Michael R. Borich

Understanding the role of the primary somatosensory cortex: Opportunities for rehabilitation

Emerging evidence indicates impairments in somatosensory function may be a major contributor to motor dysfunction associated with neurologic injury or disorders. However, the neuroanatomical substrates underlying the connection between aberrant sensory input and ineffective motor output are still under investigation. The primary somatosensory cortex (S1) plays a critical role in processing afferent somatosensory input and contributes to the integration of sensory and motor signals necessary for skilled movement. Neuroimaging and neurostimulation approaches provide unique opportunities to non-invasively study S1 structure and function including connectivity with other cortical regions. These research techniques have begun to illuminate casual contributions of abnormal S1 activity and connectivity to motor dysfunction and poorer recovery of motor function in neurologic patient populations. This review synthesizes recent evidence illustrating the role of S1 in motor control, motor learning and functional recovery with an emphasis on how information from these investigations may be exploited to inform stroke rehabilitation to reduce motor dysfunction and improve therapeutic outcomes.

2015 Brainhack Proceedings

Table of contentsI1 Introduction to the 2015 Brainhack ProceedingsR. Cameron Craddock, Pierre Bellec, Daniel S. Margules, B. Nolan Nichols, Jörg P. PfannmöllerA1 Distributed collaboration: the case for the enhancement of Brainspell’s interfaceAmanPreet Badhwar, David Kennedy, Jean-Baptiste Poline, Roberto ToroA2 Advancing open science through NiDataBen Cipollini, Ariel RokemA3 Integrating the Brain Imaging Data Structure (BIDS) standard into C-PACDaniel Clark, Krzysztof J. Gorgolewski, R. Cameron CraddockA4 Optimized implementations of voxel-wise degree centrality and local functional connectivity density mapping in AFNIR. Cameron Craddock, Daniel J. ClarkA5 LORIS: DICOM anonymizerSamir Das, Cécile Madjar, Ayan Sengupta, Zia MohadesA6 Automatic extraction of academic collaborations in neuroimagingSebastien DeryA7 NiftyView: a zero-footprint web application for viewing DICOM and NIfTI filesWeiran DengA8 Human Connectome Project Minimal Preprocessing Pipelines to NipypeEric Earl, Damion V. Demeter, Kate Mills, Glad Mihai, Luka Ruzic, Nick Ketz, Andrew Reineberg, Marianne C. Reddan, Anne-Lise Goddings, Javier Gonzalez-Castillo, Krzysztof J. GorgolewskiA9 Generating music with resting-state fMRI dataCaroline Froehlich, Gil Dekel, Daniel S. Margulies, R. Cameron CraddockA10 Highly comparable time-series analysis in NitimeBen D. FulcherA11 Nipype interfaces in CBRAINTristan Glatard, Samir Das, Reza Adalat, Natacha Beck, Rémi Bernard, Najmeh Khalili-Mahani, Pierre Rioux, Marc-Étienne Rousseau, Alan C. EvansA12 DueCredit: automated collection of citations for software, methods, and dataYaroslav O. Halchenko, Matteo Visconti di Oleggio CastelloA13 Open source low-cost device to register dog’s heart rate and tail movementRaúl Hernández-Pérez, Edgar A. Morales, Laura V. CuayaA14 Calculating the Laterality Index Using FSL for Stroke Neuroimaging DataKaori L. Ito, Sook-Lei LiewA15 Wrapping FreeSurfer 6 for use in high-performance computing environmentsHans J. JohnsonA16 Facilitating big data meta-analyses for clinical neuroimaging through ENIGMA wrapper scriptsErik Kan, Julia Anglin, Michael Borich, Neda Jahanshad, Paul Thompson, Sook-Lei LiewA17 A cortical surface-based geodesic distance package for PythonDaniel S Margulies, Marcel Falkiewicz, Julia M HuntenburgA18 Sharing data in the cloudDavid O’Connor, Daniel J. Clark, Michael P. Milham, R. Cameron CraddockA19 Detecting task-based fMRI compliance using plan abandonment techniquesRamon Fraga Pereira, Anibal Sólon Heinsfeld, Alexandre Rosa Franco, Augusto Buchweitz, Felipe MeneguzziA20 Self-organization and brain functionJörg P. Pfannmöller, Rickson Mesquita, Luis C.T. Herrera, Daniela DenticoA21 The Neuroimaging Data Model (NIDM) APIVanessa Sochat, B Nolan NicholsA22 NeuroView: a customizable browser-base utilityAnibal Sólon Heinsfeld, Alexandre Rosa Franco, Augusto Buchweitz, Felipe MeneguzziA23 DIPY: Brain tissue classificationJulio E. Villalon-Reina, Eleftherios Garyfallidis

