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Mapping causal circuit dynamics in stroke using simultaneous electroencephalography and transcranial magnetic
Camarin E Rolle1,2,3, Fiona M Baumer2,4, Joshua T Jordan5
1Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Road, MC: 5797, Stanford, CA, 94305-5797, USA.
BMC Neurology
|July 17, 2021
Summary
Transcranial Magnetic Stimulation-Electroencephalography (TMS-EEG) reveals altered brain connectivity after stroke. Increased connectivity in the healthy hemisphere during movement correlated with better arm function in stroke survivors.
Area of Science:
- Neuroscience
- Motor Control
- Brain Connectivity
Background:
- Stroke-induced motor impairment stems from tissue damage and disrupted motor network connectivity.
- Existing Transcranial Magnetic Stimulation (TMS) studies show mixed results for motor recovery, necessitating a deeper understanding of post-stroke connectivity and TMS effects.
- This study investigates causal information flow in motor networks using TMS-EEG to characterize stroke-induced alterations.
Purpose of the Study:
- To map causal information flow in the motor network of healthy adults using TMS-EEG.
- To define how stroke alters these motor circuits.
- To assess the impact of motor tasks on brain connectivity in stroke patients and controls.
Main Methods:
- TMS was applied to bilateral primary motor cortices in 14 stroke patients and 12 controls during hand movement versus rest.
- Electroencephalography (EEG) measured the cortical response to TMS pulses.
- TMS-EEG derived connectivity measurements (ΔC) were calculated for each hemisphere and compared between groups and across TMS sites, with correlations to arm function in stroke patients.
Main Results:
- In controls, right hand movement enhanced left hemisphere connectivity more than right.
- Hand movement did not significantly alter connectivity in either hemisphere for stroke patients.
- Greater increases in healthy hemisphere connectivity during paretic hand movement correlated with better arm function in stroke survivors.
Conclusions:
- TMS-EEG is sensitive to movement-induced changes in brain connectivity.
- These connectivity measures may characterize clinically relevant circuit dynamics post-stroke.
- This approach could identify specific targets for TMS-based post-stroke rehabilitation trials.
