Human Brain Mapping

Published by Wiley
Online ISSN: 1097-0193
Print ISSN: 1065-9471
Discipline: Neuroscience
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Aims and scope

Publishes peer-reviewed basic, clinical, technical, and theoretical research in the interdisciplinary and rapidly expanding field of human brain mapping.

Recent publications
A recent neuropsychoeconomic model of trust propensity argues that an individual uses economic (executive functions) and social (social cognition) rationality strategies to transform the risk of treachery (affect) into positive expectations of reciprocity, promoting trust in another person. Previous studies have shown that the trust of older adults is associated with affect and social cognition. However, little is known about the intrinsic functional connectivity correlated with trust propensity or whether trust propensity is associated with executive functions in older adults. In this study, we examined the association between trust propensity (measured by a one-shot trust game [TG]), social preference (measured by a one-shot dictator game), and executive functions (measured by a battery of neuropsychological tests). We also performed connectome-based predictive modeling (CPM) and computational lesion analysis to identify the key large-scale resting-state functional connectivity (RSFC) underlying the prediction of trust propensity. Our behavioral results showed a lower trust propensity in older adults in our study than in younger adults in a previous meta-analysis. Furthermore, trust propensity was associated with social preference, but there was no significant relationship between trust propensity and executive functions. The neuroimaging results showed that the cingulo-opercular network (CON) and the default mode network (DMN), rather than the frontoparietal network (FPN), significantly contributed to the prediction of trust propensity in older adults. Our findings suggest that older adults rely less on economic rationality (executive functions, associated with FPN) in trust games. Rather, they are likely to depend more on social rationality (social cognition, associated with social preference and DMN) to resolve the risk of treachery (affect, associated with CON) in trust dilemmas. This study contributes to a better understanding of the neural underpinnings of older adults' trust propensity.
There is a pressing need to understand the factors that predict prognosis in progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS), with high heterogeneity over the poor average survival. We test the hypothesis that the magnitude and distribution of connectivity changes in PSP and CBS predict the rate of progression and survival time, using datasets from the Cambridge Centre for Parkinson-plus and the UK National PSP Research Network (PROSPECT-MR). Resting-state functional MRI images were available from 146 participants with PSP, 82 participants with CBS, and 90 healthy controls. Large-scale networks were identified through independent component analyses, with correlations taken between component time series. Independent component analysis was also used to select between-network connectivity components to compare with baseline clinical severity, longitudinal rate of change in severity, and survival. Transdiagnostic survival predictors were identified using partial least squares regression for Cox models, with connectivity compared to patients' demographics, structural imaging, and clinical scores using five-fold cross-validation. In PSP and CBS, between-network connectivity components were identified that differed from controls, were associated with disease severity, and were related to survival and rate of change in clinical severity. A transdiagnostic component predicted survival beyond demographic and motion metrics but with lower accuracy than an optimal model that included the clinical and structural imaging measures. Cortical atrophy enhanced the connectivity changes that were most predictive of survival. Between-network connectivity is associated with variability in prognosis in PSP and CBS but does not improve predictive accuracy beyond clinical and structural imaging metrics.
The study of the brain's dynamical activity is opening a window to help the clinical assessment of patients with disorders of consciousness. For example, glucose uptake and the dysfunctional spread of naturalistic and synthetic stimuli has proven useful to characterize hampered consciousness. However, understanding of the mechanisms behind loss of consciousness following brain injury is still missing. Here, we study the propagation of endogenous and in-silico exogenous perturbations in patients with disorders of consciousness, based upon directed and causal interactions estimated from resting-state fMRI data, fitted to a linear model of activity propagation. We found that patients with disorders of consciousness suffer decreased capacity for neural propagation and responsiveness to events, and that this can be related to severe reduction of glucose metabolism as measured with [18 F]FDG-PET. In particular, we show that loss of consciousness is related to the malfunctioning of two neural circuits: the posterior cortical regions failing to convey information, in conjunction with reduced broadcasting of information from subcortical, temporal, parietal and frontal regions. These results shed light on the mechanisms behind disorders of consciousness, triangulating network function with basic measures of brain integrity and behavior.
Distinguishing imagination and thoughts from information we perceived from the environment, a process called reality-monitoring, is important in everyday situations. Although reality monitoring seems to overlap with the concept of self-monitoring, which allows one to distinguish self-generated actions or thoughts from those generated by others, the two concepts remain largely separate cognitive domains and their common brain substrates have received little attention. We investigated the brain regions involved in these two cognitive processes and explored the common brain regions they share. To do this, we conducted two separate coordinate-based meta-analyses of functional magnetic resonance imaging studies assessing the brain regions involved in reality- and self-monitoring. Few brain regions survived threshold-free cluster enhancement family-wise multiple comparison correction (p < .05), likely owing to the small number of studies identified. Using uncorrected statistical thresholds recommended by Signed Differential Mapping with Permutation of Subject Images, the meta-analysis of reality-monitoring studies (k = 9 studies including 172 healthy subjects) revealed clusters in the lobule VI of the cerebellum, the right anterior medial prefrontal cortex and anterior thalamic projections. The meta-analysis of self-monitoring studies (k = 12 studies including 192 healthy subjects) highlighted the involvement of a set of brain regions including the lobule VI of the left cerebellum and fronto-temporo-parietal regions. We showed with a conjunction analysis that the lobule VI of the cerebellum was consistently engaged in both reality- and self-monitoring. The current findings offer new insights into the common brain regions underlying reality-monitoring and self-monitoring, and suggest that the neural signature of the self that may occur during self-production should persist in memories.
The top 3 ICs were removed before back-projection and dynamic functional connectivity estimation (ICs with kurtosis <3 were removed; images with low spatial kurtosis yield noise components by identifying uniformly distributed or global connectivity).
Tourette syndrome (TS) is a neuropsychiatric disorder characterized by motor and phonic tics, which several different theories, such as basal ganglia-thalamo-cortical loop dysfunction and amygdala hypersensitivity, have sought to explain. Previous research has shown dynamic changes in the brain prior to tic onset leading to tics, and this study aims to investigate the contribution of network dynamics to them. For this, we have employed three methods of functional connectivity to resting-state fMRI data - namely the static, the sliding window dynamic and the ICA based estimated dynamic; followed by an examination of the static and dynamic network topological properties. A leave-one-out (LOO-) validated regression model with LASSO regularization was used to identify the key predictors. The relevant predictors pointed to dysfunction of the primary motor cortex, the prefrontal-basal ganglia loop and amygdala-mediated visual social processing network. This is in line with a recently proposed social decision-making dysfunction hypothesis, opening new horizons in understanding tic pathophysiology.
Several studies employ multi-site rs-fMRI data for major depressive disorder (MDD) identification, with a specific site as the to-be-analyzed target domain and other site(s) as the source domain. But they usually suffer from significant inter-site heterogeneity caused by the use of different scanners and/or scanning protocols and fail to build generalizable models that can well adapt to multiple target domains. In this article, we propose a dual-expert fMRI harmonization (DFH) framework for automated MDD diagnosis. Our DFH is designed to simultaneously exploit data from a single labeled source domain/site and two unlabeled target domains for mitigating data distribution differences across domains. Specifically, the DFH consists of a domain-generic student model and two domain-specific teacher/expert models that are jointly trained to perform knowledge distillation through a deep collaborative learning module. A student model with strong generalizability is finally derived, which can be well adapted to unseen target domains and analysis of other brain diseases. To the best of our knowledge, this is among the first attempts to investigate multi-target fMRI harmonization for MDD diagnosis. Comprehensive experiments on 836 subjects with rs-fMRI data from 3 different sites show the superiority of our method. The discriminative brain functional connectivities identified by our method could be regarded as potential biomarkers for fMRI-related MDD diagnosis.
Subcallosal cingulate gyrus (SCG) is a target of deep brain stimulation (DBS) for treatment-resistant depression. However, previous randomized controlled trials report that approximately 42% of patients are responders to this therapy of last resort, and suboptimal targeting of SCG is a potential underlying factor to this unsatisfactory efficacy. Tractography has been proposed as a supplementary method to enhance targeting strategy. We performed a connectivity-based segmentation in the SCG region via probabilistic tractography in 100 healthy volunteers from the Human Connectome Project. The SCG voxels with maximum connectivity to brain regions implicated in depression, including Brodmann Area 10 (BA10), cingulate cortex, thalamus, and nucleus accumbens were identified, and the conjunctions were deemed as tractography-based targets. We then performed deterministic tractography using these targets in additional 100 volunteers to calculate streamline counts compassing to relevant brain regions and fibers. We also evaluated the intra- and inter-subject variance using test-retest dataset. Two tractography-based targets were identified. Tractography-based target-1 had the highest streamline counts to right BA10 and bilateral cingulate cortex, while tractography-based target-2 had the highest streamline counts to bilateral nucleus accumbens and uncinate fasciculus. The mean linear distance from individual tractography-based target to anatomy-based target was 3.2 ± 1.8 mm and 2.5 ± 1.4 mm in left and right hemispheres. The mean ± SD of targets between intra- and inter-subjects were 2.2 ± 1.2 and 2.9 ± 1.4 in left hemisphere, and 2.3 ± 1.4 and 3.1 ± 1.7 in right hemisphere, respectively. Individual heterogeneity as well as inherent variability from diffusion imaging should be taken into account during SCG-DBS target planning procedure.
