disturbance in the interpretation of bodily sensation has been widely reported in patients with panic disorder (PD). However, it remains substantially unknown whether patients with PD exhibit any defect in cortical somatosensory processing of non-threatening stimuli. Thus, the present study aimed to examine the functional integrity of the cortical somatosensory system in patients with PD using neurophysiological recordings. A total of 20 patients with PD and 20 healthy controls (HC) were recruited to investigate the cortical responses to median nerve stimulation through whole-head magnetoencephalographic (MEG) imaging. To comprehensively investigate all somatosensory functioning, we studied the regional activation of the primary somatosensory cortex (SI), contralateral (SIIc), and ipsilateral (SIIi) secondary somatosensory cortices, as well as functional connectivity among the SI, SIIc, and SIIi in alpha, beta, and gamma frequency bands. We found that patients with PD demonstrated a reduction in SI activity compared with those in the HC group. Furthermore, a significantly weaker gamma-band functional connectivity between SI and SIIc was found in the PD group relative to the HC group. Our data suggest that patients with PD exhibit abnormal responses to non-threatening (i.e., pain-free) stimuli in the cortical somatosensory system.
Response inhibition is a key component of executive functioning, but the role of perceptual processes has only recently been focused. Although the interrelation of incoming information and resulting behavioural (motor) effects is well-known to depend on gain control mechanisms, the causal role of sensory gain modulation for response inhibition is elusive. We investigate it using a somatosensory response inhibition (Go/Nogo) task and examine the effects of parietal (somatosensory) cathodal and sham tDCS stimulation on a behavioural and neurophysiological level. For the latter, we combine event-related potential (ERP) and source localization analyses. Behavioural results reveal that cathodal stimulation leads to superior inhibition performance as compared to sham stimulation depending on the intensity of tDCS stimulation. The neurophysiological data show that an early (perceptual) subprocess of the Nogo-N2 ERP-component is differentially modulated by the type of stimulation but not a later (response-related) Nogo-N2 subcomponent. Under cathodal stimulation, the early N2 amplitude is reduced and the right inferior frontal gyrus (BA45) is less active. Cathodal tDCS likely enhances inhibition performance via decreasing the efficiency of gain control and the impact of sensory stimuli to trigger prepotent responses. Thereby, response inhibition processes, associated with structures of the response inhibition network, become less demanded.
The use of Whole-Genome Sequencing (WGS) in clinical settings has brought up a number of controversial scientific and ethical issues. The application of WGS is of particular relevance in neurology, as many conditions are difficult to diagnose. We conducted a worldwide, web-based survey to explore neurologists' views on the benefits of, and concerns regarding, the clinical use of WGS, as well as the resources necessary to implement it. Almost half of the 204 neurologists in the study treated mostly adult patients (48%), while the rest mainly children (37.3%), or both (14.7%). Epilepsy (73%) and headaches (57.8%) were the predominant conditions treated. Factor analysis brought out two profiles: neurologists who would offer WGS to their patients, and those who would not, or were not sure in which circumstances it should be offered. Neurologists considering the use of WGS as bringing more benefits than drawbacks currently used targeted genetic testing (P<0.05) or treated mainly children (P<0.05). WGS' benefits were directed towards the patients, while its risks were of a financial and legal nature. Furthermore, there was a correlation between respondents' current use of genetic tests and an anticipation of increased use in the future (P<0.001). However, over half of respondents did not feel sufficiently informed to use WGS in their practice (53.5%). Our results highlight gaps in education, organization, and funding to support the use of WGS in neurology, and draw attention to the need for resources that could strongly contribute to more straightforward diagnoses and possibly better treatment of neurological conditions.European Journal of Human Genetics advance online publication, 10 May 2017; doi:10.1038/ejhg.2017.64.
触觉信息在丘脑–体感皮层网络上的加工方式目前主要存在两种相对立的理论：串行加工理论与并行加工理论。串行加工理论认为触觉信息是从丘脑传输到初级躯体感觉皮层(primary somatosensory cortex, S1)，然后再从S1传输到次级躯体感觉皮层(secondary somatosensory cortex, S2)；并行加工理论认为触觉信息是从丘脑同时并行传输到S1与S2。在加工触觉信息时，非灵长类与低等灵长类动物丘脑–体感皮层网络的加工方式通常被认为是并行的，而高等灵长类动物与人类丘脑–体感皮层网络的加工方式目前还存有争议。现有研究结果的争议主要源于刺激方式、采集技术和数据分析方法等多方面的局限性。在现有技术条件下，应强化实验设计，从自上而下的调节因素、脑可塑性等方面进一步研究触觉信息在丘脑–体感皮层网络上的加工方式。 There are two conflicting theories regarding the processing of tactile information in the network between thalamus and somatosensory cortices: the serial and the parallel processing theories. The serial processing theory assumes that tactile information is transmitted from the thalamus to the primary somatosensory cortex (S1) and from the S1 to the secondary somatosensory cortex (S2). The parallel processing theory suggests that tactile information is directly transmitted from the thalamusto both the S1 and S2. In both non-primate and lower primate mammals, tactile so-matosensory information is processed in parallel in the network between thalamus and somato-sensory cortices. However, the processing of tactile somatosensory information in higher primates and humans remains, at present, a matter of debate. Indeed, the results of previous studies are somehow contradicting, which could be due to some inherent limitations: including stimulus pat-terns, data collection techniques, and data analysis methods. Under the current technical conditions, future research should rely more on experimental design to explore the top-down influence and brain plasticity on the processing of tactile information to further investigate the underlying neural mechanisms.
As the use of wearable haptic devices with vibrating alert features is commonplace, an understanding of the perceptual categorization of vibrotactile frequencies has become important. This understanding can be substantially enhanced by unveiling how neural activity represents vibrotactile frequency information. Using functional magnetic resonance imaging (fMRI), this study investigated categorical clustering patterns of the frequency-dependent neural activity evoked by vibrotactile stimuli with gradually changing frequencies from 20 to 200 Hz. First, a searchlight multi-voxel pattern analysis (MVPA) was used to find brain regions exhibiting neural activities associated with frequency information. We found that the contralateral postcentral gyrus (S1) and the supramarginal gyrus (SMG) carried frequency-dependent information. Next, we applied multidimensional scaling (MDS) to find low-dimensional neural representations of different frequencies obtained from the multi-voxel activity patterns within these regions. The clustering analysis on the MDS results showed that neural activity patterns of 20-100 Hz and 120-200 Hz were divided into two distinct groups. Interestingly, this neural grouping conformed to the perceptual frequency categories found in the previous behavioral studies. Our findings therefore suggest that neural activity patterns in the somatosensory cortical regions may provide a neural basis for the perceptual categorization of vibrotactile frequency.
