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Updated: May 12, 2025

Combined Transcranial Magnetic Stimulation and Electroencephalography of the Dorsolateral Prefrontal Cortex
Published on: August 17, 2018
TMS-EEG evidence links random exploration to inhibitory mechanisms in the dorsolateral prefrontal cortex
Mojtaba Chizari1, Keivan Navi1, Reza Khosrowabadi2
1Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran.
Abstract:
Adaptive decision-making in uncertain environments requires balancing exploration and exploitation. Computational models distinguish between directed exploration, involving deliberate information-seeking, and random exploration, characterized by stochastic variability. The neural correlates of these strategies have been investigated in previous studies. However, while prior research implicates the dorsolateral prefrontal cortex (DLPFC) in random exploration, its underlying excitatory and inhibitory mechanisms remain unclear. Understanding these processes is essential for explaining how individuals adapt to a dynamic environment. To investigate this, we combined transcranial magnetic stimulation (TMS) with electroencephalography (EEG) to directly assess cortical excitatory and inhibitory functions. Twenty-five healthy participants completed the Horizon Task, a behavioral paradigm designed to dissociate directed and random exploration, and after the task, they received single-pulse TMS over the DLPFC. The TMS-evoked potentials (TEPs) N45, P60, and N100 were examined as neurophysiological markers of GABAA, GABAB, and glutamate activity. Results revealed a significant positive correlation between the N100 amplitude at the right DLPFC and random exploration, suggesting that GABAB-mediated inhibition plays a key role in stochastic decision-making. Additionally, a correlation between the decision noise parameter in the logistic model and the N100 amplitude further validated this association. These findings highlight the importance of prefrontal inhibition in exploratory behavior and underscore the utility of TMS-EEG in uncovering the neural mechanisms underlying adaptive decision-making.
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