Mounting evidences have shown that progression of white matter hyperintensities (WMHs) with vascular origin might cause cognitive dysfunction symptoms through their effects on brain networks. However, the vulnerability of specific neural connection related to WMHs in Alzheimer's disease (AD) still remains unclear. In this study, we established an atlas-guided computational framework based on brain disconnectome to assess the spatial-temporal patterns of WMH-related structural disconnectivity within a longitudinal investigation. Alzheimer's Disease Neuroimaging Initiative (ADNI) database was adopted with 91, 90 and 44 subjects including in cognitive normal aging, stable and progressive mild cognitive impairment (MCI), respectively. The parcel-wise disconnectome was computed by indirect mapping of individual WMHs onto population-averaged tractography atlas. By performing chi-square test, we discovered a spatial-temporal pattern of brain disconnectome along AD evolution. When applied such pattern as predictor, our models achieved highest mean accuracy of 0.82, mean sensitivity of 0.86, mean specificity of 0.82 and mean area under the receiver operating characteristic curve (AUC) of 0.91 for predicting conversion from MCI to dementia, which outperformed methods utilizing lesion volume as predictors. Our analysis suggests that brain WMH-related structural disconnectome contributes to AD evolution mainly through attacking connections between: (1) parahippocampal gyrus and superior frontal gyrus, orbital gyrus, and lateral occipital cortex; and (2) hippocampus and cingulate gyrus, which are also vulnerable to Aβ and tau confirmed by other researches. All the results further indicate that a synergistic relationship exists between multiple contributors of AD as they attack similar brain connectivity at the prodromal stage of disease.
Adolescence is marked by increased peer influence on risk taking; however, recent literature suggests enormous individual variation in peer influence susceptibility to risk-taking behaviors. The current study uses representation similarity analysis to test whether neural similarity between decision-making for self and peers (i.e., best friends) in a risky context is associated with individual differences in self-reported peer influence susceptibility and risky behaviors in adolescents. Adolescent participants (N = 166, Mage = 12.89) completed a neuroimaging task in which they made risky decisions to receive rewards for themselves, their best friend, and their parents. Adolescent participants self-reported peer influence susceptibility and engagement in risk-taking behaviors. We found that adolescents with greater similarity in nucleus accumbens (NACC) response patterns between the self and their best friend reported greater susceptibility to peer influence and increased risk-taking behaviors. However, neural similarity in ventromedial prefrontal cortex (vmPFC) was not significantly associated with adolescents' peer influence susceptibility and risk-taking behaviors. Further, when examining neural similarity between adolescents' self and their parent in the NACC and vmPFC, we did not find links to peer influence susceptibility and risk-taking behaviors. Together, our results suggest that greater similarity for self and friend in the NACC is associated with individual differences in adolescents' peer influence susceptibility and risk-taking behaviors.
Humans are goal-directed; however, goal-unrelated information still affects us, but how? The Stroop task is often used to answer this question, relying on conflict (incongruency) between attributes, one targeted by the task and another irrelevant to the task. The frontal regions of the brain are known to play a crucial role in processing such conflict, as they show increased activity when we encounter incongruent stimuli. Notably, the Stroop stimuli also consist of conceptual dimensions, such as semantic or emotional content, that are independent of the attributes that define the conflict. Since the non-targeted attribute usually refers to the same conceptual dimension as the targeted-attribute, it is relevant to the task at hand. For example, when naming the emotion of an emotional face superimposed by an emotional word, both the targeted-attribute and the non-targeted attribute refer to the conceptual dimension "emotion". We designed an fMRI paradigm to investigate how conflicts between different conceptual dimensions impact us. Even though the conflict was task-irrelevant, incongruent stimuli resulted in longer reaction times, indicating a behavioral congruency effect. When examining the neural mechanisms that underlie this effect, we found that the frontal regions exhibited repetition suppression, while the bilateral intraparietal sulcus (IPS) showed a congruency effect linked to the behavioral effect. Taken together, these findings suggest that individuals are unable to completely ignore task-irrelevant information, and that the IPS plays a crucial role in processing such information.
In this study, hyperpolarized 13 C MRI (HP-13 C MRI) was used to investigate changes in the uptake and metabolism of pyruvate with age. Hyperpolarized 13 C-pyruvate was administered to healthy aging individuals (N = 35, ages 21-77) and whole-brain spatial distributions of 13 C-lactate and 13 C-bicarbonate production were measured. Linear mixed-effects regressions were performed to compute the regional percentage change per decade, showing a significant reduction in both normalized 13 C-lactate and normalized 13 C-bicarbonate production with age: - 7 % ± 2 % $$ -7\%\pm 2\% $$ per decade for 13 C-lactate and - 9 % ± 4 % $$ -9\%\pm 4\% $$ per decade for 13 C-bicarbonate. Certain regions, such as the right medial precentral gyrus, showed greater rates of change while the left caudate nucleus had a flat 13 C-lactate versus age and a slightly increasing 13 C-bicarbonate versus age. The results show that both the production of lactate (visible as 13 C-lactate signal) as well as the consumption of monocarboxylates to make acetyl-CoA (visible as 13 C-bicarbonate signal) decrease with age and that the rate of change varies by brain region.
The perception and imagery of landmarks activate similar content-dependent brain areas, including occipital and temporo-medial brain regions. However, how these areas interact during visual perception and imagery of scenes, especially when recollecting their spatial location, remains unknown. Here, we combined functional magnetic resonance imaging (fMRI), resting-state functional connectivity (rs-fc), and effective connectivity to assess spontaneous fluctuations and task-induced modulation of signals among regions entailing scene-processing, the primary visual area and the hippocampus (HC), responsible for the retrieval of stored information. First, we functionally defined the scene-selective regions, that is, the occipital place area (OPA), the retrosplenial complex (RSC) and the parahippocampal place area (PPA), by using the face/scene localizer, observing that two portions of the PPA-anterior and posterior PPA-were consistently activated in all subjects. Second, the rs-fc analysis (n = 77) revealed a connectivity pathway similar to the one described in macaques, showing separate connectivity routes linking the anterior PPA with RSC and HC, and the posterior PPA with OPA. Third, we used dynamic causal modelling to evaluate whether the dynamic couplings among these regions differ between perception and imagery of familiar landmarks during a fMRI task (n = 16). We found a positive effect of HC on RSC during the retrieval of imagined places and an effect of occipital regions on both RSC and pPPA during the perception of scenes. Overall, we propose that under similar functional architecture at rest, different neural interactions take place between regions in the occipito-temporal higher-level visual cortex and the HC, subserving scene perception and imagery.
Understanding individual variability in response to physical activity is key to developing more effective and personalised interventions for healthy ageing. Here, we aimed to unpack individual differences by using longitudinal data from a randomised-controlled trial of a 12-month muscle strengthening intervention in older adults. Physical function of the lower extremities was collected from 247 participants (66.3 ± 2.5 years) at four time-points. At baseline and at year 4, participants underwent 3 T MRI brain scans. K-means longitudinal clustering was used to identify patterns of change in chair stand performance over 4 years, and voxel-based morphometry was applied to map structural grey matter volume at baseline and year 4. Results identified three groups showing trajectories of poor (33.6%), mid (40.1%), and high (26.3%) performance. Baseline physical function, sex, and depressive symptoms significantly differed between trajectory groups. High performers showed greater grey matter volume in the motor cerebellum compared to the poor performers. After accounting for baseline chair stand performance, participants were re-assigned to one of four trajectory-based groups: moderate improvers (38.9%), maintainers (38.5%), improvers (13%), and decliners (9.7%). Clusters of significant grey matter differences were observed between improvers and decliners in the right supplementary motor area. Trajectory-based group assignments were unrelated to the intervention arms of the study. In conclusion, patterns of change in chair stand performance were associated with greater grey matter volumes in cerebellar and cortical motor regions. Our findings emphasise that how you start matters, as baseline chair stand performance was associated with cerebellar volume 4 years later.