Genomic, chromosomal, and gene-specific changes in the DNA sequence underpin both phenotypic variations in populations as well as disease associations, and the application of genomic technologies for the identification of constitutional (inherited) or somatic (acquired) alterations in DNA sequence forms a cornerstone of clinical and molecular genetics. In addition to the disruption of primary DNA sequence, the modulation of DNA function by epigenetic phenomena, in particular by DNA methylation, has long been known to play a role in the regulation of gene expression and consequent pathogenesis. However, these epigenetic factors have been identified only in a handful of pediatric conditions, including imprinting disorders. Technological advances in the past decade that have revolutionized clinical genomics are now rapidly being applied to the emerging discipline of clinical epigenomics. Here, we present an overview of epigenetic mechanisms with a focus on DNA modifications, including the molecular mechanisms of DNA methylation and subtypes of DNA modifications, and we describe the classic and emerging genomic technologies that are being applied to this study. This review focuses primarily on constitutional epigenomic conditions associated with a spectrum of developmental and intellectual disabilities. Epigenomic disorders are discussed in the context of global genomic disorders, imprinting disorders, and single gene disorders. We include a section focused on integration of genetic and epigenetic mechanisms together with their effect on clinical phenotypes. Finally, we summarize emerging epigenomic technologies and their impact on diagnostic aspects of constitutional genetic and epigenetic disorders.
Microarray-based comparative genomic hybridization is a method of molecular analysis that identifies chromosomal anomalies (or copy number variants) that correlate with clinical phenotypes. The aim of the present study was to apply a clinical score previously designated by de Vries to 329 patients with intellectual disability/developmental disorder (intellectual disability/developmental delay) referred to our tertiary center and to see whether the clinical factors are associated with a positive outcome of aCGH analyses. Another goal was to test the association between a positive microarray-based comparative genomic hybridization result and the severity of intellectual disability/developmental delay. Microarray-based comparative genomic hybridization identified structural chromosomal alterations responsible for the intellectual disability/developmental delay phenotype in 16% of our sample. Our study showed that causative copy number variants are frequently found even in cases of mild intellectual disability (30.77%). We want to emphasize the need to conduct microarray-based comparative genomic hybridization on all individuals with intellectual disability/developmental delay, regardless of the severity, because the degree of intellectual disability/developmental delay does not predict the diagnostic yield of microarray-based comparative genomic hybridization.
Autism spectrum disorder (ASD) with intellectual disability (ID) is a life-long debilitating condition, which is characterized by cognitive function impairment and other neurological signs. Children with ASD-ID typically attain motor skills with a significant delay. A sub-group of ASD-IDs has been linked to hyperlactacidemia and alterations in mitochondrial respiratory chain activity. The objective of this report is to describe the clinical features of patients with these comorbidities in order to shed light on difficult diagnostic and therapeutic approaches in such patients. We reported the different clinical features of children with ID associated with hyperlactacidemia and deficiencies in mitochondrial respiratory chain complex II-IV activity whose clinical presentations are commonly associated with the classic spectrum of mitochondrial diseases. We concluded that patients with ASD and ID presenting with persistent hyperlactacidemia should be evaluated for mitochondrial disorders. Administration of carnitine, coenzyme Q10, and folic acid is partially beneficial, although more studies are needed to assess the efficacy of this vitamin/cofactor treatment combination.
http://www.mdpi.com/1422-0067/16/2/3870
Complex processes resulting from interaction of multiple elements can rarely be understood by analytical scientific approaches alone; additional, mathematical models of system dynamics are required. This insight, which disciplines like physics have embraced for a long time already, is gradually gaining importance in the study of cognitive processes by functional neuroimaging. In this field, causal mechanisms in neural systems are described in terms of effective connectivity. Recently, dynamic causal modelling (DCM) was introduced as a generic method to estimate effective connectivity from neuroimaging data in a Bayesian fashion. One of the key advantages of DCM over previous methods is that it distinguishes between neural state equations and modality-specific forward models that translate neural activity into a measured signal. Another strength is its natural relation to Bayesian model selection (BMS) procedures. In this article, we review the conceptual and mathematical basis of DCM and its implementation for functional magnetic resonance imaging data and event-related potentials. After introducing the application of BMS in the context of DCM, we conclude with an outlook to future extensions of DCM. These extensions are guided by the long-term goal of using dynamic system models for pharmacological and clinical applications, particularly with regard to synaptic plasticity.
Several studies have suggested that, in higher primates, nociceptive somatosensory information is processed in parallel in the primary (S1) and secondary (S2) somatosensory cortices, whereas non-nociceptive somatosensory input is processed serially from S1 to S2. However, evidence suggesting that both nociceptive and non-nociceptive somatosensory inputs are processed in parallel in S1 and S2 also exists. Here, we aimed to clarify whether or not the hierarchical organization of nociceptive and non-nociceptive somatosensory processing in S1 and S2 differs in humans. To address this question, we applied dynamic causal modeling and Bayesian model selection to functional magnetic resonance imaging (fMRI) data collected during the selective stimulation of nociceptive and non-nociceptive somatosensory afferents in humans. This novel approach allowed us to explore how nociceptive and non-nociceptive somatosensory information flows within the somatosensory system. We found that the neural activities elicited by both nociceptive and non-nociceptive somatosensory stimuli are best explained by models in which the fMRI responses in both S1 and S2 depend on direct thalamocortical projections. These observations indicate that, in humans, both nociceptive and non-nociceptive information are processed in parallel in S1 and S2.
Previous animal research has revealed neuronal activity underlying short-term retention of vibrotactile stimuli, providing evidence for a parametric representation of stimulus frequency in primate tactile working memory (Romo et al., 1999). Here, we investigated the neural correlates of vibrotactile frequency processing in human working memory, using noninvasive electroencephalography (EEG). Participants judged the frequencies of vibrotactile stimuli delivered to the fingertip in a delayed match-to-sample frequency discrimination task. As expected, vibrotactile stimulation elicited pronounced steady-state evoked potentials, which were source-localized in primary somatosensory cortex. Furthermore, parametric analysis of induced EEG responses revealed that the frequency of stimulation was reflected by systematic modulations of synchronized oscillatory activity in nonprimary cortical areas. Stimulus processing was accompanied by frequency-dependent alpha-band responses (8-12 Hz) over dorsal occipital cortex. The critical new finding was that, throughout the retention interval, the stimulus frequency held in working memory was systematically represented by a modulation in prefrontal beta activity (20-25 Hz), which was source-localized to the inferior frontal gyrus. This modulation in oscillatory activity during stimulus retention was related to successful frequency discrimination, thus reflecting behaviorally relevant information. Together, the results complement previous findings of parametric working memory correlates in nonhuman primates and suggest that the quantitative representation of vibrotactile frequency in sensory memory entails systematic modulations of synchronized neural activity in human prefrontal cortex.
Mathematical models of scientific data can be formally compared using Bayesian model evidence. Previous applications in the biological sciences have mainly focussed on model selection in which one first selects the model with the highest evidence and then makes inferences based on the parameters of that model. This "best model" approach is very useful but can become brittle if there are a large number of models to compare, and if different subjects use different models. To overcome this shortcoming we propose the combination of two further approaches: (i) family level inference and (ii) Bayesian model averaging within families. Family level inference removes uncertainty about aspects of model structure other than the characteristic of interest. For example: What are the inputs to the system? Is processing serial or parallel? Is it linear or nonlinear? Is it mediated by a single, crucial connection? We apply Bayesian model averaging within families to provide inferences about parameters that are independent of further assumptions about model structure. We illustrate the methods using Dynamic Causal Models of brain imaging data.
