Stroke lesions induce not only loss of local neural function, but disruptions in spatially distributed areas. However, it is unknown whether they affect the synchrony of electrical oscillations in neural networks and if changes in network coherence are associated with neurological deficits. This study assessed these questions in a population of patients with subacute, unilateral, ischemic stroke.Spontaneous cortical oscillations were reconstructed from high-resolution electroencephalograms (EEG) with adaptive spatial filters. Maps of functional connectivity (FC) between brain areas were created and correlated with patient performance in motor and cognitive scores.In comparison to age-matched healthy controls, stroke patients showed a selective disruption of FC in the alpha frequency range. The spatial distribution of alpha band FC reflected the pattern of motor and cognitive deficits of the individual patient: network nodes that participate normally in the affected functions showed local decreases in FC with the rest of the brain. Interregional FC in the alpha band, but not in delta, theta, or beta frequencies, was highly correlated with motor and cognitive performance. In contrast, FC between contralesional areas and the rest of the brain was negatively associated with patient performance.Alpha oscillation synchrony at rest is a unique and specific marker of network function and linearly associated with behavioral performance. Maps of alpha synchrony computed from a single restingstate EEG recording provide a robust and convenient window into the functionality and organization of cortical networks with numerous potential applications.

Recent findings have demonstrated that stroke lesions affect neural communication in the entire brain. However, it is less clear whether network interactions are also relevant for plasticity and repair. This study investigated whether the coherence of neural oscillations at language or motor nodes is associated with future clinical improvement. Twenty-four stroke patients underwent high-density EEG recordings and standardized motor and language tests at 2-3 weeks (T0) and 3 months (T1) after stroke onset. In addition, EEG and motor assessments were obtained from a second population of 18 stroke patients. The graph theoretical measure of weighted node degree at language and motor areas was computed as the sum of absolute imaginary coherence with all other brain regions and compared to the amount of clinical improvement from T0 to T1. At T0, beta-band weighted node degree at the ipsilesional motor cortex was linearly correlated with better subsequent motor improvement, while beta-band weighted node degree at Broca's area was correlated with better language improvement. Clinical recovery was further associated with contralesional theta-band weighted node degree. These correlations were each specific to the corresponding brain area and independent of initial clinical severity, age, and lesion size. Findings were reproduced in the second stroke group. Conversely, later coherence increases occurring between T0 and T1 were associated with less clinical improvement. Improvement of language and motor functions after stroke is therefore associated with inter-regional synchronization of neural oscillations in the first weeks after stroke. A better understanding of network mechanisms of plasticity may lead to new prognostic biomarkers and therapeutic targets.See Ward (doi:10.1093/brain/awv265) for a scientific commentary on this article.

Objective. Several training programs have been developed in the past to restore motor functions after stroke. Their efficacy strongly relies on the possibility to assess individual levels of impairment and recovery rate. However, commonly used clinical scales rely mainly on subjective functional assessments and are not able to provide a complete description of patients’ neuro-biomechanical status. Therefore, current clinical tests should be integrated with specific physiological measurements, i.e. kinematic, muscular, and brain activities, to obtain a deep understanding of patients’ condition and of its evolution through time and rehabilitative intervention. Approach. We proposed a multivariate approach for motor control assessment that simultaneously measures kinematic, muscle and brain activity and combines the main physiological variables extracted from these signals using principal component analysis (PCA). We tested it in a group of six sub-acute stroke subjects evaluated extensively before and after a four-week training, using an upper-limb exoskeleton while performing a reaching task, along with brain and muscle measurements. Main results. After training, all subjects exhibited clinical improvements correlating with changes in kinematics, muscle synergies, and spinal maps. Movements were smoother and faster, while muscle synergies increased in numbers and became more similar to those of the healthy controls. These findings were coupled with changes in cortical oscillations depicted by EEG-topographies. When combining these physiological variables using PCA, we found that (i) patients’ kinematic and spinal maps parameters improved continuously during the four assessments; (ii) muscle coordination augmented mainly during treatment, and (iii) brain oscillations recovered mostly pre-treatment as a consequence of short-term subacute changes. Significance. Although these are preliminary results, the proposed approach has the potential of identifying significant biomarkers for patient stratification as well as for the design of more effective rehabilitation protocols.

Functional brain networks are known to be affected by focal brain lesions. However, the clinical relevance of these changes remains unclear. This study assesses resting-state functional connectivity (FC) with electroencephalography (EEG) and relates observed topography of FC to cognitive and motor deficits in patients three months after ischemic stroke. Twenty patients (mean age 61.3 years, range 37–80, 9 females) and nineteen age-matched healthy participants (mean age 66.7 years, range 36–88, 13 females) underwent a ten-minute EEG-resting state examination. The neural oscillations at each grey matter voxel were reconstructed using an adaptive spatial filter and imaginary component of coherence (IC) was calculated as an index of FC. Maps representing mean connectivity value at each voxel were correlated with the clinical data. Compared to healthy controls, alpha band IC of stroke patients was locally reduced in brain regions critical to observed behavioral deficits. A voxel-wise Pearson correlation of clinical performances with FC yielded maps of the neural structures implicated in motor, language, and executive function. This correlation was again specific to alpha band coherence. Ischemic lesions decrease the synchrony of alpha band oscillations between affected brain regions and the rest of the brain. This decrease is linearly related to cognitive and motor deficits observed in the patients.

The study presents evidence for a role of alpha-band coherence in motor learning and may lead to new strategies for rehabilitation.