Moving from association to causal analysis of neuroimaging data is crucial to advance our understanding of brain function. The arrow-of-time (AoT), that is, the known asymmetric nature of the passage of time, is the bedrock of causal structures shaping physical phenomena. However, almost all current time series metrics do not exploit this asymmetry, probably due to the difficulty to account for it in modeling frameworks. Here, we introduce an AoT-sensitive metric that captures the intensity of causal effects in multivariate time series, and apply it to high-resolution functional neuroimaging data. We find that causal effects underlying brain function are more distinctively localized in space and time than functional activity or connectivity, thereby allowing us to trace neural pathways recruited in different conditions. Overall, we provide a mapping of the causal brain that challenges the association paradigm of brain function.
In fetal alcohol spectrum disorders (FASD), brain growth deficiency is a hallmark of subjects both with fetal alcohol syndrome (FAS) and with non-syndromic FASD (NS-FASD, i.e., those without specific diagnostic features). However, although the cerebellum was suggested to be more severely undersized than the rest of the brain, it has not yet been given a specific place in the FASD diagnostic criteria where neuroanatomical features still count for little if anything in diagnostic specificity. We applied a combination of cerebellar segmentation tools on a 1.5 T 3DT1 brain MRI dataset from a monocentric population of 89 FASD (52 FAS, 37 NS-FASD) and 126 typically developing controls (6-20 years old), providing 8 volumes: cerebellum, vermis and 3 lobes (anterior, posterior, inferior), plus total brain volume. After adjustment of confounders, the allometric scaling relationship between these cerebellar volumes (Vi ) and the total brain or cerebellum volume (Vt ) was fitted (Vi = bVt a ), and the effect of group (FAS, control) on allometric scaling was evaluated. We then estimated for each cerebellar volume in the FAS population the deviation from the typical scaling (v DTS) learned in the controls. Lastly, we trained and tested two classifiers to discriminate FAS from controls, one based on the total cerebellum v DTS only, the other based on all the cerebellar v DTS, comparing their performance both in the FAS and the NS-FASD group. Allometric scaling was significantly different between FAS and control group for all the cerebellar volumes (p < .001). We confirmed the excess of total cerebellum volume deficit (v DTS = -10.6%) and revealed an antero-inferior-posterior gradient of volumetric undersizing in the hemispheres (-12.4%, 1.1%, 2.0%, repectively) and the vermis (-16.7%, -9.2%, -8.6%, repectively). The classifier based on the intracerebellar gradient of v DTS performed more efficiently than the one based on total cerebellum v DTS only (AUC = 92% vs. 82%, p = .001). Setting a high probability threshold for >95% specificity of the classifiers, the gradient-based classifier identified 35% of the NS-FASD to have a FAS cerebellar phenotype, compared to 11% with the cerebellum-only classifier (pFISHER = 0.027). In a large series of FASD, this study details the volumetric undersizing within the cerebellum at the lobar and vermian level using allometric scaling, revealing an anterior-inferior-posterior gradient of vulnerability to prenatal alcohol exposure. It also strongly suggests that this intracerebellar gradient of volumetric undersizing may be a reliable neuroanatomical signature of FAS that could be used to improve the specificity of the diagnosis of NS-FASD.
The human adult hippocampus can be subdivided into the head, or anterior hippocampus and its body and tail, or posterior hippocampus, and a wealth of functional differences along the longitudinal axis have been reported. One line of literature emphasizes specialization for different aspects of cognition, whereas another emphasizes the unique role of the anterior hippocampus in emotional processing. While some research suggests that functional differences in memory between the anterior and posterior hippocampus appear early in development, it remains unclear whether this is also the case for functional differences in emotion processing. The goal of this meta-analysis was to determine whether the long-axis functional specialization observed in adults is present earlier in development. Using a quantitative meta-analysis, long-axis functional specialization was assessed using the data from 26 functional magnetic resonance imaging studies, which included 39 contrasts and 804 participants ranging in age from 4 to 21 years. Results indicated that emotion was more strongly localized to the anterior hippocampus, with memory being more strongly localized to the posterior hippocampus, demonstrating long-axis specialization with regard to memory and emotion in children similar to that seen in adults. An additional analysis of laterality indicated that while memory was left dominant, emotion was processed bilaterally.
Longitudinal changes in the white matter/functional brain networks of semantic dementia (SD), as well as their relations with cognition remain unclear. Using a graph-theoretic method, we examined the neuroimaging (T1, diffusion tensor imaging, functional MRI) network properties and cognitive performance in processing semantic knowledge of general and six modalities (i.e., object form, color, motion, sound, manipulation and function) from 31 patients (at two time points with an interval of 2 years) and 20 controls (only at baseline). Partial correlation analyses were carried out to explore the relationships between the network changes and the declines of semantic performance. SD exhibited aberrant general and modality-specific semantic impairment, and gradually worsened over time. Overall, the brain networks showed a decreased global and local efficiency in the functional network organization but a preserved structural network organization with a 2-year follow-up. With disease progression, both structural and functional alterations were found to be extended to the temporal and frontal lobes. The regional topological alteration in the left inferior temporal gyrus (ITG.L) was significantly correlated with general semantic processing. Meanwhile, the right superior temporal gyrus and right supplementary motor area were identified to be associated with color and motor-related semantic attributes. SD manifested disrupted structural and functional network pattern longitudinally. We proposed a hub region (i.e., ITG.L) of semantic network and distributed modality-specific semantic-related regions. These findings support the hub-and-spoke semantic theory and provide targets for future therapy.
Visual inhibition of return (IOR) is a mechanism for preventing attention from returning to previously examined spatial locations. Previous studies have found that auditory stimuli presented simultaneously with a visual target can reduce or even eliminate the visual IOR. However, the mechanism responsible for decreased visual IOR accompanied by auditory stimuli is unclear. Using functional magnetic resonance imaging, we aimed to investigate how auditory stimuli reduce visual IOR. Behaviorally, we found that the visual IOR accompanying auditory stimuli was significant but smaller than the visual IOR. Neurally, only in the validly cued trials, the superior temporal gyrus showed increased neural coupling with the intraparietal sulcus, presupplementary motor area, and some other areas in audiovisual conditions compared with visual conditions. These results suggest that the reduction in visual IOR by the simultaneous auditory stimuli may be due to a dual mechanism: rescuing the suppressed visual salience and facilitating response initiation. Our results support crossmodal interactions can occur across multiple neural levels and cognitive processing stages. This study provides a new perspective for understanding attention-orienting networks and response initiation based on crossmodal information.
Unveiling the details of white matter (WM) maturation throughout ageing is a fundamental question for understanding the ageing brain. In an extensive comparison of brain age predictions and age-associations of WM features from different diffusion approaches, we analyzed UK Biobank diffusion magnetic resonance imaging (dMRI) data across midlife and older age (N = 35,749, 44.6-82.8 years of age). Conventional and advanced dMRI approaches were consistent in predicting brain age. WM-age associations indicate a steady microstructure degeneration with increasing age from midlife to older ages. Brain age was estimated best when combining diffusion approaches, showing different aspects of WM contributing to brain age. Fornix was found as the central region for brain age predictions across diffusion approaches in complement to forceps minor as another important region. These regions exhibited a general pattern of positive associations with age for intra axonal water fractions, axial, radial diffusivities, and negative relationships with age for mean diffusivities, fractional anisotropy, kurtosis. We encourage the application of multiple dMRI approaches for detailed insights into WM, and the further investigation of fornix and forceps as potential biomarkers of brain age and ageing.
Late-stage macular degeneration (MD) often causes retinal lesions depriving an individual of central vision, forcing them to learn to use peripheral vision for daily tasks. To compensate, many patients develop a preferred retinal locus (PRL), an area of peripheral vision used more often than equivalent regions of spared vision. Thus, associated portions of cortex experience increased use, while portions of cortex associated with the lesion are deprived of sensory input. Prior research has not well examined the degree to which structural plasticity depends on the amount of use across the visual field. Cortical thickness, neurite density, and orientation dispersion were measured at portions of cortex associated with the PRL, the retinal lesion, and a control region in participants with MD as well as age-matched, gender-matched, and education-matched controls. MD participants had significantly thinner cortex in both the cortical representation of the PRL (cPRL) and the control region, compared with controls, but no significant differences in thickness, neurite density, or orientation dispersion were found between the cPRL and the control region as functions of disease or onset. This decrease in thickness is driven by a subset of early-onset participants whose patterns of thickness, neurite density, and neurite orientation dispersion are distinct from matched control participants. These results suggest that people who develop MD earlier in adulthood may undergo more structural plasticity than those who develop it late in life.
