Brain Structure and Function

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Interaction effect between sex and salivary oxytocin levels on the amygdala volume The amygdala volume was divided by the intracranial volume, and controlled for age. Salivary oxytocin levels (pg/mL) were log-transformed. Regression lines are shown with 95% confidence intervals (shaded areas)
  • Qiulu ShouQiulu Shou
  • Junko YamadaJunko Yamada
  • Kuniyuki NishinaKuniyuki Nishina
  • [...]
  • Haruto TakagishiHaruto Takagishi
Salivary oxytocin levels have been widely measured and studied in relation to social behavior because of procedural simplicity and noninvasiveness. Although the relationship between oxytocin levels in the blood and the hippocampus and amygdala is now becoming clear with reliable blood oxytocin studies, few studies have examined the relationship between salivary oxytocin and the brain function and structure. This study aimed to investigate whether the salivary oxytocin level is associated with the volume of the amygdala and hippocampus in 178 adults (92 women and 86 men) in their third to seventh decade of life. We performed volumetric analysis of the amygdala and hippocampus using FreeSurfer and measured salivary oxytocin levels using enzyme-linked immunosorbent assay. The results showed contradictory effects of the salivary oxytocin level on the amygdala volume by sex and no significant effect on the hippocampal volume. Specifically, men showed a positive correlation between the salivary oxytocin level and amygdala volume, whereas women showed a negative correlation between the salivary oxytocin level and amygdala volume. The present study’s finding of sex differences in the association between salivary oxytocin and brain structure supports previous findings that there are sex differences in the oxytocin system.
  • Edith Sánchez-JaramilloEdith Sánchez-Jaramillo
  • Gábor WittmannGábor Wittmann
  • Judit MenyhértJudit Menyhért
  • [...]
  • Ronald M. LechanRonald M. Lechan
Hypophysiotropic thyrotropin-releasing hormone (TRH) neurons function as metabolic sensors that regulate the thyroid axis and energy homeostasis. Less is known about the role of other hypothalamic TRH neurons. As central administration of TRH decreases food intake and increases histamine in the tuberomammillary nuclei (TMN), and TMN histamine neurons are densely innervated by TRH fibers from an unknown origin, we mapped the location of TRH neurons that project to the TMN. The retrograde tracer, cholera toxin B subunit (CTB), was injected into the TMN E1–E2, E4–E5 subdivisions of adult Sprague–Dawley male rats. TMN projecting neurons were observed in the septum, preoptic area, bed nucleus of the stria terminalis (BNST), perifornical area, anterior paraventricular nucleus, peduncular and tuberal lateral hypothalamus (TuLH), suprachiasmatic nucleus and medial amygdala. However, CTB/pro-TRH178-199 double-labeled cells were only found in the TuLH. The specificity of the retrograde tract-tracing result was confirmed by administering the anterograde tracer, Phaseolus vulgaris leuco-agglutinin (PHAL) into the TuLH. Double-labeled PHAL-pro-TRH boutons were identified in all subdivisions of the TMN. TMN neurons double-labeled for histidine decarboxylase ( Hdc )/PHAL, Hdc / Trh receptor ( Trhr ), and Hdc / Trh . Further confirmation of a TuLH-TRH neuronal projection to the TMN was established in a transgenic mouse that expresses Cre recombinase in TRH-producing cells following microinjection of a Cre recombinase-dependent AAV that expresses mCherry into the TuLH. We conclude that, in rodents, the TRH innervation of TMN originates in part from TRH neurons in the TuLH, and that this TRH population may contribute to regulate energy homeostasis through histamine Trhr- positive neurons of the TMN.
The relationship between structural variability in late-developing association cortices like the lateral prefrontal cortex (LPFC) and the development of higher-order cognitive skills is not well understood. Recent findings show that the morphology of LPFC sulci predicts reasoning performance; this work led to the observation of substantial individual variability in the morphology of one of these sulci, the para-intermediate frontal sulcus (pimfs). Here, we sought to characterize this variability and assess its behavioral significance. To this end, we identified the pimfs in a developmental cohort of 72 participants, ages 6–18. Subsequent analyses revealed that the presence or absence of the ventral component of the pimfs was associated with reasoning, even when controlling for age. This finding shows that the cortex lining the banks of sulci can support the development of complex cognitive abilities and highlights the importance of considering individual differences in local morphology when exploring the neurodevelopmental basis of cognition.
Graphical summary of the modularity analyses, using real data from three randomly selected participants. Individualized semantic networks (ISNs) were localized using a Semantic Decision fMRI task (Wilson et al. 2018). First-level modularity analysis was then performed using structural connectivity data (diffusion imaging) to investigate community structure of each participant’s ISN. To enable comparisons across ISNs, consensus clustering (Lancichinetti and Fortunato 2012) was used, assigning each node to a consensus [group-level] module. Finally, the mean functional connectivity was calculated within and between each of the consensus modules in each participant’s ISN using data from a naturalistic resting-state scan
Consistency of task activation for defining semantic network. a Mean voxelwise activation projected onto a standardized brain. Here, we show the mean T values across participants rather than p-values because we are interested in activation at the individual level. b Nodewise activation in all 53 participants (T values). Each row represents 1 node and each column represents 1 participant. Nodes are sorted by brain lobe according to labels at left (gray box is subcortical). While there are areas of consistent activation in left frontal, temporal, and parietal lobe, there is notable interindividual variability. c Correlation of participants’ activation patterns (Pearson’s r). Correlations were calculated between each pair of participants and averaged to give a mean correlation of each individual to the rest of the group. Two participants were markedly different from the rest of the group (r < .5) and were found to be right-lateralized for language (first 2 columns in b); these participants were excluded from future analyses. Overall correlation between individuals was r = .717 including the 2 right-lateralized individuals, and r = .727 after exclusion (R² = .523)
Structural hubs in the semantic network. The size of nodes depicts the number of participants in whom the node was a hub. Nodes in red were found to be hubs in at least 15 participants. For a full list of all nodes identified as hubs, see Table S2
Consensus modules visualized on a model brain. Nodes are color-coded according to module assignment. Node size is proportional to frequency of occurrence of that node in ISNs. Full details are available in Table S1. The top row shows lateral view; the bottom row shows medial view; and the middle image shows dorsal view
Average functional connectivity within and across structurally derived consensus modules. FC within modules was greater than connectivity across modules (P < .001), and within-module1 connectivity was lower than within-module2. (P < .01); **P < .01; ***P < .001
Language function in the brain, once thought to be highly localized, is now appreciated as relying on a connected but distributed network. The semantic system is of particular interest in the language domain because of its hypothesized integration of information across multiple cortical regions. Previous work in healthy individuals has focused on group-level functional connectivity (FC) analyses of the semantic system, which may obscure interindividual differences driving variance in performance. These studies also overlook the contributions of white matter networks to semantic function. Here, we identified semantic network nodes at the individual level with a semantic decision fMRI task in 53 typically aging adults, characterized network organization using structural connectivity (SC), and quantified the segregation and integration of the network using FC. Hub regions were identified in left inferior frontal gyrus. The individualized semantic network was composed of three interacting modules: (1) default-mode module characterized by bilateral medial prefrontal and posterior cingulate regions and also including right-hemisphere homotopes of language regions; (2) left frontal module extending dorsally from inferior frontal gyrus to pre-motor area; and (3) left temporoparietal module extending from temporal pole to inferior parietal lobule. FC within Module3 and integration of the entire network related to a semantic verbal fluency task, but not a matched phonological task. These results support and extend the tri-network semantic model (Xu in Front Psychol 8: 1538 1538, 2017) and the controlled semantic cognition model (Chiou in Cortex 103: 100 116, 2018) of semantic function.
T1 MRI scans of the three patients in the native space
Reconstructions in native space of the principal tracts of interest in the left (L) hemisphere and in the right (R) hemisphere. Note the loss of fibers in left-hemisphere SLF in all the patients, as well as the caudal loss of fibers in the IFOF and ILF bundles in P1. Red: superior longitudinal fasciculus; green: inferior fronto-occipital fasciculus; blue: inferior longitudinal fasciculus; R: right; L: left
Spatial neglect usually concerns left-sided events after right-hemisphere damage. Its anatomical correlates are debated, with evidence suggesting an important role for fronto-parietal white matter disconnections in the right hemisphere. Here, we describe the less frequent occurrence of neglect for right-sided events, observed in three right-handed patients after a focal stroke in the left hemisphere. Patients were tested 1 month and 3 months after stroke. They performed a standardized paper-and-pencil neglect battery and underwent brain MRI with both structural and diffusion tensor (DT) sequences, in order to assess both grey matter and white matter tracts metrics. Lesions were manually reconstructed for each patient. Patients presented signs of mild right-sided neglect during visual search and line bisection. One patient also showed pathological performance in everyday life. Structural MRI demonstrated left parietal strokes in two patients, in the region extending from the postcentral gyrus to the temporo-parietal junction. One of these two patients also had had a previous occipital stroke. The remaining patient had a left frontal stroke, affecting the precentral, the postcentral gyri and the basal ganglia. DT MRI tractography showed disconnections in the fronto-parietal regions, concerning principally the superior longitudinal fasciculus (SLF). These results suggest an important role for left SLF disconnection in right-side neglect, which complements analogous evidence for right SLF disconnection in left-side neglect.
Inappropriate fear expression and failure of fear extinction are commonly seen in patients with post-traumatic stress disorder (PTSD) and obsessive-compulsive disorder (OCD). Among the patients, aberrant and asymmetric activation of the lateral orbitofrontal cortex (lOFC) is reported in some clinical cases. In this study, we aimed to examine the role of lOFC activation in extinction acquisition and explore the potential functional lateralization of lOFC on extinction. We bilaterally or unilaterally activated the lOFC with N-methyl-D-aspartate (NMDA) before fear extinction acquisition in rats. Our data suggested that both left and bilateral lOFC activation interfered with the in-session expression of conditioned fear, whereas activation of the right lOFC did not. In addition, pre-extinction unilateral or bilateral activation of the lOFC, regardless of the side, impaired the acquisition of fear extinction. We also quantified the neuronal activities during the late phase of extinction with immunohistochemical approach. Our data showed that activation of the lOFC increased the neuronal activities on the injection side(s) in the medial prefrontal cortex (mPFC), the lateral amygdala (LA), the basolateral amygdala (BLA; preferentially the non-GABAergic neurons), and the medial intercalated cells (mITC; preferentially the right side). To conclude, aberrant activation of the lOFC during extinction disturbed the excitatory/inhibitory balance of neuronal activities in fear-related brain regions, which interfered with the expression of conditioned fear and impaired the acquisition of fear extinction.
The role of angular gyrus (AG) in arithmetic processing remains a subject of debate. In the present study, we recorded from the AG, supramarginal gyrus (SMG), intraparietal sulcus (IPS), and superior parietal lobule (SPL) across 467 sites in 30 subjects performing addition or multiplication with digits or number words. We measured the power of high-frequency-broadband (HFB) signal, a surrogate marker for regional cortical engagement, and used single-subject anatomical boundaries to define the location of each recording site. Our recordings revealed the lowest proportion of sites with activation or deactivation within the AG compared to other subregions of the inferior parietal cortex during arithmetic processing. The few activated AG sites were mostly located at the border zones between AG and IPS, or AG and SMG. Additionally, we found that AG sites were more deactivated in trials with fast compared to slow response times. The increase or decrease of HFB within specific AG sites was the same when arithmetic trials were presented with number words versus digits and during multiplication as well as addition trials. Based on our findings, we conclude that the prior neuroimaging findings of so-called activations in the AG during arithmetic processing could have been due to group-based analyses that might have blurred the individual anatomical boundaries of AG or the subtractive nature of the neuroimaging methods in which lesser deactivations compared to the control condition have been interpreted as “activations”. Our findings offer a new perspective with electrophysiological data about the engagement of AG during arithmetic processing.
