Functional connectivity drives stroke recovery: shifting the paradigm from correlation to causation.

Stroke is a leading cause of disability, with deficits encompassing multiple functional domains. The heterogeneity underlying stroke poses significant challenges in the prediction of post-stroke recovery, prompting the development of neuroimaging-based biomarkers. Structural neuroimaging measurements, particularly those reflecting corticospinal tract injury, are well-documented in the literature as potential biomarker candidates of post-stroke motor recovery. Consistent with the view of stroke as a 'circuitopathy', functional neuroimaging measures probing functional connectivity may also prove informative in post-stroke recovery. An important step in the development of biomarkers based on functional neural network connectivity is the establishment of causality between connectivity and post-stroke recovery. Current evidence predominantly involves statistical correlations between connectivity measures and post-stroke behavioural status, either cross-sectionally or serially over time. However, the advancement of functional connectivity application in stroke depends on devising experiments that infer causality. In 1965, Sir Austin Bradford Hill introduced nine viewpoints to consider when determining the causality of an association: (i) strength; (ii) consistency; (iii) specificity; (iv) temporality; (v) biological gradient; (vi) plausibility; (vii) coherence; (viii) experiment; and (ix) analogy. Collectively referred to as the Bradford Hill Criteria, these points have been widely adopted in epidemiology. In this review, we assert the value of implementing Bradford Hill's framework to stroke rehabilitation and neuroimaging. We focus on the role of neural network connectivity measurements acquired from task-oriented and resting-state functional MRI, EEG, magnetoencephalography and functional near-infrared spectroscopy in describing and predicting post-stroke behavioural status and recovery. We also identify research opportunities within each Bradford Hill tenet to shift the experimental paradigm from correlation to causation.

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.

Coherent neural oscillations inform early stroke motor recovery.

Neural oscillations may contain important information pertaining to stroke rehabilitation. This study examined the predictive performance of electroencephalography-derived neural oscillations following stroke using a data-driven approach. Individuals with stroke admitted to an inpatient rehabilitation facility completed a resting-state electroencephalography recording and structural neuroimaging around the time of admission and motor testing at admission and discharge. Using a lasso regression model with cross-validation, we determined the extent of motor recovery (admission to discharge change in Functional Independence Measurement motor subscale score) prediction from electroencephalography, baseline motor status, and corticospinal tract injury. In 27 participants, coherence in a 1-30 Hz band between leads overlying ipsilesional primary motor cortex and 16 leads over bilateral hemispheres predicted 61.8% of the variance in motor recovery. High beta (20-30 Hz) and alpha (8-12 Hz) frequencies contributed most to the model demonstrating both positive and negative associations with motor recovery, including high beta leads in supplementary motor areas and ipsilesional ventral premotor and parietal regions and alpha leads overlying contralesional temporal-parietal and ipsilesional parietal regions. Electroencephalography power, baseline motor status, and corticospinal tract injury did not significantly predict motor recovery during hospitalization (R2  = 0-6.2%). Findings underscore the relevance of oscillatory synchronization in early stroke rehabilitation while highlighting contributions from beta and alpha frequency bands and frontal, parietal, and temporal-parietal regions overlooked by traditional hypothesis-driven prediction models.

Low-Frequency Oscillations Are a Biomarker of Injury and Recovery After Stroke.