In this paper, we compare mean-field and neural-mass models of electrophysiological responses using Bayesian model comparison. In previous work, we presented a mean-field model of neuronal dynamics as observed with magnetoencephalography and electroencephalography. Unlike neural-mass models, which consider only the mean activity of neuronal populations, mean-field models track the distribution (e.g., mean and dispersion) of population activity. This can be important if the mean affects the dispersion or vice versa. Here, we introduce a dynamical causal model based on mean-field (i.e., population density) models of neuronal activity, and use it to assess the evidence for a coupling between the mean and dispersion of hidden neuronal states using observed electromagnetic responses. We used Bayesian model comparison to compare homologous mean-field and neural-mass models, asking whether empirical responses support a role for population variance in shaping neuronal dynamics. We used the mismatch negativity (MMN) and somatosensory evoked potentials (SEP) as representative neuronal responses in physiological and non-physiological paradigms respectively. Our main conclusion was that although neural-mass models may be sufficient for cognitive paradigms, there is clear evidence for an effect of dispersion at the high levels of depolarization evoked in SEP paradigms. This suggests that (i) the dispersion of neuronal states within populations generating evoked brain signals can be manifest in observed brain signals and that (ii) the evidence for their effects can be accessed with dynamic causal model comparison.
Dynamic causal modeling (DCM) is a generic Bayesian framework for inferring hidden neuronal states from measurements of brain activity. It provides posterior estimates of neurobiologically interpretable quantities such as the effective strength of synaptic connections among neuronal populations and their context-dependent modulation. DCM is increasingly used in the analysis of a wide range of neuroimaging and electrophysiological data. Given the relative complexity of DCM, compared to conventional analysis techniques, a good knowledge of its theoretical foundations is needed to avoid pitfalls in its application and interpretation of results. By providing good practice recommendations for DCM, in the form of ten simple rules, we hope that this article serves as a helpful tutorial for the growing community of DCM users.
An important and unresolved question is how the human brain processes speech for meaning after initial analyses in early auditory cortical regions. A variety of left-hemispheric areas have been identified that clearly support semantic processing, although a systematic analysis of directed interactions among these areas is lacking. We applied dynamic causal modeling of functional magnetic resonance imaging responses and Bayesian model selection to investigate, for the first time, experimentally induced changes in coupling among three key multimodal regions that were activated by intelligible speech: the posterior and anterior superior temporal sulcus (pSTS and aSTS, respectively) and pars orbitalis (POrb) of the inferior frontal gyrus. We tested 216 different dynamic causal models and found that the best model was a "forward" system that was driven by auditory inputs into the pSTS, with forward connections from the pSTS to both the aSTS and the POrb that increased considerably in strength (by 76 and 150%, respectively) when subjects listened to intelligible speech. Task-related, directional effects can now be incorporated into models of speech comprehension.
Reinforcing effects of reward on action are well established, but possible effects on sensory function are less well explored. Here, using functional magnetic resonance imaging, we assessed whether reward can influence somatosensory judgments and modulate activity in human somatosensory cortex. Participants discriminated electrical somatosensory stimuli on an index finger with correct performance rewarded financially at trial end, at one of four different anticipated levels. Higher rewards improved tactile performance and led to increased hemodynamic signals from ventral striatum on rewarded trials. Remarkably, primary somatosensory cortex contralateral to the judged hand was reactivated at the point of reward delivery, despite the absence of concurrent somatosensory input at that time point. This side-specific reactivation of primary somatosensory cortex increased monotonically with level of reward. Moreover, the level of reward received on a particular trial influenced somatosensory performance and neural activity on the subsequent trial, with better discrimination and enhanced hemodynamic response in contralateral primary somatosensory cortex for trials that followed higher rewards. These results indicate that rewards can influence not only classical reward-related regions, but also early somatosensory cortex when a decision is required for that modality.
Maps of orientation preference and selectivity, inferred from differential images of orientation (Blasdel, 1992), reveal linear organizations in patches, 0.5-1.0 mm across, where orientation selectivities are high, and where preferred orientations rotate linearly along one axis while remaining constant along the other. Most of these linear zones lie between the centers of adjacent ocular dominance columns, with their short iso-orientation slabs oriented perpendicular, in regions enjoying the greatest binocular overlap. These two-dimensional linear zones are segregated by one- and zero-dimensional discontinuities that are particularly abundant in the centers of ocular dominance columns, and that are also correlated with cytochrome oxidase-rich zones within them. Discontinuities smaller than 90 degrees extend in one dimension, as fractures, while discontinuities greater than 90 degrees are confined to points, in the form of singularities, that are generated when orientation preferences rotate continuously through +/- 180 degrees along circular paths. The continuous rotations through 180 degrees imply that direction preferences are not organized laterally in striate cortex. And they also ensure that preferences for all orientations converge at each singularity, with perpendicular orientations represented uniquely close together on opposite sides. The periodic interspersing of linear zones and singularities suggests that orientation preferences are organized by at least two competing schemes. They are optimized for linearity, along with selectivity and binocularity, in the linear zones, and they are optimized for density near singularities. Since upper-layer neurons are likely to have similarly sized dendritic fields in all regions (Lund and Yoshioka, 1991), those in the linear zones should receive precise information about narrowly constrained orientations, while those near singularities should receive coarse information about all orientations--very different inputs that suggest different perceptual functions.
Differential images of ocular dominance, acquired by comparing responses to the two eyes, reveal dark and light bands where cortical cells are dominated by the right and left eyes. These include most (but not all) histochemically stained cytochrome oxidase blobs in their centers. Differential images of orientation, acquired by comparing responses to orthogonal orientations, reveal dark and light bands that are reminiscent of the "orientation columns" reported earlier, on the basis of 2-deoxyglucose (2DG) autoradiograms (Hubel et al., 1978). However, they are shorter and more fragmented because they do not include regions lacking selectivity for orientation. Even though these "bands" derive from orientation-selective areas, comparisons with differential images of other orientations reveal that regions along their centers prefer different orientations. Hence, the orientation preferences inferred from "bands" in single differential images, or single 2DG autoradiograms, are not necessarily incorrect. Interactions between ocular dominance and orientation were investigated by comparing differential images of orientation obtained with binocular and monocular stimulation, as well as by comparing differential images of ocular dominance obtained with different orientations. In both cases, the elicited interactions were minimal, indicating a remarkable and unexpected independence that subsequent experiments revealed arises, at least in part, from a lateral segregation of regions most selective for one eye and regions most selective for one orientation, in the centers and edges of ocular dominance columns. Since this can also be viewed as a lateral correlation between binocularity and orientation selectivity, it fits with the simultaneous emergence of these properties in layers receiving input from layer 4c, and suggests that each of these properties requires the other.
