Connectome-based lesion-symptom mapping (CLSM): A novel approach to map neurological function

Damage to the structural connectome reflected in resting-state fMRI functional connectivity

The relationship between structural and functional connectivity has been mostly examined in intact brains. Fewer studies have examined how differences in structure as a result of injury alters function. In this study we analyzed the relationship of structure to function across patients with stroke among whom infarcts caused heterogenous structural damage. We estimated relationships between distinct brain regions of interest (ROIs) from functional MRI in two pipelines. In one analysis pipeline, we measured functional connectivity by using correlation and partial correlation between 114 cortical ROIs. We found fMRI-BOLD partial correlation was altered at more edges as a function of the structural connectome (SC) damage, relative to the correlation. In a second analysis pipeline, we limited our analysis to fMRI correlations between pairs of voxels for which we possess SC information. We found that voxel-level functional connectivity showed the effect of structural damage that we could not see when examining correlations between ROIs. Further, the effects of structural damage on functional connectivity are consistent with a model of functional connectivity, diffusion, which expects functional connectivity to result from activity spreading over multiple edge anatomical paths.

Neural substrates of subcortical aphasia in subacute stroke: Voxel-based lesion symptom mapping study

Subcortical aphasia develops as a result of damage to subcortical brain areas without loss of cortical functions. Although earlier voxel-based lesion-symptom mapping (VLSM) studies have shown possible neural correlates for aphasia, it remains to be clarified which brain regions are associated with subcortical aphasia. The aim of this study was to investigate the neural substrates associated with subcortical aphasia in patients with stroke using VLSM and atlas-based analyses to explore the involvement of white matter tracts and subcortical structures. Fifty patients with subacute subcortical stroke without cortical involvement were retrospectively enrolled: 24 with and 26 without aphasia. We performed VLSM and atlas-based analyses of the patients' fluid-attenuated inversion recovery images and found that the left perisylvian white matter, left fronto-occipital fasciculus, uncinate fasciculus, and forceps minor were significantly more greatly affected in the aphasia than in the non-aphasia group. The left anterior thalamic radiation, cingulum (cingulate gyrus), and superior longitudinal fasciculus also showed higher involvement in this group (marginal significance). Among the subcortical regions, the left caudate and putamen were more greatly involved in the aphasia group. Our findings confirm language processing as one of the integrated sensory-motor processes that occur in the region around the left sylvian fissure. Our atlas-based analysis approach can be used to complement VLSM analyses.

Rapid Quantification of White Matter Disconnection in the Human Brain

With an estimated five million new stroke survivors every year and a rapidly aging population suffering from hyperintensities and diseases of presumed vascular origin that affect white matter and contribute to cognitive decline, it is critical that we understand the impact of white matter damage on brain structure and behavior. Current techniques for assessing the impact of lesions consider only location, type, and extent, while ignoring how the affected region was connected to the rest of the brain. Regional brain function is a product of both local structure and its connectivity. Therefore, obtaining a map of white matter disconnection is a crucial step that could help us predict the behavioral deficits that patients exhibit. In the present work, we introduce a new practical method for computing lesion-based white matter disconnection maps that require only moderate computational resources. We achieve this by creating diffusion tractography models of the brains of healthy adults and assessing the connectivity between small regions. We then interrupt these connectivity models by projecting patients' lesions into them to compute predicted white matter disconnection. A quantified disconnection map can be computed for an individual patient in approximately 35 seconds using a single core CPU-based computation. In comparison, a similar quantification performed with other tools provided by MRtrix3 takes 5.47 minutes.

Topological and hodological aspects of body representation in right brain damaged patients

