Abstract
Stroke is one of the leading causes of death and disability. Despite the high prevalence of stroke, characterizing the acute neural recovery patterns that follow stroke and predicting long-term recovery remains challenging. Objective methods to quantify and characterize neural injury are still lacking. Since neuroimaging methods have a poor temporal resolution, EEG has been used as a method for characterizing post-stroke recovery mechanisms for various deficits including motor, language, and cognition as well as predicting treatment response to experimental therapies. In addition, transcranial magnetic stimulation (TMS), a form of non-invasive brain stimulation, has been used in conjunction with EEG (TMS-EEG) to evaluate neurophysiology for a variety of indications. TMS-EEG has significant potential for exploring brain connectivity using focal TMS-evoked potentials and oscillations, which may allow for the system-specific delineation of recovery patterns after stroke. In this review, we summarize the use of EEG alone or in combination with TMS in post-stroke motor, language, cognition, and functional/global recovery. Overall, stroke leads to a reduction in higher frequency activity (≥8 Hz) and intra-hemispheric connectivity in the lesioned hemisphere, which creates an activity imbalance between non-lesioned and lesioned hemispheres. Compensatory activity in the non-lesioned hemisphere leads mostly to unfavorable outcomes and further aggravated interhemispheric imbalance. Balanced interhemispheric activity with increased intrahemispheric coherence in the lesioned networks correlates with improved post-stroke recovery. TMS-EEG studies reveal the clinical importance of cortical reactivity and functional connectivity within the sensorimotor cortex for motor recovery after stroke. Although post-stroke motor studies support the prognostic value of TMS-EEG, more studies are needed to determine its utility as a biomarker for recovery across domains including language, cognition, and hemispatial neglect. As a complement to MRI-based technologies, EEG-based technologies are accessible and valuable non-invasive clinical tools in stroke neurology.
Highlights
Stroke is a leading cause of functionally limiting neurological impairment and mortality in the United States, and many stroke survivors suffer from impairments of varying degrees and durations [1, 2]
Predicting post-stroke recovery at an individual level is crucial in determining the treatment needs of patients, both to improve the functional outcome for the patients and properly allocate increasingly scarce healthcare resources [6]
We review EEG studies in various behavioral systems such as motor, language, cognition, and functional/global systems since the post-stroke recovery patterns might differ by system
Summary
Stroke is a leading cause of functionally limiting neurological impairment and mortality in the United States, and many stroke survivors suffer from impairments of varying degrees and durations [1, 2]. Electroencephalography (EEG) is a non-invasive technique that measures cortical brain activity with a high degree of temporal resolution [7]. Transcranial magnetic stimulation (TMS) is a non-invasive stimulation method whereby brief magnetic pulses generate focal electrical currents in the cortex These electrical currents induce evoked potentials in focal brain areas. The most common technique in stroke EEG studies is the power spectral analysis technique that quantifies coherence between spatially remote regions in different frequency band powers (often defined as delta 0.5–4 Hz, theta 4– 8 Hz, alpha 8–13 Hz, beta 13–30 Hz, gamma >30 Hz). As complementary techniques to linear connectivity analyses, nonlinear and information-based are alternative methods [21] These techniques were not commonly used in stroke EEG studies. FMA is a comprehensive, stroke-specific assessment that quantifies and characterizes sensorimotor impairment in the affected
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