1. Selective ablations of the hand representations in postcentral cortical areas 3a, 3b, 1, and 2 were made in different combinations to determine each area's contribution to the responsivity and modality properties of neurons in the hand representation in SII. 2. Ablations that left intact only the postcentral areas that process predominantly cutaneous inputs (i.e., areas 3b and 1) yielded SII recording sites responsive to cutaneous stimulation and none driven exclusively by high-intensity or "deep" stimulation. Conversely, ablations that left intact only the postcentral areas that process predominantly deep receptor inputs (i.e., areas 3a and 2) yielded mostly SII recording sites that responded exclusively to deep stimulation. 3. Ablations that left intact only area 3a or only area 2 yielded substantial and roughly equal reductions in the number of deep receptive fields in SII. By contrast, ablations that left intact only area 3b or only area 1 yielded unequal reductions in the number of cutaneous receptive fields in SII: a small reduction when area 3b alone was intact but a somewhat larger one when only area 1 was intact. 4. Finally, when the hand representation in area 3b was ablated, leaving areas 3a, 1, and 2 fully intact, there was again a substantial reduction in the encounter rate of cutaneous receptive fields. 5. The partial ablations often led to unresponsive sites in the SII hand representation. In SII representations other than of the hand no such unresponsive sites were found and there were no substantial changes in the ratio of cutaneous to deep receptive fields, indicating that the foregoing results were not due to long-lasting postsurgical depression or effects of anesthesia. 6. The findings indicate that modality-specific information is relayed from postcentral cortical areas to SII along parallel channels, with cutaneous inputs transmitted via areas 3b and 1, and deep inputs via areas 3a and 2. Further, area 3b provides the major source of cutaneous input to SII, directly and perhaps also via area 1. 7. The results are in line with accumulating anatomic and electrophysiologic evidence pointing to an evolutionary shift in the organization of the somatosensory system from the general mammalian plan, in which tactile information is processed in parallel in SI and SII, to a new organization in higher primates in which the processing of tactile information proceeds serially from SI to SII. The presumed functional advantages of this evolutionary shift are unknown.
We used simultaneous multi-site neural ensemble recordings to investigate the representation of tactile information in three areas of the primate somatosensory cortex (areas 3b, SII and 2). Small neural ensembles (30-40 neurons) of broadly tuned somatosensory neurons were able to identify correctly the location of a single tactile stimulus on a single trial, almost simultaneously. Furthermore, each of these cortical areas could use different combinations of encoding strategies, such as mean firing rate (areas 3b and 2) or temporal patterns of ensemble firing (area SII), to represent the location of a tactile stimulus. Based on these results, we propose that ensembles of broadly tuned neurons, located in three distinct areas of the primate somatosensory cortex, obtain information about the location of a tactile stimulus almost concurrently.
Recent attempts at high-resolution sensory-stimulated fMRI performed at 1.5 T have had very limited success at demonstrating a somatotopic organization for individual digits. Our purpose was to determine if functional MRI at 4 T can demonstrate the sensory somatotopic map of the human hand. Sensory functional MRI was performed at 4 T in five normal volunteers using a low-frequency vibratory stimulus on the pad of each finger of the left hand. A simple motor control task was also performed. The data were normalized to a standard atlas, and individual and group statistical parametric maps (SPMs) were computed for each task. Volume of activation and distribution of cluster maxima were compared for each task. For three of the subjects, the SPMs demonstrated a somatotopic organization of the sensory cortex. The group SPMs demonstrated a clear somatotopic organization of the sensory cortex. The thumb to fifth finger were organized, in general, with a lateral to medial, inferior to superior, and anterior to posterior relationship. There was overlap in the individual SPMs between fingers. The sensory activation spanned a space of 12-18 mm (thumb to fifth finger) on the primary sensory cortex. The motor activation occurred consistently at the superior-most extent of the sensory activation within and across subjects. The sensory somatotopic map of the human hand can be identified at 4 T. High-resolution imaging at 4 T can be useful for detailed functional imaging studies.
The flutter sensation is felt when mechanical vibrations between 5 and 50 Hz are applied to the skin. Neurons with rapidly adapting properties in the somatosensory system of primates are driven very effectively by periodic flutter stimuli; their evoked spike trains typically have a periodic structure with highly regular time differences between spikes. A long-standing conjecture is that, such periodic structure may underlie a subject's capacity to discriminate the frequencies of periodic vibrotactile stimuli and that, in primary somatosensory areas, stimulus frequency is encoded by the regular time intervals between evoked spikes, not by the mean rate at which these are fired. We examined this hypothesis by analyzing extracellular recordings from primary (S1) and secondary (S2) somatosensory cortices of awake monkeys performing a frequency discrimination task. We quantified stimulus-driven modulations in firing rate and in spike train periodicity, seeking to determine their relevance for frequency discrimination. We found that periodicity was extremely high in S1 but almost absent in S2. We also found that periodicity was enhanced when the stimuli were relevant for behavior. However, periodicity did not covary with psychophysical performance in single trials. On the other hand, rate modulations were similar in both areas, and with periodic and aperiodic stimuli, they were enhanced when stimuli were important for behavior, and were significantly correlated with psychophysical performance in single trials. Thus, the exquisitely timed, stimulus-driven spikes of primary somatosensory neurons may or may not contribute to the neural code for flutter frequency, but firing rate seems to be an important component of it.
Optical imaging of intrinsic cortical activity was used to study the somatotopic map and the representation of pressure, flutter, and vibration in area 3b of the squirrel monkey (Saimiri sciureus) cortex under pentothal or isoflurane anesthesia. The representation of the fingerpads in primary somatosensory cortex was investigated by stimulating the glabrous skin of distal fingerpads (D1-D5) with Teflon probes (3-mm diam) attached through an armature to force feedback-controlled torque motors. Under pentothal anesthesia, intrinsic signal maps in area 3b obtained in response to stimulation (trapezoidal indentation) of individual fingerpads showed focal activations. These activations (ranging from 0.5 to 1.0 mm) were discrete and exhibited minimal overlap between adjacent fingerpad representations. Consistent with previously published maps, a somatotopic representation of the fingerpads was observed with an orderly medial to lateral progression from the D5 to D1 fingerpads. Under isoflurane anesthesia, general topography was still maintained, but the representation of fingerpads on adjacent fingers had higher degrees of overlap than with pentothal anesthesia. Multi- and single-unit recordings in the activation zones confirmed the somatotopic maps. To examine preferential inputs from slowly adapting type I (SA) and rapidly adapting type I (RA) and type II (PC) mechanoreceptors, we applied stimuli consisting of sinusoidal indentations that produce sensations of pressure (1 Hz), flutter (30 Hz), and vibration (200 Hz). Under pentothal anesthesia, activation patterns to these different stimuli were focal and coincided on the cortex. Under isoflurane, activation zones from pressure, flutter, and vibratory stimuli differed in size and shape and often contained multiple foci, although overall topography was maintained. Subtraction and vector maps revealed cortical areas (approximate 250-microm diam) that were preferentially activated by the sensations of pressure, flutter, and vibration. Multi- and single-unit recordings aided in the interpretation of the imaging maps. In conclusion, the cortical signals observed with intrinsic signal optical imaging delineated a somatotopic organization of area 3b and revealed different topographical cortical activation patterns for pressure, flutter, and vibratory stimuli. These patterns were dependent on anesthesia type. Possible relationships of these anesthesia effects to somatosensory cortical plasticity are discussed.