A fundamental characteristic of the human brain that supports behavior is its capacity to create connections between brain regions. A promising approach holds that during social behavior, brain regions not only create connections with other brain regions within a brain, but also coordinate their activity with other brain regions of an interaction partner. Here we ask whether between-brain and within-brain coupling contribute differentially to movement synchronization. We focused on coupling between the inferior frontal gyrus (IFG), a brain region associated with the observation-execution system, and the dorsomedial prefrontal cortex (dmPFC), a region associated with error-monitoring and prediction. Participants, randomly divided into dyads, were simultaneously scanned with functional near infra-red spectroscopy (fNIRS) while performing an open-ended 3D hand movement task consisting of three conditions: back-to-back movement, free movement, or intentional synchronization. Results show that behavioral synchrony was higher in the intentional synchrony compared with the back-to-back and free movement conditions. Between-brain coupling in the IFG and dmPFC was evident in the free movement and intentional synchrony conditions but not in the back-to-back condition. Importantly, between-brain coupling was found to positively predict intentional synchrony, while within-brain coupling was found to predict synchronization during free movement. These results indicate that during intentional synchronization, brain organization changes such that between-brain networks, but not within-brain connections, contribute to successful communication, pointing to shift from a within-brain feedback loop to a two-brains feedback loop.
Humans possess an intuitive understanding of the environment's physical properties and dynamics, which allows them to predict the outcomes of physical scenarios and successfully interact with the physical world. This predictive ability is thought to rely on mental simulations and has been shown to involve frontoparietal areas. Here, we investigate whether such mental simulations may be accompanied by visual imagery of the predicted physical scene. We designed an intuitive physical inference task requiring participants to infer the parabolic trajectory of an occluded ball falling in accordance with Newtonian physics. Participants underwent fMRI while (i) performing the physical inference task alternately with a visually matched control task, and (ii) passively observing falling balls depicting the trajectories that had to be inferred during the physical inference task. We found that performing the physical inference task activates early visual areas together with a frontoparietal network when compared with the control task. Using multivariate pattern analysis, we show that these regions contain information specific to the trajectory of the occluded ball (i.e., fall direction), despite the absence of visual inputs. Using a cross-classification approach, we further show that in early visual areas, trajectory-specific activity patterns evoked by the physical inference task resemble those evoked by the passive observation of falling balls. Together, our findings suggest that participants simulated the ball trajectory when solving the task, and that the outcome of these simulations may be represented in form of the perceivable sensory consequences in early visual areas.
Understanding the evolutionarily conserved feature of functional laterality in the habenula has been attracting attention due to its potential role in human cognition and neuropsychiatric disorders. Deciphering the structure of the human habenula remains to be challenging, which resulted in inconsistent findings for brain disorders. Here, we present a large-scale meta-analysis of the left-right differences in the habenular volume in the human brain to provide a clearer picture of the habenular asymmetry. We searched PubMed, Web of Science, and Google Scholar for articles that reported volume data of the bilateral habenula in the human brain, and assessed the left-right differences. We also assessed the potential effects of several moderating variables including the mean age of the participants, magnetic field strengths of the scanners and different disorders by using meta-regression and subgroup analysis. In total 52 datasets (N = 1427) were identified and showed significant heterogeneity in the left-right differences and the unilateral volume per se. Moderator analyses suggested that such heterogeneity was mainly due to different MRI scanners and segmentation approaches used. While inversed asymmetry patterns were suggested in patients with depression (leftward) and schizophrenia (rightward), no significant disorder-related differences relative to healthy controls were found in either the left-right asymmetry or the unilateral volume. This study provides useful data for future studies of brain imaging and methodological developments related to precision habenula measurements, and also helps to further understand potential roles of the habenula in various disorders.
Previous studies have debated whether the ability for bilinguals to mentally control their languages is a consequence of their experiences switching between languages or whether it is a specific, yet highly-adaptive, cognitive ability. The current study investigates how variations in the language-related gene FOXP2 and executive function-related genes COMT, BDNF, and Kibra/WWC1 affect bilingual language control during two phases of speech production, namely the language schema phase (i.e., the selection of one language or another) and lexical response phase (i.e., utterance of the target). Chinese-English bilinguals (N = 119) participated in a picture-naming task involving cued language switches. Statistical analyses showed that both genes significantly influenced language control on neural coding and behavioral performance. Specifically, FOXP2 rs1456031 showed a wide-ranging effect on language control, including RTs, F(2, 113) = 4.00, FDR p = .036, and neural coding across three-time phases (N2a: F(2, 113) = 4.96, FDR p = .014; N2b: F(2, 113) = 4.30, FDR p = .028, LPC: F(2, 113) = 2.82, FDR p = .060), while the COMT rs4818 (ts >2.69, FDR ps < .05), BDNF rs6265 (Fs >5.31, FDR ps < .05), and Kibra/WWC1 rs17070145 (ts > -3.29, FDR ps < .05) polymorphisms influenced two-time phases (N2a and N2b). Time-resolved correlation analyses revealed that the relationship between neural coding and cognitive performance is modulated by genetic variations in all four genes. In all, these findings suggest that bilingual language control is shaped by an individual's experience switching between languages and their inherent genome.
We investigated the cortical representation of emotional prosody in normal-hearing listeners using functional near-infrared spectroscopy (fNIRS) and behavioural assessments. Consistent with previous reports, listeners relied most heavily on F0 cues when recognizing emotion cues; performance was relatively poor-and highly variable between listeners-when only intensity and speech-rate cues were available. Using fNIRS to image cortical activity to speech utterances containing natural and reduced prosodic cues, we found right superior temporal gyrus (STG) to be most sensitive to emotional prosody, but no emotion-specific cortical activations, suggesting that while fNIRS might be suited to investigating cortical mechanisms supporting speech processing it is less suited to investigating cortical haemodynamic responses to individual vocal emotions. Manipulating emotional speech to render F0 cues less informative, we found the amplitude of the haemodynamic response in right STG to be significantly correlated with listeners' abilities to recognise vocal emotions with uninformative F0 cues. Specifically, listeners more able to assign emotions to speech with degraded F0 cues showed lower haemodynamic responses to these degraded signals. This suggests a potential objective measure of behavioural sensitivity to vocal emotions that might benefit neurodiverse populations less sensitive to emotional prosody or hearing-impaired listeners, many of whom rely on listening technologies such as hearing aids and cochlear implants-neither of which restore, and often further degrade, the F0 cues essential to parsing emotional prosody conveyed in speech.
There has been growing attention on the effect of COVID-19 on white-matter microstructure, especially among those that self-isolated after being infected. There is also immense scientific interest and potential clinical utility to evaluate the sensitivity of single-shell diffusion magnetic resonance imaging (MRI) methods for detecting such effects. In this work, the performances of three single-shell-compatible diffusion MRI modeling methods are compared for detecting the effect of COVID-19, including diffusion-tensor imaging, diffusion-tensor decomposition of orthogonal moments and correlated diffusion imaging. Imaging was performed on self-isolated patients at the study initiation and 3-month follow-up, along with age- and sex-matched controls. We demonstrate through simulations and experimental data that correlated diffusion imaging is associated with far greater sensitivity, being the only one of the three single-shell methods to demonstrate COVID-19-related brain effects. Results suggest less restricted diffusion in the frontal lobe in COVID-19 patients, but also more restricted diffusion in the cerebellar white matter, in agreement with several existing studies highlighting the vulnerability of the cerebellum to COVID-19 infection. These results, taken together with the simulation results, suggest that a significant proportion of COVID-19 related white-matter microstructural pathology manifests as a change in tissue diffusivity. Interestingly, different b-values also confer different sensitivities to the effects. No significant difference was observed in patients at the 3-month follow-up, likely due to the limited size of the follow-up cohort. To summarize, correlated diffusion imaging is shown to be a viable single-shell diffusion analysis approach that allows us to uncover opposing patterns of diffusion changes in the frontal and cerebellar regions of COVID-19 patients, suggesting the two regions react differently to viral infection.