Background and Purpose- Low-frequency oscillations reflect brain injury but also contribute to normal behaviors. We examined hypotheses relating electroencephalography measures, including low-frequency oscillations, to injury and motor recovery poststroke. Methods- Patients with stroke completed structural neuroimaging, a resting-state electroencephalography recording and clinical testing. A subset admitted to an inpatient rehabilitation facility also underwent serial electroencephalography recordings. The relationship that electroencephalography measures (power and coherence with leads overlying ipsilesional primary motor cortex [iM1]) had with injury and motor status was assessed, focusing on delta (1-3 Hz) and high-beta (20-30 Hz) bands. Results- Across all patients (n=62), larger infarct volume was related to higher delta band power in bilateral hemispheres and to higher delta band coherence between iM1 and bilateral regions. In chronic stroke, higher delta power bilaterally correlated with better motor status. In subacute stroke, higher delta coherence between iM1 and bilateral areas correlated with poorer motor status. These coherence findings were confirmed in serial recordings from 18 patients in an inpatient rehabilitation facility. Here, interhemispheric coherence between leads overlying iM1 and contralesional M1 was elevated at inpatient rehabilitation facility admission compared with healthy controls (n=22), declining to control levels over time. Decreases in interhemispheric coherence between iM1 and contralesional M1 correlated with better motor recovery. Conclusions- Delta band coherence with iM1 related to greater injury and poorer motor status subacutely, while delta band power related to greater injury and better motor status chronically. Low-frequency oscillations reflect both injury and recovery after stroke and may be useful biomarkers in stroke recovery and rehabilitation.

Corticospinal Tract Injury Estimated From Acute Stroke Imaging Predicts Upper Extremity Motor Recovery After Stroke.

Background and Purpose- Injury to the corticospinal tract (CST) has been shown to have a major effect on upper extremity motor recovery after stroke. This study aimed to examine how well CST injury, measured from neuroimaging acquired during the acute stroke workup, predicts upper extremity motor recovery. Methods- Patients with upper extremity weakness after ischemic stroke were assessed using the upper extremity Fugl-Meyer during the acute stroke hospitalization and again at 3-month follow-up. CST injury was quantified and compared, using 4 different methods, from images obtained as part of the stroke standard-of-care workup. Logistic and linear regression were performed using CST injury to predict ΔFugl-Meyer. Injury to primary motor and premotor cortices were included as potential modifiers of the effect of CST injury on recovery. Results- N=48 patients were enrolled 4.2±2.7 days poststroke and completed 3-month follow-up (median 90-day modified Rankin Scale score, 3; interquartile range, 1.5). CST injury distinguished patients who reached their recovery potential (as predicted from initial impairment) from those who did not, with area under the curve values ranging from 0.70 to 0.8. In addition, CST injury explained ≈20% of the variance in the magnitude of upper extremity recovery, even after controlling for the severity of initial impairment. Results were consistent when comparing 4 different methods of measuring CST injury. Extent of injury to primary motor and premotor cortices did not significantly influence the predictive value that CST injury had for recovery. Conclusions- Structural injury to the CST, as estimated from standard-of-care imaging available during the acute stroke hospitalization, is a robust way to distinguish patients who achieve their predicted recovery potential and explains a significant amount of the variance in poststroke upper extremity motor recovery.

Electroencephalography Measures are Useful for Identifying Large Acute Ischemic Stroke in the Emergency Department.

BACKGROUND: Early diagnosis of stroke optimizes reperfusion therapies, but behavioral measures have incomplete accuracy. Electroencephalogram (EEG) has high sensitivity for immediately detecting brain ischemia. This pilot study aimed to evaluate feasibility and utility of EEG for identifying patients with a large acute ischemic stroke during Emergency Department (ED) evaluation, as these data might be useful in the prehospital setting. METHODS: A 3-minute resting EEG was recorded using a dense-array (256-lead) system in patients with suspected acute stroke arriving at the ED of a US Comprehensive Stroke Center. RESULTS: An EEG was recorded in 24 subjects, 14 with acute cerebral ischemia (including 5 with large acute ischemic stroke) and 10 without acute cerebral ischemia. Median time from stroke onset to EEG was 6.6 hours; and from ED arrival to EEG, 1.9 hours. Delta band power (P = .004) and the alpha/delta frequency band ratio (P = .0006) each significantly distinguished patients with large acute ischemic stroke (n = 5) from all other patients with suspected stroke (n = 19), with the best diagnostic utility coming from contralesional hemisphere signals. Larger infarct volume correlated with higher EEG power in the alpha/delta frequency band ratio within both the ipsilesional (r = -0.64, P = .013) and the contralesional (r = -0.78, P = .001) hemispheres. CONCLUSIONS: Within hours of stroke onset, EEG measures (1) identify patients with large acute ischemic stroke and (2) correlate with infarct volume. These results suggest that EEG measures of brain function may be useful to improve diagnosis of large acute ischemic stroke in the ED, findings that might be useful to pre-hospital applications.

