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Synchronization lag in post stroke: relation to motor function and structural connectivity.

ABSTRACT: Stroke is characterized by delays in the resting-state hemodynamic response, resulting in synchronization lag in neural activity between brain regions. However, the structural basis of this lag remains unclear. In this study, we used resting-state functional MRI (rs-fMRI) to characterize synchronization lag profiles between homotopic regions in 15 individuals (14 males, 1 female) with brain lesions consequent to stroke as well as a group of healthy comparison individuals. We tested whether the network communication efficiency of each individual's structural brain network (connectome) could explain interindividual and interregional variation in synchronization lag profiles. To this end, connectomes were mapped using diffusion MRI data, and communication measures were evaluated under two schemes: shortest paths and navigation. We found that interindividual variation in synchronization lags was inversely associated with communication efficiency under both schemes. Interregional variation in lag was related to navigation efficiency and navigation distance, reflecting its dependence on both distance and structural constraints. Moreover, severity of motor deficits significantly correlated with average synchronization lag in stroke. Our results provide a structural basis for the delay of information transfer between homotopic regions inferred from rs-fMRI and provide insight into the clinical significance of structural-functional relationships in stroke individuals.

SUBMITTER: Wang X

PROVIDER: S-EPMC6777982 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Synchronization lag in post stroke: relation to motor function and structural connectivity.

Wang Xin X Seguin Caio C Zalesky Andrew A Wong Wan-Wa WW Chu Winnie Chiu-Wing WC Tong Raymond Kai-Yu RK

Network neuroscience (Cambridge, Mass.) 20190901 4

Stroke is characterized by delays in the resting-state hemodynamic response, resulting in synchronization lag in neural activity between brain regions. However, the structural basis of this lag remains unclear. In this study, we used resting-state functional MRI (rs-fMRI) to characterize synchronization lag profiles between homotopic regions in 15 individuals (14 males, 1 female) with brain lesions consequent to stroke as well as a group of healthy comparison individuals. We tested whether the n ...[more]

PMID: 31637341

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Project description:Clinical research based on neuroimaging data has benefited from machine learning methods, which have the ability to provide individualized predictions and to account for the interaction among units of information in the brain. Application of machine learning in structural imaging to investigate diseases that involve brain injury presents an additional challenge, especially in conditions like stroke, due to the high variability across patients regarding characteristics of the lesions. Extracting data from anatomical images in a way that translates brain damage information into features to be used as input to learning algorithms is still an open question. One of the most common approaches to capture regional information from brain injury is to obtain the lesion load per region (i.e. the proportion of voxels in anatomical structures that are considered to be damaged). However, no systematic evaluation has yet been performed to compare this approach with using patterns of voxels (i.e. considering each voxel as a single feature). In this paper we compared both approaches applying Gaussian Process Regression to decode motor scores in 50 chronic stroke patients based solely on data derived from structural MRI. For both approaches we compared different ways to delimit anatomical areas: regions of interest from an anatomical atlas, the corticospinal tract, a mask obtained from fMRI analysis with a motor task in healthy controls and regions selected using lesion-symptom mapping. Our analysis showed that extracting features through patterns of voxels that represent lesion probability produced better results than quantifying the lesion load per region. In particular, from the different ways to delimit anatomical areas compared, the best performance was obtained with a combination of a range of cortical and subcortical motor areas as well as the corticospinal tract. These results will inform the appropriate methodology for predicting long term motor outcomes from early post-stroke structural brain imaging.