Altered postural control in the trunk/hip musculature is a characteristic of multiple neurological and musculoskeletal conditions. Previously it was not possible to determine if altered cortical and subcortical sensorimotor brain activation underlies impairments in postural control. This study used a novel fMRI-compatible paradigm to identify the brain activation associated with postural control in the trunk and hip musculature. BOLD fMRI imaging was conducted as participants performed two versions of a lower limb task involving lifting the left leg to touch the foot to a target. For the supported leg raise (SLR) the leg is raised from the knee while the thigh remains supported. For the unsupported leg raise (ULR) the leg is raised from the hip, requiring postural muscle activation in the abdominal/hip extensor musculature. Significant brain activation during the SLR task occurred predominantly in the right primary and secondary sensorimotor cortical regions. Brain activation during the ULR task occurred bilaterally in the primary and secondary sensorimotor cortical regions, as well as cerebellum and putamen. In comparison with the SLR, the ULR was associated with significantly greater activation in the right premotor/SMA, left primary motor and cingulate cortices, primary somatosensory cortex, supramarginal gyrus/parietal operculum, superior parietal lobule, cerebellar vermis, and cerebellar hemispheres. Cortical and subcortical regions activated during the ULR, but not during the SLR, were consistent with the planning, and execution of a task involving multisegmental, bilateral postural control. Future studies using this paradigm will determine mechanisms underlying impaired postural control in patients with neurological and musculoskeletal dysfunction.
White matter hyperintensity (WMH) lesions on T2 fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) and changes in adjacent normal-appearing white matter can disrupt computerized tract reconstruction and result in inaccurate measures of structural brain connectivity. The virtual lesion approach provides an alternative strategy for estimating structural connectivity changes due to WMH. To assess the impact of using young versus older subject diffusion MRI data for virtual lesion tractography, we leveraged recently available diffusion MRI data from the Human Connectome Project (HCP) Lifespan database. Neuroimaging data from 50 healthy young (39.2 ± 1.6 years) and 46 healthy older (74.2 ± 2.5 years) subjects were obtained from the publicly available HCP-Aging database. Three WMH masks with low, moderate, and high lesion burdens were extracted from the WMH lesion frequency map of locally acquired FLAIR MRI data. Deterministic tractography was conducted to extract streamlines in 21 WM bundles with and without the WMH masks as regions of avoidance in both young and older cohorts. For intact tractography without virtual lesion masks, 7 out of 21 WM pathways showed a significantly lower number of streamlines in older subjects compared to young subjects. A decrease in streamline count with higher native lesion burden was found in corpus callosum, corticostriatal tract, and fornix pathways. Comparable percentages of affected streamlines were obtained in young and older groups with virtual lesion tractography using the three WMH lesion masks of increasing severity. We conclude that using normative diffusion MRI data from young subjects for virtual lesion tractography of WMH is, in most cases, preferable to using age-matched normative data.
The hippocampus is known to be critically involved in associative memory formation. However, the role of the hippocampus during the learning of associative memory is still controversial; while the hippocampus is considered to play a critical role in the integration of related stimuli, numerous studies also suggest a role of the hippocampus in the separation of different memory traces for rapid learning. Here, we employed an associative learning paradigm consisting of repeated learning cycles. By tracking the changes in the hippocampal representations of associated stimuli on a cycle-by-cycle basis as learning progressed, we show that both integration and separation processes occur in the hippocampus with different temporal dynamics. We found that the degree of shared representations for associated stimuli decreased significantly during the early phase of learning, whereas it increased during the later phase of learning. Remarkably, these dynamic temporal changes were observed only for stimulus pairs remembered 1 day or 4 weeks after learning, but not for forgotten pairs. Further, the integration process during learning was prominent in the anterior hippocampus, while the separation process was obvious in the posterior hippocampus. These results demonstrate temporally and spatially dynamic hippocampal processing during learning that can lead to the maintenance of associative memory.
Acute exercise suppresses appetite and alters food-cue reactivity, but the extent exercise-induced changes in cerebral blood flow (CBF) influences the blood-oxygen-level-dependent (BOLD) signal during appetite-related paradigms is not known. This study examined the impact of acute running on visual food-cue reactivity and explored whether such responses are influenced by CBF variability. In a randomised crossover design, 23 men (mean ± SD: 24 ± 4 years, 22.9 ± 2.1 kg/m2 ) completed fMRI scans before and after 60 min of running (68% ± 3% peak oxygen uptake) or rest (control). Five-minute pseudo-continuous arterial spin labelling fMRI scans were conducted for CBF assessment before and at four consecutive repeat acquisitions after exercise/rest. BOLD-fMRI was acquired during a food-cue reactivity task before and 28 min after exercise/rest. Food-cue reactivity analysis was performed with and without CBF adjustment. Subjective appetite ratings were assessed before, during and after exercise/rest. Exercise CBF was higher in grey matter, the posterior insula and in the region of the amygdala/hippocampus, and lower in the medial orbitofrontal cortex and dorsal striatum than control (main effect trial p ≤ .018). No time-by-trial interactions for CBF were identified (p ≥ .087). Exercise induced moderate-to-large reductions in subjective appetite ratings (Cohen's d = 0.53-0.84; p ≤ .024) and increased food-cue reactivity in the paracingulate gyrus, hippocampus, precuneous cortex, frontal pole and posterior cingulate gyrus. Accounting for CBF variability did not markedly alter detection of exercise-induced BOLD signal changes. Acute running evoked overall changes in CBF that were not time dependent and increased food-cue reactivity in regions implicated in attention, anticipation of reward, and episodic memory independent of CBF.
It has been suggested that the inferior longitudinal fasciculus (ILF) may play an important role in several aspects of language processing such as visual object recognition, visual memory, lexical retrieval, reading, and specifically, in naming visual stimuli. In particular, the ILF appears to convey visual information from the occipital lobe to the anterior temporal lobe (ATL). However, direct evidence proving the essential role of the ILF in language and semantics remains limited and controversial. The first aim of this study was to prove that patients with a brain glioma damaging the left ILF would be selectively impaired in picture naming of objects; the second aim was to prove that patients with glioma infiltrating the ATL would not be impaired due to functional reorganization of the lexical retrieval network elicited by the tumor. We evaluated 48 right-handed patients with neuropsychological testing and magnetic resonance imaging (MRI) before and after surgery for resection of a glioma infiltrating aspects of the left temporal, occipital, and/or parietal lobes; diffusion tensor imaging (DTI) was acquired preoperatively in all patients. Damage to the ILF, inferior frontal occipital fasciculus (IFOF), uncinate fasciculus (UF), arcuate fasciculus (AF), and associated cortical regions was assessed by means of preoperative tractography and pre-/pos-toperative MRI volumetry. The association of fascicles damage with patients' performance in picture naming and three additional cognitive tasks, namely, verbal fluency (two verbal non-visual tasks) and the Trail Making Test (a visual attentional task), was evaluated. Nine patients were impaired in the naming test before surgery. ILF damage was demonstrated with tractography in six (67%) of these patients. The odds of having an ILF damage was 6.35 (95% CI: 1.27-34.92) times higher among patients with naming deficit than among those without it. The ILF was the only fascicle to be significantly associated with naming deficit when all the fascicles were considered together, achieving an adjusted odds ratio of 15.73 (95% CI: 2.30-178.16, p = .010). Tumor infiltration of temporal and occipital cortices did not contribute to increase the odd of having a naming deficit. ILF damage was found to be selectively associated with picture naming deficit and not with lexical retrieval assessed by means of verbal fluency. Early after surgery, 29 patients were impaired in naming objects. The association of naming deficit with percentage of ILF resection (assessed by 3D-MRI) was confirmed (beta = -56.78 ± 20.34, p = .008) through a robust multiple linear regression model; no significant association was found with damage of IFOF, UF or AF. Crucially, postoperative neuropsychological evaluation showed that naming scores of patients with tumor infiltration of the anterior temporal cortex were not significantly associated with the percentage of ILF damage (rho = .180, p > .999), while such association was significant in patients without ATL infiltration (rho = -.556, p = .004). The ILF is selectively involved in picture naming of objects; however, the naming deficits are less severe in patients with glioma infiltration of the ATL probably due to release of an alternative route that may involve the posterior segment of the AF. The left ILF, connecting the extrastriatal visual cortex to the anterior region of the temporal lobe, is crucial for lexical retrieval on visual stimulus, such as in picture naming. However, when the ATL is also damaged, an alternative route is released and the performance improves.