Neuroimaging Identifies Patients Most Likely to Respond to a Restorative Stroke Therapy.

BACKGROUND AND PURPOSE: Patient heterogeneity reduces statistical power in clinical trials of restorative therapies. Valid predictors of treatment responsiveness are needed, and several have been studied with a focus on corticospinal tract (CST) injury. We studied performance of 4 such measures for predicting behavioral gains in response to motor training therapy. METHODS: Patients with subacute-chronic hemiparetic stroke (n=47) received standardized arm motor therapy, and change in arm Fugl-Meyer score was calculated from baseline to 1 month post-therapy. Injury measures calculated from baseline magnetic resonance imaging included (1) percent CST overlap with stroke, (2) CST-related atrophy (cerebral peduncle area), (3) CST integrity (fractional anisotropy) in the cerebral peduncle, and (4) CST integrity in the posterior limb of internal capsule. RESULTS: Percent CST overlap with stroke, CST-related atrophy, and CST integrity did not correlate with one another, indicating that these 3 measures captured independent features of CST injury. Percent injury to CST significantly predicted treatment-related behavioral gains (r=-0.41; P=0.004). The other CST injury measures did not, neither did total infarct volume nor baseline behavioral deficits. When directly comparing patients with mild versus severe injury using the percent CST injury measure, the odds ratio was 15.0 (95% confidence interval, 1.54-147; P<0.005) for deriving clinically important treatment-related gains. CONCLUSIONS: Percent CST injury is useful for predicting motor gains in response to therapy in the setting of subacute-chronic stroke. This measure can be used as an entry criterion or a stratifying variable in restorative stroke trials to increase statistical power, reduce sample size, and reduce the cost of such trials.

Interhemispheric Inhibition Measurement Reliability in Stroke: A Pilot Study.

OBJECTIVE: Reliable transcranial magnetic stimulation (TMS) measures for probing corticomotor excitability are important when assessing the physiological effects of noninvasive brain stimulation. The primary objective of this study was to examine test-retest reliability of an interhemispheric inhibition (IHI) index measurement in stroke. MATERIALS AND METHODS: Ten subjects with chronic stroke (≥6 months) completed two IHI testing sessions per week for three weeks (six testing sessions total). A single investigator measured IHI in the contra-to-ipsilesional primary motor cortex direction and in the opposite direction using bilateral paired-pulse TMS. Weekly sessions were separated by 24 hours with a 1-week washout period separating testing weeks. To determine if motor-evoked potential (MEP) quantification method affected measurement reliability, IHI indices computed from both MEP amplitude and area responses were found. Reliability was assessed with two-way, mixed intraclass correlation coefficients (ICC(3,k) ). Standard error of measurement and minimal detectable difference statistics were also determined. RESULTS: With the exception of the initial testing week, IHI indices measured in the contra-to-ipsilesional hemisphere direction demonstrated moderate to excellent reliability (ICC = 0.725-0.913). Ipsi-to-contralesional IHI indices depicted poor or invalid reliability estimates throughout the three-week testing duration (ICC= -1.153-0.105). The overlap of ICC 95% confidence intervals suggested that IHI indices using MEP amplitude vs. area measures did not differ with respect to reliability. CONCLUSIONS: IHI indices demonstrated varying magnitudes of reliability irrespective of MEP quantification method. Several strategies for improving IHI index measurement reliability are discussed.

Primed low-frequency repetitive transcranial magnetic stimulation and constraint-induced movement therapy in pediatric hemiparesis: a randomized controlled trial.