Diffusion imaging and transcranial magnetic stimulation assessment of transcallosal pathways in chronic stroke

OBJECTIVE To examine the relationship of transcallosal pathway microstructure and transcallosal inhibition (TCI) with motor function and impairment in chronic stroke. METHODS Diffusion-weighted magnetic resonance imaging and transcranial magnetic stimulation (TMS) data were collected from 24 participants with chronic stroke and 11 healthy older individuals. Post-stroke motor function (Wolf Motor Function Test) and level of motor impairment (Fugl-Meyer score) were evaluated. RESULTS Fractional anisotropy (FA) of transcallosal tracts between prefrontal cortices and the mean amplitude decrease in muscle activity during the ipsilateral silent period evoked by TMS over the non-lesioned hemisphere (termed NL-iSPmean) were significantly associated with level of motor impairment and motor function after stroke (p<0.05). A regression model including age, post-stroke duration, lesion volume, lesioned corticospinal tract FA, transcallosal prefrontal tract FA and NL-iSPmean accounted for 84% of variance in motor impairment (p<0.01). Both transcallosal prefrontal tract FA (ΔR(2)=0.12, p=0.04) and NL-iSPmean (ΔR(2)=0.09, p=0.04) accounted for unique variance in motor impairment level. CONCLUSIONS Prefrontal transcallosal tract microstructure and TCI are each uniquely associated with motor impairment in chronic stroke. SIGNIFICANCE Utilizing a multi-modal approach to assess transcallosal pathways may improve our capacity to identify important neural substrates of motor impairment in the chronic phase of stroke.

Alterations in resting state brain networks in concussed adolescent athletes

Sports-related concussion in adolescents is a major public health issue; however, little is known about the underlying changes in functional brain connectivity. We evaluated connectivity of resting-state brain networks to determine whether alterations in specific networks distinguish adolescents with sports-related concussion from a group of healthy, active control adolescents. Twelve adolescents with a clinical diagnosis of subacute concussion and ten healthy adolescents matched for age, gender, and physical activity completed functional magnetic resonance imaging (fMRI) scanning. Functional connectivity of resting-state brain networks was evaluated in both groups using probabilistic independent component analysis (ICA). Altered functional connectivity was found within three resting-state networks in adolescents with concussion. Specifically, we noted: a) alterations within the default mode network; b) increased connectivity in the right frontal pole in the executive function network; and c) increased connectivity in the left frontal operculum cortex associated with the ventral attention network. This preliminary report shows that whole-brain functional connectivity is altered in networks related to cognition and attention in adolescents in the subacute phase following sports-related concussion. This first report in adolescents should be used to inform future studies in larger cohorts of adolescents with sports-related concussion. Increased knowledge of these changes may lead to improvements in clinical management and help to develop rehabilitation programs.

Combining Whole-Brain Voxel-Wise Analysis with In Vivo Tractography of Diffusion Behavior after Sports-Related Concussion in Adolescents: A Preliminary Report

We have previously shown that sports-related concussion in adolescents is associated with changes in whole-brain properties of white-matter pathways. Here, we assess local changes within these pathways. Twelve adolescents with a clinical diagnosis of subacute concussion and 10 healthy adolescents matched for age, gender, and physical activity completed magnetic resonance imaging scanning. Voxel-wise tract-based spatial statistics and tractography were performed to assess local changes in diffusion-based measures of microstructural properties of white-matter pathways (fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity) between the two groups. Fractional anisotropy values were higher for the concussed group in multiple cluster regions using tract-based spatial statistics, primarily in frontal white-matter regions, including the anterior corona radiata bilaterally. Using these regions of altered diffusion characteristics to seed fiber tractography, significantly reduced axial diffusivity in tracts passing through these areas were detected in the concussed group (p=0.04). A trend toward reduced mean and radial diffusivity in the concussed group was also observed within the same reconstructed tracts. Diffusion behavior within these tracts was significantly correlated with an assessment of concussion status (Sports Concussion Assessment Tool 2). Fractional anisotropy within the reconstructed tracts was not significantly different between the two groups. These results suggest that subacute concussion in adolescents is associated with altered diffusion properties within regional white-matter tissue and along reconstructed fiber pathways. Combining voxel-wise analysis with fiber tractography provides an alternative objective approach to evaluate and identify subtle changes in white-matter fiber integrity after concussion.