Scientists traditionally use passive stimulation to examine the organisation of primary somatosensory cortex (SI). However, given the close, bidirectional relationship between the somatosensory and motor systems, active paradigms involving free movement may uncover alternative SI representational motifs. Here, we used 7 Tesla functional magnetic resonance imaging to compare hallmark features of SI digit representation between active and passive tasks which were unmatched on task or stimulus properties. The spatial location of digit maps, somatotopic organisation, and inter-digit representational structure were largely consistent between tasks, indicating representational consistency. We also observed some task differences. The active task produced higher univariate activity and multivariate representational information content (inter-digit distances). The passive task showed a trend towards greater selectivity for digits versus their neighbours. Our findings highlight that, while the gross features of SI functional organisation are task invariant, it is important to also consider motor contributions to digit representation.
a shows the result of the tractogram from an axial slice for a representative participant in diffusion space. The colour indicates directionality; red for right-left, green for anterior-posterior and blue for superior-inferior. b shows an example of the extracted streamlines connecting two ROIs in the inferior frontal cortex. We extracted streamlines between all of the ROIs pairs to compute connectivity strength. c shows the 230 ROIs covering the left hemisphere only.
The average language connectivity matrix across individuals after thresholding and binarization based on Euclidean distance. The different levels of alpha with 10% on the top, 20% on the middle, and 30% on the bottom were superimposed onto one matrix wherein anything that survives the 10% would also survive 20% and 30%.
The projections of the average language connectivity matrix generated by using Euclidean distance in the brain with three alpha levels of 10% (red), 20% (green) and 30% (blue) and the difference plots between them (gold). The wider the connection line indicates the stronger the connections.
Tractography is widely used in human studies of connectivity with respect to every brain region, function, and is explored developmentally, in adulthood, ageing, and in disease. However, the core issue of how to systematically threshold, taking into account the inherent differences in connectivity values for different track lengths, and to do this in a comparable way across studies has not been solved. By utilising 54 healthy individuals' diffusion-weighted image data taken from HCP, this study adopted Monte Carlo derived distance-dependent distributions (DDDs) to generate distance-dependent thresholds with various levels of alpha for connections of varying lengths. As a test case, we applied the DDD approach to generate a language connectome. The resulting connectome showed both short- and long-distance structural connectivity in the close and distant regions as expected for the dorsal and ventral language pathways, consistent with the literature. The finding demonstrates that the DDD approach is feasible to generate data-driven DDDs for common thresholding and can be used for both individual and group thresholding. Critically, it offers a standard method that can be applied to various probabilistic tracking datasets.
The cognitive and behavioral development of children and adolescents is closely related to the maturation of brain morphology. Although the trajectory of brain development has been depicted in detail, the underlying biological mechanism of normal cortical morphological development in childhood and adolescence remains unclear. By combining the Allen Human Brain Atlas dataset with two single-site magnetic resonance imaging data including 427 and 733 subjects from China and the United States, respectively, we performed partial least squares regression and enrichment analysis to explore the relationship between the gene transcriptional expression and the development of cortical thickness in childhood and adolescence. We found that the spatial model of normal cortical thinning during childhood and adolescence is associated with genes expressed predominantly in astrocytes, microglia, excitatory and inhibitory neurons. Top cortical development-related genes are enriched for energy-related and DNA-related terms and are associated with psychological and cognitive disorders. Interestingly, there is a great deal of similarity between the findings derived from the two single-site datasets. This fills the gap between early cortical development and transcriptomes, which promotes an integrative understanding of the potential biological neural mechanisms.
Turner syndrome (TS) is a common sex chromosome aneuploidy in females associated with various physical, cognitive, and socio-emotional phenotypes. However, few studies have examined TS-associated alterations in the development of cortical gray matter volume and the two components that comprise this measure-surface area and thickness. Moreover, the longitudinal direct (i.e., genetic) and indirect (i.e., hormonal) effects of X-monosomy on the brain are unclear. Brain structure was assessed in 61 girls with TS (11.3 ± 2.8 years) and 55 typically developing girls (10.8 ± 2.3 years) for up to 4 timepoints. Surface-based analyses of cortical gray matter volume, thickness, and surface area were conducted to examine the direct effects of X-monosomy present before pubertal onset and indirect hormonal effects of estrogen deficiency/X-monosomy emerging after pubertal onset. Longitudinal analyses revealed that, whereas typically developing girls exhibited normative declines in gray matter structure during adolescence, this pattern was reduced or inverted in TS. Further, girls with TS demonstrated smaller total surface area and larger average cortical thickness overall. Regionally, the TS group exhibited decreased volume and surface area in the pericalcarine, postcentral, and parietal regions relative to typically developing girls, as well as larger volume in the caudate, amygdala, and temporal lobe regions and increased thickness in parietal and temporal regions. Surface area alterations were predominant by age 8, while maturational differences in thickness emerged by age 10 or later. Taken together, these results suggest the involvement of both direct and indirect effects of X-chromosome haploinsufficiency on brain development in TS.
Learning and recognition can be improved by sorting novel items into categories and subcategories. Such hierarchical categorization is easy when it can be performed according to learned rules (e.g., "if car, then automatic or stick shift" or "if boat, then motor or sail"). Here, we present results showing that human participants acquire categorization rules for new visual hierarchies rapidly, and that, as they do, corresponding hierarchical representations of the categorized stimuli emerge in patterns of neural activation in the dorsal striatum and in posterior frontal and parietal cortex. Participants learned to categorize novel visual objects into a hierarchy with superordinate and subordinate levels based on the objects' shape features, without having been told the categorization rules for doing so. On each trial, participants were asked to report the category and subcategory of the object, after which they received feedback about the correctness of their categorization responses. Participants trained over the course of a one-hour-long session while their brain activation was measured using functional magnetic resonance imaging. Over the course of training, significant hierarchy learning took place as participants discovered the nested categorization rules, as evidenced by the occurrence of a learning trial, after which performance suddenly increased. This learning was associated with increased representational strength of the newly acquired hierarchical rules in a corticostriatal network including the posterior frontal and parietal cortex and the dorsal striatum. We also found evidence suggesting that reinforcement learning in the dorsal striatum contributed to hierarchical rule learning.
No significant difference was found in age, gender, and years of
Dopamine replacement therapy (DRT) represents the standard treatment for Parkinson's disease (PD), however, instant and long-term medication influence on patients' brain function have not been delineated. Here, a total of 97 drug-naïve patients, 43 patients under long-term DRT, and 94 normal control (NC) were, retrospectively, enrolled. Resting-state functional magnetic resonance imaging data and motor symptom assessments were conducted before and after levodopa challenge test. Whole-brain functional connectivity (FC) matrices were constructed. Network-based statistics were performed to assess FC difference between drug-naïve patients and NC, and these significant FCs were defined as disease-related connectomes, which were used for further statistical analyses. Patients showed better motor performances after both long-term DRT and levodopa challenge test. Two disease-related connectomes were observed with distinct patterns. The FC of the increased connectome, which mainly consisted of the motor, visual, subcortical, and cerebellum networks, was higher in drug-naïve patients than that in NC and was normalized after long-term DRT (p-value <.050). The decreased connectome was mainly composed of the motor, medial frontal, and salience networks and showed significantly lower FC in all patients than NC (p-value <.050). The global FC of both increased and decreased connectome was significantly enhanced after levodopa challenge test (q-value <0.050, false discovery rate-corrected). The global FC of increased connectome in ON-state was negatively associated with levodopa equivalency dose (r = -.496, q-value = 0.007). Higher global FC of the decreased connectome was related to better motor performances (r = -.310, q-value = 0.022). Our findings provided insights into brain functional alterations under dopaminergic medication and its benefit on motor symptoms.
This study investigated associations between psychological resilience and characteristics of white matter microstructure in pediatric concussion. This is a case control study and a planned substudy of a larger randomized controlled trial. Children with an acute concussion or orthopedic injury were recruited from the emergency department. Participants completed both the Connor-Davidson Resilience Scale 10 and an MRI at 72 h and 4-weeks post-injury. The association between resiliency and fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) at both timepoints were examined. We examined whether these associations were moderated by group. The association between resiliency captured at 72 h and diffusion tensor imaging metrics at 4 weeks was also investigated. Clusters were extracted using a significance threshold of threshold-free cluster enhancement corrected p < .05. A total of 66 children with concussion (median (IQR) age = 12.88 (IQR: 11.80-14.36); 47% female) and 29 children with orthopedic-injury (median (IQR) age = 12.49 (IQR: 11.18-14.01); 41% female) were included. A negative correlation was identified in the concussion group between 72 h resilience and 72 h FA. Meanwhile, positive correlations were identified in the concussion group with concussion between 72 h resilience and both 72 h MD and 72 h RD. These findings suggest that 72 h resilience is associated with white matter microstructure of the forceps minor, superior longitudinal fasciculus, and anterior thalamic radiation at 72 h post-concussion. Resilience seems to be associated with neural integrity only in the acute phase of concussion and thus may be considered when researching concussion recovery.