Layer 3 neurons differ within and between dorsolateral prefrontal cortex (DLPFC) and posterior parietal cortex (PPC). A: Schematic representation of the macaque lateral hemisphere highlighting the approximate location of tissue dissections from the two areas. B: Pie charts comparing regular spiking (RS) and bursting (B) populations in DLPFC and PPC. In DLPFC, the two populations are equivalent, but in PPC there is a significantly higher proportion of RS neurons. C, D: Reconstructions of biocytin-filled neurons in layer 3 of DLPFC (C) and PPC (D). Basal dendrites (in blue) are significantly larger and more complex in DLPFC. Apical dendrites, in grey, and somata in magenta. Adapted from Gonzalez-Burgos et al. 2019 (their Figs. 2, 3)
Schematic lateral and medial views of the macaque cerebral hemisphere. Injections of classical tracers in four parietal subdivisions demonstrate the major interconnected cortical areas, co-colored with the respective injection sites (in blue, red, black, and green). At left: Ipsilateral connections; At right: Contralateral connections. Note the dense homotopic callosal connections (mirroring the injection sites) and widespread, but less dense heterotopic callosal connections, especially in the superior temporal sulcus, lateral fissure, arcuate and principal sulci in the frontal lobe, and cingulate sulcus and gyrus. With permission, from Cavada and Goldman-Rakic 1989a (their Figs. 15, 16)
Two-photon images of the spatial organization of dendritic excitatory inputs on basal dendrites of a layer 3 neuron in macaque area V1. A: Orientation-selective ROIs. B: Spatial frequency preferences of the orientation-selective inputs in A). C: Color-selective inputs. D: A functional preference map of dendritic inputs color coded for orientation (in blue) vs. color preference (in red). Scale bar, 20 µm Adapted from Ju et al. 2020 (their Fig. 2)
The angular gyrus is associated with a spectrum of higher order cognitive functions. This mini-review undertakes a broad survey of putative neuroanatomical substrates, guided by the premise that area-specific specializations derive from a combination of extrinsic connections and intrinsic area properties. Three levels of spatial resolution are discussed: cellular, supracellular connectivity, and synaptic micro-scale, with examples necessarily drawn mainly from experimental work with nonhuman primates. A significant factor in the functional specialization of the human parietal cortex is the pronounced enlargement. In addition to "more" cells, synapses, and connections, however, the heterogeneity itself can be considered an important property. Multiple anatomical features support the idea of overlapping and temporally dynamic membership in several brain wide subnetworks, but how these features operate in the context of higher cognitive functions remains for continued investigations.
The angular gyrus (AG) has been associated with multiple cognitive functions, such as language, spatial and memory functions. Since the AG is thought to be a cross-modal hub region suffering from significant age-related structural atrophy, it may also play a key role in age-related cognitive decline. However, the exact relation between structural atrophy of the AG and cognitive decline in older adults is not fully understood, which may be related to two aspects: First, the AG is cytoarchitectonically divided into two areas, PGa and PGp, potentially sub-serving different cognitive functions. Second, the older adult population is characterized by high between-subjects variability which requires targeting individual phenomena during the aging process. We therefore performed a multimodal (gray matter volume [GMV], resting-state functional connectivity [RSFC] and structural connectivity [SC]) characterization of AG subdivisions PGa and PGp in a large older adult population, together with relations to age, cognition and lifestyle on the group level. Afterwards, we switched the perspective to the individual, which is especially important when it comes to the assessment of individual patients. The AG can be considered a heterogeneous structure in of the older brain: we found the different AG parts to be associated with different patterns of whole-brain GMV associations as well as their associations with RSFC, and SC patterns. Similarly, differential effects of age, cognition and lifestyle on the GMV of AG subdivisions were observed. This suggests each region to be structurally and functionally differentially involved in the older adult’s brain network architecture, which was supported by differential molecular and genetic patterns, derived from the EBRAINS multilevel atlas framework. Importantly, individual profiles deviated considerably from the global conclusion drawn from the group study. Hence, general observations within the older adult population need to be carefully considered, when addressing individual conditions in clinical practice.
In this work, we identify a problem with the process of volume-to-surface mapping of functional Magnetic Resonance Imaging (fMRI) data that emerges in local connectivity analysis. We show that neighborhood correlations on the surface of the brain vary spatially with the gyral structure, even when the underlying volumetric data are uncorrelated noise. This could potentially have impacted studies focusing upon local neighborhood connectivity. We explore the effects of this anomaly across varying data resolutions and surface mesh densities, and propose several measures to mitigate these unwanted effects.
Studies investigating the correlation between deficits after stroke. A Histogram of number of deficits. 61% of individuals with deficit after stroke have deficit in more than 1 domain. Histogram depicts how many significant deficits (< 2SD below controls) stroke patients have. Patients with at least one significant deficit out of five behavioral domains were included (n = 56). (Ramsey et al. 2017) B Correlation in deficits across more than 40 different behavioral measures in a cohort of N = 132 stroke patients (Corbetta et al. 2015). C Correlation structure between major behavioral domains, represented graphically. The scatter plots at right demonstrate correlation between the primary dimension of deficit in different behavioral domains. Each dot represents a single subject. D Moderation graph—arrows indicate that deficit in the behavioral domain at the root has significant influence on recovery of deficit in the behavioral domain at the tip
The complexity of brain-to-behavior links. A A graphical representation illustrates the complexity and non-linear relationships between lesion, brain system, and behavior. The one-to-many and many-to-one mapping (indicated by the black arrows) make attempts to localize functional with lesion-symptom mapping nearly impossible. The numbered gray arrows indicate relationships explored in the stroke literature: lesion-symptom mapping studies (1) identify links between a single brain location and a behavior. But recently, studies comparing behavioral deficits (2) across cohorts have identified substantial correlation and clustering between behavioral domains. Consequently, efforts to link brain connectivity to behavior (3) suggest complex relationships between brain network dysfunction and behavior. The interdependence of brain networks provides one possible explanation for correlated deficits. Computational models predict, and human imaging confirms, that an isolated lesion can affect distant parts of the brain (4). By connecting links (3) and (4), we can build a new framework for how lesions affect behavior. B An example. A single right temporoparietal lesion damages several interhemispheric and interhemispheric white matter tracts. Because the brain is a network, the entire brain graph is disrupted. Though particular systems (default, dorsal attention, motor) are more impaired than others. The consequence is deficit across a range of tasks (motor, attention, spatial memory)
Domain specificity by brain system (based on cortical network parcellation from Laumann et al. 2015. “Domain-specific systems” are those in which control of a specific perceptual or behavioral domain (e.g. visual, auditory, sensory, motor) is highly localized. These systems tend to be the most amenable to lesion-deficit mapping approaches. “Semi-specific systems” instantiate functions that can be thought of as domain specific, but are in fact utilized across a wider range of tasks (one-to-many). For example, dorsal attention areas allow modulation of attention in response to environmental cues. (Corbetta et al. 2008). This ‘attention’ function is used across a wide variety of behaviors that we may classify as ‘language’ or ‘motor’. “Domain-general ‘control’ systems” conduct operations critical to control of goal-directed behavior and for the maintenance and adaptation of other brain systems
Studies linking functional and structural disruption to deficit after stroke provide insight into principles underlying low-dimensional and multi-domain deficit. Functional connectivity: A Disruption to the functional connections shown was predictive of multi-domain (across 6 behavioral domains) deficit. Two specific patterns of connectivity can be observed—reduced homotopic FC (green bars running laterally across the hemispheres) and increased intrahemispheric FC (orange bars running anterior-posterior) (from Siegel et al. 2016a, b). These two phenomena can be thought of as two sides of the same coin: reduced network modularity after stroke. B A spring-embedded representation of resting state networks after stroke demonstrates loss of network modularity. Following stroke, resting state networks become less strongly integrated and less segregated from each other (from Siegel et al. 2018). Structural Connectivity: A renewed attention has been put on the study of white matter tract damage. C The gray overlay indicates the number of white-matter tracts is close proximity. The orange overlay indicates number of behavioral deficits based on lesion-symptom mapping. The overlap suggests that damage to regions in which numerous tracts converge corresponds to multi-domain deficit (from Corbetta et al. 2015). D Using a common atlas to model all tracts that would typically run through the region of damage (‘disconnectome mapping’) may provide a more complete picture of the extent of brain disruption that contributes to deficit. Structural-Functional: Direct comparison between modalities indicate that a lesion’s impact on the structural connectome primarily determines its impact on FCf. E, F When structural (white matter) disconnection is directly compared to FC after stroke, a link is found between interhemispheric (transcallosal) disconnections and the same two dimensions of FC disruption identified previously (decreased homotopic FC and increased intrahemispheric FC) (Griffis et al. 2019).
Understanding the relationships between brain organization and behavior is a central goal of neuroscience. Traditional teaching emphasizes that the human cerebrum includes many distinct areas for which damage or dysfunction would lead to a unique and specific behavioral syndrome. This teaching implies that brain areas correspond to encapsulated modules that are specialized for specific cognitive operations. However, empirically, local damage from stroke more often produces one of a small number of clusters of deficits and disrupts brain-wide connectivity in a small number of predictable ways (relative to the vast complexity of behavior and brain connectivity). Behaviors that involve shared operations show correlated deficits following a stroke, consistent with a low-dimensional behavioral space. Because of the networked organization of the brain, local damage from a stroke can result in widespread functional abnormalities, matching the low dimensionality of behavioral deficit. In alignment with this, neurological disease, psychiatric disease, and altered brain states produce behavioral changes that are highly correlated across a range of behaviors. We discuss how known structural and functional network priors in addition to graph theoretical concepts such as modularity and entropy have provided inroads to understanding this more complex relationship between brain and behavior. This model for brain disease has important implications for normal brain-behavior relationships and the treatment of neurological and psychiatric diseases.
The cerebellum has established associations with motor function and a well-recognized role in cognition. In advanced age, cognitive and motor impairments contribute to reduced quality of life and are more common. Regional cerebellar volume is associated with performance across these domains and sex hormones may influence this volume. Examining sex differences in regional cerebellar volume in conjunction with age, and in the context of reproductive stage stands to improve our understanding of cerebellar aging and pathology. Data from 508 healthy adults (ages 18–88; 47% female) from the Cambridge Centre for Ageing and Neuroscience database were used here. CERES was used to assess lobular volume in T1-weighted images. We examined sex differences in adjusted regional cerebellar volume while controlling for age. A subgroup of participants (n = 370, 50% female) was used to assess group differences in female reproductive stages as compared to age-matched males. Sex differences in adjusted volume were seen across most anterior and posterior cerebellar lobules. Most of these lobules had significant linear relationships with age in males and females. While there were no interactions between sex and reproductive stage groups, exploratory analyses in females alone revealed multiple regional differences by reproductive stage. We found sex differences in volume across much of the cerebellum, linear associations with age, and did not find an interaction for sex and reproductive stage on regional cerebellar volume. Longitudinal investigation into hormonal influences on cerebellar structure and function is warranted as hormonal changes with menopause may impact cerebellar volume over time.
Historically, the central mesencephalic reticular formation has been regarded as a purely horizontal gaze center based on the fact that electrical stimulation of this region produces horizontal saccades, it provides monosynaptic input to medial rectus motoneurons, and cells recorded in this region often display a peak in firing when horizontal saccades are made. We tested the proposition that the central mesencephalic reticular formation is purely a horizontal gaze center by examining whether this region also supplies terminals to superior rectus and levator palpebrae superioris motoneurons, both of which fire when making vertical eye movements. The experiments were carried out using dual tracer techniques at the light and electron microscopic level in macaque monkeys. Injections of biotinylated dextran amine or Phaseolus vulgaris leukoagglutinin into the central mesencephalic reticular formation produced anterogradely labeled terminals that were in synaptic contact with superior rectus and levator palpebrae superioris motoneurons that had been retrogradely labeled. These results indicate that this region is not purely connected with horizontal gaze motoneurons. In addition, we found that the number of contacts on vertical gaze motoneurons increased with more rostral injections involving the mesencephalic reticular formation adjacent to the interstitial nucleus of Cajal. This suggests that there is a caudal to rostral gradient for horizontal to vertical saccades, respectively, represented within the midbrain reticular formation. Finally, we utilized post-embedding immunohistochemistry to show that a portion of the labeled terminals were GABAergic, indicating they likely originate from downgaze premotor neurons.
Seasonally reproducing small mammals often undergo changes in brain anatomy throughout the year. Much of the research on this seasonal neuroplasticity has focused on changes in hippocampus volume and neurogenesis, with relatively little attention paid to neuronal morphology. Here, we test for sex, season and sex–season interaction effects on hippocampal neuron morphology and dendritic spine density in a seasonally reproducing rodent: Richardson’s ground squirrel (Urocitellus richardsonii). We quantified the morphology and spine densities of Golgi-stained pyramidal neurons and granule cells in the hippocampus and tested for differences between sexes and seasons with generalized linear models. Although we found no significant sex differences or sex–season interaction effects on any of our morphological measurements, there were significant differences in neuron morphology and spine density between breeding and non-breeding seasons. In the non-breeding season, ground squirrels had CA1 neurons with longer basal dendrites with more branches than in the breeding season. Non-breeding season animals also had higher apical and basal dendrite spine density in CA1 and CA3 neurons than breeding-season animals. Conversely, the spine densities of CA1 somata and granule cells were higher in breeding than in non-breeding season. These differences in neuron morphology and spine density between breeding and non-breeding seasons likely arise from a combination of activity levels, stress hormones, and photoperiod. Although the functional implications of seasonal changes in hippocampal neuron morphology and spine density are uncertain, our data suggest that ground squirrels may be a good model for understanding seasonal neuroplasticity in mammals.