The triadic taxonomy posits that three distinct types of body representations do exist, namely the body schema (BS), which corresponds to the representation derived from multiple sensory and motor inputs, the body structural representation (BSR), which corresponds to the structural description of spatial relations among the body parts, and the body semantics (SEM), which corresponds to the lexical-semantic representation of the body. Although several studies have assessed neural correlates of these representations, no study has compared them in brain-damaged patients, controlling for deficits in other cognitive domains. Also, little is known about the contribution of the right hemisphere to different body representations. Here we used a computerized battery to test these three body representations in twenty-six right brain damaged patients, controlling for other cognitive deficits by means of tests tapping similar spatial and lexical processes on non-body related stimuli. Residual scores corresponding to the BS, the BSR and the SEM were used to test neural correlates, which were assessed by integrating topological and hodological approaches to lesion-deficit analyses. We found that the BSR was associated with lesion of the superior temporal gyrus, the insula, the supramarginal gyrus and the temporo-parietal junction, extending also to the Rolandic operculum and the inferior frontal gyrus. Also, it was associated with the disconnection probability of the posterior arcuate segment. The BS was associated with a small cluster of voxels in the precentral and postcentral gyri, whereas the SEM was associated with white matter lesion at the boundary between the parietal and temporal lobes. Overall, these results provide strong support to the regional and connectional contribution of the right hemisphere to body representation, and more specifically to the BSR.

Brain structures and cognitive abilities important for the self-monitoring of speech errors

The brain structures and cognitive abilities necessary for successful monitoring of one's own speech errors remain unknown. We aimed to inform self-monitoring models by examining the neural and behavioral correlates of phonological and semantic error detection in individuals with post-stroke aphasia. First, we determined whether detection related to other abilities proposed to contribute to monitoring according to various theories, including naming ability, fluency, word-level auditory comprehension, sentence-level auditory comprehension, and executive function. Regression analyses revealed that fluency and executive scores were independent predictors of phonological error detection, while a measure of word-level comprehension related to semantic error detection. Next, we used multivariate lesion-symptom mapping to determine lesion locations associated with reduced error detection. Reduced overall error detection related to damage to a region of frontal white matter extending into dorsolateral prefrontal cortex (DLPFC). Detection of phonological errors related to damage to the same areas, but the lesion-behavior association was stronger, suggesting the localization for overall error detection was driven primarily by phonological error detection. These findings demonstrate that monitoring of different error types relies on distinct cognitive functions, and provide causal evidence for the importance of frontal white matter tracts and DLPFC for self-monitoring of speech.

Imaging Developmental and Interventional Plasticity Following Perinatal Stroke

Perinatal stroke occurs around the time of birth and leads to lifelong neurological disabilities including hemiparetic cerebral palsy. Magnetic resonance imaging (MRI) has revolutionized our understanding of developmental neuroplasticity following early injury, quantifying volumetric, structural, functional, and metabolic compensatory changes after perinatal stroke. Such techniques can also be used to investigate how the brain responds to treatment (interventional neuroplasticity). Here, we review the current state of knowledge of how established and emerging neuroimaging modalities are informing neuroplasticity models in children with perinatal stroke. Specifically, we review structural imaging characterizing lesion characteristics and volumetrics, diffusion tensor imaging investigating white matter tracts and networks, task-based functional MRI for localizing function, resting state functional imaging for characterizing functional connectomes, and spectroscopy examining neurometabolic changes. Key challenges and exciting avenues for future investigations are also considered.

Structural Disconnection of the Tool Use Network after Left Hemisphere Stroke Predicts Limb Apraxia Severity

Producing a tool use gesture is a complex process drawing upon the integration of stored knowledge of tools and their associated actions with sensory-motor mechanisms supporting the planning and control of hand and arm actions. Understanding how sensory-motor systems in parietal cortex interface with semantic representations of actions and objects in the temporal lobe remains a critical issue and is hypothesized to be a key determinant of the severity of limb apraxia, a deficit in producing skilled action after left hemisphere stroke. We used voxel-based and connectome-based lesion-symptom mapping with data from 57 left hemisphere stroke participants to assess the lesion sites and structural disconnection patterns associated with poor tool use gesturing. We found that structural disconnection among the left inferior parietal lobule, lateral and ventral temporal cortices, and middle and superior frontal gyri predicted the severity of tool use gesturing performance. Control analyses demonstrated that reductions in right-hand grip strength were associated with motor system disconnection, largely bypassing regions supporting tool use gesturing. Our findings provide evidence that limb apraxia may arise, in part, from a disconnection between conceptual representations in the temporal lobe and mechanisms enabling skilled action production in the inferior parietal lobule.

