EEG provides insights into motor control and neuroplasticity during stroke recovery

"V体育官网" Introduction

Stroke is a major cause of long-term disability. Motor deficits are persistent in 50–75% of cases and are a major contributor to post-stroke impairment and disability. 1 Acute reperfusion therapies can improve functional outcomes with ischemic stroke, but only 20% of patients in the US get treated,2 and many nevertheless have long-term disability. As a result, increasing attention is being devoted to therapies that promote neural repair, particularly those initiated during the early days-weeks post-stroke given their potential for greater effect in this period. 3 These points underscore the need for an improved understanding of brain plasticity during subacute stroke, as well as the pressing need for validated biomarkers that capture brain activity in a manner that can stratify patients and inform clinical decision-making V体育平台登录. The current review considers this with a focus on EEG applications during motor recovery post-stroke. EEG is attractive because it can be acquired at the bedside in complex medical settings, safely, with low cost and excellent temporal resolution. Together, these qualities suggest that EEG is a promising tool for understanding and treating patients with stroke.

The metrics provided by EEG reflect the temporal and spatial summation of excitatory and inhibitory post-synaptic dendritic potentials of pyramidal neurons belonging mainly to layers III and V of the cortex. EEG signals therefore have amplitude and frequency characteristics that vary over time. Recording from the scalp places limits on the spatial resolution with which signals can be localized neuroanatomically, which can be partially offset using source analysis. EEG can be recorded at rest, though this does not capture events underlying movement generation, or it can be recorded during motor task performance, which provides insight into movement planning and execution and so is the current focus. Task-related EEG measures the activity within and between cortical areas related to motor control VSports注册入口. Longitudinal recordings capture the neural plasticity underlying stroke recovery and have the potential to inform the timing, dose, and duration of rehabilitation/recovery therapies in individual patients.

Event-Related Desynchronization and Synchronization

Event-related desynchronization and synchronization are measures derived from EEG recordings that are used to study cortical activity and inhibition, respectively.

At rest, neurons within a cortical area show substantial synchronous activity. During unilateral voluntary movements, neurons involved in the task become desynchronized, decreasing EEG power, predominantly in sensorimotor cortex contralateral to movement. This reduction in task-related spectral power (TR-pow) reflects cortical activation,4,5 a phenomenon known as event-related desynchronization (ERD). ERD begins 1–2 seconds before the onset of, and persists during, a spontaneous voluntary movement6, and is mainly in the beta frequency band (≈13–30Hz), suggesting that the cortical activity changes in this frequency band reflect cortical activation and corticospinal excitability changes involved in the initiation and execution of voluntary movements. 5,7 As cortical activity is calculated in slightly different ways in the literature (TR-pow or ERD), we will refer to these two metrics as cortical activity VSports在线直播.

The return of cortical activity to a resting state can also be measured. Also predominantly in the beta frequency band, EEG power increases (compared with baseline) at the end of a movement, predominantly in the sensorimotor areas contralateral to movement. 6 This phenomenon, known as event-related synchronization (ERS), corresponds to a return to the basal state, reflecting deactivation and active inhibition. 6,8 ERD and ERS manifest in different frequency bands in different contexts, providing additional insights: in the theta frequency band (4–8Hz), with high cognitive involvement; in the alpha frequency band (8–12Hz), with high attention involvement;9 and in the gamma frequency band (30–90Hz), with intense motor contraction. 10 Use of brain cognitive resources varies with choice of motor task,11 and so calculation of ERD and ERS in multiple frequency bands provides a measure of cognitive network engagement in controlling motor strategy. These measures enable a robust understanding of brain function after stroke and its change over time related to neuroplasticity V体育2025版.

"V体育安卓版" Functional connectivity

Measuring activity in different cortical areas during movement can be used to study their functional interactions, beyond their anatomical links.²³ Towards this, functional connectivity between two cortical areas can be measured using EEG coherence, which estimates the consistency of amplitude and phase between any signal pair in a particular frequency band.²⁴

The first EEG connectivity studies observed that, during voluntary muscle contraction, functional connectivity increased between premotor cortex (PMC), primary motor cortex (M1) and supplementary motor areas (SMA) contralateral to movement, in the alpha and beta frequency bands.^23,25 That this was seen during movement preparation and execution^23,25 echoes anatomic relationships between these cortical areas²⁶. Other studies specifically examined causal relationships within a predefined functional network using effective connectivity to model influences of one region on another;²⁷ this approach is promising but has received less attention. The high temporal resolution of EEG allows examination of cortical network interactions preceding and during movement using event-related coherence,²⁸ which provides information that may be useful to target when as well as where brain function may be therapeutically modulated, such as by non-invasive brain stimulation.

Limits and perspectives

Strengths include that ipsilesional ERD studies are numerous and convergent. Contralesional hemisphere activity changes¹⁵ and ipsilesional control of the non-paretic hand³³ provide insights into motor system function after stroke and warrant additional investigation. Few studies have examined serial EEG in a clinical trial setting, e.g., during telerehabilitation,³⁴ though this approach is promising. Candidate EEG-based biomarkers require further study, e.g., of their psychometric properties and their performance across different patient subgroups. A key limitation is that EEG captures cortical signals and so is less sensitive to subcortical processes.

EEG biomarkers have the potential to guide neurorehabilitation clinical practice/research, much as CT/MRI is used in acute stroke. EEG acquired during performance of a motor task provides detailed insights into function and plasticity of cortical networks; different tasks can be used, depending on a patient’s motor status, including a simple motor task such as gripping or tapping, a complex multi-joint movement with large amplitude such as targeted reaching, or a task with high functional ecology such as bringing a cup to the mouth or driving. Medical therapies are often guided by measuring their effects on the target physiological system, e.g., serum TSH levels are used to guide levothyroxine treatment of hypothyroidism. In this context, several EEG measures hold promise as tools to measure brain function during the early weeks post-stroke when the brain is maximally galvanized for plasticity. The low cost, safety, and ease of use of EEG at the bedside enable frequent recordings, which stand to monitor cortical function and its plasticity in the stroke rehabilitation setting in much the same way that an EKG is used to monitor cardiac function in the ICU.