Anatomical and functional evidence suggests that the PFC is fairly unique among all cortical regions, as it not only receives input from, but also robustly projects back to mesopontine monoaminergic and cholinergic cell groups. Thus, the PFC is in position to exert a powerful top-down control over several state-setting modulatory transmitter systems that are critically involved in the domains of arousal, motivation, reward/aversion, working memory, mood regulation, and stress processing. Regarding this scenario, the origin of cortical afferents to the ventral tegmental area (VTA), laterodorsal tegmental nucleus (LDTg), and median raphe nucleus (MnR) was here compared in rats, using the retrograde tracer cholera toxin subunit b (CTb). CTb injections into VTA, LDTg, or MnR produced retrograde labeling in the cortical mantle, which was mostly confined to frontal polar, medial, orbital, and lateral PFC subdivisions, along with anterior- and mid-cingulate areas. Remarkably, in all of the three groups, retrograde labeling was densest in layer V pyramidal neurons of the infralimbic, prelimbic, medial/ventral orbital and frontal polar cortex. Moreover, a lambda-shaped region around the apex of the rostral pole of the nucleus accumbens stood out as heavily labeled, mainly after injections into the lateral VTA and LDTg. In general, retrograde PFC labeling was strongest following injections into MnR and weakest following injections into VTA. Altogether, our findings reveal a fairly similar set of prefrontal afferents to VTA, LDTg, and MnR, further supporting an eminent functional role of the PFC as a controller of major state-setting mesopontine modulatory transmitter systems.
Mild cognitive impairment (MCI) is clinically characterized by memory loss and cognitive impairment closely associated with the hippocampal atrophy. Accumulating studies have confirmed the presence of neural signal changes within white matter (WM) in resting-state functional magnetic resonance imaging (fMRI). However, it remains unclear how abnormal hippocampus activity affects the WM regions in MCI. The current study employs 43 MCI, 71 very MCI (VMCI) and 87 age-, gender-, and education-matched healthy controls (HCs) from the public OASIS-3 dataset. Using the left and right hippocampus as seed points, we obtained the whole-brain functional connectivity (FC) maps for each subject. We then perform one-way ANOVA analysis to investigate the abnormal FC regions among HCs, VMCI, and MCI. We further performed probabilistic tracking to estimate whether the abnormal FC correspond to structural connectivity disruptions. Compared to HCs, MCI and VMCI groups exhibited reduced FC in the right middle temporal gyrus within gray matter, and right temporal pole, right inferior frontal gyrus within white matter. Specific dysconnectivity is shown in the cerebellum Crus II, left inferior temporal gyrus within gray matter, and right frontal gyrus within white matter. In addition, the fiber bundles connecting the left hippocampus and right temporal pole within white matter show abnormally increased mean diffusivity in MCI. The current study proposes a new functional imaging direction for exploring the mechanism of memory decline and pathophysiological mechanisms in different stages of Alzheimer’s disease.
‘Dynamic activity model’ diagraming voluntary control of movement. A Normal state, B Parkinson's disease, C Dystonia. Spatial distributions (left) and temporal patterns (right) of neuronal activity are illustrated in each panel. STN; subthalamic nucleus, GPi/SNr; internal global pallidus/substantia nigra, Th; thalamus. Reprinted with permission from Nambu et al. (2015)
The neuropathological substrates of Parkinson’s disease (PD) patients with motor subtypes tremor-dominance (TD), non-tremor dominance (nTD), postural instability and gait difficulty (PIGD), and akinetic-rigid (AR) are not completely differentiated. While extensive pathological research has been conducted on neuronal tissue of PD patients, data have not been discussed in the context of mechanistic circuitry theories differentiating motor subtypes. It is, therefore, expected that a more specific and tailored management of PD symptoms can be accomplished by understanding symptom-specific neuropathological mechanisms with the detail histology can provide. This scoping review gives an overview of the literature comparing TD and nTD PD motor subtypes by clarify observed pathology with underlying physiological circuitry theories. Studies using an array of pathological examination techniques have shown significant differences between TD and nTD PD subtypes. nTD PD patients show higher neuronal loss, gliosis, extraneuronal melanin deposits, and neuroaxonal dystrophy in multiple subregions of the substantia nigra (SN) related to the overactivity of the indirect motor loop. TD patients show more severe cell loss specifically in medial SN subdivisions, and have damage in the retrorubral field A-8 that projects to the dorsolateral striatum and ventromedial thalamus in the direct motor loop. Pathological studies are consistent with neuroimaging data and support contemporary mechanistic circuitry theories of PD motor symptom genesis. Further multimodal neuroimaging and histological studies are required to validate and expand upon these findings.
In rare cases, cortical infarcts lead to vertigo. We evaluated structural and functional disconnection in patients with acute vertigo due to unilateral ischemic cortical infarcts compared to infarcts without vertigo in a similar location with a focus on the connectivity of the vestibular cortex, i.e., the parieto-opercular (retro-)insular cortex (PIVC). Using lesion maps from the ten published case reports, we computed lesion-functional connectivity networks in a set of healthy individuals from the human connectome project. The probability of lesion disconnection was evaluated by white matter disconnectome mapping. In all ten cases with rotational vertigo, disconnections of interhemispheric connections via the corpus callosum were present but were spared in lesions of the PIVC without vertigo. Further, the arcuate fascicle was affected in 90% of the lesions that led to vertigo and spared in lesions that did not lead to vertigo. The lesion-functional connectivity network included vestibulo-cerebellar hubs, the vestibular nuclei, the PIVC, the retro-insular and posterior insular cortex, the multisensory vestibular ventral intraparietal area, motion-sensitive areas (temporal area MT+ and cingulate visual sulcus) as well as hubs for ocular motor control (lateral intraparietal area, cingulate and frontal eye fields). However, this was not sufficient to differentiate between lesions with and without vertigo. Disruption of interhemispheric connections of both PIVC via the corpus callosum and intra-hemispheric disconnection via the arcuate fascicle might be the distinguishing factor between vestibular cortical network lesions that manifest with vertigo compared to those without vertigo.
The paraventricular nucleus of the thalamus (PVT) projects to areas of the forebrain involved in regulating behavior. Homeostatic challenges and salient cues activate the PVT and evidence shows that the PVT regulates appetitive and aversive responses. The brainstem is a source of afferents to the PVT and the present study was done to determine if the lateral parabrachial nucleus (LPB) is a relay for inputs to the PVT. Retrograde tracing experiments with cholera toxin B (CTB) demonstrate that the LPB contains more PVT projecting neurons than other regions of the brainstem including the catecholamine cell groups. The hypothesis that the LPB is a relay for signals to the PVT was assessed using an intersectional monosynaptic rabies tracing approach. Sources of inputs to LPB included the reticular formation; periaqueductal gray (PAG); nucleus cuneiformis; and superior and inferior colliculi. Distinctive clusters of input cells to LPB-PVT projecting neurons were also found in the dorsolateral bed nucleus of the stria terminalis (BSTDL) and the lateral central nucleus of the amygdala (CeL). Anterograde viral tracing demonstrates that LPB-PVT neurons densely innervate all regions of the PVT in addition to providing collateral innervation to the preoptic area, lateral hypothalamus, zona incerta and PAG but not the BSTDL and CeL. The paper discusses the anatomical evidence that suggests that the PVT is part of a network of interconnected neurons involved in arousal, homeostasis, and the regulation of behavioral states with forebrain regions potentially providing descending modulation or gating of signals relayed from the LPB to the PVT.
a Lesion overlap between 4 and 16 cases. Lesions are confined to the left hemisphere and are frontoparietal, peaking in the precentral and middle frontal gyri. b Structural disconnection overlap between 19 and 23 cases, generated using the BCB Toolkit. Structural disconnection is left lateralised at this threshold and shows maximal overlap with the superior longitudinal fasciculus and inferior fronto-occipital fasciculus. c Functional disconnection overlap between 19 and 23 cases, generated using CONN. Functional disconnection is bilateral and extensive, peaking in the temporooccipital part of the left inferior temporal gyrus and the right inferior frontal gyrus pars triangularis. 3D renderings generated in SurfIce. d A line graph displaying the numbers of cases showing overlapping lesions, structural disconnection (confined to white matter) and functional disconnection (confined to grey matter), expressed as a percentage of the total number of voxels damaged or disconnected for at least one participant. This figure demonstrates the homogeneity of patterns of anticipated structural and functional disconnection, relative to the lesion overlap map. N = 23
a The mean percentage lesioned for each network of interest (confined to the left hemisphere). DMN default mode network, SCN semantic control network, MDN multiple demand network. This peaks in the semantic control network at 26%, followed by areas shared between the multiple demand and semantic control networks at 23%, core semantic regions and regions exclusive to the multiple demand network both at 14%, and the default mode network at 6%. Locations of most frequent damage are displayed for each network in following sections. Any right hemisphere aspects of each network are visualised but were never impacted by lesion. b The default mode network, lesion peaks in the angular gyrus and insular cortex at a threshold of 12 cases. c Core semantic regions, lesion peaks in the inferior frontal gyrus pars opercularis at a threshold of 14 cases. d The semantic control network, lesion peaks in the inferior frontal gyrus pars opercularis at a threshold of 14 cases. e Regions shared by the semantic control and multiple demand networks, lesion peaks in the middle frontal and precentral gyri at 13 cases. f The multiple demand network, lesion peaks in the precentral gyrus at a threshold of 15 cases. Keys under each map reflect the number of patients with lesion to a given voxel. N = 23
Clusters associated with lower semantic cognition composite scores (left) and lower scores on the Brixton Spatial Anticipation Test (right), for a lesion, b structural disconnection, and c functional disconnection. Generated using non-parametric permutation tests in Randomise with threshold-free cluster enhancement. Highlighted voxels have a t value of 2.6 or higher. Small clusters are highlighted in orange circles. 3D rendering generated in Surface. Lesioned clusters associated with poorer semantic and Brixton performance are large and left lateralised, and reflect the regions listed in Section “Lesion-symptom mapping”. Structurally disconnected clusters are small and left lateralised for semantic cognition, reflecting regions listed in Section “Structural disconnection-symptom mapping”, while for poorer Brixton performance one large cluster is observed across the corpus callosum. Functionally disconnected clusters are small for both measures, and reflect the regions listed in Section “Functional disconnection-symptom mapping”. N=20
Patient performance on background neuropsychological testing.
Patients with semantic aphasia have impaired control of semantic retrieval, often accompanied by executive dysfunction following left hemisphere stroke. Many but not all of these patients have damage to the left inferior frontal gyrus, important for semantic and cognitive control. Yet semantic and cognitive control networks are highly distributed, including posterior as well as anterior components. Accordingly, semantic aphasia might not only reflect local damage but also white matter structural and functional disconnection. Here, we characterise the lesions and predicted patterns of structural and functional disconnection in individuals with semantic aphasia and relate these effects to semantic and executive impairment. Impaired semantic cognition was associated with infarction in distributed left-hemisphere regions, including in the left anterior inferior frontal and posterior temporal cortex. Lesions were associated with executive dysfunction within a set of adjacent but distinct left frontoparietal clusters. Performance on executive tasks was also associated with interhemispheric structural disconnection across the corpus callosum. In contrast, poor semantic cognition was associated with small left-lateralized structurally disconnected clusters, including in the left posterior temporal cortex. Little insight was gained from functional disconnection symptom mapping. These results demonstrate that while left-lateralized semantic and executive control regions are often damaged together in stroke aphasia, these deficits are associated with distinct patterns of structural disconnection, consistent with the bilateral nature of executive control and the left-lateralized yet distributed semantic control network.
Source plots of the statistical t-maps or univariate contrasts corresponding to Identity effects (A), Life Stage (B) and interaction Identity × Life Stage (C) during the 250–300 ms time window. Reported brain regions significantly activated at a posterior statistical threshold p < 0.01. aCC anterior cingulate cortex, ATL anterior temporal lobule, dlPFC dorsolateral prefrontal cortex, dmPFC dorsomedial prefrontal cortex, FG fusiform gyrus, IFG inferior frontal gyrus, ITG inferior temporal gyrus, MTG middle temporal gyrus, pCC posterior cingulate cortex, TPJ temporoparietal junction
Source plots of the statistical t-maps for univariate contrasts corresponding to Identity effects (A) and the interaction Identity × Life Stage (B) during the 300–600 ms time window. Reported brain regions significantly activated at a posterior statistical threshold p < 0.01. dlPFC dorsolateral prefrontal cortex, FG fusiform gyrus, IFG inferior frontal gyrus, mPFC medial prefrontal cortex, MTG middle temporal gyrus, pHC parahippocampal cortex, pCC posterior cingulate cortex
Current research on self-identity suggests that the self is settled in a unique mental representation updated across the lifespan in autobiographical memory. Spatio-temporal brain dynamics of these cognitive processes are poorly understood. ERP studies revealed early (N170-N250) and late (P3-LPC) waveforms modulations tracking the temporal processing of global face configuration, familiarity processes, and access to autobiographical contents. Neuroimaging studies revealed that such processes encompass face-specific regions of the occipitotemporal cortex, and medial cortical regions tracing the self-identity into autobiographical memory across the life span. The present study combined both approaches, analyzing brain source power using a data-driven, beamforming approach. Face recognition was used in two separate tasks: identity (self, close friend and unknown) and life stages (childhood, adolescence, adulthood) recognition. The main areas observed were specific-face areas (fusiform area), autobiographical memory areas (medial prefrontal cortex, parahippocampus, posterior cingulate cortex/precuneus), along with executive areas (dorsolateral prefrontal and anterior temporal cortices). The cluster-permutation test yielded no significant early effects (150–200 ms). However, during the 250–300 ms time window, the precuneus and the fusiform cortices exhibited larger activation to familiar compared to unknown faces, regardless of life stages. Subsequently (300–600 ms), the medial prefrontal cortex discriminates between self-identity vs. close-familiar and unknown. Moreover, significant effects were found in the cluster-permutation test specifically on self-identity discriminating between adulthood from adolescence and childhood. These findings suggest that recognizing self-identity from other facial identities (diachronic self) comprises the temporal coordination of anterior and posterior areas. While mPFC maintained an updated representation of self-identity (diachronic self) based on actual rewarding value, the dlPFC, FG, MTG, paraHC, PCC was sensitive to different life stages of self-identity (synchronic self) during the access to autobiographical memory.