The sensations of pressure, flutter, and vibration are psychophysically distinct tactile modalities produced by frequency-specific vibrotactile stimulation of different mechanoreceptors in the skin. The information coded by the different low-threshold mechanoreceptors are carried by anatomically and electrophysiologically distinct pathways that remain separate at least up to and including the input stage of primary somatosensory cortex (SI) in primates, area 3b. Little is known about the functional organization of tactile representation beyond that stage. By using intrinsic optical imaging methods to record from area 1, the second processing stage of SI, we present evidence that pressure, flutter, and vibratory stimuli activate spatially distinct cortical domains in area 1, further strengthening the foundation for modality-specific processing streams in SI. These modality domains exhibit an organization that is unlike the discontinuous modality maps in visual area V2 but more like the continuous visual orientation maps in V1. The results demonstrate that psychophysically distinct sensory modalities can have fundamentally different modes of cortical representation.
The present functional magnetic resonance imaging (fMRI) study investigated human brain regions subserving the discrimination of vibrotactile frequency. An event-related adaptation paradigm was used in which blood-oxygen-level-dependent (BOLD) responses are lower to same compared with different pairs of stimuli (BOLD adaptation). This adaptation effect serves as an indicator for feature-specific responding of neuronal subpopulations. Subjects had to discriminate two vibrotactile stimuli sequentially applied with a delay of 600 ms to their left middle fingertip. The stimulus frequency was in the flutter range of 18-26 Hz. In half of the trials, the two stimuli possessed identical frequency (same), whereas in the other half, a frequency difference of +/-2 Hz was used (diff). As a result, BOLD adaptation was observed in the contralateral primary somatosensory cortex (S1), precentral gyrus, superior temporal gyrus (STG); ipsilateral insula as well as bilateral secondary somatosensory cortex and supplementary motor area. When statistically comparing the BOLD time courses between same and diff trials in these cortical areas, it was found that the vibrotactile BOLD adaptation is initiated in the contralateral S1 and STG simultaneously. These findings suggest that the cortical areas responsive to the frequency difference between two serially presented stimuli sequentially process the frequency of a vibrotactile stimulus and constitute a putative neuronal network underlying human vibrotactile frequency discrimination.
Characterizing the cortical representation of the body surface is fundamental to understanding the neural basis of human somatic
sensation. Monkey studies benefited from the detailed somatotopic maps obtained from electrophysiology methods. Advances in
noninvasive neuroimaging techniques now permit such questions to be probed in humans. The present study characterizes the
detailed somatotopic representation of individual digits within subregions of the postcentral gyrus in humans using high-spatial
resolution functional magnetic resonance imaging and surface-based mapping. Four areas of consistent activation included area
3b, area 2, and 2 discrete foci within area 1. Area 3b and the superior area 1 foci demonstrated an orderly somatotopic distribution
for all digits of the hand, whereby the thumb was represented most lateral, anterior, and inferior and the fifth digit was
most medial, posterior, and superior. Compared with area 3b, somatotopic variability was greater in area 1 and the digits
spanned less cortical territory. This study additionally identified the specific digit pairs that are separable in areas 3b
and 1 using current imaging methods. Somatotopy was not resolved in area 2 or in the inferior area 1 foci.
Fine-scale functional organization of the finger areas in the human primary somatosensory cortex was investigated by high-resolution BOLD MRI at 3 T using a multi-echo FLASH sequence with a voxel size of 2 mm(3). In six subjects independent tactile stimulation of the distal phalanx of the fingers of the right hand resulted in small circumscribed and barely overlapping activations precisely located along the posterior wall of the central sulcus. Three out of six subjects showed a complete succession of activation sites for all five fingers. The maps also allowed for the identification of individual variations in finger somatotopy. When registered onto the individual high-resolution MRI anatomy and compared with cytoarchitectonical maps, the finger representations were confirmed to lie within Brodmann area 3b as the main input region of the primary somatosensory cortex.
This fMRI study investigated the human somatosensory system, especially the secondary somatosensory cortex (SII), with respect to its potential somatotopic organization. Eight subjects received electrical stimulation on their right second finger, fifth finger and hallux. Within SII, the typical finding for both fingers was a representation site within the contralateral parietal operculum roughly halfway between the lip of the lateral sulcus and its fundus, whereas the representation site of the hallux was found more medially to this position at the fundus of the lateral sulcus, near the posterior pole of the insula. Somatotopy in SII seems to be less fine-grained than in primary somatosensory cortex (SI), as, in contrast to SI, no separate representations of the two fingers in SII were observed. A similar somatotopic representation pattern between fingers and the hallux was also observed within ipsilateral SII, indicating somatotopy of contra- as well as ipsilateral SII using unilateral stimulation. Further areas exhibiting activation were found in the superior and inferior parietal lobule, in the supplementary and cingulate motor area, and in the insula.
Exploration of neural sources and their effective connectivity based on transient changes in electrophysiological activities to external stimuli is important for understanding brain mechanisms of sensory information processing. However, such cortical mechanisms have not yet been well characterized in electrophysiological studies since (1) it is difficult to estimate the stimulus-activated neural sources and their activities and (2) it is difficult to identify transient effective connectivity between neural sources in the order of milliseconds. To address these issues, we developed a time-varying source connectivity approach to effectively capture fast-changing information flows between neural sources from high-density Electroencephalography (EEG) recordings. This time-varying source connectivity approach was applied to somatosensory evoked potentials (SEPs), which were elicited by electrical stimulation of right hand and recorded using 64 channels from 16 subjects, to reveal human somatosensory information processing. First, SEP sources and their activities were estimated, both at single-subject and group level, using equivalent current dipolar source modeling. Then, the functional integration among SEP sources was explored using a Kalman smoother based time-varying effective connectivity inference method. The results showed that SEPs were mainly generated from the contralateral primary somatosensory cortex (SI), bilateral secondary somatosensory cortex (SII), and cingulate cortex (CC). Importantly, we observed a serial processing of somatosensory information in human somatosensory cortices (from SI to SII) at earlier latencies (<150 ms) and a reciprocal processing between SII and CC at later latencies (>200 ms).
