Modulation of task-related cortical connectivity in the acute and subacute phase after stroke

Task-residual effective connectivity of motor network in transient ischemic attack

Transient ischemic attack (TIA) is a temporary episode of neurological dysfunction that results from focal brain ischemia. Although TIA symptoms are quickly resolved, patients with TIA have a high risk of stroke and persistent impairments in multiple domains of cognitive and motor functions. In this study, using spectral dynamic causal modeling, we investigate the changes in task-residual effective connectivity of patients with TIA during fist-closing movements. 28 healthy participants and 15 age-matched patients with TIA undergo functional magnetic resonance imaging at 7T. Here we show that during visually cued motor movement, patients with TIA have significantly higher effective connectivity toward the ipsilateral primary motor cortex and lower connectivity to the supplementary motor area than healthy controls. Our results imply that TIA patients have aberrant connections among motor regions, and these changes may reflect the decreased efficiency of primary motor function and disrupted control of voluntary movement in patients with TIA.

Cortical connectivity in stroke using signals from resting-state EEG: a review of current literature

INTRODUCTION

Stroke is considered a substantial cause of disability worldwide and many researches are focused on rehabilitative interventions. Functional magnetic resonance imaging studies centered on brain networks after stroke describe affected functional connectivity between areas within the default mode, sensorimotor, visual, fronto-parietal and executive networks. Recent studies renewed the perspective of utilizing electroencephalography to describe markers of cortical activity in stroke and recovery neurophysiological processes.

METHODS

We included in our research studies realized on patients that had an ischemic or hemorrhagic stroke that performed electroencephalography and had an analysis of connectivity indices. Resting-state electroencephalography has the advantage of including patients with any neurological deficit and it is easier to perform than the task-based variant. The changes in resting-state EEG networks after stroke are important to determine a relationship between frequency cortical activity and spatial conformation of a network. From conventional to quantitative EEG analysis in stroke, these techniques are improved with additional brain connectivity tools that lead to a better characterization between injured areas and other intra- and inter-hemispheric areas.

RESULTS

There are studies that underline the disruptions in local networks in a frequency-dependent modality after stroke, while other results are focused on bilateral changes in resting-state cortical networks, independent of the side of the lesions.

CONCLUSIONS

Many studies found alterations in various connectivity measures after stroke with the help of EEG, but the clinical significance of these findings is a field of increasing interest in research area.

Multi-Granularity Analysis of Brain Networks Assembled With Intra-Frequency and Cross-Frequency Phase Coupling for Human EEG After Stroke

Evaluating the impact of stroke on the human brain based on electroencephalogram (EEG) remains a challenging problem. Previous studies are mainly analyzed within frequency bands. This article proposes a multi-granularity analysis framework, which uses multiple brain networks assembled with intra-frequency and cross-frequency phase-phase coupling to evaluate the stroke impact in temporal and spatial granularity. Through our experiments on the EEG data of 11 patients with left ischemic stroke and 11 healthy controls during the mental rotation task, we find that the brain information interaction is highly affected after stroke, especially in delta-related cross-frequency bands, such as delta-alpha, delta-low beta, and delta-high beta. Besides, the average phase synchronization index (PSI) of the right hemisphere between patients with stroke and controls has a significant difference, especially in delta-alpha (p = 0.0186 in the left-hand mental rotation task, p = 0.0166 in the right-hand mental rotation task), which shows that the non-lesion hemisphere of patients with stroke is also affected while it cannot be observed in intra-frequency bands. The graph theory analysis of the entire task stage reveals that the brain network of patients with stroke has a longer feature path length and smaller clustering coefficient. Besides, in the graph theory analysis of three sub-stags, the more stable significant difference between the two groups is emerging in the mental rotation sub-stage (500–800 ms). These findings demonstrate that the coupling between different frequency bands brings a new perspective to understanding the brain's cognitive process after stroke.

Cortical signatures of precision grip force control in children, adolescents, and adults

Human dexterous motor control improves from childhood to adulthood, but little is known about the changes in cortico-cortical communication that support such ontogenetic refinement of motor skills. To investigate age-related differences in connectivity between cortical regions involved in dexterous control, we analyzed electroencephalographic data from 88 individuals (range 8-30 years) performing a visually guided precision grip task using dynamic causal modelling and parametric empirical Bayes. Our results demonstrate that bidirectional coupling in a canonical 'grasping network' is associated with precision grip performance across age groups. We further demonstrate greater backward coupling from higher-order to lower-order sensorimotor regions from late adolescence in addition to differential associations between connectivity strength in a premotor-prefrontal network and motor performance for different age groups. We interpret these findings as reflecting greater use of top-down and executive control processes with development. These results expand our understanding of the cortical mechanisms that support dexterous abilities through development.

The Relationship between Oscillations in Brain Regions and Functional Connectivity: A Critical Analysis with the Aid of Neural Mass Models

Propagation of brain rhythms among cortical regions is a relevant aspect of cognitive neuroscience, which is often investigated using functional connectivity (FC) estimation techniques. The aim of this work is to assess the relationship between rhythm propagation, FC and brain functioning using data generated from neural mass models of connected Regions of Interest (ROIs). We simulated networks of four interconnected ROIs, each with a different intrinsic rhythm (in θ, α, β and γ ranges). Connectivity was estimated using eight estimators and the relationship between structural connectivity and FC was assessed as a function of the connectivity strength and of the inputs to the ROIs. Results show that the Granger estimation provides the best accuracy, with a good capacity to evaluate the connectivity strength. However, the estimated values strongly depend on the input to the ROIs and hence on nonlinear phenomena. When a population works in the linear region, its capacity to transmit a rhythm increases drastically. Conversely, when it saturates, oscillatory activity becomes strongly affected by rhythms incoming from other regions. Changes in functional connectivity do not always reflect a physical change in the synapses. A unique connectivity network can propagate rhythms in very different ways depending on the specific working conditions.