Efficient communication across fields of research is challenging, especially when they are at opposite ends of the physical and digital spectrum. Neuroanatomy and neuroimaging may seem close to each other. When neuroimaging studies try to isolate structures of interest, according to a specific anatomical definition, a variety of challenges emerge. It is a non-trivial task to convert the neuroanatomical knowledge to instructions and rules to be executed in neuroimaging software. In the process called “virtual dissection” used to isolate coherent white matter structure in tractography, each white matter pathway has its own set of landmarks (regions of interest) used as inclusion and exclusion criteria. The ability to segment and study these pathways is critical for scientific progress, yet, variability may depend on region placement, and be influenced by the person positioning the region (i.e., a rater). When raters’ variability is taken into account, the impact made by each region of interest becomes even more difficult to interpret. A delicate balance between anatomical validity, impact on the virtual dissection and raters’ reproducibility emerge. In this work, we investigate this balance by leveraging manual delineation data of a group of raters from a previous study to quantify which set of landmarks and criteria contribute most to variability in virtual dissection. To supplement our analysis, the variability of each pathway with a region-by-region exploration was performed. We present a detailed exploration and description of each region, the causes of variability and its impacts. Finally, we provide a brief overview of the lessons learned from our previous virtual dissection projects and propose recommendations for future virtual dissection protocols as well as perspectives to reach better community agreement when it comes to anatomical definitions of white matter pathways.
Group-based atlas and examples of three individualized cortex parcellations
Spatial distribution of cortical dice coefficient (subcortical areas were not included). A The mean dice coefficient across blocks within subjects. B The mean dice coefficient between individualized cortex parcellation and the group-based atlas. C The mean dice coefficient across subjects (vdice)
The maps of local brain activity at the group level (A–C) and the individual variability of local activity (D–F) and connectivity (G) (subcortical areas were not included). A–C mALFF, mfALFF, and mReHo, respectively. D–F stdALFF, stdfALFF, and stdReHo, respectively. G individual variability in local functional connectivity (vLFC)
Regression results between individual variability of local functional features and the mean scan age across windows after regressing out covariates of sex and meanFD. A Relationship between age and the global mean values of vdice. B–D Relationship between age and the global mean values of stdALFF, stdfALFF, and stdReHo. E Relationship between the global mean values of vLFC and age. Each dot represents one age window. The blue color represents the left hemisphere, and the red color represents the right hemisphere
Brain regions with significantly positive age effect in local brain functional individual variability; the value represents the slope of linear regression after regressing out sex and meanFD. Significantly positive relationship between age and stdALFF (A), stdfALFF (B), stdReHo (C), and vLFC (D) (subcortical areas were not included)
Individual variability in cognition and behavior results from the differences in brain structure and function that have already emerged before birth. However, little is known about individual variability in brain functional architecture at local level in neonates which is of great significance to explore owing to largely undeveloped long-range functional connectivity and segregated functions in early brain development. To address this, resting-state fMRI data of 163 neonates ranged from 32 to 45 postconceptional weeks (PCW) were used in this study, and various functional features including functional parcellation similarity, local brain activity and local functional connectivity were used to characterize individual functional variability. We observed significantly higher local functional individual variability in superior parietal, sensorimotor, and visual cortex, and lower variability in the frontal, insula and cingulate cortex relative to other regions within each hemisphere. The mean local functional individual variability significantly increased with age, and the age effect was found larger in brain regions such as the occipital, temporal, prefrontal and parietal cortex. Our findings promote the understanding of brain plasticity and regional differential maturation in the early stage.
Average whole-brain white and grey matter datasets and estimated granularity indices across Brainnetome atlas regions: a Average cortical connectivity (of all 30 subjects) across left (LH) and right (RH) hemispheres: average connectivity matrix, representing (log(number of tracts)) for connections that appear in at least 75% of subjects (colour scheme adapted from Charles 2021). b Average cortical laminar composition (of all 30 subjects) across left hemisphere: where: top row—supragranular layers (SG), middle row- granular layer (G), bottom row—infragranular layers (IG), and columns represent different viewpoints. c Granularity indices (left-1) and Brainnetome atlas regions (right-2) across left hemisphere, from several viewpoints: left side (a), right side (B), front (C), occipital (D), top (E), and bottom (F). Features in b and their respective counterparts in c correspond to unique granular presence (circled in red): features (i) and (ii): high presence of granular laminar component in V1 (in b), in correspondence with a high granularity index (in c); feature (iii): low presence of granular laminar component in M1 (in b), in correspondence with a low granularity index (in c)
30-subject average cortical laminar connectivity (top) and standard deviations for both connectomes (bottom) across Brainnetome atlas regions: a Average supra-adjacency matrix, representing whole-brain laminar-level connections, where the following abbreviations correspond to laminar components: IG infragranular, G granular, SG supragranular. Model results are displayed as log(number of tracts) for all connections that appear in at least 75% of subjects. b A closer look at the supragranular–supragranular component of the average supra-adjacency matrix. c Standard deviation of standard cortical connectomes. d Standard deviation of cortical laminar connectomes (colour schemes
adapted from Charles 2021)
Degree distributions: Distributions of degrees for both the standard cortical connectome (a), as well as the cortical laminar connectome (b1), of the average connectomes for all connections that appear in at least 75% of subjects. Each of the two is presented against a random network with an equal number of nodes and edges (histogram outlines in green). For the laminar connectome, distributions for each laminar connectome are coloured individually b2: infragranular (IG)—red, granular (G)—green, supragranular (SG)—blue. Notice the positive skew, or “heavy-tail”, in degree distributions in both cases and expressly in the laminar connectome
Node degree: a Distribution of degree values for the average standard connectome across cortical regions of the Brainnetome atlas, top view (a1) and lateral view (a2). b Whole-brain distributions of degree values for the average standard connectome (b1) compared to the average laminar connectome (b2), including: infragranular (IG), granular (G) and supragranular (SG) components (3 right columns, left to right). Each connectome depicts cortical connections (top) and subcortical connections (bottom). For each laminar component, cortical connections include connections between the specified component and all other components (top), and subcortical connections include connections between the specified component and the subcortex (bottom). c Regional degree values across gyral classifications of the Brainnetome atlas, including: degree values in cortical regions of the standard connectome, where above-threshold values appear in yellow and borderline values appear in white (c1), betweenness values in cortical regions of the standard connectome, where the abovementioned central regions are marked with a yellow star and borderline regions are marked with a white star (c2), and whole-brain degree values in the laminar connectome, where laminar components are coloured individually: infragranular (IG)—red, granular (G)—green, supragranular (SG)—blue (c3). For both c1 and c2 mean values are marked by a solid line and one standard deviation above the mean is marked by a dashed line
Node strength: a Whole-brain distributions of strength values for the average standard connectome (left column) compared to the average laminar connectome, including: infragranular (IG), granular (G) and supragranular (SG) components (3 right columns, left to right). Each connectome depicts cortical connections (top) and subcortical connections (bottom). For each laminar component, cortical connections include connections between the specified component and all other components (top), and subcortical connections include connections between the specified component and the subcortex (bottom). Feature (i) (circled in red) shows high centrality of subcortical regions for the granular component of the laminar connectome. b Distribution of strength values for the granular (G) component of the laminar connectome across both left (L, top) and right (R, bottom) hemispheres, from lateral view (left) and sagittal view (right). Features (circled in red) show high strength values in the auditory cortex (ii), as well as the primary motor (iii) and primary visual (iv) cortices. c Regional strength values across gyral classifications of the Brainnetome atlas, including: degree values in cortical regions of the standard connectome, where the mean value is marked by a solid line, one standard deviation above the mean is marked by a dashed line, and above-threshold values appear in yellow and borderline value appear in white (c1), and whole-brain strength values in the laminar connectome, where laminar components are coloured individually: infragranular (IG)—red, granular (G)—green, supragranular (SG)—blue (c2)
The human connectome is the complete structural description of the network of connections and elements that form the ‘wiring diagram’ of the brain. Due to the current scarcity of information regarding laminar end points of white matter tracts inside cortical grey matter, tractography remains focused on cortical partitioning into regions, while ignoring radial partitioning into laminar components. To overcome this biased representation of the cortex as a single homogenous unit, we use a recent data-derived model of cortical laminar connectivity, which has been further explored and corroborated in the macaque brain by comparison to published studies. The model integrates multimodal MRI imaging datasets of both white matter connectivity and grey matter laminar composition into a laminar-level connectome. In this study, we model the laminar connectome of healthy human brains (N = 30) and explore them via a set of complex network measures. Our analysis demonstrates a subdivision of network hubs that appear in the standard connectome into each individual component of the laminar connectome, giving a fresh look into the role of laminar components in cortical connectivity and offering new prospects in the fields of both structural and functional connectivity.
Comparison of different tracing vectors. A AAV5–Ef1a–DIO–mCherry. B AAV5–EF1a–DIO–ChR2–mCh C AAV8–hEF1a–DIO–synaptophysin–mCherry
Mice are stereotactically injected with a vector (A), After 4–5 weeks, they are perfused (B), and their brains are dissected, sliced and stained (C, D). Brain tissue sections are mounted (E) and slide-scanned (F), then Nissl counter-stained (G) and re-scanned (H). The original image is analyzed with BoutonNet (I) to propose (J) and confirm (K) boutons to create bouton plots (L)
Comparison of different methods of visualizing synaptophysin–mCherry labeling. Adjacent sections
A Example labeling of BoutonNet and human raters. B Dice coefficient distance matrix. Value at a given square are the Dice coefficients between the two raters across all boutons on all sections. C Total boutons counted across sections. Scale bar 100 μm D Fraction of Human Boutons counted. BNST bed nucleus of the stria terminalis, PB parabrachial nucleus, VPMpc ventroposterior medial parvicellular thalamic nucleus
Example boutons labeled by BoutonNet and human raters. Scale bar 10 μm
Neurons emit axons, which form synapses, the fundamental unit of the nervous system. Neuroscientists use genetic anterograde tracing methods to label the synaptic output of specific neuronal subpopulations, but the resulting data sets are too large for manual analysis, and current automated methods have significant limitations in cost and quality. In this paper, we describe a pipeline optimized to identify anterogradely labeled presynaptic boutons in brain tissue sections. Our histologic pipeline labels boutons with high sensitivity and low background. To automatically detect labeled boutons in slide-scanned tissue sections, we developed BoutonNet. This detector uses a two-step approach: an intensity-based method proposes possible boutons, which are checked by a neural network-based confirmation step. BoutonNet was compared to expert annotation on a separate validation data set and achieved a result within human inter-rater variance. This open-source technique will allow quantitative analysis of the fundamental unit of the brain on a whole-brain scale.
Anorexia Nervosa (AN) is characterized by voluntary food restriction, excessive exercise and extreme body weight loss. AN is particularly prevalent among adolescent females experiencing stress-induced anxiety. We used the animal model, activity-based anorexia (ABA), which captures these characteristics of AN, to reveal the neurobiology underlying individual differences in AN vulnerability. Dorsal raphe (DR) regulates feeding and is recruited when coping inescapable stress. Through chemogenetic activation, we investigated the role of mPFC pyramidal neurons projecting to DR (mPFC→DR) in adolescent female mice’s decision to eat or exercise following ABA induction. Although the DREADD ligand C21 could activate 44% of the mPFC→DR neurons, this did not generate significant group mean difference in the amount of food intake, compared to control ABA mice without chemogenetic activation. However, analysis of individuals’ responses to C21 revealed a significant, positive correlation between food intake and mPFC→DR neurons that co-express cFos, a marker for neuronal activity. cFos expression by GABAergic interneurons (GABA-IN) in mPFC was significantly greater than that for the control ABA mice, indicating recruitment of GABA-IN by mPFC→DR neurons. Electron microscopic immunohistochemistry revealed that GABAergic innervation is 60% greater for the PFC→DR neurons than adjacent Layer 5 pyramidal neurons without projections to DR. Moreover, individual differences in this innervation correlated negatively with food intake specifically on the day of C21 administration. We propose that C21 activates two antagonistic pathways: (1) PFC→DR pyramidal neurons that promote food intake; and (2) GABA-IN in the mPFC that dampen food intake through feedback inhibition of mPFC→DR neurons.