We investigated to which extent the discrimination of tactile patterns and vibrotactile frequencies share common cortical areas. An adaptation paradigm has been used to identify cortical areas specific for processing particular features of tactile stimuli. Healthy right-handed subjects performed a delayed-match-to-sample (DMTS) task discriminating between pairs of tactile patterns or vibrotactile frequencies in separate functional MRI sessions. The tactile stimuli were presented to the right middle fingertip sequentially with a 5.5 s delay. Regions of interest (ROIs) were defined by cortical areas commonly activated in both tasks and those that showed differential activation between both tasks. Results showed recruitment of many common brain regions along the sensory motor pathway (such as bilateral somatosensory, premotor areas, and anterior insula) in both tasks. Three cortical areas, the right intraparietal sulcus (IPS), supramarginal gyrus (SMG)/parietal operculum (PO), and PO, were significantly more activated during the pattern than in the frequency task. Further BOLD time course analysis was performed in the ROIs. Significant BOLD adaptation was found in bilateral IPS, right anterior insula, and SMG/PO in the pattern task, whereas there was no significant BOLD adaptation found in the frequency task. In addition, the right hemisphere was found to be more dominant in the pattern than in the frequency task, which could be attributed to the differences between spatial (pattern) and temporal (frequency) processing. From the different spatio-temporal characteristics of BOLD activation in the pattern and frequency tasks, we concluded that different neuronal mechanisms are underlying the tactile spatial and temporal processing.
Bayesian model selection (BMS) is a powerful method for determining the most likely among a set of competing hypotheses about the mechanisms that generated observed data. BMS has recently found widespread application in neuroimaging, particularly in the context of dynamic causal modelling (DCM). However, so far, combining BMS results from several subjects has relied on simple (fixed effects) metrics, e.g. the group Bayes factor (GBF), that do not account for group heterogeneity or outliers. In this paper, we compare the GBF with two random effects methods for BMS at the between-subject or group level. These methods provide inference on model-space using a classical and Bayesian perspective respectively. First, a classical (frequentist) approach uses the log model evidence as a subject-specific summary statistic. This enables one to use analysis of variance to test for differences in log-evidences over models, relative to inter-subject differences. We then consider the same problem in Bayesian terms and describe a novel hierarchical model, which is optimised to furnish a probability density on the models themselves. This new variational Bayes method rests on treating the model as a random variable and estimating the parameters of a Dirichlet distribution which describes the probabilities for all models considered. These probabilities then define a multinomial distribution over model space, allowing one to compute how likely it is that a specific model generated the data of a randomly chosen subject as well as the exceedance probability of one model being more likely than any other model. Using empirical and synthetic data, we show that optimising a conditional density of the model probabilities, given the log-evidences for each model over subjects, is more informative and appropriate than both the GBF and frequentist tests of the log-evidences. In particular, we found that the hierarchical Bayesian approach is considerably more robust than either of the other approaches in the presence of outliers. We expect that this new random effects method will prove useful for a wide range of group studies, not only in the context of DCM, but also for other modelling endeavours, e.g. comparing different source reconstruction methods for EEG/MEG or selecting among competing computational models of learning and decision-making.
Microelectrode mapping experiments indicate that the classical primary somatosensory cortex of monkeys consists of as many as four separate body representations rather than just one. Two complete body surface representations occupy cortical fields 3b and 1. In addition, area 2 contains an orderly representation of predominantly "deep" body tissues. Area 3a may constitute a fourth representation.
To describe a clinically useful application of functional magnetic resonance (MR) imaging--presurgical mapping of the sensory motor cortex--and to validate the results with established physiologic techniques.
Functional MR mapping of the sensory motor cortex was performed in two women, aged 24 and 38 years. Both had intractable, simple partial motor seizures due to tumors located in or near the sensory motor cortex. They subsequently underwent invasive cortical mapping--direct cortical stimulation and/or sensory-evoked-potential recording--to localize the affected sensory motor area prior to tumor resection.
In both patients, the functional MR study demonstrated task activation of the sensory motor cortex. In both cases, results of cortical functional mapping with invasive techniques matched those obtained with functional MR imaging.
Presurgical mapping of the sensory motor cortex is a potentially useful clinical application of functional MR imaging.
Our understanding of the functional organization of somatosensory cortex and thalamus in primates and other mammals has greatly increased over the last few years. It is now clear that higher primates have four strip-like representations of skin and muscle receptors corresponding to areas 3 a, 3b, 1 and 2 of anterior parietal cortex. Areas 3b and 1 receive cutaneous information from the ventroposterior nucleus, while a ventroposterior superior nucleus provides areas 3a and 2 with information from muscle receptors. Area 3b is the homolog of S-I in prosimians and non-primates and it provides most of the activating cutaneous inputs to areas 1 and 2. Most of the further processing that allows tactile recognition of objects involves somatosensory areas of the lateral sulcus, where both S-II and the parietal ventral area (PV) receive activating inputs from areas 3a, 3b, 1 and 2. S-II also projects to PV and to a parietal rostral area where further connections with the amygdala and hippocampus may occur to allow the formation of tactile memories. Areas of anterior parietal cortex also project to posterior parietal cortex, where regions of cortex are largely somatosensory, but the functional subdivisions remain uncertain. All of the somatosensory fields have access to motor areas of the frontal lobe, but the magnitude and targets of the projections differ.
1. The two principal tactile processing areas in the cerebral cortex, somatosensory areas I and II, receive direct projections from the thalamus and, as well, are linked through intracortical reciprocal connections. Tactile information may therefore be conveyed to SII, for example, over either a direct path from the thalamus or an indirect, or serial, path from the thalamus via SI.
2. Reports in recent years that tactile responsiveness within the hand area of SII was abolished by surgical ablation of the hand area of the postcentral, or SI, area of cortex in the macaque and marmoset monkeys indicated that a serial processing scheme may operate, at least in primates.
However, as the surgical ablation is clearly irreversible and precludes examination of individual SII neurons in both the control and test circumstances, that is, when SI is intact and when it is inactivated, we have examined in the cat, the rabbit and the marmoset monkey the behaviour of SII neurons before, during and after the selective, rapidly-reversible inactivation of SI by means of localized cooling.
3. The results demonstrate that in the cat and rabbit, SII responsiveness is never abolished and infrequently affected by SI inactivation and that tactile inputs to SII therefore traverse a direct path from thalamus, organized in parallel with that to SI. In the marmoset (Callithrix jacchus), in contrast to earlier studies based on ablation of SI we found that with reversible inactivation of SI, SII responsiveness was unaffected in 25% of neurons and, although reduced in the remainder, was rarely abolished (<10% of SII neurons).
4. The results indicate that there is substantial direct thalamic input to SII, even in this simian primate, and therefore necessitate revision of the hypothesis that tactile processing at the thalamocortical level in simian primates is based on a strict serial scheme in which tactile information is conveyed from the thalamus to SI and thence to SII.
