Insights and Perspectives on Sensory-Motor Integration and Rehabilitation

The present review focuses on the flow and interaction of somatosensory-motor signals in the central and peripheral nervous system. Specifically, where incoming sensory signals from the periphery are processed and interpreted to initiate behaviors, and how ongoing behaviors produce sensory consequences encoded and used to fine-tune subsequent actions. We describe the structure-function relations of this loop, how these relations can be modeled and aspects of somatosensory-motor rehabilitation. The work reviewed here shows that it is imperative to understand the fundamental mechanisms of the somatosensory-motor system to restore accurate motor abilities and appropriate somatosensory feedback. Knowledge of the salient neural mechanisms of sensory-motor integration has begun to generate innovative approaches to improve rehabilitation training following neurological impairments such as stroke. The present work supports the integration of basic science principles of sensory-motor integration into rehabilitation procedures to create new solutions for sensory-motor disorders

Modulatory Effects of Motor State During Paired Associative Stimulation on Motor Cortex Excitability and Motor Skill Learning

Repeated pairing of electrical stimulation of a peripheral nerve with transcranial magnetic stimulation (TMS) over the primary motor cortex (M1) representation for a target muscle can induce neuroplastic adaptations in the human brain related to motor learning. The extent to which the motor state during this form of paired associative stimulation (PAS) influences the degree and mechanisms of neuroplasticity or motor learning is unclear. Here, we investigated the effect of volitional muscle contraction during PAS on: (1) measures of general corticomotor excitability and intracortical circuit excitability; and (2) motor performance and learning. We assessed measures of corticomotor excitability using TMS and motor skill performance during a serial reaction time task (SRTT) at baseline and at 0, 30, 60 min post-PAS. Participants completed a SRTT retention test 1 week following the first two PAS sessions. Following the PAS intervention where the hand muscle maintained an active muscle contraction (PASACTIVE), there was lower short interval intracortical inhibition compared to PAS during a resting motor state (PASREST) and a sham PAS condition (PASCONTROL). SRTT performance improved within the session regardless of PAS condition. SRTT retention was greater following both PASACTIVE and PASREST after 1 week compared to PASCONTROL. These findings suggest that PAS may enhance motor learning retention and that motor state may be used to target different neural mechanisms of intracortical excitation and inhibition during PAS. This observation may be important to consider for the use of therapeutic noninvasive brain stimulation in neurologic patient populations

Putting the “Sensory” Into Sensorimotor Control: The Role of Sensorimotor Integration in Goal-Directed Hand Movements After Stroke

Integration of sensory and motor information is one-step, among others, that underlies the successful production of goal-directed hand movements necessary for interacting with our environment. Disruption of sensorimotor integration is prevalent in many neurologic disorders, including stroke. In most stroke survivors, persistent paresis of the hand reduces function and overall quality of life. Current rehabilitative methods are based on neuroplastic principles to promote motor learning that focuses on regaining motor function lost due to paresis, but the sensory contributions to motor control and learning are often overlooked and currently understudied. There is a need to evaluate and understand the contribution of both sensory and motor function in the rehabilitation of skilled hand movements after stroke. Here, we will highlight the importance of integration of sensory and motor information to produce skilled hand movements in healthy individuals and individuals after stroke. We will then discuss how compromised sensorimotor integration influences relearning of skilled hand movements after stroke. Finally, we will propose an approach to target sensorimotor integration through manipulation of sensory input and motor output that may have therapeutic implications

The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain–behavior relationships after stroke

The goal of the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well‐powered meta‐ and mega‐analytic approaches. ENIGMA Stroke Recovery has data from over 2,100 stroke patients collected across 39 research studies and 10 countries around the world, comprising the largest multisite retrospective stroke data collaboration to date. This article outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multisite stroke brain magnetic resonance imaging, behavioral and demographics data. Specifically, the processes for scalable data intake and preprocessing, multisite data harmonization, and large‐scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided

Chronic Stroke Sensorimotor Impairment Is Related to Smaller Hippocampal Volumes: An ENIGMA Analysis