The mirror technique adapted for electron microscopy allows correlating neuronal structures across the cutting plane of adjoining light microscopic sections which, however, have a limited thickness, typically less than 100 µm (Talapka et al. in Front Neuroanat, 2021, 10.3389/fnana.2021.652422 ). Here, we extend the mirror technique for tissue blocks in the millimeter range and demonstrate compatibility with serial block-face electron microscopy (SBEM). An essential step of the methodological improvement regards the recognition that unbound resin must be removed from the tissue surface to gain visibility of surface structures. To this, the tissue block was placed on absorbent paper during the curing process. In this way, neuronal cell bodies could be unequivocally identified using epi-illumination and confocal microscopy. Thus, the layout of cell bodies which were cut by the sectioning plane can be correlated with the layout of their complementary part in the adjoining section processed for immunohistochemistry. The modified mirror technique obviates the spatial limit in investigating synaptology of neurochemically identified structures such as neuronal processes, dendrites and axons.
Quantifying the microstructural and macrostructural geometrical features of the human brain’s connections is necessary for understanding normal aging and disease. Here, we examine brain white matter diffusion magnetic resonance imaging data from one cross-sectional and two longitudinal data sets totaling in 1218 subjects and 2459 sessions of people aged 50–97 years. Data was drawn from well-established cohorts, including the Baltimore Longitudinal Study of Aging data set, Cambridge Centre for Ageing Neuroscience data set, and the Vanderbilt Memory & Aging Project. Quantifying 4 microstructural features and, for the first time, 11 macrostructure-based features of volume, area, and length across 120 white matter pathways, we apply linear mixed effect modeling to investigate changes in pathway-specific features over time, and document large age associations within white matter. Conventional diffusion tensor microstructure indices are the most age-sensitive measures, with positive age associations for diffusivities and negative age associations with anisotropies, with similar patterns observed across all pathways. Similarly, pathway shape measures also change with age, with negative age associations for most length, surface area, and volume-based features. A particularly novel finding of this study is that while trends were homogeneous throughout the brain for microstructure features, macrostructural features demonstrated heterogeneity across pathways, whereby several projection, thalamic, and commissural tracts exhibited more decline with age compared to association and limbic tracts. The findings from this large-scale study provide a comprehensive overview of the age-related decline in white matter and demonstrate that macrostructural features may be more sensitive to heterogeneous white matter decline. Therefore, leveraging macrostructural features may be useful for studying aging and could facilitate comparisons in a variety of diseases or abnormal conditions.
A flowchart of this study. (1) The T1 images were segmented into GM, WM, and cerebrospinal fluid (CSF) and normalized to standard Montreal Neurological Institute (MNI) space. (2) GM images were isotropically smoothed with an 8 mm full-width at half-maximum (FWHM) Gaussian kernel. (3) The morphological distributions from GM images were defined by estimated probability density functions (PDFs) for each region through kernel density estimation (KDE), and the regions were defined by the AAL atlas. (4) The individual GM networks were constructed by computing the symmetric Kullback–Leibler (KL) divergence of their morphological distributions between two regions and converting the KL to similarity measure KLS. (5) The network metrics were calculated by the GRETNA toolbox, and the between-group differences were computed. (6) The age-related differences in network metrics in the two groups and the relationships between cognitive tests and network metrics were computed
Between-group differences in global network metrics as a function of sparsity. (1) The middle column is the schematic representation and calculation formula of network metrics. From top to bottom, they are clustering coefficient, shortest path length or characteristic path length, local efficiency, global efficiency, and the schematic representation of the small-world network and random network. (2) The left and right columns are the between-group differences of the network metrics. The arrows point from the representation of the network parameters to the results of the between-group differences. The error bars represent the standard deviation. One asterisk indicates p < 0.05, and two asterisks indicate p < 0.01, and three asterisks indicate p < 0.001
Between-group differences in rich-club organization and network connections as well as age-related differences in individuals with SCD and NCs. A The hub distributions of the GM networks in the NC group and SCD group. An illustration of the connections divided by hub regions. B The between-group differences in the strength of the network, feeder connectivity, and long connectivity. C The disrupted subnetwork in individuals with SCD is calculated by the network-based statistic (NBS) approach. D The receiver operating characteristic (ROC) curve of the NBS connection strength. E Between-group differences in the intraconnectivity of the five functional organizations. The intraconnectivity strength of the five modules in the NC group (blue line) was normalized to 0, and the relative difference differences in intraconnectivity strength of the five modules in the SCD group are shown by the orange line. F Group-specific age-related differences in NBS connection strength in individuals with SCD and normal controls
Age-related differences in global efficiency and characteristic path length (A), and the distribution of regions with significant age-related differences in nodal global efficiency (B). The anatomical structures were visualized by the BrainNet Viewer toolbox
Age-related differences in local efficiency and clustering coefficient (A), and the distribution of regions with significant age-related differences in nodal local efficiency (B). The anatomical structures were visualized by the BrainNet Viewer toolbox
Subjective cognitive decline (SCD) is characterized by self-experienced deficits in cognitive capacity with normal performance in objective cognitive tests. Previous structural covariance studies showed specific insights into understanding the structural alterations of the brain in neurodegenerative diseases. Moreover, in subjects with neurodegenerative diseases, accelerated brain degeneration with aging was shown. However, the age-related variations in coordinated topological patterns of morphological networks in individuals with SCD remain poorly understood. In this study, 77 individual morphological networks were constructed, including 42 normal controls (NCs) and 35 SCD individuals, from structural magnetic resonance imaging (sMRI). A stepwise linear regression model and partial correlation analysis were constructed to evaluate the differences in age-related alterations of the network properties in individuals with SCD compared with NCs. Compared with NC, the properties of integration and segregation in individuals with SCD were lower, and the aberrant metrics were negatively correlated with age in SCD. The rich-club connections persevered, but the paralimbic system connections were disrupted in individuals with SCD compared with NCs. In addition, age-related differences in nodal global efficiency are distributed mainly in prefrontal cortex regions. In conclusion, the age-related disruption of topological organizations in individuals with SCD may indicate that the degeneration of brain efficiency with aging was accelerated in individuals with SCD.
In the past decades, there has been a growing scientific interest in characterizing neural correlates of meditation training. Nonetheless, the mechanisms underlying meditation remain elusive. In the present work, we investigated meditation-related changes in functional dynamics and structural connectivity (SC). For this purpose, we scanned experienced meditators and control (naive) subjects using magnetic resonance imaging (MRI) to acquire structural and functional data during two conditions, resting-state and meditation (focused attention on breathing). In this way, we aimed to characterize and distinguish both short-term and long-term modifications in the brain’s structure and function. First, to analyze the fMRI data, we calculated whole-brain effective connectivity (EC) estimates, relying on a dynamical network model to replicate BOLD signals’ spatio-temporal structure, akin to functional connectivity (FC) with lagged correlations. We compared the estimated EC, FC, and SC links as features to train classifiers to predict behavioral conditions and group identity. Then, we performed a network-based analysis of anatomical connectivity. We demonstrated through a machine-learning approach that EC features were more informative than FC and SC solely. We showed that the most informative EC links that discriminated between meditators and controls involved several large-scale networks mainly within the left hemisphere. Moreover, we found that differences in the functional domain were reflected to a smaller extent in changes at the anatomical level as well. The network-based analysis of anatomical pathways revealed strengthened connectivity for meditators compared to controls between four areas in the left hemisphere belonging to the somatomotor, dorsal attention, subcortical and visual networks. Overall, the results of our whole-brain model-based approach revealed a mechanism underlying meditation by providing causal relationships at the structure-function level.
ROIs correlated with vitamin B12 status
In previous studies, decreased vitamin B12 and increased plasma homocysteine levels were reported as risk factors for dementia. The aim of this study was to clarify this relationship in earlier ages. Twenty-one healthy middle-aged adults (9 females, 12 males) with a mean age of 46.21 ± 7.99 were retrospectively included in the study. A voxel-based morphometry analysis was performed to measure brain volume. Plasma homocysteine, vitamin B12 levels, verbal and non-verbal memory test performances were recorded. Correlation analyses showed that increased plasma homocysteine was associated with lower memory score. Decreased vitamin B12 level was found to be associated with smaller brain volume in temporal regions. These results suggest that vitamin B12 and plasma homocysteine levels are associated with brain and cognition as early as middle adulthood. Future studies are needed to clarify whether they might be utilized as early hematological biomarkers to predict cognitive decline and neural loss.
The PV2 (Celio 1990), a cluster of parvalbumin-positive neurons located in the ventromedial region of the distal periaqueductal gray (PAG) has not been previously described as its own entity, leading us to study its extent, connections, and gene expression. It is an oval, bilateral, elongated cluster composed of approximately 475 parvalbumin-expressing neurons in a single mouse hemisphere. In its anterior portion it impinges upon the paratrochlear nucleus (Par4) and in its distal portion it is harbored in the posterodorsal raphe nucleus (PDR). It is known to receive inputs from the orbitofrontal cortex and from the parvafox nucleus in the ventrolateral hypothalamus. Using anterograde tracing methods in parvalbumin-Cre mice, the main projections of the PV2 cluster innervate the supraoculomotor periaqueductal gray (Su3) of the PAG, the parvafox nucleus of the lateral hypothalamus, the gemini nuclei of the posterior hypothalamus, the septal regions, and the diagonal band in the forebrain, as well as various nuclei within the reticular formation in the midbrain and brainstem. Within the brainstem, projections were discrete, but involved areas implicated in autonomic control. The PV2 cluster expressed various peptides and receptors, including the receptor for Adcyap1, a peptide secreted by one of its main afferences, namely, the parvafox nucleus. The expression of GAD1 and GAD2 in the region of the PV2, the presence of Vgat-1 in a subpopulation of PV2-neurons as well as the coexistence of GAD67 immunoreactivity with parvalbumin in terminal endings indicates the inhibitory nature of a subpopulation of PV2-neurons. The PV2 cluster may be part of a feedback controlling the activity of the hypothalamic parvafox and the Su3 nuclei in the periaqueductal gray.