Eight right-handed adult humans underwent functional magnetic resonance imaging (fMRI) of their brain while a vibratory stimulus was applied to an individual digit tip (digit 1, 2, or 5) on the right hand. Multislice echoplanar imaging techniques were utilized during digit stimulation to investigate the organization of the human primary somatosensory (SI) cortex, cortical regions located on the upper bank of the Sylvian fissure (SII region), insula, and posterior parietal cortices. The t test and cluster size analyses were performed to produce cortical activation maps, which exhibited significant regions of interest (ROIs) in all four cortical regions investigated. The frequency of significant ROIs was much higher in SI and the SII region than in the insula and posterior parietal region. Multiple digit representations were observed in the primary somatosensory cortex, corresponding to the four anatomic subdivisions of this cortex (areas 3a, 3b, 1, and 2), suggesting that the organization of the human somatosensory cortex resembles that described in other primates. Overall, there was no simple medial to lateral somatotopic representation in individual subject activity maps. However, the spatial distance between digit 1 and digit 5 cortical representations was the greatest in both SI and the SII region within the group. Statistical analyses of multiple activity parameters showed significant differences between cortical regions and between digits, indicating that vibrotactile activations of the cortex are dependent on both the stimulated digit and cortical region investigated.
Sensory stimuli from the visceral domain exhibit perceptual characteristics different from stimuli applied to the body surface. Compared with somatosensation there is not much known about the cortical projection and functional organization of visceral sensation in humans. In this study, we determined the cortical areas activated by non-painful electrical stimulation of visceral afferents in the distal oesophagus, and somatosensory afferents in the median nerve and the lip in seven healthy volunteers using whole-head magnetoencephalography. Stimulation of somatosensory afferents elicited short-latency responses (approximately 20-60 ms) in the primary somatosensory cortex (SI) contralateral (median nerve) or bilateral (lip) to the stimulated side, and long-latency responses (approximately 60-160 ms) bilaterally in the second somatosensory cortex (SII). In contrast, stimulation of visceral oesophageal afferents did not evoke discernible responses in SI but well reproducible bilateral SII responses (approximately 70-190 ms) in close vicinity to long-latency SII responses following median nerve and lip stimuli. Psychophysically, temporal discrimination of successive stimuli became worse with increasing stimulus repetition rates (0.25 Hz, 0.5 Hz, 1 Hz, 2 Hz) only for visceral oesophageal, but not for somatosensory median nerve stimuli. Correspondingly, amplitudes of the first cortical response to oesophageal stimulation emerging in the SII cortex declined with increasing stimulus repetition rates whereas the earliest cortical response elicited by median nerve stimuli (20 ms SI response) remained unaffected by the stimulus frequency. Our results indicate that visceral afferents from the oesophagus primarily project to the SII cortex and, unlike somatosensory afferents, lack a significant SI representation. We propose that this cortical projection pattern forms the neurophysiological basis of the low temporal and spatial resolution of conscious visceral sensation.
This study defines cytoarchitectonic areas 3a, 3b, and 1 of the human primary somatosensory cortex by objective delineation of cytoarchitectonic borders and ensuing cytoarchitectonic classification. This avoids subjective evaluation of microstructural differences which has so far been the only way to structurally define cortical areas. Ten brains were fixed in formalin or Bodian's fixative, embedded in paraffin, sectioned as a whole in the coronal plane at 20 microm, and cell stained. Cell bodies were segmented from the background by adaptive thresholding. Equidistant density profiles (125 microm wide, spacing 300 or 150 microm) were extracted perpendicularly to the pial surface across cortical layers II-VI and processed with multivariate statistical procedures. Positions of significant differences in shape between adjacent groups of profiles were correlated with the cytoarchitectonic pattern. Statistically significant borders can be reproduced at corresponding positions across a series of nearby sections. They match visible changes in cytoarchitecture in the cell-stained sections. Area 3a lies in the fundus of the central sulcus, and area 3b in the rostral bank of the postcentral gyrus. Area 1 lies on its crown and reaches down into the postcentral sulcus. Interareal borders, however, do not match macrostructural landmarks of the postcentral gyrus, and they considerably vary in their positions relative to these landmarks across different brains. Hence, only genuine microstructural analysis can define the borders between these cortical areas. Additional significant borders which do not correlate with visible changes in cytoarchitecture can be found within areas 3b and 1. They may represent somatotopy and/or cortical representations of different somatosensory receptors.
Three studies were carried out to assess the applicability of fMRI at 3.0 T to analysis of vibrotaction in humans. A novel piezoelectric device provided clean sinusoidal stimulation at 80 Hz, which was initially applied in separate runs within a scanning session to digits 2 and 5 of the left hand in eight subjects, using a birdcage RF (volume) coil. Significant clusters of activation were found in the primary somatosensory cortex (SI), the secondary somatosensory cortex (SII), subcentral gyrus, the precentral gyrus, posterior insula, posterior parietal regions (area 5), and the posterior cingulate. Digit separation in SI was possible in all subjects and the activation sites reflected the known lateral position of the representation of digit 2 relative to that of digit 5. A second study carried out in six additional subjects using a surface coil, replicated the main contralateral activation patterns detected in study one and further improved the discrimination of the digits in SI. Significant digit separation was also found in SII and in the posterior insula. A third study to investigate the frequency dependence of the response focused on the effect of an increase in vibrotactile frequency from 30 to 80 Hz, with both frequencies applied to digit 2 during the same scanning session in four new subjects. A significant increase in the number of pixels activated within both SII and the posterior insula was found, while the number of pixels activated in SI declined. No significant change in signal intensity with frequencies was found in any of the activated areas.
Using electrical finger nerve stimulation in normal human subjects, fMRI detected separate representations for all 5 fingers in the primary somatosensory cortex. Responses were located in the posterior wall of the deep central sulcus (most likely corresponding to Brodmann Area (BA) 3b), and the anterior (BA 1) or posterior crown of the postcentral gyrus (BA 2) with rare activations in BA 3a and 4. In BA 3b we found a regular somatotopic mediolateral digit arrangement for fingers 5 to 1 with a mean Euclidean distance of 16 mm between fingers 1 and 5. In contrast BA 1/2 showed a greater number of adjacent activation foci with significantly more overlap and partly even reversed ordering of neighbouring fingers.
Interindividual topographical variability of cytoarchitectonically defined somatosensory areas 3a, 3b, and 1 was analyzed in the standard anatomical format of a computerized brain atlas. T1-weighted magnetic resonance images were obtained from 10 postmortem brains. The brains were serially sectioned at 20 mcm, sections were stained for cell bodies, and areas 3a, 3b, and 1 were defined with an observer-independent cytoarchitectonic technique. After correction of the sections for deformations due to histological processing, the 3-D reconstructed histological volumes of the individual brains and the volume representations of the cytoarchitectonic areas were adapted to the reference brain of a computerized atlas. Corresponding areas were superimposed in the 3-D space of the reference brain. These population maps describe, for each voxel, how many brains have a representation of one particular cytoarchitectonic area. Each area's extent is very variable across different brains, but representations of areas 3a, 3b, and 1 in >/=50% of the brains were found in the fundus of the central sulcus, its caudal bank, and on the crown of the postcentral gyrus, respectively. Volumes of interest (VOIs) were defined for each area in which >/=50% of the brains have a representation of that area. Despite close spatial relationship of areas 3a, 3b, and 1 in the postcentral gyrus, the three VOIs overlap by <1% of their volumes. Functional imaging data can now be brought into the same standard anatomical format, and changes in regional cerebral blood flow can be calculated in VOIs of areas 3a, 3b, and 1, which are derived from genuine cytoarchitectonic data.
