Real-Time Modulation of Prefrontal Activity via Automated EEG-tDCS Closed-Loop Interventions: A Feasibility Study ^†

This research presents the development and feasibility testing of a novel closed-loop neuromodulation system targeting the prefrontal cortex based on real-time EEG analysis. Performance in executive-demanding tasks, such as mental arithmetic and emotion regulation, is monitored via electroencephalography (EEG), while transcranial direct current stimulation (tDCS) parameters are dynamically adapted based on the participant’s neural responses. To overcome the accessibility barriers posed by proprietary software development kits, we implemented a custom Robotic Process Automation (RPA) framework in Python 3.10 and Computer Vision to autonomously control the Neuroelectrics Starstim 32 hardware. The system isolates alpha (8–13 Hz) frequency band, extracted primarily from prefrontal channels (e.g., F3, F4, Fp1, Fp2), to establish individualized stimulation thresholds. Results from a pilot session confirm the system’s ability to maintain stable real-time acquisition and automate stimulation triggers without manual intervention. This architecture demonstrates a cost-effective and reliable approach for state-dependent interventions, providing a personalized framework for enhancing cognitive control and supporting clinical neuromodulation.