Diagrams presenting the overall POND imaging samples which includes children with autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), obsessive compulsive disorder (OCD) and typically developing children (TDC) scanned at the Hospital for Sick Children as of January 2020. Imaging data from T1-weighted (T1w), resting state fMRI (rsfMRI) and diffusion weighted imaging (DWI) sequences are presented. The reasons for exclusion presented for level 1: participants being outside the 6–18 age range at time of scan, a greater than 12 month time gap between scan and CBCL administration, and missing CBCL data; level 2: persistent processing errors at any point within the processing pipeline (e.g. errors in the fMRIprep pipeline); level 3: exclusion based on quality control (QC; details presented in the paper and supplement). The numbers for the final analysed sample for each imaging modality are presented. For the T1w and rs-fMRI samples, participants were scanned on a 3 T Siemens Tim Trio scanner prior to June 2016 when the scanner was upgraded to the PrismaFIT. For rs-fMRI acquisitions, participants scanned on the Tim Trio selected a movie to watch and participants scanned on the PrismaFIT viewed a naturalistic film (inscapes). The study includes only single-shell DWI acquisitions (n = 262) completed on the Tim Trio scanner
Unthresholded spatial p-map of the relationship between externalizing/internalizing behaviors and cortico-amygdalar structural and functional connectivity. A Unthresholded spatial p-maps depicting the relationship between the interaction of externalizing and internalizing behavior and left amygdala volume on each cortical vertex. B Unthresholded spatial p-maps depicting the relationship between externalizing and internalizing behavior and functional connectivity between the left amygdala seed and each cortical vertex. A logp value of 1.6 is considered significant. As seen in the figure, none of the results reached this significance threshold
Relationship between externalizing or internalizing behavior and fractional anisotropy and mean diffusivity (units: mm²/s) of the two white matter tracts of interest: the cingulum bundle and uncinate fasciculus. The depicted relationships are all non-significant. The black line is the regression line and the shaded gray area is the confidence interval. These figures include all data points, including potential outliers. Analyses were run with and without outlier removal; the results remained non-significant in either case. ADHD attention deficit hyperactivity disorder, ASD autism spectrum disorder, OCD obsessive compulsive disorder, CTRL healthy control/typically developing
This figure depicts the bootstrap resampling results for the models examining associations between the externalizing behavior-left amygdala interaction term and whole brain structural covariance and functional connectivity. All other models examined feature similar results as those depicted here (see supplementary). In Panel A, the scatterplots illustrate associations between the mean regression coefficient (averaged across 1000 bootstrapped resamples) and the bootstrapped standard errors of the regression coefficients of each vertex for the structural covariance and functional connectivity models. Pink points depict the vertices with a higher signal (a t-statistic greater than 4). Blue points depict the vertices with low signal (t-statistic less than 4). The low standard errors found for both high and low signal vertices indicate stable results across resampling. Panel B depicts the histogram of the mean regression coefficients of each vertex across the 1000 bootstrapped resampled analyses (distribution–structural covariance: 2.56e-06 ± 1.37e-05; functional connectivity: 0.0002 ± 0.004). Panel C depicts the histogram of the mean t-statistic of each vertex across the 1000 bootstrapped resampled analyses (distribution–structural covariance: 0.357 ± 1.91; functional connectivity: 0.119 ± 1.99). Panel D depicts the histogram of the mean effect size of the model at each vertex across the 1000 bootstrapped resampled analyses (distribution—structural covariance: 8.45e-06 ± 4.66e-05; functional connectivity: 0.00045 ± 0.009). Note, all model parameter distributions (B-D) are centred around zero. The density y-axis in panels B-D figures is the number of points (i.e., vertices) that are in each histogram bin
Background Externalizing and internalizing behaviors contribute to clinical impairment in children with neurodevelopmental disorders (NDDs). Although associations between externalizing or internalizing behaviors and cortico-amygdalar connectivity have been found in clinical and non-clinical pediatric samples, no previous study has examined whether similar shared associations are present across children with different NDDs. Methods Multi-modal neuroimaging and behavioral data from the Province of Ontario Neurodevelopmental Disorders (POND) Network were used. POND participants aged 6–18 years with a primary diagnosis of autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD) or obsessive–compulsive disorder (OCD), as well as typically developing children (TDC) with T1-weighted, resting-state fMRI or diffusion weighted imaging (DWI) and parent-report Child Behavioral Checklist (CBCL) data available, were analyzed (total n = 346). Associations between externalizing or internalizing behavior and cortico-amygdalar structural and functional connectivity indices were examined using linear regressions, controlling for age, gender, and image-modality specific covariates. Behavior-by-diagnosis interaction effects were also examined. Results No significant linear associations (or diagnosis-by-behavior interaction effects) were found between CBCL-measured externalizing or internalizing behaviors and any of the connectivity indices examined. Post-hoc bootstrapping analyses indicated stability and reliability of these null results. Conclusions The current study provides evidence towards an absence of a shared linear relationship between internalizing or externalizing behaviors and cortico-amygdalar connectivity properties across a transdiagnostic sample of children with different primary NDD diagnoses and TDC. Different methodological approaches, including incorporation of multi-dimensional behavioral data (e.g., task-based fMRI) or clustering approaches may be needed to clarify complex brain-behavior relationships relevant to externalizing/internalizing behaviors in heterogeneous clinical NDD populations.
Overview of selected cortical (column 1) and cerebellar (column 2) regions of interest (ROIs) and an example of a corticospinal tract mask derived from the diffusion weighted tractography overlaid on a myelin map derived from the human connectome project pipelines (column 3). Note that the corticospinal tract in column 1 represents the probabilistic tractography model before thresholding, while the representation in column 3 shows the tract after thresholding at 20% of the maximum probability
Association between Cortical Thickness measures pre-flight and a Motor Performance measures post-flight (row 1 and 2); or b differences in Motor Performance from pre- to post-flight (row 3). Results are overlaid on the average mid-thickness surface map for all individuals. Anatomical labels were obtained from the Destrieux atlas except for '*' (originally: posterior ramus of the lateral sulcus). Blue colors indicate negative correlations (e.g., thicker cortex relates to shorter recovery times). Red colors indicate positive correlations (e.g., thicker cortex relates to higher balance scores)
Motor adaptations to the microgravity environment during spaceflight allow astronauts to perform adequately in this unique environment. Upon return to Earth, this adaptation is no longer appropriate and can be disruptive for mission critical tasks. Here, we measured if metrics derived from MRI scans collected from astronauts can predict motor performance post-flight. Structural and diffusion MRI scans from 14 astronauts collected before launch, and motor measures (balance performance, speed of recovery from fall, and tandem walk step accuracy) collected pre-flight and post-flight were analyzed. Regional measures of gray matter volume (motor cortex, paracentral lobule, cerebellum), myelin density (motor cortex, paracentral lobule, corticospinal tract), and white matter microstructure (corticospinal tract) were derived as a-priori predictors. Additional whole-brain analyses of cortical thickness, cerebellar gray matter, and cortical myelin were also tested for associations with post-flight and pre-to-post-flight motor performance. The pre-selected regional measures were not significantly associated with motor behavior. However, whole-brain analyses showed that paracentral and precentral gyri thickness significantly predicted recovery from fall post-spaceflight. Thickness of vestibular and sensorimotor regions, including the posterior insula and the superior temporal gyrus, predicted balance performance post-flight and pre-to-post-flight decrements. Greater cortical thickness pre-flight predicted better performance post-flight. Regional thickness of somatosensory, motor, and vestibular brain regions has some predictive value for post-flight motor performance in astronauts, which may be used for the identification of training and countermeasure strategies targeted for maintaining operational task performance.
Broca’s area is composed of the pars opercularis (PO) and the pars triangularis (PTR) of the inferior frontal gyrus; the anterior ascending ramus of the lateral sulcus (aals) separates the PO from the PTR, and the horizontal ascending ramus of the lateral sulcus (hals) separates the PTR from the pars orbitalis. The morphometry of these two sulci maybe has potential effects on the various functions of Broca’s area. Exploring the morphological variations, hemispheric differences and sex differences of these two sulci contributed to a better localization of Broca's area. BrainVISA was used to reconstruct and parameterize these two sulci based on data from 3D MR images of 90 healthy right-handed subjects. The 3D anatomic morphologies of these two sulci were investigated using 4 sulcal parameters: average depth (AD), average width (AW), outer length (OL) and inner length (IL). The aals and hals could be identified in 98.89% and 98.33%, respectively, of the hemispheres evaluated. The morphological patterns of these two sulci were categorized into four typical types. There were no statistically significant interhemispheric or sex differences in the frequency of the morphological patterns. There was statistically significant interhemispheric difference in the IL of the aals. Significant sex differences were found in the AD and the IL of the aals and OL of the hals. Our results not only provide a structural basis for functional studies related to Broca’s area but also are helpful in determining the precise position of Broca’s area in neurosurgery.
Myelination within the central nervous system (CNS) is crucial for the conduction of action potentials by neurons. Variation in compact myelin morphology and the structure of the paranode are hypothesised to have significant impact on the speed of action potentials. There are, however, limited experimental data investigating the impact of changes in myelin structure upon conductivity in the central nervous system. We have used a genetic model in which myelin thickness is reduced to investigate the effect of myelin alterations upon action potential velocity. A detailed examination of the myelin ultrastructure of mice in which the receptor tyrosine kinase Tyro3 has been deleted showed that, in addition to thinner myelin, these mice have significantly disrupted paranodes. Despite these alterations to myelin and paranodal structure, we did not identify a reduction in conductivity in either the corpus callosum or the optic nerve. Exploration of these results using a mathematical model of neuronal conductivity predicts that the absence of Tyro3 would lead to reduced conductivity in single fibres, but would not affect the compound action potential of multiple myelinated neurons as seen in neuronal tracts. Our data highlight the importance of experimental assessment of conductivity and suggests that simple assessment of structural changes to myelin is a poor predictor of neural functional outcomes.
The human brain spends several years bootstrapping itself through intrinsic and extrinsic modulation, thus gradually developing both spatial organization and functions. Based on previous studies on developmental patterns and inter-individual variability of the corpus callosum (CC), we hypothesized that inherent variations of CC shape among infants emerge, depending on the position within the CC, along the developmental timeline. Here we used longitudinal magnetic resonance imaging data from infancy to toddlerhood and investigated the area, thickness, and shape of the midsagittal plane of the CC by applying multilevel modeling. The shape characteristics were extracted using the Procrustes method. We found nonlinearity, region-dependency, and inter-individual variability, as well as intra-individual consistencies, in CC development. Overall, the growth rate is faster in the first year than in the second year, and the trajectory differs between infants; the direction of CC formation in individual infants was determined within six months and maintained to two years. The anterior and posterior subregions increase in area and thickness faster than other subregions. Moreover, we clarified that the growth rate of the middle part of the CC is faster in the second year than in the first year in some individuals. Since the division of regions exhibiting different tendencies coincides with previously reported divisions based on the diameter of axons that make up the region, our results suggest that subregion-dependent individual variability occurs due to the increase in the diameter of the axon caliber, myelination partly due to experience and axon elimination during the early developmental period.
The study was designed to analyze the nNOS positive neurons present in the indusium griseum by describing their distribution and morphology. To this purpose, sagittal serial sections from paraffin or frozen autopsy specimens of corpus callosum including the overlying indusium griseum were processed by immunohistochemistry and immunofluorescence, using an antibody against the neuronal form of the enzyme nitric oxyde synthase. To test the specificity of the antibody used, Western Blot was performed in the indusium griseum of the same specimens. The stainings revealed the presence of many neuronal nitric oxyde synthase-immunopositive neurons in human indusium griseum, located along both rostral-caudal and medio-lateral directions. In particular, they were more numerous 1 mm apart from the midline, and their number peaked over the body of the corpus callosum. They showed different morphologies; in some cases, they were located at the boundary between indusium griseum and corpus callosum, more densely packed in proximity to the pial arteries penetrating into the corpus callosum. The significant presence and distribution of neuronal nitric oxyde synthase-immunopositive neurons suggests that indusium griseum likely plays a functional role in the neurovascular regulation within the corpus callosum. Graphical abstract Schematic representation of human adult IG and the neurovascular unit originating from sopracallosal artery (Sca) that branches into smaller arterioles (Br) (created in PowerPoint). The arterioles cross the three layers of IG (layers I, II and III) and penetrate into the CC separated from IG by the Virchow-Robin space (VRs). As the arterioles go deeper, this space disappears and the vascular basement membrane comes into direct contact with the astrocytic end-feets (intracallosal arterioles and capillaries). nNOS-immunopositive neurons (nNOS IP N) surround the arterioles and control the vasomotore tone secreting nitric oxyde (NO). Two morphological types of nNOS IP N can be appreciated by the use of different colors: fusiform (blue) and ovoidal (pink). Also NeuN-immunopositive neurons (N) and many astrocytes (As) are present, more numerous in IG than in CC.
Spatially remote brain regions show synchronized activity as typically revealed by correlated functional MRI (fMRI) signals. An emerging line of research has focused on the temporal fluctuations of connectivity; however, its relationships with stationary connectivity have not been clearly illustrated. We examined dynamic and stationary connectivity when the participants watched four different movie clips. We calculated point-by-point multiplication between two regional time series to estimate the time-resolved dynamic connectivity, and estimated the inter-individual consistency of the dynamic connectivity time series. Widespread consistent dynamic connectivity was observed for each movie clip, which also showed differences between the clips. For example, a cartoon movie clip, Wall-E, showed more consistent of dynamic connectivity with the posterior cingulate cortex and supramarginal gyrus, while a court drama clip, A Few Good Men, showed more consistent of dynamic connectivity with the auditory cortex and temporoparietal junction, which might suggest the involvement of specific brain processing for different movie contents. In contrast, the stationary connectivity as measured by the correlations between regional time series was highly similar among the movie clips, and showed fewer statistically significant differences. The patterns of consistent dynamic connectivity could be used to classify different movie clips with higher accuracy than the stationary connectivity and regional activity. These results support the functional significance of dynamic connectivity in reflecting functional brain changes, which could provide more functionally relevant information than stationary connectivity.