Accuracy and practical aspects of semi- and fully automatic segmentation methods for resected brain areas

Purpose

Precise segmentation of brain lesions is essential for neurological research. Specifically, resection volume estimates can aid in the assessment of residual postoperative tissue, e.g. following surgery for glioma. Furthermore, behavioral lesion-symptom mapping in epilepsy relies on accurate delineation of surgical lesions. We sought to determine whether semi- and fully automatic segmentation methods can be applied to resected brain areas and which approach provides the most accurate and cost-efficient results.

Methods

We compared a semi-automatic (ITK-SNAP) with a fully automatic (lesion_GNB) method for segmentation of resected brain areas in terms of accuracy with manual segmentation serving as reference. Additionally, we evaluated processing times of all three methods. We used T1w, MRI-data of epilepsy patients (n = 27; 11 m; mean age 39 years, range 16–69) who underwent temporal lobe resections (17 left).

Results

The semi-automatic approach yielded superior accuracy (p < 0.001) with a median Dice similarity coefficient (mDSC) of 0.78 and a median average Hausdorff distance (maHD) of 0.44 compared with the fully automatic approach (mDSC 0.58, maHD 1.32). There was no significant difference between the median percent volume difference of the two approaches (p > 0.05). Manual segmentation required more human input (30.41 min/subject) and therefore inferring significantly higher costs than semi- (3.27 min/subject) or fully automatic approaches (labor and cost approaching zero).

Conclusion

Semi-automatic segmentation offers the most accurate results in resected brain areas with a moderate amount of human input, thus representing a viable alternative compared with manual segmentation, especially for studies with large patient cohorts.

Functional anomaly mapping reveals local and distant dysfunction caused by brain lesions

The lesion method has been important for understanding brain-behavior relationships in humans, but has previously used maps based on structural damage. Lesion measurement based on structural damage may label partly damaged but functional tissue as abnormal, and moreover, ignores distant dysfunction in structurally intact tissue caused by deafferentation, diaschisis, and other processes. A reliable method to map functional integrity of tissue throughout the brain would provide a valuable new approach to measuring lesions. Here, we use machine learning on four dimensional resting state fMRI data obtained from left-hemisphere stroke survivors in the chronic period of recovery and control subjects to generate graded maps of functional anomaly throughout the brain in individual patients. These functional anomaly maps identify areas of obvious structural lesions and are stable across multiple measurements taken months and even years apart. Moreover, the maps identify functionally anomalous regions in structurally intact tissue, providing a direct measure of remote effects of lesions on the function of distant brain structures. Multivariate lesion-behavior mapping using functional anomaly maps replicates classic behavioral localization, identifying inferior frontal regions related to speech fluency, lateral temporal regions related to auditory comprehension, parietal regions related to phonology, and the hand area of motor cortex and descending corticospinal pathways for hand motor function. Further, this approach identifies relationships between tissue function and behavior distant from the structural lesions, including right premotor dysfunction related to ipsilateral hand movement, and right cerebellar regions known to contribute to speech fluency. Brain-wide maps of the functional effects of focal lesions could have wide implications for lesion-behavior association studies and studies of recovery after brain injury.

Damage to the shortest structural paths between brain regions is associated with disruptions of resting-state functional connectivity after stroke

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 estimated the impact of each patient's lesion on the structural connectome by embedding the lesion in a diffusion MRI streamline tractography atlas constructed using data from healthy individuals. 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. We then tested the hypothesis that functional connectivity disruptions would be more severe for disconnected regions than for regions with spared connections. On average, nearly 20% of all region pairs were estimated to be either directly or indirectly disconnected by the lesions in our sample, and extensive disconnections were associated primarily with damage to deep white matter locations. 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.

