Biology subjects

Shulman, G. L.

Publications and source records attributed to Shulman, G. L..

7 recordsLinked to original sources

bioRxiv2025

Spontaneously emerging patterns in human motor cortex code for somatotopic specific movements

The role of spontaneous brain activity remains a key question in neuroscience. While prior work shows sensory regions preferentially replay stimulus-specific patterns (e.g., faces in fusiform face area), we investigated whether motor cortex replays reflect somatotopic organization. Using fMRI, we compared resting-state activity to task-evoked patterns during specific movements (finger, toe, tongue). Spontaneous activity in each effector-specific motor subregion (hand, foot, mouth) exhibited greater similarity to task patterns of its corresponding movement than to non-preferred ones. For instance, hand movement patterns replayed more in hand regions than elsewhere. Positive rest-task correlations emerged for preferred movements, while negative correlations characterized non-preferred ones (except toe). This structured somatotopic organization suggests spontaneous activity encodes functional specialization, not just activation strength, mirroring task-evoked representations.

neuroscience↗

bioRxiv2020

Spontaneous emergence of behaviorally relevant motifs in human motor cortex

Spontaneous neural activity has been shown to preserve the inter-regional structure of cortical activity evoked by a task. It is unclear, however, whether patterns of spontaneous activity within a cortical region comprise representations associated with specific behaviors or mental states. The current study investigated the hypothesis that spontaneous neural activity in human motor cortex represents motor responses that commonly occur in daily life. To test this hypothesis 15 healthy participants were scanned in a 3T fMRI scanner while performing four simple hand movements differing by their daily life relevance, and while not performing any specific task (resting-state scans). Using the task data, we identified cortical patterns in a motor ROI corresponding to the different hand movements. These task-defined patterns were compared to spontaneous cortical activity patterns in the same motor ROI. The results indicated a higher similarity of the spontaneous patterns to the most common hand movement than to the least common hand movement. This finding provides the first evidence that spontaneous activity in human cortex forms fine-scale, patterned representations associated with behaviors that frequently occur in daily life.

neuroscience↗

bioRxiv2020

Lesion Quantification Toolkit: A MATLAB software tool for estimating grey matter damage and white matter disconnections in patients with focal brain lesions

Lesion studies are an important tool for cognitive neuroscientists and neurologists. However, while brain lesion studies have traditionally aimed to localize neurological symptoms to specific anatomical loci, a growing body of evidence indicates that neurological diseases such as stroke are best conceptualized as brain network disorders. While researchers in the fields of neuroscience and neurology are therefore increasingly interested in quantifying the effects of focal brain lesions on the white matter connections that form the brains structural connectome, few dedicated tools exist to facilitate this endeavor. Here, we present the Lesion Quantification Toolkit, a publicly available MATLAB software package for quantifying the structural impacts of focal brain lesions. The Lesion Quantification Toolkit uses atlas-based approaches to estimate parcel-level grey matter lesion loads and multiple measures of white matter disconnection severity that include tract-level disconnection measures, voxel-wise disconnection maps, and parcel-wise disconnection matrices. The toolkit also estimates lesion-induced increases in the lengths of the shortest structural paths between parcel pairs, which provide information about changes in higher-order structural network topology. We describe in detail each of the different measures produced by the toolkit, discuss their applications and considerations relevant to their use, and perform example analyses using real behavioral data collected from sub-acute stroke patients. We show that analyses performed using the different measures produced by the toolkit produce results that are highly consistent with results that have been reported in the prior literature, and we demonstrate the consistency of results obtained from analyses conducted using the different disconnection measures produced by the toolkit. We anticipate that the Lesion Quantification Toolkit will empower researchers to address research questions that would be difficult or impossible to address using traditional lesion analyses alone, and ultimately, lead to advances in our understanding of how white matter disconnections contribute to the cognitive, behavioral, and physiological consequences of focal brain lesions.

neuroscience↗

bioRxiv2019

Structural disconnections contribute to lesion-induced brain functional connectivity disruptions via direct and indirect mechanisms