Experimental tasks. A Visual motion task. Blocks of coherently moving dot fields (flow fields) were interleaved with blocks of randomly moving dot fields. B Pointing/Saccade task. Subjects alternated blocks of memory delayed saccadic and hand/foot pointing movements to peripheral visual targets with passive fixation blocks
Region sensitivity to saccadic and hand/foot pointing movements. A Group overlap of the six individually defined egomotion-related ROIs rendered on the flattened and inflated (dorsomedial, medial, and lateral views) representation of the left hemisphere of the Conte69 surface-based atlas. Each yellow patch represents the weighted average location of individual ROIs. The color bar shows the level of saturation, where solid yellow represents the maximum overlap across 90% of total subjects. In the flat map, each colored ring visualizes the distribution of regional hemodynamic responses for the eye (red), hand (green), and foot (blue) conditions in the respective ROI. In inset of Fig. 2A, raw sketches describe the effector used and an example of the movement trajectory. Note that target positions in the raw sketches were shown for display purpose only, since movements were performed only during the ‘go phase’ with respect to a ‘remembered’ target location not present anymore on the screen (see Fig. 1B). On the right, the plot shows the average of BOLD signal changes (± SE) in each ROI considered B visual and C visuomotor areas for eye, hand, and foot conditions relative to the fixation baseline. Asterisks above the columns refer to the t test versus zero. *p < .017, Bonferroni correction; **p < .01; ***p < .005; ****p < .001. Asterisks above square brackets refer to paired comparisons used to explore effector-related differences. **p < .01; ****p < .001
PPIs seed-to-seed. PPIs showing significant effects are schematically represented by directional arrows. Arrows identify source-to-target directions for each experimental condition: A eye condition with red arrows, B hand condition with green arrows, and C foot condition with blue arrows. In inset, raw sketches describe the effector used and an example of the movement trajectory. Different arrow line thicknesses represent the statistical significance of each connection. For each of these conditions, a group overlap of the three individually defined visual (left column) and visuomotor (right column) areas is rendered on the inflated (left column: posterolateral and medial views; right column: medial and lateral views) representation of the left hemisphere of the Conte69 surface-based atlas. Each yellow patch represents the weighted average location of an individual ROI
A The table resumes significant seed-to-seed PPIs. • = Eye saccade; • = Hand pointing; • = Foot pointing. B The plot shows the average of BOLD signal changes (± SE) as a function of effector (eye, hand, and foot) and source (visual and visuomotor). In inset of Fig. 4B, raw sketches describe the effector used and an example of the movement trajectory. Asterisks above square brackets refer to Bonferroni-corrected post hoc tests. *p < .05; ****p < .001
Integration of proprioceptive signals from the various effectors with visual feedback of self-motion from the retina is necessary for whole-body movement and locomotion. Here, we tested whether the human visual motion areas involved in processing optic flow signals simulating self-motion are also activated by goal-directed movements (as saccades or pointing) performed with different effectors (eye, hand, and foot), suggesting a role in visually guiding movements through the external environment. To achieve this aim, we used a combined approach of task-evoked activity and effective connectivity (PsychoPhysiological Interaction, PPI) by fMRI. We localized a set of six egomotion-responsive visual areas through the flow field stimulus and distinguished them into visual (pIPS/V3A, V6+ , IPSmot/VIP) and visuomotor (pCi, CSv, PIC) areas according to recent literature. We tested their response to a visuomotor task implying spatially directed delayed eye, hand, and foot movements. We observed a posterior-to-anterior gradient of preference for eye-to-foot movements, with posterior (visual) regions showing a preference for saccades, and anterior (visuomotor) regions showing a preference for foot pointing. No region showed a clear preference for hand pointing. Effective connectivity analysis showed that visual areas were more connected to each other with respect to the visuomotor areas, particularly during saccades. We suggest that visual and visuomotor egomotion regions can play different roles within a network that integrates sensory–motor signals with the aim of guiding movements in the external environment.
Summarized methodology of extraction of behavioral metrics. A1, A2, and A3 figure an example of a possible distribution across time of activity episodes for a participant, A1 and A2 being activity episodes in the free phase and A3 an activity episode in the guided phase. In this specific case, the computation of activity time ratio is described, for instance for the free phase, as the sum of the durations of A1 and A2 activity episodes divided by the total duration of the free phase. Similarly, W1–W8 figure a possible distribution across time of walking episodes for a participant. In this specific case, walking metrics, for instance for the free phase, are computed as follows: walking occurrences is the total number of walking episodes in the free phase (W1–W4), walking acceleration is the mean acceleration of walking episodes W1–W4, walking duration is the mean duration of walking episodes W1–W4
Effects of group and phase on four metrics quantifying goal-directed behaviors. A Activity time ratio. B Occurrences of walking episodes. C Mean acceleration of walking episodes. D Mean duration of walking episodes. BvFTD patients: N = 20; controls: N = 16. Only significant effects obtained from ANOVA tests are displayed for each of the four metrics. Extreme outlier measures were identified and removed: 3 measures of activity time ratio (1 control in free phase/2 controls in guided phase), 2 measures of walking acceleration (1 bvFTD in free phase/1 control in guided phase) and 1 measure of walking duration (1 control in free phase). In the boxplots: horizontal lines represent the first, second (median) and third quartiles of the distribution; vertical bars above and below the boxes figure the lowest 25% and the highest 25% of values, respectively; the dots indicate outliers (which were not identified as extreme outliers)
Correlations between apathy measured by the SAS and the four behavioral metrics. A Activity time ratio averaged on free and guided phases. B Occurrences of walking episodes averaged on free and guided phases. C Mean acceleration of walking episodes averaged on free and guided phases. D Mean duration of walking episodes averaged on free and guided phases. BvFTD patients: N = 20; Controls: N = 16. R is the Spearman’s rank correlation coefficient between the two variables; SAS, Starkstein Apathy Scale
Negative association between F1 and fALFF index of signal power in several regions of the prefrontal cortex. N = 34 (bvFTD: N = 18/controls: N = 16). Effects are corrected for age and sex, and for family-wise error at the level of individual clusters at P < 0.05. F1, global reduction of goal-directed behaviors
Associations found between F1/F2 and the connectivity of SN/DMN hubs. We observed a negative association between F1 and the seed-based connectivity of SN hubs and on the opposite, a positive association between F2 and the seed-based connectivity of two DMN hubs. N = 34 (bvFTD: N = 18/controls: N = 16). Effects are corrected for age and sex, and for family-wise error at the level of individual clusters at P < 0.05. SBC, seed-based connectivity; F1, global reduction of goal-directed behaviors; F2, specific deficit of self-initiation
We explored the resting state functional connectivity correlates of apathy assessed as a multidimensional construct, using behavioral metrics, in behavioral variant frontotemporal dementia (bvFTD). We recorded the behavior of 20 bvFTD patients and 16 healthy controls in a close-to-real-life situation including a free phase (FP—in which actions were self-initiated) and a guided phase (GP—in which initiation of actions was facilitated by external guidance). We investigated the activity time and walking episode features as quantifiers of apathy. We used the means ((FP + GP)/2) and the differences (FP-GP) calculated for these metrics as well as measures by questionnaires to extract apathy dimensions by factor analysis. We assessed two types of fMRI-based resting state connectivity measures (local activity and seed-based connectivity) and explored their relationship with extracted apathy dimensions. Apathy in bvFTD was associated with lower time spent in activity combined with walking episodes of higher frequency, lower acceleration and higher duration. Using these behavioral metrics and apathy measures by questionnaires, we disentangled two dimensions: the global reduction of goal-directed behaviors and the specific deficit of self-initiation. Global apathy was associated with lower resting state activity within prefrontal cortex and lower connectivity of salience network hubs while the decrease in self-initiation was related to increased connectivity of parietal default-mode network hubs. Through a novel dimensional approach, we dissociated the functional connectivity correlates of global apathy and self-initiation deficit. We discussed in particular the role of the modified connectivity of lateral parietal cortex in the volitional process.
The frontoparietal control network (FPCN) plays a central role in tuning connectivity between brain networks to achieve integrated cognitive processes. It has been proposed that two subnetworks within the FPCN separately regulate two antagonistic networks: the FPCNa is connected to the default network (DN) that deals with internally oriented introspective processes, whereas the FPCNb is connected to the dorsal attention network (DAN) that deals with externally oriented perceptual attention. However, cooperation between the DN and DAN induced by distinct task demands has not been well-studied. Here, we characterized the dynamic cooperation among the DN, DAN, and two FPCN subnetworks in a task in which internally oriented self-referential processing could facilitate externally oriented visual working memory. Functional connectivity analysis showed enhanced coupling of a circuit from the DN to the FPCNa, then to the FPCNb, and finally to the DAN when the self-referential processing improved memory recognition in high self-referential conditions. The direct connection between the DN and DAN was not enhanced. This circuit could be reflected by an increased chain-mediating effect of the FPCNa and the FPCNb between the DN and DAN in high self-referential conditions. Graph analysis revealed that high self-referential conditions were accompanied by increased global and local efficiencies, and the increases were mainly driven by the increased efficiency of FPCN nodes. Together, our findings extend prior observations and indicate that the coupling between the two FPCN subnetworks serves as a bridge between the DN and DAN, supporting the interaction between internally oriented and externally oriented processes.
Stimuli, conditions and trial structures. A Examples of stimuli used in the main study. Top panel: tools presented at 45, 0, and 315 degrees. Bottom panel: tools presented at 135, 180, and 225 degrees. B Four study conditions resulting from the combination of three different action goals (indicated by goal cues) and two sets of stimulus orientations. C Trial structure and timing of the main experiment, using an event-related design. D Trial structure and timing of the visual tool use localizer task with a block design. E Trial structure and timing of the background study on structure-based (i.e., grasping to displace or move) vs. function-based pantomimed grasping of tools, utilizing a block design
Brain areas showing significant increases of neural activity during critical localizer tasks, and background comparisons from the main experiment, involving the planning of tool-directed grasps compared to the planning of the reach-and-move task. A Significantly greater neural activity observed for pantomimed grasp-to-use vs. grasp-to-displace task, shown in warm colors, and its inverse contrast shown in cold colors, collapsed across the dominant right and non-dominant left hand. B Neural activity in pantomimed tool use vs. manually simulated animal movements (shown in warm colors), and its inverse contrast (shown in cold colors), collapsed across hands. C Planning of tool-directed grasp pantomimes with the right hand. D Planning of tool-directed grasp pantomimes with the left hand. Both in (C) and (D), the obtained neural activity was averaged across three different study conditions, involving difficult grasp-to-use, easy grasp-to-use, and grasp-to-pass tasks. E Overlays of neural activity for the three tasks, contrasted separately with the reach-and-move task, but collapsed across the two hands. The obtained clusters, and their most representative slices in panel C and D, were thresholded at least at Z > 3.1, and a corrected cluster significance threshold of p = 0.05. Volumetric surface renderings were obtained by means of trilinear interpolation, and their projection onto mid-thickness inflated, and flat surfaces of the connectome workbench atlas, and subsequently demarcated with borders of multi-modal parcellations implemented in this software. The labels of the involved areas can be found on flat maps, and more detailed descriptions of the obtained effects can be found in the main text
Brain areas showing significant increases of neural activity during planning different tool-directed grasps, contingent on action goal and tool orientation. Brain areas with significantly greater increases for the planning of demanding grasp-to-use, as compared to grasp-to-pass tasks with (A) the right hand, and (B) the left hand. Areas showing significantly greater increases of neural activity during the planning of grasp-to-pass as compared to easy grasp-to-use tasks with (C) the right hand, and (D) the left hand. Areas with significantly greater increases of neural activity for the planning of demanding as compared to easy grasp-to-use tasks, with (E) the right hand, and (F) the left hand
Brain areas showing significant decodings of planning grasp-to-use (GTU) and grasp-to-pass (GTP) tasks. A The demanding GTU (dGTU) and GTP tasks decoded for the right hand. B The dGTU and GTP tasks decoded for the left hand. C The easy GTU (eGTU) and GTP tasks decoded for the right hand. D The eGTU and GTP tasks decoded for the left hand. E–J The dGTU, GTP, and eGTU tasks decoded in the context of the reach-and-move (RAM) task, both for the right and left hand. Borders in panels A–D were displayed in areas where significant decoding accuracies were obtained. A constant set of parietal borders was used throughout panels E–J (except for cases with no decoding capabilities) as these borders correspond to the outcomes from the contrast involving planning reach-and-move action from the univariate analysis
The results of ROI analyses for the planning phase. A–G Mean percent signal change within each ROI is plotted relative to the resting baseline for the following Tasks: demanding grasp-to-use (dGTU) task, easy grasp-to-use (eGTU) task, grasp-to-pass (GTP) task, and reach-and-move (RAM) task. (H) The overview of ROI locations depicted on the Connectome Workbench template brain. Asterisks indicate differences with Bonferroni-corrected p values of at least 0.05 (*), 0.01 (**), or 0.001 (***)
The praxis representation network (PRN) of the left cerebral hemisphere is typically linked to the control of functional interactions with familiar tools. Surprisingly, little is known about the PRN engagement in planning and execution of tool-directed actions motivated by non-functional but purposeful action goals. Here we used functional neuroimaging to perform both univariate and multi-voxel pattern analyses (MVPA) in 20 right-handed participants who planned and later executed, with their dominant and non-dominant hands, disparate grasps of tools for different goals, including: (1) planning simple vs. demanding functional grasps of conveniently vs. inconveniently oriented tools with an intention to immediately use them, (2) planning simple—but non-functional—grasps of inconveniently oriented tools with a goal to pass them to a different person, (3) planning reaching movements directed at such tools with an intention to move/push them with the back of the hand, and (4) pantomimed execution of the earlier planned tasks. While PRN contributed to the studied interactions with tools, the engagement of its critical nodes, and/or complementary right hemisphere processing, was differently modulated by task type. E.g., planning non-functional/structural grasp-to-pass movements of inconveniently oriented tools, regardless of the hand, invoked the left parietal and prefrontal nodes significantly more than simple, non-demanding functional grasps. MVPA corroborated decoding capabilities of critical PRN areas and some of their right hemisphere counterparts. Our findings shed new lights on how performance of disparate action goals influences the extraction of object affordances, and how or to what extent it modulates the neural activity within the parieto-frontal brain networks.