Intervention-induced changes in neural connectivity during motor preparation may affect cortical activity at motor execution

Effective interventions have demonstrated the ability to improve motor function by reengaging ipsilesional resources, which appears to be critical and feasible for hand function recovery even in individuals with severe chronic stroke. However, previous studies focus on changes in brain activity related to motor execution. How changes in motor preparation may facilitate these changes at motor execution is still unclear. To address this question, 8 individuals with severe chronic hemiparetic stroke participated in a device-assisted intervention for seven weeks. We then quantified changes in both coupling between regions during motor preparation and changes in topographical cortical activity at motor execution for both hand opening in isolation and together with the shoulder using high-density EEG. We hypothesized that intervention-induced changes in cortico-cortico interactions during motor preparation would lead to changes in activity at motor execution specifically towards an increased reliance on the ipsilesional hemisphere. In agreement with this hypothesis, we found that, following the intervention, individuals displayed a reduction in coupling from ipsilesional M1 to contralesional M1 within gamma frequencies during motor preparation for hand opening. This was followed by a reduction in activity in the contralesional primary sensorimotor cortex during motor execution. Similarly, during lifting and opening, a shift to negative coupling within ipsilesional M1 from gamma to beta frequencies was accompanied by an increase in ipsilesional primary sensorimotor cortex activity following the intervention. Together, these results show that intervention-induced changes in coupling within or between motor regions during motor preparation may affect cortical activity at execution.

Acute Subcortical Infarcts Cause Secondary Degeneration in the Remote Non-involved Cortex and Connecting Fiber Tracts

Background and Purpose: Remote white matter and cortex reorganization may contribute to functional reorganization and clinical outcome after acute infarcts. To determine the microstructural changes in the remote intact corticospinal tract (CST) and precentral gyrus cortex connected to the acute infarct after subcortical stroke involving the CST over 6 months. Methods: Twenty-two patients with subcortical stroke involving the CST underwent magnetic resonance imaging (MRI) and clinical assessment in the acute phase (baseline) and 6 months (follow-up) after the stroke. The MRI sequences included T1-weighted imaging, T2-weighted imaging, fluid-attenuated inversion recovery, diffusion tensor imaging (DTI), and diffusion kurtosis imaging. Fractional anisotropy (FA) and track-density imaging (TDI) values were generated using DTI data for the centrum semiovale, corona radiata, posterior limb of internal capsule, and cerebral peduncle. The mean kurtosis (MK) value of the precentral gyrus cortex was calculated. Changes in the FA, TDI, and MK values between the baseline and follow-up and the relationship between these changes were analyzed. Results: The TDI and FA values of all parts of the ipsilesional (IL) CST, including the noninvolved upper and lower parts, decreased at the 6-month follow-up (P < 0.001). The MK values of the stroke lesion (P < 0.001) and IL precentral gyrus cortex (P = 0.002) were lower at follow-up than at the baseline. The ΔTDI (r = 0.689, P < 0.001) and Δ FA values (r = 0.463, P = 0.03) of the noninvolved upper part of the IL CST were positively correlated with the ΔMK value of the IL precentral gyrus cortex. Conclusion: Secondary degeneration occurred in the remote part of the CST and the remote IL precentral gyrus cortex after subcortical stroke involving the CST. The secondary degeneration in the upper part of the CST was correlated with that in the IL precentral gyrus cortex.

A systematic review investigating the relationship of electroencephalography and magnetoencephalography measurements with sensorimotor upper limb impairments after stroke

BACKGROUND

Predicting sensorimotor upper limb outcome receives continued attention in stroke. Neurophysiological measures by electroencephalography (EEG) and magnetoencephalography (MEG) could increase the accuracy of predicting sensorimotor upper limb recovery.

NEW METHOD

The aim of this systematic review was to summarize the current evidence for EEG/MEG-based measures to index neural activity after stroke and the relationship between abnormal neural activity and sensorimotor upper limb impairment. Relevant papers from databases EMBASE, CINHAL, MEDLINE and pubMED were identified. Methodological quality of selected studies was assessed with the Modified Downs and Black form. Data collected was reported descriptively.

RESULTS

Seventeen papers were included; 13 used EEG and 4 used MEG applications. Findings showed that: (a) the presence of somatosensory evoked potentials in the acute stage are related to better outcome of upper limb motor impairment from 10 weeks to 6 months post-stroke; (b) an interhemispheric imbalance of cortical oscillatory signals associated with upper limb impairment; and (c) predictive models including beta oscillatory cortical signal factors with corticospinal integrity and clinical measures could enhance upper limb motor prognosis.

COMPARING WITH EXISTING METHOD

The combination of neurological biomarkers with clinical measures results in higher statistical power than using neurological biomarkers alone when predicting motor recovery in stroke.

CONCLUSIONS

Alterations in neural activity by means of EEG and MEG are demonstrated from the early post-stroke stage onwards, and related to sensorimotor upper limb impairment. Future work exploring cortical oscillatory signals in the acute stage could provide further insight about prediction of upper limb sensorimotor recovery.