AIM: The aim of this study was to determine the feasibility and efficacy of five treatments of 6 Hz primed, low-frequency, repetitive transcranial magnetic stimulation (rTMS) combined with constraint-induced movement therapy (CIMT) to promote recovery of the paretic hand in children with congenital hemiparesis. METHOD: Nineteen children with congenital hemiparesis aged between 8 and 17 years (10 males, nine females; mean age 10 years 10 months, SD 2 years 10 months; Manual Ability Classification Scale levels I-III) underwent five sessions of either real rTMS (n=10) or sham rTMS (n=9) alternated daily with CIMT. CIMT consisted of 13 days of continuous long-arm casting with five skin-check sessions. Each child received a total of 10 hours of one-to-one therapy. The primary outcome measure was the Assisting Hand Assessment (AHA) and the secondary outcome variables were the Canadian Occupational Performance Measure (COPM) and stereognosis. A Wilcoxon signed-rank sum test was used to analyze differences between pre- and post-test scores within the groups. Analysis of covariance was used to compute mean differences between groups adjusting for baseline. Fisher's exact test was used to compare individual change in AHA raw scores with the smallest detectable difference (SDD) of 4 points. RESULTS: All participants receiving treatment finished the study. Improvement in AHA differed significantly between groups (p=0.007). No significant differences in the secondary outcome measures were found. Eight out of 10 participants in the rTMS/CIMT group showed improvement greater than the SDD, but only two out of nine in the sham rTMS/CIMT group showed such improvement (p=0.023). No serious adverse events occurred. INTERPRETATION: Primed, low-frequency rTMS combined with CIMT appears to be safe, feasible, and efficacious in pediatric hemiparesis. Larger clinical trials are now indicated.

Cross-Frequency Coupling as a Biomarker for Early Stroke Recovery.

BACKGROUND: The application of neuroimaging-based biomarkers in stroke has enriched our understanding of post-stroke recovery mechanisms, including alterations in functional connectivity based on synchronous oscillatory activity across various cortical regions. Phase-amplitude coupling, a type of cross-frequency coupling, may provide additional mechanistic insight. OBJECTIVE: To determine how the phase of prefrontal cortex delta (1-3 Hz) oscillatory activity mediates the amplitude of motor cortex beta (13-20 Hz) oscillations in individual's early post-stroke. METHODS: Participants admitted to an inpatient rehabilitation facility completed resting and task-based EEG recordings and motor assessments around the time of admission and discharge along with structural neuroimaging. Unimpaired controls completed EEG procedures during a single visit. Mixed-effects linear models were performed to assess within- and between-group differences in delta-beta prefrontomotor coupling. Associations between coupling and motor status and injury were also determined. RESULTS: Thirty individuals with stroke and 17 unimpaired controls participated. Coupling was greater during task versus rest conditions for all participants. Though coupling during affected extremity task performance decreased during hospitalization, coupling remained elevated at discharge compared to controls. Greater baseline coupling was associated with better motor status at admission and discharge and positively related to motor recovery. Coupling demonstrated both positive and negative associations with injury involving measures of lesion volume and overlap injury to anterior thalamic radiation, respectively. CONCLUSIONS: This work highlights the utility of prefrontomotor cross-frequency coupling as a potential motor status and recovery biomarker in stroke. The frequency- and region-specific neurocircuitry featured in this work may also facilitate novel treatment strategies in stroke.

Aerobic exercise and action observation priming modulate functional connectivity.

Aerobic exercise and action observation are two clinic-ready modes of neural priming that have the potential to enhance subsequent motor learning. Prior work using transcranial magnetic stimulation to assess priming effects have shown changes in corticospinal excitability involving intra- and interhemispheric circuitry. The objective of this study was to determine outcomes exclusive to priming- how aerobic exercise and action observation priming influence functional connectivity within a sensorimotor neural network using electroencephalography. We hypothesized that both action observation and aerobic exercise priming would alter resting-state coherence measures between dominant primary motor cortex and motor-related areas in alpha (7-12 Hz) and beta (13-30 Hz) frequency bands with effects most apparent in the high beta (20-30 Hz) band. Nine unimpaired individuals (24.8 ± 3 years) completed a repeated-measures cross-over study where they received a single five-minute bout of action observation or moderate-intensity aerobic exercise priming in random order with a one-week washout period. Serial resting-state electroencephalography recordings acquired from 0 to 30 minutes following aerobic and action observation priming revealed increased alpha and beta coherence between leads overlying dominant primary motor cortex and supplementary motor area relative to pre- and immediate post-priming timepoints. Aerobic exercise priming also resulted in enhanced high beta coherence between leads overlying dominant primary motor and parietal cortices. These findings indicate that a brief bout of aerobic- or action observation-based priming modulates functional connectivity with effects most pronounced with aerobic priming. The gradual increases in coherence observed over a 10 to 30-minute post-priming window may guide the pairing of aerobic- or action observation-based priming with subsequent training to optimize learning-related outcomes.