Motor skill learning is associated with diffusion characteristics of white matter in individuals with chronic stroke.

Background and Purpose: Imaging advances allow investigation of white matter after stroke; a growing body of literature has shown links between diffusion-based measures of white matter microstructure and motor function. However, the relationship between these measures and motor skill learning has not been considered in individuals with stroke. The aim of this study was to investigate the relationships between posttraining white matter microstructural status, as indexed by diffusion tensor imaging within the ipsilesional posterior limb of the internal capsule (PLIC), and learning of a novel motor task in individuals with chronic stroke. Methods: A total of 13 participants with chronic stroke and 9 healthy controls practiced a visuomotor pursuit task across 5 sessions. Change in motor behavior associated with learning was indexed by comparing baseline performance with a delayed retention test. Fractional anisotropy (FA) indexed at the retention test was the primary diffusion tensor imaging-derived outcome measure. Results: In individuals with chronic stroke, we discovered an association between posttraining ipsilesional PLIC FA and the magnitude of change associated with motor learning; hierarchical multiple linear regression analyses revealed that the combination of age, time poststroke, and ipsilesional PLIC FA posttraining was associated with motor learning-related change (R2 = 0.649; P = 0.02). Baseline motor performance was not related to posttraining ipsilesional PLIC FA. Discussion and Conclusions: Diffusion characteristics of posttraining ipsilesional PLIC were linked to the magnitude of change in skilled motor behavior. These results imply that the microstructural properties of regional white matter indexed by diffusion behavior may be an important factor to consider when determining potential response to rehabilitation in persons with stroke. Video Abstract available (see Video, Supplemental Digital Content 1, http://links.lww.com/JNPT/A59) for more insights from the authors.

Comparing a diffusion tensor and non-tensor approach to white matter fiber tractography in chronic stroke.

Diffusion tensor imaging (DTI)-based tractography has been used to demonstrate functionally relevant differences in white matter pathway status after stroke. However, it is now known that the tensor model is insensitive to the complex fiber architectures found in the vast majority of voxels in the human brain. The inability to resolve intra-voxel fiber orientations may have important implications for the utility of standard DTI-based tract reconstruction methods. Intra-voxel fiber orientations can now be identified using novel, tensor-free approaches. Constrained spherical deconvolution (CSD) is one approach to characterize intra-voxel diffusion behavior. In the current study, we performed DTI- and CSD-based tract reconstruction of the corticospinal tract (CST) and corpus callosum (CC) to test the hypothesis that characterization of complex fiber orientations may improve the robustness of fiber tract reconstruction and increase the sensitivity to identify functionally relevant white matter abnormalities in individuals with chronic stroke. Diffusion weighted magnetic resonance imaging was performed in 27 chronic post-stroke participants and 12 healthy controls. Transcallosal pathways and the CST bilaterally were reconstructed using DTI- and CSD-based tractography. Mean fractional anisotropy (FA), apparent diffusion coefficient (ADC), axial diffusivity (AD), and radial diffusivity (RD) were calculated across the tracts of interest. The total number and volume of reconstructed tracts was also determined. Diffusion measures were compared between groups (Stroke, Control) and methods (CSD, DTI). The relationship between post-stroke motor behavior and diffusion measures was evaluated. Overall, CSD methods identified more tracts than the DTI-based approach for both CC and CST pathways. Mean FA, ADC, and RD differed between DTI and CSD for CC-mediated tracts. In these tracts, we discovered a difference in FA for the CC between stroke and healthy control groups using CSD but not DTI. CSD identified ipsilesional CST pathways in 9 stroke participants who did not have tracts identified with DTI. Additionally, CSD differentiated between stroke ipsilesional and healthy control non-dominant CST for several measures (number of tracts, tract volume, FA, ADC, and RD) whereas DTI only detected group differences for number of tracts. In the stroke group, motor behavior correlated with fewer diffusion metrics derived from the DTI as compared to CSD-reconstructed ipsilesional CST and CC. CSD is superior to DTI-based tractography in detecting differences in diffusion characteristics between the nondominant healthy control and ipsilesional CST. CSD measures of microstructure tissue properties related to more motor outcomes than DTI measures did. Our results suggest the potential utility and functional relevance of characterizing complex fiber organization using tensor-free diffusion modeling approaches to investigate white matter pathways in the brain after stroke.

