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Updated: Aug 17, 2025

Combined Transcranial Magnetic Stimulation and Electroencephalography of the Dorsolateral Prefrontal Cortex
Published on: August 17, 2018
Cortical reactivity to transcranial magnetic stimulation predicts risk of post-stroke delirium
Yang Bai1, Paolo Belardinelli2, Catrina Thoennes3
1Department of Neurology & Stroke, University of Tübingen, Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany; School of Basic Medical Sciences, Hangzhou Normal University, Hangzhou, China.
Objective:
Post-stroke delirium (PSD) is a frequent and with regard to outcome unfavorable complication in acute stroke. The neurobiological mechanisms predisposing to PSD remain poorly understood, and biomarkers predicting its risk have not been established. We tested the hypothesis that hypoexcitable or disconnected brain networks predispose to PSD by measuring brain reactivity to transcranial magnetic stimulation with electroencephalography (TMS-EEG).
Methods:
We conducted a cross-sectional study in 33 acute stroke patients within 48 hours of stroke onset. Brain reactivity to single-pulse TMS of dorsolateral prefrontal cortex, primary motor cortex and superior parietal lobule of the right hemisphere was quantified by response intensity, effective connectivity, perturbational complexity index (PCIST), and natural frequency of the TMS-EEG response. PSD development was clinically tracked every 8 hours before and for 7 days following TMS-EEG.
Results:
Fourteen patients developed PSD while 19 patients did not. The PSD group showed lower excitability, effective connectivity, PCIST and natural frequency compared to the non-PSD group. The maximum PCIST over all three TMS sites demonstrated largest classification accuracy with a ROC-AUC of 0.943. This effect was independent of lesion size, affected hemisphere and stroke severity. Maximum PCIST and maximum natural frequency correlated inversely with delirium duration.
Conclusions:
Brain reactivity to TMS-EEG can unravel brain network states of reduced excitability, effective connectivity, perturbational complexity and natural frequency that identify acute stroke patients at high risk for development of delirium.
Significance:
Findings provide novel insight into the pathophysiology of pre-delirium brain states and may promote effective delirium prevention strategies in those patients at high risk.
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