Abstract
Resting‐state studies conducted with stroke patients are scarce. First objective was to explore whether patients with good cognitive recovery showed differences in resting‐state functional patterns of brain activity when compared to patients with poor cognitive recovery. Second objective was to determine whether such patterns were correlated with cognitive performance. Third objective was to assess the existence of prognostic factors for cognitive recovery. Eighteen right‐handed stroke patients and eighteen healthy controls were included in the study. Stroke patients were divided into two groups according to their cognitive improvement observed at three months after stroke. Probabilistic independent component analysis was used to identify resting‐state brain activity patterns. The analysis identified six networks: frontal, fronto‐temporal, default mode network, secondary visual, parietal, and basal ganglia. Stroke patients showed significant decrease in brain activity in parietal and basal ganglia networks and a widespread increase in brain activity in the remaining ones when compared with healthy controls. When analyzed separately, patients with poor cognitive recovery (n = 10) showed the same pattern as the whole stroke patient group, while patients with good cognitive recovery (n = 8) showed increased activity only in the default mode network and fronto‐temporal network, and decreased activity in the basal ganglia. We observe negative correlations between basal ganglia network activity and performance in Semantic Fluency test and Part A of the Trail Making Test for patients with poor cognitive recovery. A reverse pattern was observed between frontal network activity and the abovementioned tests for the same group. Hum Brain Mapp 35:3819–3831, 2014. © 2014 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.
Highlights
Acute ischemic stroke is the second most common cause of death worldwide and a major cause of disability in the elder population [Gorelick et al, 2011]
The study reported in this paper investigates the resting-state functional connectivity patterns of the whole brain on functional MRI captured three months after a focal stroke event, using the probabilistic independent component analysis approach [Beckmann et al, 2005]. pICA does not need a priori definition of a seed region, allowing unbiased exploration of the association between the resting state networks (RSNs) and patient’s cognitive improvement
Comparing the two groups of cognitive recovery, no statistical difference was found in lesion volume (Z 5 20.446; P 5 0.656), affected hemisphere or stroke severity at baseline measured by the National Institute of Health Stroke Scale (NIHSS) scale (good cognitive recovery: 9.50 6 6.437; poor cognitive recovery: 10.70 6 7.027; t 5 20.7373 (16), P 5 0.714]
Summary
Acute ischemic stroke is the second most common cause of death worldwide and a major cause of disability in the elder population [Gorelick et al, 2011]. Resting-state functional magnetic resonance imaging (rs-fMRI) demonstrates task unrelated brain networks, such as the default mode network (DMN), and networks of functionally related areas, such as the motor, visual, auditory, and attentional networks [Biswal et al, 2010, Buckner et al, 2009]. These resting state networks (RSNs) have shown a high reproducibility across subjects, time and research sites [Damoiseaux et al, 2006], and have been proved as surrogate biomarkers of neurological diseases (including schizophrenia, autism and Alzheimer’s disease)
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