Following the development of magnetic resonance imaging (MRI) methods to assay the integrity of catecholamine nuclei, including the locus coeruleus (LC), there has been an effort to develop automated methods that can accurately segment this small structure in an automated manner to promote its widespread use and overcome limitations of manual segmentation. Here we characterize an automated LC segmentation approach (referred to as the funnel-tip [FT] method) in healthy individuals and individuals with LC degeneration in the context of Alzheimer's disease (AD, confirmed with tau-PET imaging using [18F]MK6240). The first sample included n = 190 individuals across the AD spectrum from cognitively normal to moderate AD. LC signal assayed with FT segmentation showed excellent agreement with manual segmentation (intraclass correlation coefficient [ICC] = 0.91). Compared to other methods, the FT method showed numerically higher correlation to AD status (defined by presence of tau: Cohen's d = 0.64) and AD severity (Braak stage: Pearson R = -.35, cognitive function: R = .25). In a separate sample of n = 12 control participants, the FT method showed excellent scan-rescan reliability (ICC = 0.82). In another sample of n = 30 control participants, we found that the structure of the LC defined by FT segmentation approximated its expected shape as a contiguous line: <5% of LC voxels strayed >1 voxel (0.69 mm) from this line. The FT LC segmentation shows high agreement with manual segmentation and captures LC degeneration in AD. This practical method may facilitate larger research studies of the human LC-norepinephrine system and has potential to support future use of neuromelanin-sensitive MRI as a clinical biomarker.
reports the 4 color-coded clusters on the Atlas template. The first cluster (green), named Fronto-Temporal, was mainly formed by associative regions of the prefrontal (orbito-frontal cortex, superior, middle, and inferior frontal gyrus) and temporal (temporal pole, middle temporal gyrus, fusiform gyrus) cortex. The second cluster (cyan), named Parieto-Occipital, included associative regions of the parietal lobe, the calcarine cortex and structures of the limbic system (amygdalae, hippocampi, parahippocampal gyri). The third cluster (purple), named Insular-DGM, consisted of the insulae, the deep GM (DGM) nuclei and the thalami, and the Heschl gyri (primary auditory
In preterm (PT) infants, regional cerebral blood flow (CBF) disturbances may predispose to abnormal brain maturation even without overt brain injury. Therefore, it would be informative to determine the spatial distribution of grey matter (GM) CBF in PT and full-term (FT) newborns at term-equivalent age (TEA) and to assess the relationship between the features of the CBF pattern and both prematurity and prematurity-related brain lesions. In this prospective study, we obtained measures of CBF in 66 PT (51 without and 15 with prematurity-related brain lesions) and 38 FT newborns through pseudo-continuous arterial spin labeling (pCASL) MRI acquired at TEA. The pattern of GM CBF was characterized by combining an atlas-based automated segmentation of structural MRI with spatial normalization and hierarchical clustering. The effects of gestational age (GA) at birth and brain injury on the CBF pattern were investigated. We identified 4 physiologically-derived clusters of brain regions that were labeled Fronto-Temporal, Parieto-Occipital, Insular-Deep GM (DGM) and Sensorimotor, from the least to the most perfused. We demonstrated that GM perfusion was associated with GA at birth in the Fronto-Temporal and Sensorimotor clusters, positively and negatively, respectively. Moreover, the presence of periventricular leukomalacia was associated with significantly increased Fronto-Temporal GM perfusion and decreased Insular-DGM perfusion, while the presence of germinal matrix hemorrhage appeared to mildly decrease the Insular-DGM perfusion. Prematurity and prematurity-related brain injury heterogeneously affect brain perfusion. ASL MRI may, therefore, have strong potential as a noninvasive tool for the accurate stratification of individuals at risk of domain-specific impairment.
Functional connectivity (FC) network characterizes the functional interactions between brain regions and is considered to root in the underlying structural connectivity (SC) network. If this is the case, individual variations in SC should cause corresponding individual variations in FC. However, divergences exist in the correspondence between direct SC and FC and researchers still cannot capture individual differences in FC via direct SC. As brain regions may interact through multi-hop indirect SC pathways, we conceived that one can capture the individual specific SC-FC relationship via incorporating indirect SC pathways appropriately. In this study, we designed graph propagation network (GPN) that models the information propagation between brain regions based on the SC network. Effects of interactions through multi-hop SC pathways naturally emerge from the multilayer information propagation in GPN. We predicted the individual differences in FC network based on SC network via multilayer GPN and results indicate that multilayer GPN incorporating effects of multi-hop indirect SCs greatly enhances the ability to predict individual FC network. Furthermore, the SC-FC relationship evaluated via the prediction accuracy is negatively correlated with the functional gradient, suggesting that the SC-FC relationship gradually uncouples along the functional hierarchy spanning from unimodal to transmodal cortex. We also revealed important intermediate brain regions along multi-hop SC pathways involving in the individual SC-FC relationship. These results suggest that multilayer GPN can serve as a method to establish individual SC-FC relationship at the macroneuroimaging level.
The pedunculopontine nucleus (PPN) is a small brainstem structure and has attracted attention as a potentially effective deep brain stimulation (DBS) target for the treatment of Parkinson's disease (PD). However, the in vivo location of PPN remains poorly described and barely visible on conventional structural magnetic resonance (MR) images due to a lack of high spatial resolution and tissue contrast. This study aims to delineate the PPN on a high-resolution (HR) atlas and investigate the visibility of the PPN in individual quantitative susceptibility mapping (QSM) images. We combine a recently constructed Montreal Neurological Institute (MNI) space unbiased QSM atlas (MuSus-100), with an implicit representation-based self-supervised image super-resolution (SR) technique to achieve an atlas with improved spatial resolution. Then guided by a myelin staining histology human brain atlas, we localize and delineate PPN on the atlas with improved resolution. Furthermore, we examine the feasibility of directly identifying the approximate PPN location on the 3.0-T individual QSM MR images. The proposed SR network produces atlas images with four times the higher spatial resolution (from 1 to 0.25 mm isotropic) without a training dataset. The SR process also reduces artifacts and keeps superb image contrast for further delineating small deep brain nuclei, such as PPN. Using the myelin staining histological atlas as guidance, we first identify and annotate the location of PPN on the T1-weighted (T1w)-QSM hybrid MR atlas with improved resolution in the MNI space. Then, we relocate and validate that the optimal targeting site for PPN-DBS is at the middle-to-caudal part of PPN on our atlas. Furthermore, we confirm that the PPN region can be identified in a set of individual QSM images of 10 patients with PD and 10 healthy young adults. The contrast ratios of the PPN to its adjacent structure, namely the medial lemniscus, on images of different modalities indicate that QSM substantially improves the visibility of the PPN both in the atlas and individual images. Our findings indicate that the proposed SR network is an efficient tool for small-size brain nucleus identification. HR QSM is promising for improving the visibility of the PPN. The PPN can be directly identified on the individual QSM images acquired at the 3.0-T MR scanners, facilitating a direct targeting of PPN for DBS surgery.
In real life, it is not unusual that we face potential threats (i.e., physical stimuli and environments that may cause harm or danger) with other individuals together, yet it remains largely unknown how threat-induced anxious feelings influence prosocial behaviors such as resource sharing. In this study, we investigated this question by combining functional magnetic resonance imaging and a novel paradigm. Together with an anonymous partner, each participant faced the possibility of receiving a 10-s noise administration, which had a low or high probability to be a threat (i.e., the intensity of noise can induce a high level of unpleasantness). Each participant first reported her/his immediate feeling of anxiety about the current situation (being threatened by the unpleasant noise), then decided how to split a number of resources (which could relieve the noise) between her/him and the partner. Behavioral results revealed that the participants showed a selfish bias in the threat conditions than in the safe conditions, and that self-reported anxiety feeling significantly predicted this bias. Functional magnetic resonance imaging results revealed that: (1) the activation level of the anterior insula was correlated with self-reported anxiety and (2) the connectivity between the anterior insula and the temporoparietal junction was sensitive to the modulating effect of anxiety on the selfish bias. These findings indicate the neural correlates of the association between threat-induced anxiety and prosocial tendencies in social interactions.
