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

One-Year Risk of Stroke after Transient Ischemic Attack or Minor Stroke

BACKGROUND Previous studies conducted between 1997 and 2003 estimated that the risk of stroke or an acute coronary syndrome was 12 to 20% during the first 3 months after a transient ischemic attack (TIA) or minor stroke. The TIAregistry.org project was designed to describe the contemporary profile, etiologic factors, and outcomes in patients with a TIA or minor ischemic stroke who receive care in health systems that now offer urgent evaluation by stroke specialists. METHODS We recruited patients who had had a TIA or minor stroke within the previous 7 days. Sites were selected if they had systems dedicated to urgent evaluation of patients with TIA. We estimated the 1-year risk of stroke and of the composite outcome of stroke, an acute coronary syndrome, or death from cardiovascular causes. We also examined the association of the ABCD2 score for the risk of stroke (range, 0 [lowest risk] to 7 [highest risk]), findings on brain imaging, and cause of TIA or minor stroke with the risk of recurrent stroke over a period of 1 year. RESULTS From 2009 through 2011, we enrolled 4789 patients at 61 sites in 21 countries. A total of 78.4% of the patients were evaluated by stroke specialists within 24 hours after symptom onset. A total of 33.4% of the patients had an acute brain infarction, 23.2% had at least one extracranial or intracranial stenosis of 50% or more, and 10.4% had atrial fibrillation. The Kaplan–Meier estimate of the 1-year event rate of the composite cardiovascular outcome was 6.2% (95% confidence interval, 5.5 to 7.0). Kaplan–Meier estimates of the stroke rate at days 2, 7, 30, 90, and 365 were 1.5%, 2.1%, 2.8%, 3.7%, and 5.1%, respectively. In multivariable analyses, multiple infarctions on brain imaging, large-artery atherosclerosis, and an ABCD2 score of 6 or 7 were each associated with more than a doubling of the risk of stroke. CONCLUSIONS We observed a lower risk of cardiovascular events after TIA than previously reported. The ABCD2 score, findings on brain imaging, and status with respect to large-artery atherosclerosis helped stratify the risk of recurrent stroke within 1 year after a TIA or minor stroke. (Funded by Sanofi and Bristol-Myers Squibb.)Supported by an unrestricted grant from Sanofi and Bristol-Myers Squibb

A Novel fMRI Paradigm Suggests that Pedaling-related Brain Activation is Altered after Stroke

The purpose of this study was to examine the feasibility of using functional magnetic resonance imaging (fMRI) to measure pedaling-related brain activation in individuals with stroke and age-matched controls. We also sought to identify stroke-related changes in brain activation associated with pedaling. Fourteen stroke and 12 control subjects were asked to pedal a custom, MRI-compatible device during fMRI. Subjects also performed lower limb tapping to localize brain regions involved in lower limb movement. All stroke and control subjects were able to pedal while positioned for fMRI. Two control subjects were withdrawn due to claustrophobia, and one control data set was excluded from analysis due to an incidental finding. In the stroke group, one subject was unable to enter the gantry due to excess adiposity, and one stroke data set was excluded from analysis due to excessive head motion. Consequently, 81% of subjects (12/14 stroke, 9/12 control) completed all procedures and provided valid pedaling-related fMRI data. In these subjects, head motion was ≤3 mm. In both groups, brain activation localized to the medial aspect of M1, S1, and Brodmann’s area 6 (BA6) and to the cerebellum (vermis, lobules IV, V, VIII). The location of brain activation was consistent with leg areas. Pedaling-related brain activation was apparent on both sides of the brain, with values for laterality index (LI) of –0.06 (0.20) in the stroke cortex, 0.05 (±0.06) in the control cortex, 0.29 (0.33) in the stroke cerebellum, and 0.04 (0.15) in the control cerebellum. In the stroke group, activation in the cerebellum – but not cortex – was significantly lateralized toward the damaged side of the brain (p = 0.01). The volume of pedaling-related brain activation was smaller in stroke as compared to control subjects. Differences reached statistical significance when all active regions were examined together [p = 0.03; 27,694 (9,608) μL stroke; 37,819 (9,169) μL control]. When individual regions were examined separately, reduced brain activation volume reached statistical significance in BA6 [p = 0.04; 4,350 (2,347) μL stroke; 6,938 (3,134) μL control] and cerebellum [p = 0.001; 4,591 (1,757) μL stroke; 8,381 (2,835) μL control]. Regardless of whether activated regions were examined together or separately, there were no significant between-group differences in brain activation intensity [p = 0.17; 1.30 (0.25)% stroke; 1.16 (0.20)% control]. Reduced volume in the stroke group was not observed during lower limb tapping and could not be fully attributed to differences in head motion or movement rate. There was a tendency for pedaling-related brain activation volume to increase with increasing work performed by the paretic limb during pedaling (p = 0.08, r = 0.525). Hence, the results of this study provide two original and important contributions. First, we demonstrated that pedaling can be used with fMRI to examine brain activation associated with lower limb movement in people with stroke. Unlike previous lower limb movements examined with fMRI, pedaling involves continuous, reciprocal, multijoint movement of both limbs. In this respect, pedaling has many characteristics of functional lower limb movements, such as walking. Thus, the importance of our contribution lies in the establishment of a novel paradigm that can be used to understand how the brain adapts to stroke to produce functional lower limb movements. Second, preliminary observations suggest that brain activation volume is reduced during pedaling post-stroke. Reduced brain activation volume may be due to anatomic, physiology, and/or behavioral differences between groups, but methodological issues cannot be excluded. Importantly, brain action volume post-stroke was both task-dependent and mutable, which suggests that it could be modified through rehabilitation. Future work will explore these possibilities