Focal brain lesions disrupt resting-state functional connectivity, but the underlying structural mechanisms are unclear. Here, we examined the direct and indirect effects of structural disconnections on resting-state functional connectivity in a large sample of sub-acute stroke patients with heterogeneous brain lesions. We defined direct disconnections as the loss of direct structural connections between two regions, and indirect disconnections as increases in the shortest structural path length between two regions that lack direct structural connections. On average, nearly 20% of all region pairs suffered either a direct or indirect disconnection by the lesions in our sample. Importantly, both directly and indirectly disconnected region pairs showed more severe functional connectivity disruptions than region pairs with spared direct and indirect connections, respectively, although functional connectivity disruptions tended to be most severe between region pairs that sustained direct structural disconnections. Together, these results emphasize the widespread impacts of focal brain lesions on the structural connectome, and show that these impacts are reflected by disruptions of the functional connectome. Further, they indicate that in addition to direct structural disconnections, lesion-induced increases in the structural shortest path lengths between indirectly structurally connected region pairs provide information about the remote functional disruptions caused by focal brain lesions.

neuroscience↗

bioRxiv2019

Structural disconnections explain brain network dysfunction after stroke

SummaryFunctional connectivity (FC) studies have identified physiological signatures of stroke that correlate with behavior. Using structural and functional MRI data from 114 stroke patients, 24 matched controls, and the Human Connectome Project, we tested the hypothesis that structural disconnection, not damage to critical regions, underlies FC disruptions. Disconnection severity outperformed damage to putative FC connector nodes for explaining reductions in system modularity, and multivariate models based on disconnection outperformed damage models for explaining FC disruptions within and between systems. Across patients, disconnection and FC patterns exhibited a low-dimensional covariance dominated by a single axis linking interhemispheric disconnections to reductions in FC measures of interhemispheric system integration, ipsilesional system segregation, and system modularity, and that correlated with multiple behavioral deficits. These findings clarify the structural basis of FC disruptions in stroke patients and demonstrate a low-dimensional link between perturbations of the structural connectome, disruptions of the functional connectome, and behavioral deficits.

neuroscience↗

bioRxiv2019

Resting multivoxel activity patterns in human visual cortex are linked to patterns evoked by preferred visual stimuli

The function of spontaneous brain activity is an important issue in neuroscience. Here we test the hypothesis that patterns of spontaneous activity code representational patterns evoked by stimuli and tasks. We compared in human visual cortex multi-vertex patterns of spontaneous activity to patterns evoked by ecological visual stimuli (faces, bodies, scenes) and low-level visual features (e.g. phase-scrambled faces). Specifically, we identified regions that preferred particular stimulus categories during localizer scans (e.g. extra-striate body area for bodies), measured multi-vertex patterns for each category during event-related task scans, and then correlated over vertices these stimulus-evoked patterns to the pattern measured on each frame of resting-state scans. The mean correlation coefficient was essentially zero for all regions/stimulus categories, indicating that resting multi-vertex patterns were not biased toward particular stimulus-evoked patterns. However, the spread of correlation coefficients between stimulus-evoked and resting patterns, i.e. both positive and negative, was significantly greater for the preferred stimulus category of an ROI (e.g. body category in body-preferring ROIs). The relationship between spontaneous and stimulus-evoked multi-vertex patterns also governed the temporal correlation or functional connectivity of patterns of spontaneous activity between individual regions (pattern-based functional connectivity). Resting patterns related to an object category fluctuated preferentially between ROIs preferring the same category, and patterns related to different categories fluctuated independently within their respective preferred ROIs (e.g. body- and scene-related multi-vertex patterns within body- and scene-preferring ROIs). These results support the general proposal that spontaneous multi-vertex activity patterns are linked to stimulus-evoked patterns, consistent with a representational function for spontaneous activity.

neuroscience↗

bioRxiv2017

Measuring functional connectivity in stroke: approaches and considerations

Recent research has demonstrated the importance of global changes to the functional organization of brain network following stroke. Resting functional MRI (R-fMRI) is a non-invasive tool that enables the measurement of functional connectivity (FC) across the entire brain while placing minimal demands on the subject. For these reasons, it is a uniquely appealing tool for studying the distant effects of stroke. However, R-fMRI studies rely on a number of premises that cannot be assumed without careful validation in the context of stroke. Here, we describe strategies to identify and mitigate confounds specific to R-fMRI research in cerebrovascular disease. Five main topics are discussed: 1) achieving adequate co-registration of lesioned brains, 2) identifying and removing hemodynamic lags in resting BOLD, 3) identifying other vascular disruptions that affect the resting BOLD signal, 4) selecting an appropriate control cohort, and 5) acquiring sufficient fMRI data to reliably identify FC changes. For each topic, we provide evidence-based guidelines for steps to improve the interpretability and reproducibility of FC-stroke research. We include a table of confounds and approaches to identify and mitigate each. Our recommendations extend to any research using R-fMRI to study diseases that might alter cerebrovascular flow and dynamics or brain anatomy.

neuroscience↗