Project description:The robust, reciprocal anatomical connections between the cerebellum and contralateral sensorimotor cerebral hemisphere underscores the strong physiological interdependence between these two regions in relation to human behavior. Previous studies have shown that damage to sensorimotor cortex can result in a lasting reduction of cerebellar metabolism, the magnitude of which has been linked to poor rehabilitative outcomes. A better understanding of movement-related cerebellar physiology as well as cortico-cerebellar coherence (CCC) in the chronic, post-stroke state may be key to developing novel neuromodulatory techniques that promote upper limb motor rehabilitation. As a part of the first in-human phase-I trial investigating the effects of deep brain stimulation of the cerebellar dentate nucleus (DN) on chronic, post-stroke motor rehabilitation, we collected invasive recordings from DN and scalp EEG in subjects (both sexes) with middle cerebral artery stroke during a visuo-motor tracking task. We investigated the excitability of ipsilesional cortex, DN and the their interaction as a function of motor impairment and performance. Our results indicate that 1) event-related oscillations in the ipsilesional cortex and DN were significantly correlated at movement onset in the low-β band, with moderately and severely impaired subjects showing desynchronization and synchronization, respectively. 2) Significant CCC was observed during isometric 'hold' period in the low-β band, which was critical for maintaining task accuracy. Our findings support a strong coupling between ipsilesional cortex and DN in the low-β band during motor control across all impairment levels which encourages the exploitation of the cerebello-thalamo-cortical pathway as a neuromodulation target to promote rehabilitation.Significance Statement:Cerebral infarct due to stroke can lead to lasting reduction in cerebellar metabolism resulting in poor rehabilitative outcomes. Thorough investigation of the cerebellar electrophysiology as well as cortico-cerebellar connectivity in humans that could provide key insights to facilitate development of novel neuromodulatory technologies, has been lacking. As a part of the first in-human phase-I trial investigating deep brain stimulation of the cerebellar dentate nucleus (DN) for chronic, post-stroke motor rehabilitation, we collected invasive recordings from DN and scalp EEG while stroke patients performed a motor task. Our data indicate strong coupling between ipsilesional sensorimotor cortex and DN in the low-β band across all impairment levels encouraging the exploration of electrical stimulation of the DN.

Project description:BackgroundMotor and cognitive impairments are frequently observed following stroke, but are often managed as distinct entities, and there is little evidence regarding how they are related. The aim of this study was to describe the prevalence of concurrent motor and cognitive impairments 3 months after stroke and to examine how motor performance was associated with memory, executive function and global cognition.MethodsThe Norwegian Cognitive Impairment After Stroke (Nor-COAST) study is a prospective multicentre cohort study including patients hospitalized with acute stroke between May 2015 and March 2017. The National Institutes of Health Stroke Scale (NIHSS) was used to measure stroke severity at admission. Level of disability was assessed by the Modified Rankin Scale (mRS). Motor and cognitive functions were assessed 3 months post-stroke using the Montreal Cognitive Assessment (MoCA), Trail Making Test Part B (TMT-B), 10-Word List Recall (10WLR), Short Physical Performance Battery (SPPB), dual-task cost (DTC) and grip strength (Jamar®). Cut-offs were set according to current recommendations. Associations were examined using linear regression with cognitive tests as dependent variables and motor domains as covariates, adjusted for age, sex, education and stroke severity.ResultsOf 567 participants included, 242 (43%) were women, mean (SD) age was 72.2 (11.7) years, 416 (75%) had an NIHSS score???4 and 475 (84%) had an mRS score of ?2. Prevalence of concurrent motor and cognitive impairment ranged from 9.5% for DTC and 10WLR to 22.9% for grip strength and TMT-B. SPPB was associated with MoCA (regression coefficient B?=?0.465, 95%CI [0.352, 0.578]), TMT-B (B?=?-9.494, 95%CI [-?11.726, -?7.925]) and 10WLR (B?=?0.132, 95%CI [0.054, 0.211]). Grip strength was associated with MoCA (B?=?0.075, 95%CI [0.039, 0.112]), TMT-B (B?=?-1.972, 95%CI [-?2.672, -?1.272]) and 10WLR (B?=?0.041, 95%CI [0.016, 0.066]). Higher DTC was associated with more time needed to complete TMT-B (B?=?0.475, 95%CI [0.075, 0.875]) but not with MoCA or 10WLR.ConclusionThree months after suffering mainly minor strokes, 30-40% of participants had motor or cognitive impairments, while 20% had concurrent impairments. Motor performance was associated with memory, executive function and global cognition. The identification of concurrent impairments could be relevant for preventing functional decline.Trial registrationClinicalTrials.gov Identifier: NCT02650531 .

Dataset Information

Synchronization lag in post stroke: relation to motor function and structural connectivity.

Publications

Synchronization lag in post stroke: relation to motor function and structural connectivity.

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