Background. Persistent sensorimotor impairments after stroke can negatively impact quality of life. The hippocampus is vulnerable to poststroke secondary degeneration and is involved in sensorimotor behavior but has not been widely studied within the context of poststroke upper‐limb sensorimotor impairment. We investigated associations between non‐lesioned hippocampal volume and upper limb sensorimotor impairment in people with chronic stroke, hypothesizing that smaller ipsilesional hippocampal volumes would be associated with greater sensorimotor impairment. Methods and Results. Cross‐sectional T1‐weighted magnetic resonance images of the brain were pooled from 357 participants with chronic stroke from 18 research cohorts of the ENIGMA (Enhancing NeuoImaging Genetics through Meta‐Analysis) Stroke Recovery Working Group. Sensorimotor impairment was estimated from the FMA‐UE (Fugl‐Meyer Assessment of Upper Extremity). Robust mixed‐effects linear models were used to test associations between poststroke sensorimotor impairment and hippocampal volumes (ipsilesional and contralesional separately; Bonferroni‐corrected, P<0.025), controlling for age, sex, lesion volume, and lesioned hemisphere. In exploratory analyses, we tested for a sensorimotor impairment and sex interaction and relationships between lesion volume, sensorimotor damage, and hippocampal volume. Greater sensorimotor impairment was significantly associated with ipsilesional (P=0.005; β=0.16) but not contralesional (P=0.96; β=0.003) hippocampal volume, independent of lesion volume and other covariates (P=0.001; β=0.26). Women showed progressively worsening sensorimotor impairment with smaller ipsilesional (P=0.008; β=−0.26) and contralesional (P=0.006; β=−0.27) hippocampal volumes compared with men. Hippocampal volume was associated with lesion size (P<0.001; β=−0.21) and extent of sensorimotor damage (P=0.003; β=−0.15). Conclusions. The present study identifies novel associations between chronic poststroke sensorimotor impairment and ipsilesional hippocampal volume that are not caused by lesion size and may be stronger in women.S.-L.L. is supported by NIH K01 HD091283; NIH R01 NS115845. A.B. and M.S.K. are supported by National Health and Medical Research Council (NHMRC) GNT1020526, GNT1045617 (A.B.), GNT1094974, and Heart Foundation Future Leader Fellowship 100784 (A.B.). P.M.T. is supported by NIH U54 EB020403. L.A.B. is supported by the Canadian Institutes of Health Research (CIHR). C.M.B. is supported by NIH R21 HD067906. W.D.B. is supported by the Heath Research Council of New Zealand. J.M.C. is supported by NIH R00HD091375. A.B.C. is supported by NIH R01NS076348-01, Hospital Israelita Albert Einstein 2250-14, CNPq/305568/2016-7. A.N.D. is supported by funding provided by the Texas Legislature to the Lone Star Stroke Clinical Trial Network. Its contents are solely the responsibility of the authors and do not necessarily represent the of ficial views of the Government of the United States or the State of Texas. N.E.-B. is supported by Australian Research Council NIH DE180100893. W.F. is sup ported by NIH P20 GM109040. F.G. is supported by Wellcome Trust (093957). B.H. is funded by and NHMRC fellowship (1125054). S.A.K is supported by NIH P20 HD109040. F.B. is supported by Italian Ministry of Health, RC 20, 21. N.S. is supported by NIH R21NS120274. N.J.S. is supported by NIH/National Institute of General Medical Sciences (NIGMS) 2P20GM109040-06, U54-GM104941. S.R.S. is supported by European Research Council (ERC) (NGBMI, 759370). G.S. is supported by Italian Ministry of Health RC 18-19-20-21A. M.T. is sup ported by National Institute of Neurological Disorders and Stroke (NINDS) R01 NS110696. G.T.T. is supported by Temple University sub-award of NIH R24 –NHLBI (Dr Mickey Selzer) Center for Experimental Neurorehabilitation Training. N.J.S. is funded by NIH/National Institute of Child Health and Human Development (NICHD) 1R01HD094731-01A1

A large, curated, open-source stroke neuroimaging dataset to improve lesion segmentation algorithms.

Accurate lesion segmentation is critical in stroke rehabilitation research for the quantification of lesion burden and accurate image processing. Current automated lesion segmentation methods for T1-weighted (T1w) MRIs, commonly used in stroke research, lack accuracy and reliability. Manual segmentation remains the gold standard, but it is time-consuming, subjective, and requires neuroanatomical expertise. We previously released an open-source dataset of stroke T1w MRIs and manually-segmented lesion masks (ATLAS v1.2, N = 304) to encourage the development of better algorithms. However, many methods developed with ATLAS v1.2 report low accuracy, are not publicly accessible or are improperly validated, limiting their utility to the field. Here we present ATLAS v2.0 (N = 1271), a larger dataset of T1w MRIs and manually segmented lesion masks that includes training (n = 655), test (hidden masks, n = 300), and generalizability (hidden MRIs and masks, n = 316) datasets. Algorithm development using this larger sample should lead to more robust solutions; the hidden datasets allow for unbiased performance evaluation via segmentation challenges. We anticipate that ATLAS v2.0 will lead to improved algorithms, facilitating large-scale stroke research

Association of Brain Age, Lesion Volume, and Functional Outcome in Patients With Stroke