Reduced brain UCP2 expression mediated by microRNA-503 contributes to increased stroke susceptibility in the high-salt fed stroke-prone spontaneously hypertensive rat

UCP2 maps nearby the lod score peak of STR1-stroke QTL in the SHRSP rat strain. We explored the potential contribution of UCP2 to the high-salt diet (JD)-dependent increased stroke susceptibility of SHRSP. Male SHRSP, SHRSR, two reciprocal SHRSR/SHRSP-STR1/QTL stroke congenic lines received JD for 4 weeks to detect brain UCP2 gene/protein modulation as compared with regular diet (RD). Brains were also analyzed for NF-κB protein expression, oxidative stress level and UCP2-targeted microRNAs expression level. Next, based on knowledge that fenofibrate and Brassica Oleracea (BO) stimulate UCP2 expression through PPARα activation, we monitored stroke occurrence in SHRSP receiving JD plus fenofibrate versus vehicle, JD plus BO juice versus BO juice plus PPARα inhibitor. Brain UCP2 expression was markedly reduced by JD in SHRSP and in the (SHRsr.SHRsp-(D1Rat134-Mt1pa)) congenic line, whereas NF-κB expression and oxidative stress level increased. The opposite phenomenon was observed in the SHRSR and in the (SHRsp.SHRsr-(D1Rat134-Mt1pa)) reciprocal congenic line. Interestingly, the UCP2-targeted rno-microRNA-503 was significantly upregulated in SHRSP and decreased in SHRSR upon JD, with consistent changes in the two reciprocal congenic lines. Both fenofibrate and BO significantly decreased brain microRNA-503 level, upregulated UCP2 expression and protected SHRSP from stroke occurrence. In vitro overexpression of microRNA-503 in endothelial cells suppressed UCP2 expression and led to a significant increase of cell mortality with decreased cell viability. Brain UCP2 downregulation is a determinant of increased stroke predisposition in high-salt-fed SHRSP. In this context, UCP2 can be modulated by both pharmacological and nutraceutical agents. The microRNA-503 significantly contributes to mediate brain UCP2 downregulation in JD-fed SHRSP

Functional connectivity in relation to motor performance and recovery after stroke.

Plasticity after stroke has traditionally been studied by observing changes only in the spatial distribution and laterality of focal brain activation during affected limb movement. However, neural reorganization is multifaceted and our understanding may be enhanced by examining dynamics of activity within large-scale networks involved in sensorimotor control of the limbs. Here, we review functional connectivity as a promising means of assessing the consequences of a stroke lesion on the transfer of activity within large-scale neural networks. We first provide a brief overview of techniques used to assess functional connectivity in subjects with stroke. Next, we review task-related and resting-state functional connectivity studies that demonstrate a lesion-induced disruption of neural networks, the relationship of the extent of this disruption with motor performance, and the potential for network reorganization in the presence of a stroke lesion. We conclude with suggestions for future research and theories that may enhance the interpretation of changing functional connectivity. Overall findings suggest that a network level assessment provides a useful framework to examine brain reorganization and to potentially better predict behavioral outcomes following stroke

Visual feedback alters force control and functional activity in the visuomotor network after stroke.

Modulating visual feedback may be a viable option to improve motor function after stroke, but the neurophysiological basis for this improvement is not clear. Visual gain can be manipulated by increasing or decreasing the spatial amplitude of an error signal. Here, we combined a unilateral visually guided grip force task with functional MRI to understand how changes in the gain of visual feedback alter brain activity in the chronic phase after stroke. Analyses focused on brain activation when force was produced by the most impaired hand of the stroke group as compared to the non-dominant hand of the control group. Our experiment produced three novel results. First, gain-related improvements in force control were associated with an increase in activity in many regions within the visuomotor network in both the stroke and control groups. These regions include the extrastriate visual cortex, inferior parietal lobule, ventral premotor cortex, cerebellum, and supplementary motor area. Second, the stroke group showed gain-related increases in activity in additional regions of lobules VI and VIIb of the ipsilateral cerebellum. Third, relative to the control group, the stroke group showed increased activity in the ipsilateral primary motor cortex, and activity in this region did not vary as a function of visual feedback gain. The visuomotor network, cerebellum, and ipsilateral primary motor cortex have each been targeted in rehabilitation interventions after stroke. Our observations provide new insight into the role these regions play in processing visual gain during a precisely controlled visuomotor task in the chronic phase after stroke