Politics, policies, and patient care: Rehabilitation therapists' experiences during the COVID-19 Pandemic.

The year 2020 represents a historically turbulent period for the United States marked by the COVID-19 pandemic, a contentious political season, and heightened awareness of racism among citizens. This intersection of medicine, politics, and social unrest generated a demanding clinical environment for healthcare workers, including understudied groups such as physical therapists, occupational therapists, and speech-language pathologists. This descriptive qualitative study focused on experiences and perspectives of clinical rehabilitation therapists working in inpatient rehabilitation and acute-care units from September to November, 2020. Thirteen participants completed individual, semi-structured interviews focused on clinical practice and coping strategies. The analysis included a multi-step, inductive process. Four interconnecting factors chronicling participants' experiences emerged: sociopolitical, institutional, hospital unit, and personal. Stressors and buffers were noted that further shaped individual experiences. Utilization of an ecological framework provided a way to recognize the impact of a complex range of social and environmental factors affecting participants' experiences on personal and professional levels. Awareness of rehabilitation therapists' experiences enriches understanding of the pandemic's effect on healthcare workers and presents clinical implications for healthcare systems to promote therapist well-being.

Remote ischaemic conditioning combined with bimanual task training to enhance bimanual skill learning and corticospinal excitability in children with unilateral cerebral palsy: a study protocol of a single centre, phase II randomised controlled trial.

INTRODUCTION: Children with unilateral cerebral palsy (UCP) have difficulty in bimanual coordination that restricts the child's independence in daily activities. Although several efficacious interventions to improve bimanual coordination exist, these interventions often require higher training doses and have modest effect sizes. Thus, there is a critical need to find an effective priming agent that, when paired with task-specific training, will facilitate neurobiological processes to enhance the magnitude of training effects and subsequently improve functional capabilities of children with UCP. The aim of this study is to determine the effects of a novel priming agent, remote ischaemic conditioning (RIC), combined with bimanual training on bimanual skill learning and corticospinal excitability in children with UCP. METHODS AND ANALYSES: 46 children, aged 8-16 years, will be randomly assigned to receive RIC or sham conditioning combined with 5 days of bimanual skill (cup stacking) training (15 trials per session). RIC or sham conditioning will be performed with a standard conditioning protocol of five cycles of alternative inflation and deflation of a pressure cuff on the affected arm with the pressure of at least 20 mm Hg above systolic blood pressure for RIC and 25 mm Hg for sham conditioning. Primary outcomes will be movement time and corticospinal excitability measures determined with a single-pulse transcranial magnetic stimulation (TMS). Secondary outcomes include Assisting Hand Assessment, spatio-temporal kinematic variables and paired pulse TMS measures. All measures will be conducted before and immediately after the intervention. A mixed model analysis of variance will test the group×time interaction for all outcomes with group (RIC and sham) as between-subject and time (preintervention, postintervention) as within-subject factors. ETHICS AND DISSEMINATION: The study has been approved by the University Medical Centre Institutional Review Board (UMCIRB #21-001913). We will disseminate the study findings via peer-reviewed publications and presentations at professional conferences. TRIAL REGISTRATION NUMBER: NCT05777070.

Corticomuscular Coherence in Children with Unilateral Cerebral Palsy: A Feasibility and Preliminary Protocol Study.