3D reconstruction of the right hemisphere (in lateral view) of human and macaque brains showing the location and extent of the areas that occupy the human angular gyrus and their macaque counterparts. Abbreviations: pcs post-central sulcus, as angular sulcus, ips intraparietal sulcus, lf lateral fissure, sts superior temporal sulcus, its inferior temporal sulcus, aos anterior occipital sulcus, los lateral occipital sulcus, tos transverse occipital sulcus, cs central sulcus, pos parietal-occipital sulcus
High-resolution photomicrographs of representative cytoarchitectonic fields through human areas PGp and PGa, and macaque areas Opt and PG. Scale bar, 300 μm. Roman numerals indicate cytoarchitectonic layers
High-resolution photomicrographs of representative myeloarchitectonic fields through human areas PGp and PGa, and macaque areas Opt and PG. Scale bar, 300 μm. Arabic numerals indicate myeloarchitectonic layers
Laminar distribution of receptors for glutamate (AMPA, kainate, NMDA), GABA (GABAA, GABAB, GABAA/BZ), acetylcholine (M1, M2, M3), norepinephrine (α1,α2)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(\alpha_{1} ,\,\alpha_{2} )$$\end{document}, serotonin (5-HT1A, 5-HT2), and dopamine (D1) in human areas PGp and PGa, and macaque areas Opt and PG. Color coding indicates receptor densities in fmol/mg protein. Blue tones indicate low densities and red tones high densities. For numeric information concerning receptor densities, see Table 2
The angular gyrus roughly corresponds to Brodmann’s area 39, which is a multimodal association brain region located in the posterior apex of the human inferior parietal lobe, at its interface with the temporal and occipital lobes. It encompasses two cyto- and receptor architectonically distinct areas: caudal PGp and rostral PGa. The macaque brain does not present an angular gyrus in the strict sense, and the establishment of homologies was further hindered by the fact that Brodmann defined a single cytoarchitectonic area covering the entire guenon inferior parietal lobule in the monkey brain, i.e. area 7. Latter architectonic studies revealed the existence of 6 architectonically distinct areas within macaque area 7, further connectivity and functional imaging studies supported the hypothesis that the most posterior of these macaque areas, namely Opt and PG, may constitute the homologs of human areas PGp and PGa, respectively. The present review provides an overview of the cyto-, myelo and receptor architecture of human areas PGp and PGa, as well as of their counterparts in the macaque brain, and summarizes current knowledge on the connectivity of these brain areas. Finally, the present study elaborates on the rationale behind the definition of these homologies and their importance in translational studies.
The parietal lobe is a region of especially pronounced change in human brain evolution. Based on comparative neuroanatomical studies, the inferior parietal lobe (IPL) has been shown to be disproportionately larger in humans relative to chimpanzees and macaques. However, it remains unclear whether the underlying histological architecture of IPL cortical areas displays human-specific organization. Chimpanzees are among the closest living relatives of humans, making them an ideal comparative species to investigate potential evolutionary changes in the IPL. We parcellated the chimpanzee IPL using cytoarchitecture and myeloarchitecture, in combination with quantitative comparison of cellular features between the identified cortical areas. Four major areas on the lateral convexity of the chimpanzee IPL (PF, PFG, PG, OPT) and two opercular areas (PFOP, PGOP) were identified, similar to what has been observed in macaques. Analysis of the quantitative profiles of cytoarchitecture showed that cell profile density was significantly different in a combination of layers III, IV, and V between bordering cortical areas, and that the density profiles of these six areas supports their classification as distinct. The similarity to macaque IPL cytoarchitecture suggests that chimpanzees share homologous IPL areas. In comparison, human rostral IPL is reported to differ in its anatomical organization and to contain additional subdivisions, such as areas PFt and PFm. These changes in human brain evolution might have been important as tool making capacities became more complex.
A histogram of all latencies reported in previous EEG/MEG of Table 1 with a source localized in the AG. Latencies are calculated across studies for the left (top plot) and right (bottom plot) AG (bin width = 10 ms)
A schematic illustration of the role(s) of the AG in sensemaking. (top) Sensemaking is an active optimization process that culminates in the integration of different sources of information (converging multimodal inputs, current context, prior experiences, and goal/purpose). The converging inputs to the AG convey information not limited to linguistic materials but might also include for instance gestures, facial expressions, or body movements. The outcome of this process is to give meaning to external sensory information or internal thoughts so that apposite actions and decisions are made within a rapidly-changing environment. See “A unifying model about the AG in sensemaking” for a detailed rationale. (bottom, left) the main processes involved in the three-phase unifying model are illustrated along two dimensions: by time of occurrence on the vertical axis (in [ms] after stimulus presentation) and by hemisphere on the horizontal axis (with a bias toward the left or right AG). For example, outlining current context is defined at early latencies with a relative dominance/bias toward the right AG. Likewise, retrieval of relevant knowledge is defined at later latencies with a relative dominance/bias toward the left AG. (bottom, right) the most likely white matter connections and cortical regions that interact with the AG at different time windows (roughly ranked from top to bottom for early versus late interactions). This list of connection and regions is not exhaustive. This is also a crude approximation as some interactions may start early but last longer than other interactions, and some regions might be activated much earlier but only interact with the AG at later stages. For a detailed discussion see “A unifying model about the AG in sensemaking”
EEG/MEG studies that identified an effect in the AG (listed alphabetically).
Here, the functions of the angular gyrus (AG) are evaluated in the light of current evidence from transcranial magnetic/electric stimulation (TMS/TES) and EEG/MEG studies. 65 TMS/TES and 52 EEG/MEG studies were examined in this review. TMS/TES literature points to a causal role in semantic processing, word and number processing, attention and visual search, self-guided movement, memory, and self-processing. EEG/MEG studies reported AG effects at latencies varying between 32 and 800 ms in a wide range of domains, with a high probability to detect an effect at 300–350 ms post-stimulus onset. A three-phase unifying model revolving around the process of sensemaking is then suggested: (1) early AG involvement in defining the current context, within the first 200 ms, with a bias toward the right hemisphere; (2) attention re-orientation and retrieval of relevant information within 200–500 ms; and (3) cross-modal integration at late latencies with a bias toward the left hemisphere. This sensemaking process can favour accuracy (e.g. for word and number processing) or plausibility (e.g. for comprehension and social cognition). Such functions of the AG depend on the status of other connected regions. The much-debated semantic role is also discussed as follows: (1) there is a strong TMS/TES evidence for a causal semantic role, (2) current EEG/MEG evidence is however weak, but (3) the existing arguments against a semantic role for the AG are not strong. Some outstanding questions for future research are proposed. This review recognizes that cracking the role(s) of the AG in cognition is possible only when its exact contributions within the default mode network are teased apart.
Grey and white matter structures damaged in personal neglect. a The lesions from the voxel lesion symptom mapping (Lesymap) and the comparison with the null model (i.e. only clinical variables). Numbers refer to the Z in the MNI coordinates. b Thalamus (X = 18; Y = 17; Z = 5); in the square, details of the thalamic cluster of lesion are shown. c Lesions in the gyrus of Heschl (X = 46; Y = 12; Z = 8). Colour bar represents the p statistics resulting from the lesion analyses. 10-FWER: p values are calculated from the tenth highest t value and familywise error corrected. d Medial and lateral view of the fornix. e Antero-medial view of the network of personal neglect as resulting from the comparisons of the regression models and including the gyrus of Heschl (green), thalamus (yellow), and fornix (blue). L left, R right
Personal neglect is a disorder in the perception and representation of the body that causes the patients to behave as if the contralesional side of their body does not exist. This clinical condition has not been adequately investigated in the past as it has been considered a symptom of unilateral spatial neglect, which has mainly been studied with reference to extrapersonal space. Only a few studies with small samples have investigated the neuroanatomical correlates of personal neglect, and these have mainly focused on discrete cortical lesions and modular accounts, as well as being based on the hypothesis that this disorder is associated with somatosensory and spatial deficits. In the present study, we tested the novel hypothesis that personal neglect may be associated not only with discrete cortical and subcortical lesions, but also with disconnections of white matter tracts. We performed an advanced lesion analyses in a large sample of 104 right hemisphere damaged patients, 72 of whom were suffering from personal neglect. Results from the analyses of the grey and white matter were controlled for co-occurrent clinical variables such as extrapersonal neglect, anosognosia for hemiplegia and motor deficits, along with other lesion-related variables such as lesion size and the interval from the lesion onset to neuroimaging recordings. Our results reveal that personal neglect is associated with lesions in a medial network which involves the temporal cortex (Heschl’s gyrus), the ventro-lateral nuclei of the thalamus and the fornix. This suggests that personal neglect involves a convergence between sensorimotor processes, spatial representation and the processing of self-referred information (episodic memory).
Neuroanatomical location of the parietal cortex and its major subdivisions. Here we focus on the intraparietal sulcus (IPS), angular gyrus (AG), and supramarginal gyrus (SMG)
Top left: The four LPC functional connectivity networks derived from ICA (Humphreys et al. 2020a). The results show four separable functional networks (executive network in blue, DMN in green, language network in red, and parieto-visual network in yellow) that implicate different LPC regions: a dorsal region (1: dorsal PGa/IPS) and three ventral AG regions: a central region (2: mid PGp; mAG), an anterior region (3: ventral PGa; aAG), and a posterior region (4: posterior PGp; pAG). Top right: The results from the DTI analysis (Humphreys et al. 2022b), using the four functional ICA-derived ROIs as seed regions. Consistent with the functional connectivity data, the dorsal region (AG/IPS) showed long-range connectivity with lateral frontal executive control regions (dorsolateral prefrontal cortex; DLPFC). In contrast, within the ventral AG, the anterior region (aAG) showed connectivity with temporal lobe language areas (middle- and superior-temporal gyrus (MTG and STG); the mAG showed connectivity with areas involved in the DMN and the core recollection network (hippocampus and precuneus) and the pAG connected with areas including the medial parietal cortex [inferior temporal gyrus (ITG) and fusiform gyrus (FG)] and occipital cortex. Note: there are also some additional connections shown in the figure (e.g. mAG to MTG/STG, and mAG to occipital cortex), which may be consistent with the evidence of a graded- rather than sharp-shift in connectivity between regions. Bottom panel: The ROI results from two fMRI studies (Humphreys et al. 2020a, 2022b) using the same LPC regions shown in the top panel above. The task activation profile varied across subregions, the pattern of which closely mirrored its functional and structural connectivity profile. Specifically, consistent with the role of IPS as part of a domain-general executive processing network, the dorsal region (blue) demonstrated a domain-general response with the level of activation correlating with task difficulty both within and across cognitive tasks. Ventral AG also showed a functional response consistent with each region’s individual connectivity profile. Specifically, the central AG (mAG; green), which is functionally connected with the DMN and episodic retrieval network, showed a strong positive response during episodic retrieval, with activation correlating with memory vividness. This region was deactivated by all other tasks, with the level of deactivation inversely correlated with task difficulty. In contrast, the anterior region (aAG; red) that connected with the fronto-temporal language system showed positive activation for only the sentence task alone, and the posterior region (pAG; yellow) was part of the visual/SPL network only responded to tasks with pictorial stimuli (the picture sequence and picture-decision tasks)
Decades of neuropsychological and neuroimaging evidence have implicated the lateral parietal cortex (LPC) in a myriad of cognitive domains, generating numerous influential theoretical models. However, these theories fail to explain why distinct cognitive activities appear to implicate common neural regions. Here we discuss a unifying model in which the angular gyrus forms part of a wider LPC system with a core underlying neurocomputational function; the multi-sensory buffering of spatio-temporally extended representations. We review the principles derived from computational modelling with neuroimaging task data and functional and structural connectivity measures that underpin the unified neurocomputational framework. We propose that although a variety of cognitive activities might draw on shared underlying machinery, variations in task preference across angular gyrus, and wider LPC, arise from graded changes in the underlying structural connectivity of the region to different input/output information sources. More specifically, we propose two primary axes of organisation: a dorsal–ventral axis and an anterior–posterior axis, with variations in task preference arising from underlying connectivity to different core cognitive networks (e.g. the executive, language, visual, or episodic memory networks).
Top-cited authors
Simon B Eickhoff
  • Forschungszentrum Jülich
Angela R Laird
  • Florida International University
Karl Zilles
  • Forschungszentrum Jülich
Hugues Duffau
  • Centre Hospitalier Universitaire de Montpellier
Patrick Hof
  • Icahn School of Medicine at Mount Sinai