Coevolution of language and symbolic meaning: Co-opting meaning underlying the initial arts in early human culture

Many of language's components, including communicating symbolic meaning, have neurobiological roots that go back millions of years in evolutionary time. The intersection with the human social survival strategy spawned additional adaptive meaning systems. Under conditions threatening survival in socially oriented human groups, extra-language meaning systems co-opted and adapted to facilitate unity, including the early formats of the arts. They would have percolated into cultural practice for this social purpose and ultimately survival. With evolutionary pressures tapping into biologically inherited, physiologically functioning sensory-motor pathways, anchored specifically in rhythm cognition and motor synchrony output, initial art practice conveyed symbolic group cohesion through communal, all-inclusive synchronously moving dance formations and rhythmically produced vocal or percussion sounds. As with the sounds of language in the deep past, and numerous other cultural behaviors, such nonmaterial early art formats would not have left marks in the archeological record but their evolutionary driven practice would have contributed to adaptive genetic factors woven into brain-behavior evolution. Their practice is likely to have well predated unearthed art-related objects. Consolidation of evidence and notions from language evolution, genetics, human physiology, comparative animal communication, archeology, and climate history in the distant past of early humans in Africa supports the evolutionary driven practice of initial nonmaterial art formats conveying symbolic expressions optimizing group survival. This article is categorized under: Cognitive Biology > Evolutionary Roots of Cognition Linguistics > Evolution of Language Psychology > Comparative Psychology.

Lesion Studies in Contemporary Neuroscience

Studies of humans with focal brain damage and non-human animals with experimentally induced brain lesions have provided pivotal insights into the neural basis of behavior. As the repertoire of neural manipulation and recording techniques expands, the utility of studying permanent brain lesions bears re-examination. Studies on the effects of permanent lesions provide vital data about brain function that are distinct from those of reversible manipulations. Focusing on work carried out in humans and nonhuman primates, we address the inferential strengths and limitations of lesion studies, recent methodological developments, the integration of this approach with other methods, and the clinical and ecological relevance of this research. We argue that lesion studies are essential to the rigorous assessment of neuroscience theories.

Finding maximally disconnected subnetworks with shortest path tractography

Connectome-based lesion symptom mapping (CLSM) can be used to relate disruptions of brain network connectivity with clinical measures. We present a novel method that extends current CLSM approaches by introducing a fast reliable and accurate way for computing disconnectomes, i.e. identifying damaged or lesioned connections. We introduce a new algorithm that finds the maximally disconnected subgraph containing regions and region pairs with the greatest shared connectivity loss. After normalizing a stroke patient's segmented MRI lesion into template space, probability weighted structural connectivity matrices are constructed from shortest paths found in white matter voxel graphs of 210 subjects from the Human Connectome Project. Percent connectivity loss matrices are constructed by measuring the proportion of shortest-path probability weighted connections that are lost because of an intersection with the patient's lesion. Maximally disconnected subgraphs of the overall connectivity loss matrix are then derived using a computationally fast greedy algorithm that closely approximates the exact solution. We illustrate the approach in eleven stroke patients with hemiparesis by identifying expected disconnections of the corticospinal tract (CST) with cortical sensorimotor regions. Major disconnections are found in the thalamus, basal ganglia, and inferior parietal cortex. Moreover, the size of the maximally disconnected subgraph quantifies the extent of cortical disconnection and strongly correlates with multiple clinical measures. The methods provide a fast, reliable approach for both visualizing and quantifying the disconnected portion of a patient's structural connectome based on their routine clinical MRI, without reliance on concomitant diffusion weighted imaging. The method can be extended to large databases of stroke patients, multiple sclerosis or other diseases causing focal white matter injuries helping to better characterize clinically relevant white matter lesions and to identify biomarkers for the recovery potential of individual patients.

•

Significantly accelerated shortest path tractography approach for constructing connectomes and disconnectomes.

•

New algorithm extracts the subnetwork containing cortical connections and regions with maximal shared connectivity loss.

•

The size of the maximally disconnected subnetwork quantifies the extent of disconnection and correlates with stroke measures.

•

Fast and accurate approach for visualizing and analyzing the disconnected portion of a patient's structural connectome.