Objective This study assessed the feasibility of corticomuscular coherence measurement during a goal-directed task in children with unilateral cerebral palsy while establishing optimal experimental parameters. Methods Participants (Manual Ability Classification System levels I-III) completed a submaximal isometric goal-directed grip task during simultaneous electroencephalography and electromyography (EMG) acquisition. Results All participants (n = 11, 6 females, mean age 11.3 ±2.4 years) completed corticomuscular coherence procedures. Of the 40 trials obtained per extremity, an average of 29 (n = 9) and 27 (n = 10) trials were retained from the more- and less-affected extremities, respectively. Obtaining measurement stability required an average of 28 trials per extremity. Conclusion Findings from this work support the feasibility of corticomuscular coherence measurement in children with unilateral cerebral palsy. Acquiring 28 to 40 corticomuscular coherence trials per extremity is ideal. The experimental parameters established in this work will inform future corticomuscular coherence application in pediatric unilateral cerebral palsy.

Data-driven biomarkers outperform theory-based biomarkers in predicting stroke motor outcomes.

Chronic motor impairments are a leading cause of disability after stroke. Previous studies have predicted motor outcomes based on the degree of damage to predefined structures in the motor system, such as the corticospinal tract. However, such theory-based approaches may not take full advantage of the information contained in clinical imaging data. The present study uses data-driven approaches to predict chronic motor outcomes after stroke and compares the accuracy of these predictions to previously-identified theory-based biomarkers. Using a cross-validation framework, regression models were trained using lesion masks and motor outcomes data from 789 stroke patients (293 female/496 male) from the ENIGMA Stroke Recovery Working Group (age 64.9±18.0 years; time since stroke 12.2±0.2 months; normalised motor score 0.7±0.5 (range [0,1]). The out-of-sample prediction accuracy of two theory-based biomarkers was assessed: lesion load of the corticospinal tract, and lesion load of multiple descending motor tracts. These theory-based prediction accuracies were compared to the prediction accuracy from three data-driven biomarkers: lesion load of lesion-behaviour maps, lesion load of structural networks associated with lesion-behaviour maps, and measures of regional structural disconnection. In general, data-driven biomarkers had better prediction accuracy - as measured by higher explained variance in chronic motor outcomes - than theory-based biomarkers. Data-driven models of regional structural disconnection performed the best of all models tested (R2 = 0.210, p < 0.001), performing significantly better than predictions using the theory-based biomarkers of lesion load of the corticospinal tract (R2 = 0.132, p< 0.001) and of multiple descending motor tracts (R2 = 0.180, p < 0.001). They also performed slightly, but significantly, better than other data-driven biomarkers including lesion load of lesion-behaviour maps (R2 =0.200, p < 0.001) and lesion load of structural networks associated with lesion-behaviour maps (R2 =0.167, p < 0.001). Ensemble models - combining basic demographic variables like age, sex, and time since stroke - improved prediction accuracy for theory-based and data-driven biomarkers. Finally, combining both theory-based and data-driven biomarkers with demographic variables improved predictions, and the best ensemble model achieved R2 = 0.241, p < 0.001. Overall, these results demonstrate that models that predict chronic motor outcomes using data-driven features, particularly when lesion data is represented in terms of structural disconnection, perform better than models that predict chronic motor outcomes using theory-based features from the motor system. However, combining both theory-based and data-driven models provides the best predictions.

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 (ß = 0.21; 95% CI 0.04-0.38, p = 0.015), which in turn was associated with poorer outcomes, both in the sensorimotor domain (ß = -0.28; 95% CI -0.41 to -0.15, p < 0.001) and across multiple domains of function (ß = -0.14; 95% CI -0.22 to -0.06, p < 0.001). Brain age mediated 15% of the impact of lesion damage on sensorimotor performance (95% CI 3%-58%, p = 0.01). Greater brain resilience explained why people have better outcomes, given matched lesion damage (odds ratio 1.04, 95% CI 1.01-1.08, p = 0.004). 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.