Evaluation of differences in brain neurophysiology and morphometry associated with hand function in individuals with chronic stroke.

PURPOSE Rehabilitation interventions need to be optimized to maximize therapeutic effects and minimize stroke-related disability. However, a comprehensive understanding of the neural substrates underlying recovery is lacking. The purpose of this study was to investigate relationships between brain anatomy, physiology and hand motor function in individuals with chronic stroke. METHODS Transcranial magnetic stimulation (TMS) and magnetic resonance imaging (MRI) approaches were used to evaluate cortical excitability and brain structural morphometry in individuals with chronic stroke. Hemispheric differences and relationships between these measures and hand dexterity were evaluated. RESULTS Hemispheric differences were observed for TMS and MRI measures. Bilateral hand dexterity correlated with TMS resting motor threshold and precentral gyral thickness. Transcallosal inhibition across hemispheres was positively associated with midcallosal white matter volume. Regression modeling results demonstrated that combining TMS and MRI measures predicted unique amounts of variance in hand dexterity. CONCLUSIONS RESULTS confirm and extend findings showing differences in brain structure and function after stroke. RESULTS suggested a structure-function relationship underlying interhemispheric connectivity in chronic stroke. The utility of combined TMS and MRI measures to predict motor function can be used in future investigations to aid identifying optimal biomarkers of stroke recovery to predict response to rehabilitation to maximize treatment outcomes.

Multiple measures of corticospinal excitability are associated with clinical features of multiple sclerosis

In individuals with multiple sclerosis (MS), transcranial magnetic stimulation (TMS) may be employed to assess the integrity of corticospinal system and provides a potential surrogate biomarker of disability. The purpose of this study was to provide a comprehensive examination of the relationship between multiple measures corticospinal excitability and clinical disability in MS (expanded disability status scale (EDSS)). Bilateral corticospinal excitability was assessed using motor evoked potential (MEP) input-output (IO) curves, cortical silent period (CSP), short-interval intracortical inhibition (SICI), intracortical facilitation (ICF) and transcallosal inhibition (TCI) in 26 individuals with MS and 11 healthy controls. Measures of corticospinal excitability were compared between individuals with MS and controls. We evaluated the relationship(s) between age and clinical demographics such as age at MS onset (AO), disease duration (DD) and clinical disability (EDSS) with measures of corticospinal excitability. Corticospinal excitability thresholds were higher, MEP latency and CSP onset delayed and MEP durations prolonged in individuals with MS compared to controls. Age, DD and EDSS correlated with corticospinal excitability thresholds. Also, TCI duration and the linear slope of the MEP amplitude IO curve correlated with EDSS. Hierarchical regression modeling demonstrated that combining multiple TMS-based measures of corticospinal excitability accounted for unique variance in clinical disability (EDSS) beyond that of clinical demographics (AO, DD). Our results indicate that multiple TMS-based measures of corticospinal and interhemispheric excitability provide insights into the potential neural mechanisms associated with clinical disability in MS. These findings may aid in the clinical evaluation, disease monitoring and prediction of disability in MS.

Motor Skill Acquisition Promotes Human Brain Myelin Plasticity

Experience-dependent structural changes are widely evident in gray matter. Using diffusion weighted imaging (DWI), the neuroplastic effect of motor training on white matter in the brain has been demonstrated. However, in humans it is not known whether specific features of white matter relate to motor skill acquisition or if these structural changes are associated to functional network connectivity. Myelin can be objectively quantified in vivo and used to index specific experience-dependent change. In the current study, seventeen healthy young adults completed ten sessions of visuomotor skill training (10,000 total movements) using the right arm. Multicomponent relaxation imaging was performed before and after training. Significant increases in myelin water fraction, a quantitative measure of myelin, were observed in task dependent brain regions (left intraparietal sulcus [IPS] and left parieto-occipital sulcus). In addition, the rate of motor skill acquisition and overall change in myelin water fraction in the left IPS were negatively related, suggesting that a slower rate of learning resulted in greater neuroplastic change. This study provides the first evidence for experience-dependent changes in myelin that are associated with changes in skilled movements in healthy young adults.