Cortical and structural-connectivity damage correlated with impaired syntactic processing in aphasia

Agrammatism in aphasia is not a homogeneous syndrome, but a characterization of a nonuniform set of language behaviors in which grammatical markers and complex syntactic structures are omitted, simplified, or misinterpreted. In a sample of 71 left-hemisphere stroke survivors, syntactic processing was quantified with the Northwestern Assessment of Verbs and Sentences (NAVS). Classification analyses were used to assess the relation between NAVS performance and morphosyntactically reduced speech in picture descriptions. Voxel-based and connectivity-based lesion-symptom mapping were applied to investigate neural correlates of impaired syntactic processing. Despite a nonrandom correspondence between NAVS performance and morphosyntactic production deficits, there was variation in individual patterns of syntactic processing. Morphosyntactically reduced production was predicted by lesions to left-hemisphere inferior frontal cortex. Impaired verb argument structure production was predicted by damage to left-hemisphere posterior superior temporal and angular gyrus, as well as to a ventral pathway between temporal and frontal cortex. Damage to this pathway was also predictive of impaired sentence comprehension and production, particularly of noncanonical sentences. Although agrammatic speech production is primarily predicted by lesions to inferior frontal cortex, other aspects of syntactic processing rely rather on regional integrity in temporoparietal cortex and the ventral stream.

Lesions Responsible for Impaired Visual Perception in Poststroke Patients Using Voxel-Based Lesion Symptom Mapping

We aimed to clarify the clinical characteristics that affect visual perception (VP) and elucidate lesion locations correlated with impaired VP. We reviewed 61 patients with stroke. Clinical assessments of a motor-free VP test were used to evaluate VP after stroke. Regression analyses were performed to examine predictors of impaired VP. We generated statistical maps of lesions related to impaired VP using voxel-based lesion symptom mapping (VLSM). The group of patients who had right hemispheric lesions had significantly low VP function. In a regression model, impaired VP was predicted by cognitive function, age, lesion volume, and right hemispheric lesion. Using VLSM, we found lesion location associated with impaired VP after adjusting for age, lesion volume, and Korean version of mini mental status exam. The results showed a lesion pattern with predominant distribution in the right parietal lobe and deep white matter. Age, lesion volume, and cognitive impairment affected the results of VP tests. Even after adjustments, we found that lesions responsible for impaired VP were located in the right parietal lobe and deep white matter. This result confirmed right hemispheric dominance for VP using VLSM. Clin. Anat. 32:689-696, 2019. © 2019 Wiley Periodicals, Inc.

Repetitive verbal behaviors are not always harmful signs: Compensatory plasticity within the language network in aphasia

Repetitive verbal behaviors such as conduite d'approche (CdA) and mitigated echolalia (ME) are well-known phenomena since early descriptions of aphasia. Nevertheless, there is no substantial fresh knowledge on their clinical features, neural correlates and treatment interventions. In the present study we take advantage of three index cases of chronic fluent aphasia showing CdA, ME or both symptoms to dissect their clinical and neural signatures. Using multimodal neuroimaging (structural magnetic resonance imaging and [18]-fluorodeoxyglucose positron emission tomography during resting state), we found that despite of the heterogeneous lesions in terms of etiology (stroke, traumatic brain injury), volume and location, CdA was present when the lesion affected in greater extent the left dorsal language pathway, while ME resulted from preferential damage to the left ventral stream. The coexistence of CdA and ME was associated with involvement of areas overlapping with the structural lesions and metabolic derangements described in the subjects who showed one of these symptoms (CdA or ME). These findings suggest that CdA and ME represent the clinical expression of plastic changes that occur within the spared language network and its interconnected areas in order to compensate for the linguistic functions that previously relied on the activity of the damaged pathway. We discuss the results in the light of this idea and consider alternative undamaged neural networks that may support CdA and ME.

Estimating effects of graded white matter damage and binary tract disconnection on post-stroke language impairment

Despite the critical importance of close replications in strengthening and advancing scientific knowledge, there are inherent challenges to conducting replications of lesion-based studies. In the present study, we conducted a close conceptual replication of a study (i.e., Hope et al., 2016) that found that fluency and naming scores in post-stoke aphasia were more strongly associated with a binary measure of structural white matter integrity (tract disconnection) than a graded measure (lesion load). Using a different sample of stroke patients (N = 128) and four language deficit measures (aphasia severity, picture naming, and composite scores for speech production and semantic cognition), we examined tract disconnection and lesion load in three white matter tracts that have been implicated in language processing: arcuate fasciculus, uncinate fasciculus, and inferior fronto-occipital fasciculus. We did not find any consistent evidence that binary tract disconnection was more strongly associated with language impairment over and above lesion load, though individual deficit measures differed with respect to whether lesion load or tract disconnection was the stronger predictor. Given the mixed findings, we suggest caution when using such indirect estimates of structural white matter integrity, and direct individual measurements (for example, using diffusion weighted imaging) should be preferred when they are available. We end by highlighting the complex nature of replication in lesion-based studies and offer some potential solutions.