Leveraging Factors of Self-Efficacy and Motivation to Optimize Stroke Recovery.

The International Classification of Functioning, Disability and Health framework recognizes that an individual's functioning post-stroke reflects an interaction between their health condition and contextual factors encompassing personal and environmental factors. Personal factors significantly impact rehabilitation outcomes as they determine how an individual evaluates their situation and copes with their condition in daily life. A key personal factor is self-efficacy-an individual's belief in their capacity to achieve certain outcomes. Self-efficacy influences an individual's motivational state to execute behaviors necessary for achieving desired rehabilitation outcomes. Stroke rehabilitation practice and research now acknowledge self-efficacy and motivation as critical elements in post-stroke recovery, and increasing evidence highlights their contributions to motor (re)learning. Given the informative value of neuroimaging-based biomarkers in stroke, elucidating the neurological underpinnings of self-efficacy and motivation may optimize post-stroke recovery. In this review, we examine the role of self-efficacy and motivation in stroke rehabilitation and recovery, identify potential neural substrates underlying these factors from current neuroimaging literature, and discuss how leveraging these factors and their associated neural substrates has the potential to advance the field of stroke rehabilitation.

Observational Study of Neuroimaging Biomarkers of Severe Upper Limb Impairment After Stroke.

BACKGROUND AND OBJECTIVES: It is difficult to predict post-stroke outcome for people with severe motor impairment, as both clinical tests and corticospinal tract (CST) microstructure may not reliably indicate severe motor impairment. Here, we test whether imaging biomarkers beyond the CST relate to severe upper limb impairment post-stroke by evaluating white matter microstructure in the corpus callosum (CC). In an international, multisite hypothesis-generating observational study we determined if: a) CST asymmetry index can differentiate between individuals with mild-moderate and severe upper limb impairment; and b) CC biomarkers relate to upper limb impairment within individuals with severe impairment post-stroke. We hypothesised that CST asymmetry index would differentiate between mild-moderate and severe impairment, but CC microstructure would relate to motor outcome for individuals with severe upper limb impairment. METHODS: Seven cohorts with individual diffusion imaging and motor impairment (Fugl Meyer-Upper Limb) data were pooled. Hand-drawn regions-of-interest were used to seed probabilistic tractography for CST (ipsilesional/contralesional) and CC (prefrontal/premotor/motor/sensory/posterior) tracts. Our main imaging measure was mean fractional anisotropy. Linear mixed-effect regression explored relationships between candidate biomarkers and motor impairment, controlling for observations nested within cohorts, as well as age, sex, time post-stroke and lesion volume. RESULTS: Data from 110 individuals (30 mild-moderate, 80 with severe motor impairment) were included. In the full sample, greater CST asymmetry index (i.e., lower fractional anisotropy in the ipsilesional hemisphere, p<.001) and larger lesion volume (p=.139) were negatively related to impairment. In the severe subgroup, CST asymmetry index was not reliably associated with impairment across models. Instead, lesion volume and CC microstructure explained impairment in the severe group beyond CST asymmetry index (p's<.010). CONCLUSIONS: Within a large cohort of individuals with severe upper limb impairment, CC microstructure related to motor outcome post-stroke. Our findings demonstrate that CST microstructure does relate to upper limb outcome across the full range of motor impairment but was not reliably associated within the severe subgroup. Therefore, CC microstructure may provide a promising biomarker for severe upper limb outcome post-stroke, which may advance our ability to predict recovery in people with severe motor impairment after stroke.

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; ß=0.16) but not contralesional (P=0.96; ß=0.003) hippocampal volume, independent of lesion volume and other covariates (P=0.001; ß=0.26). Women showed progressively worsening sensorimotor impairment with smaller ipsilesional (P=0.008; ß=-0.26) and contralesional (P=0.006; ß=-0.27) hippocampal volumes compared with men. Hippocampal volume was associated with lesion size (P<0.001; ß=-0.21) and extent of sensorimotor damage (P=0.003; ß=-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.

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.