Based on the fluctuations ensembled over neighbouring neurons, blood oxygen level-dependent (BOLD) signal is a mesoscale measurement of brain signals. Intraregional temporal features (IRTFs) of BOLD signal, extracted from regional neural activities, are utilized to investigate how the brain functions in local brain areas. This literature highlights four types of IRTFs and their representative calculations including variability in the temporal domain, variability in the frequency domain, entropy, and intrinsic neural timescales, which are tightly related to cognitions. In the brain-wide spatial organization, these brain features generally organized into two spatial hierarchies, reflecting structural constraints of regional dynamics and hierarchical functional processing workflow in brain. Meanwhile, the spatial organization gives rise to the link between neuronal properties and cognitive performance. Disrupted or unbalanced spatial conditions of IRTFs emerge with suboptimal cognitive states, which improved our understanding of the aging process and/or neuropathology of brain disease. This review concludes that IRTFs are important properties of the brain functional system and IRTFs should be considered in a brain-wide manner.
Substantial studies of human amygdala function have revealed its importance in processing emotional experience, autonomic regulation, and sensory information; however, the neural substrates and circuitry subserving functions have not been directly mapped at the level of the subnuclei in humans. We provide a useful overview of amygdala functional characterization by using direct electrical stimulation to various amygdala regions in 48 patients with drug-resistant epilepsy undergoing stereoelectroencephalography recordings. This stimulation extends beyond the anticipated emotional, neurovegetative, olfactory, and somatosensory responses to include visual, auditory, and vestibular sensations, which may be explained by the functional connectivity with cortical and subcortical regions due to evoked amygdala-cortical potentials. Among the physiological symptom categories for each subnucleus, the most frequently evoked neurovegetative symptoms were distributed in almost every subnucleus. Laterobasal subnuclei are mainly associated with emotional responses, somatosensory responses, and vestibular sensations. Superficial subnuclei are mainly associated with emotional responses and olfactory and visual hallucinations. Our findings contribute to a better understanding of the functional architecture of the human amygdala at the subnuclei level and as a mechanistic basis for the clinical practice of amygdala stimulation in treating patients with neuropsychiatric disorders.
Attentional control of auditory N100/M100 gain is reduced in individuals with first-episode psychosis (FEP). Persistent problems with executive modulation of auditory sensory activity may impact multiple aspects of psychosis. As a follow-up to our prior work reporting deficits in attentional M100 gain modulation in auditory cortex, we examined changes in M100 gain modulation longitudinally, and further examined relationships between auditory M100 and symptoms of psychosis. We compared auditory M100 in auditory sensory cortex between 21 FEP and 29 matched healthy participants and between timepoints separated by 220 ± 100 days. Magnetoencephalography data were recorded while participants alternately attended or ignored tones in an auditory oddball task. M100 was measured as the average of 80-140 ms post-stimulus in source-localized evoked responses within bilateral auditory cortex. Symptoms were assessed using the PANSS and PSYRATS. M100 amplitudes, attentional modulation of M100 amplitudes, and symptom severity all improved in FEP over time. Further, improvement in M100 modulation correlated with improvements in negative symptoms (PANSS) as well as physical, cognitive, and emotional components of hallucinations (PSYRATS). Conversely, improvements in the overall size of the M100, rather than the difference between active and passive M100 amplitudes, were related to worsening of positive symptoms (PANSS) and physical components of hallucinations. Results indicate a link between symptoms (particularly auditory hallucinations) and auditory cortex neurophysiology in FEP, where auditory attention and auditory sensation have opposed relationships to symptom change. These findings may inform current models of psychosis etiology and could provide nonpharmaceutical avenues for early intervention.
Most fMRI inferences are based on analyzing the scans of a cohort. Thus, the individual variability of a subject is often overlooked in these studies. Recently, there has been a growing interest in individual differences in brain connectivity also known as individual connectome. Various studies have demonstrated the individual specific component of functional connectivity (FC), which has enormous potential to identify participants across consecutive testing sessions. Many machine learning and dictionary learning-based approaches have been used to extract these subject-specific components either from the blood oxygen level dependent (BOLD) signal or from the FC. In addition, several studies have reported that some resting-state networks have more individual-specific information than others. This study compares four different dictionary-learning algorithms that compute the individual variability from the network-specific FC computed from resting-state functional Magnetic Resonance Imaging (rs-fMRI) data having 10 scans per subject. The study also compares the effect of two FC normalization techniques, namely, Fisher Z normalization and degree normalization on the extracted subject-specific components. To quantitatively evaluate the extracted subject-specific component, a metric named Overlap $$ Overlap $$ is proposed, and it is used in combination with the existing differential identifiability I diff $$ \left({I}_{diff}\right) $$ metric. It is based on the hypothesis that the subject-specific FC vectors should be similar within the same subject and different across different subjects. Results indicate that Fisher Z transformed subject-specific fronto-parietal and default mode network extracted using Common Orthogonal Basis Extraction (COBE) dictionary learning have the best features to identify a participant.
The human brain is constantly subjected to a multimodal stream of probabilistic sensory inputs. Electroencephalography (EEG) signatures, such as the mismatch negativity (MMN) and the P3, can give valuable insight into neuronal probabilistic inference. Although reported for different modalities, mismatch responses have largely been studied in isolation, with a strong focus on the auditory MMN. To investigate the extent to which early and late mismatch responses across modalities represent comparable signatures of uni- and cross-modal probabilistic inference in the hierarchically structured cortex, we recorded EEG from 32 participants undergoing a novel tri-modal roving stimulus paradigm. The employed sequences consisted of high and low intensity stimuli in the auditory, somatosensory and visual modalities and were governed by unimodal transition probabilities and cross-modal conditional dependencies. We found modality specific signatures of MMN (~100-200 ms) in all three modalities, which were source localized to the respective sensory cortices and shared right lateralized prefrontal sources. Additionally, we identified a cross-modal signature of mismatch processing in the P3a time range (~300-350 ms), for which a common network with frontal dominance was found. Across modalities, the mismatch responses showed highly comparable parametric effects of stimulus train length, which were driven by standard and deviant response modulations in opposite directions. Strikingly, P3a responses across modalities were increased for mispredicted stimuli with low cross-modal conditional probability, suggesting sensitivity to multimodal (global) predictive sequence properties. Finally, model comparisons indicated that the observed single trial dynamics were best captured by Bayesian learning models tracking unimodal stimulus transitions as well as cross-modal conditional dependencies.
Assessing the consistency of quantitative MRI measurements is critical for inclusion in longitudinal studies and clinical trials. Intraclass coefficient correlation and coefficient of variation were used to evaluate the different consistency aspects of diffusion- and myelin-based MRI measures. Multi-shell diffusion and inhomogeneous magnetization transfer data sets were collected from 20 healthy adults at a high-frequency of five MRI sessions. The consistency was evaluated across whole bundles and the track-profile along the bundles. The impact of the fiber populations on the consistency was also evaluated using the number of fiber orientations map. For whole and profile bundles, moderate to high reliability of diffusion and myelin measures were observed. We report higher reliability of measures for multiple fiber populations than single. The overall portrait of the most consistent measurements and bundles drawn from a wide range of MRI techniques presented here will be particularly useful for identifying reliable biomarkers capable of detecting, monitoring and predicting white matter changes in clinical applications and has the potential to inform patient-specific treatment strategies.
A cognitive map is an internal representation of the external world that guides flexible behavior in a complex environment. Cognitive map theory assumes that relationships between entities can be organized using Euclidean-based coordinates. Previous studies revealed that cognitive map theory can also be generalized to inferences about abstract spaces, such as social spaces. However, it is still unclear whether humans can construct a cognitive map by combining relational knowledge between discrete entities with multiple abstract dimensions in nonsocial spaces. Here we asked subjects to learn to navigate a novel object space defined by two feature dimensions, price and abstraction. The subjects first learned the rank relationships between objects in each feature dimension and then completed a transitive inferences task. We recorded brain activity using functional magnetic resonance imaging (fMRI) while they performed the transitive inference task. By analyzing the behavioral data, we found that the Euclidean distance between objects had a significant effect on response time (RT). The longer the one-dimensional rank distance and two-dimensional (2D) Euclidean distance between objects the shorter the RT. The task-fMRI data were analyzed using both univariate analysis and representational similarity analysis. We found that the hippocampus, entorhinal cortex, and medial orbitofrontal cortex were able to represent the Euclidean distance between objects in 2D space. Our findings suggest that relationship inferences between discrete objects can be made in a 2D nonsocial space and that the neural basis of this inference is related to cognitive maps.
Journal metrics
$3,850 / £3,140 / €,3,520
Article Processing Charges (APC)
Acceptance rate
33 days
Submission to first decision
5.399 (2021)
Journal Impact Factor™
8.3 (2021)
Top-cited authors
Karl J Friston
  • University College London
Richard Frackowiak
  • École Polytechnique Fédérale de Lausanne
Jean-Baptiste Poline
  • University of California, Berkeley
Angela R Laird
  • Florida International University
John Ashburner
  • University College London