BACKGROUND AND OBJECTIVES: Functional outcomes after stroke are strongly related to focal injury measures. However, the role of global brain health is less clear. In this study, we examined the impact of brain age, a measure of neurobiological aging derived from whole-brain structural neuroimaging, on poststroke outcomes, with a focus on sensorimotor performance. We hypothesized that more lesion damage would result in older brain age, which would in turn be associated with poorer outcomes. Related, we expected that brain age would mediate the relationship between lesion damage and outcomes. Finally, we hypothesized that structural brain resilience, which we define in the context of stroke as younger brain age given matched lesion damage, would differentiate people with good vs poor outcomes. METHODS: We conducted a cross-sectional observational study using a multisite dataset of 3-dimensional brain structural MRIs and clinical measures from the ENIGMA Stroke Recovery. Brain age was calculated from 77 neuroanatomical features using a ridge regression model trained and validated on 4,314 healthy controls. We performed a 3-step mediation analysis with robust mixed-effects linear regression models to examine relationships between brain age, lesion damage, and stroke outcomes. We used propensity score matching and logistic regression to examine whether brain resilience predicts good vs poor outcomes in patients with matched lesion damage. RESULTS: We examined 963 patients across 38 cohorts. Greater lesion damage was associated with older brain age (β = 0.21; 95% CI 0.04-0.38, DISCUSSION: We provide evidence that younger brain age is associated with superior poststroke outcomes and modifies the impact of focal damage. The inclusion of imaging-based assessments of brain age and brain resilience may improve the prediction of poststroke outcomes compared with focal injury measures alone, opening new possibilities for potential therapeutic targets

Perturbation-imaging Approaches to Study Functional Contributions of Cortical Activity to Human Movement

Presented on September 30, 2019 at 11:15 a.m. in the Krone Engineered Biosystems Building, Room 1005.Dr. Michael Borich is an Assistant Professor in the Department of Physical Therapy in the School of Rehabilitation Medicine at Emory University. Dr. Borich is keenly interested in understanding and harnessing the plastic capacity of the human nervous system in health and disease in an effort to improve rehabilitation outcomes for individuals with neurologic injury and disease. His research utilizes multimodal neuroimaging and neurostimulation techniques to characterize the brain structural and functional correlates of neural plasticity associated with learning and experience.Runtime: 57:55 minutesThe ability to learn and produce skilled movements is required for humans to successfully engage with each other and their environment. A principal role of the brain is to guide current, and plan future, movements based on past actions and potential rewards. In this talk, I will describe ongoing work in our lab employing multiple approaches to investigate the functional contributions of brain activity to normal and abnormal human movement. I will discuss how transcranial magnetic stimulation (TMS), a form of non-invasive brain stimulation, can be used both characterize and modulate cortical activity and connectivity during movement. I will also describe our recent findings showing abnormal TMS-evoked cortical reactivity post-stroke that is related to persistent paretic arm impairment. Lastly, I will discuss preliminary work applying alternative perturbation paradigms to study brain-behavior relationships in health and disease

Identifying and Targeting Potential Biomarkers of Motor Dysfunction after Stroke using Non-invasive Neurostimulation and Neuroimaging

Presented on September 19, 2016 at 11:00 a.m. in the Engineered Biosystems Building (EBB), room 1005.Dr. Michael R. Borich is keenly interested in understanding and harnessing the plastic capacity of the human nervous system in health and disease in an effort to improve rehabilitation outcomes for individuals with neurologic injury and disease. His research utilizes multimodal neuroimaging and neurostimulation techniques to characterize the brain structural and functional correlates of neural plasticity associated with learning and experience.Runtime: 52:40 minutesUp to 80% of stroke survivors have persistent motor impairment of the paretic arm that interferes with performing functional activities and limits activity participation. Stroke can trigger maladaptive changes in the strength and organization of structural and functional connections between brain regions. During paretic arm movement, there is exaggerated interhemispheric inhibition (IHI) from the contralesional hemisphere to the ipsilesional hemisphere. Exaggerated IHI creates an abnormal activity imbalance between brain hemispheres and this imbalance seems to be a primary contributor to motor impairment of the paretic arm after stroke. Although restoring the balance of activity between brain hemispheres has been a primary target of many novel rehabilitation strategies, limited progress has been made to improve arm motor function and reduce persistent disability for stroke survivors. In this talk, I will describe work in our lab using transcranial magnetic stimulation (TMS), a form of non-invasive brain stimulation, to both characterize and modulate cortical activity and connectivity in the brain after stroke. In the first part of my talk, I will describe how abnormal cortical excitability after stroke has been traditionally characterized using standalone TMS techniques. In the second part of my talk, I will discuss current findings from our lab using concurrent EEG recordings of TMS-evoked cortical activity that demonstrate abnormal interhemispheric interactions are present in the human brain after stroke and these abnormal interactions are related to arm motor impairment. Finally, I will introduce an upcoming project in our lab investigating the use of bifocal TMS to transiently modulate local cortical excitability and IHI in the human brain in an effort to restore the balance of activity between the hemispheres and improve arm motor function after stroke