Embedded Finite Elements for Modeling Axonal Injury

The purpose of this paper is to propose and develop a large strain embedded finite element formulation that can be used to explicitly model axonal fiber bundle tractography from diffusion tensor imaging of the brain. Once incorporated, the fibers offer the capability to monitor tract-level strains that give insight into the biomechanics of brain injury. We show that one commercial software has a volume and mass redundancy issue when including embedded axonal fiber and that a newly developed algorithm is able to correct this discrepancy. We provide a validation analysis for stress and energy to demonstrate the method.

The Original Social Network: White Matter and Social Cognition

Social neuroscience has traditionally focused on the functionality of gray matter regions, ignoring the critical role played by axonal fiber pathways in supporting complex social processes. In this paper, we argue that research on white matter is essential for understanding a range of topics in social neuroscience, such as face processing, theory of mind, empathy, and imitation, as well as clinical disorders defined by aberrant social behavior, such as prosopagnosia, autism, and schizophrenia. We provide practical advice on how best to carry out these studies, which ultimately will substantially deepen our understanding of the neurobiological basis of social behavior.

Mapping Language Networks Using the Structural and Dynamic Brain Connectomes

Lesion-symptom mapping is often employed to define brain structures that are crucial for human behavior. Even though poststroke deficits result from gray matter damage as well as secondary white matter loss, the impact of structural disconnection is overlooked by conventional lesion-symptom mapping because it does not measure loss of connectivity beyond the stroke lesion. This study describes how traditional lesion mapping can be combined with structural connectome lesion symptom mapping (CLSM) and connectome dynamics lesion symptom mapping (CDLSM) to relate residual white matter networks to behavior. Using data from a large cohort of stroke survivors with aphasia, we observed improved prediction of aphasia severity when traditional lesion symptom mapping was combined with CLSM and CDLSM. Moreover, only CLSM and CDLSM disclosed the importance of temporal-parietal junction connections in aphasia severity. In summary, connectome measures can uniquely reveal brain networks that are necessary for function, improving the traditional lesion symptom mapping approach.

Cortical disconnection of the ipsilesional primary motor cortex is associated with gait speed and upper extremity motor impairment in chronic left hemispheric stroke

Advances in neuroimaging have enabled the mapping of white matter connections across the entire brain, allowing for a more thorough examination of the extent of white matter disconnection after stroke. To assess how cortical disconnection contributes to motor impairments, we examined the relationship between structural brain connectivity and upper and lower extremity motor function in individuals with chronic stroke. Forty-three participants [mean age: 59.7 (±11.2) years; time poststroke: 64.4 (±58.8) months] underwent clinical motor assessments and MRI scanning. Nonparametric correlation analyses were performed to examine the relationship between structural connectivity amid a subsection of the motor network and upper/lower extremity motor function. Standard multiple linear regression analyses were performed to examine the relationship between cortical necrosis and disconnection of three main cortical areas of motor control [primary motor cortex (M1), premotor cortex (PMC), and supplementary motor area (SMA)] and motor function. Anatomical connectivity between ipsilesional M1/SMA and the (1) cerebral peduncle, (2) thalamus, and (3) red nucleus were significantly correlated with upper and lower extremity motor performance (P ≤ 0.003). M1-M1 interhemispheric connectivity was also significantly correlated with gross manual dexterity of the affected upper extremity (P = 0.001). Regression models with M1 lesion load and M1 disconnection (adjusted for time poststroke) explained a significant amount of variance in upper extremity motor performance (R²  = 0.36-0.46) and gait speed (R²  = 0.46), with M1 disconnection an independent predictor of motor performance. Cortical disconnection, especially of ipsilesional M1, could significantly contribute to variability seen in locomotor and upper extremity motor function and recovery in chronic stroke. Hum Brain Mapp 39:120-132, 2018. © 2017 Wiley Periodicals, Inc.