Vibratory stimuli on the skin are mediated by two major receptors: Meissner corpuscles and Pacinian corpuscles. These receptors differ in properties such as density distribution, receptive field size, frequency sensitivity and depth of location. The cortical response to stimulation of these corpuscles can be tested by taking advantage of the differences in frequency discrimination of the receptors. Meissner corpuscles are most sensitive to frequencies around 10-50 Hz (flutter), while Pacinian corpuscles are most sensitive to high frequency (100-300 Hz) vibration. This study compared the neuronal responses (hemodynamic response) generated from vibratory stimuli of 35 Hz and 150 Hz with functional MRI. Group functional activation maps showed differences in the activation pattern for the two stimulus frequencies.
This fMRI study investigated the human somatosensory system, especially the secondary somatosensory cortex (SII), with respect to its potential somatotopic organization. Eight subjects received electrical stimulation on their right second finger, fifth finger and hallux. Within SII, the typical finding for both fingers was a representation site within the contralateral parietal operculum roughly halfway between the lip of the lateral sulcus and its fundus, whereas the representation site of the hallux was found more medially to this position at the fundus of the lateral sulcus, near the posterior pole of the insula. Somatotopy in SII seems to be less fine-grained than in primary somatosensory cortex (SI), as, in contrast to SI, no separate representations of the two fingers in SII were observed. A similar somatotopic representation pattern between fingers and the hallux was also observed within ipsilateral SII, indicating somatotopy of contra- as well as ipsilateral SII using unilateral stimulation. Further areas exhibiting activation were found in the superior and inferior parietal lobule, in the supplementary and cingulate motor area, and in the insula.
In this paper we present an approach to the identification of nonlinear input-state-output systems. By using a bilinear approximation to the dynamics of interactions among states, the parameters of the implicit causal model reduce to three sets. These comprise (1) parameters that mediate the influence of extrinsic inputs on the states, (2) parameters that mediate intrinsic coupling among the states, and (3) [bilinear] parameters that allow the inputs to modulate that coupling. Identification proceeds in a Bayesian framework given known, deterministic inputs and the observed responses of the system. We developed this approach for the analysis of effective connectivity using experimentally designed inputs and fMRI responses. In this context, the coupling parameters correspond to effective connectivity and the bilinear parameters reflect the changes in connectivity induced by inputs. The ensuing framework allows one to characterise fMRI experiments, conceptually, as an experimental manipulation of integration among brain regions (by contextual or trial-free inputs, like time or attentional set) that is revealed using evoked responses (to perturbations or trial-bound inputs, like stimuli). As with previous analyses of effective connectivity, the focus is on experimentally induced changes in coupling (cf., psychophysiologic interactions). However, unlike previous approaches in neuroimaging, the causal model ascribes responses to designed deterministic inputs, as opposed to treating inputs as unknown and stochastic.
Correlating the activation foci identified in functional imaging studies of the human brain with structural (e.g., cytoarchitectonic) information on the activated areas is a major methodological challenge for neuroscience research. We here present a new approach to make use of three-dimensional probabilistic cytoarchitectonic maps, as obtained from the analysis of human post-mortem brains, for correlating microscopical, anatomical and functional imaging data of the cerebral cortex. We introduce a new, MATLAB based toolbox for the SPM2 software package which enables the integration of probabilistic cytoarchitectonic maps and results of functional imaging studies. The toolbox includes the functionality for the construction of summary maps combining probability of several cortical areas by finding the most probable assignment of each voxel to one of these areas. Its main feature is to provide several measures defining the degree of correspondence between architectonic areas and functional foci. The software, together with the presently available probability maps, is available as open source software to the neuroimaging community. This new toolbox provides an easy-to-use tool for the integrated analysis of functional and anatomical data in a common reference space.
The human secondary somatosensory cortex (SII) is located on the parietal operculum, as shown by intraoperative stimulation and functional imaging studies. The position and extent of the anatomical correlates of this functionally defined region, however, are still unknown. We have therefore histologically mapped the putative anatomical correlates of the SII cortex in cell-body-stained histological sections of 10 human postmortem brains using quantitative cytoarchitectonic analysis. The gray level index (GLI), which is an indicator of the volume fraction of nerve cell bodies, was measured in the parietal operculum. GLI profiles as measures of the laminar pattern of the cortex were extracted perpendicular to cortical layers. Cytoarchitectonic borders were detected observer-independently by multivariate statistical analysis of the laminar profiles. Four cytoarchitectonic areas (termed OP 1-4) were identified. This cytoarchitectonic heterogeneity of the parietal operculum corresponds to results of functional imaging studies on the human SII cortex and data from non-human primates where multiple subregions within SII have been demonstrated by electrophysiological and connectivity studies.
In this study we describe the localization of the cytoarchitectonic subdivisions of the human parietal operculum in stereotaxic space and relate these anatomically defined cortical areas to the location of the functionally defined secondary somatosensory cortex (SII cortex) using a meta-analysis of functional imaging results. The human parietal operculum consists of four distinct cytoarchitectonic areas (OP 1-4) as shown in the preceding publication. The 10 cytoarchitectonically examined brains were 3-D-reconstructed and spatially normalized to the T1-weighted single-subject template of the Montreal Neurological Institute (MNI). A probabilistic map was calculated for each area in this standard stereotaxic space. A cytoarchitectonic summary map of the four cortical areas on the human parietal operculum which combines these probabilistic maps was subsequently computed for the comparison with a meta-analysis of functional locations of SII. The meta-analysis used the results from 57 fMRI and PET studies and allowed the comparison of the functionally defined SII region to the cytoarchitectonic map of the parietal operculum. The functional localization of SII showed a good match to the cytoarchitectonically defined region. Therefore the cytoarchitectonic maps of OP 1-4 of the human parietal operculum can be interpreted as an anatomical correlate of the (functionally defined) human SII region. Our results also suggest that the SII foci reported in functional imaging studies may actually reflect activations in either of its architectonic subregions.
Comparing families of dynamic causal models Reward facilitates tactile judgments and modulates hemodynamic responses in human primary somatosen-sory cortex
- W D Penny
- K E Stephan
- J Daunizeau
- M J Rosa
- K J Friston
- T M Schofield
- A P Leff
Penny, W.D., Stephan, K.E., Daunizeau, J., Rosa, M.J., Friston, K.J., Schofield, T.M., Leff, A.P., 2010. Comparing families of dynamic causal models. PLoS Comput. Biol. 6 (3), e1000709. Pleger, B., Blankenburg, F., Ruff, C., Driver, J., Dolan, R., 2008. Reward facilitates tactile judgments and modulates hemodynamic responses in human primary somatosen-sory cortex. J. Neurosci. 28, 8161–8168.