Sign in
NeurosciencebioRxiv
Preprint

A portable cortical evoked potential operant conditioning system (C-EPOCS): System development

Disha GuptaiD, Jodi A. BrangaccioiD, Helia MojtabaviiD, N. Jeremy HilliD

Abstract

This study presents customizations and evaluations aimed at adapting the Cortical-Evoked Potential Operant Conditioning System (C-EPOCS) into a portable, user-friendly platform for real-time neurofeedback applications. A primary goal was to simplify the component-heavy setup by integrating electroencephalography (EEG) and electromyography (EMG) data acquisition into a single system--while still supporting cortical and muscle response assessment and real-time feedback. One key limitation of portable biosignal acquisition systems is their typically lower sampling rates (e.g., 300-600 Hz) compared to high-resolution systems (e.g., 3200 Hz), which are commonly used for detecting transient responses such as the H-reflex and M-wave. In a C-EPOCS setup, these responses are useful for determining the target stimulation intensity and minimizing inter-session variability in effective afferent excitation. We evaluated whether lower-resolution EMG signals could still support the generation of H-reflex and M-wave recruitment curves for determining target stimulation intensity. Results showed that while EMG sampled at [~]600 Hz and [~]300 Hz produced greater dispersion in recruitment curve data--particularly at 300 Hz--they still yielded comparable estimates for stimulation intensities that elicit Hmax and Mthreshold, the key parameters for C-EPOCS. Additionally, we demonstrate the feasibility of using an automated response delineation algorithm under these conditions. Despite reduced signal clarity, the algorithm reliably identifies M-wave and H-reflex responses in real time. Overall, this study demonstrates the feasibility of a portable C-EPOCS system capable of providing immediate feedback based on both EMG and EEG signals. It also offers practical recommendations for selecting acquisition hardware to support reliable signal quality, real-time processing, and portability.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISWilliams '20Wehrman '21Ravagli '26Fukuda '26Naas '19Brucker-Hah '26
63% semantic matchNeuroscience
Nikolas Williams, Genevieve M. McArthur, Nicholas A. Badcock·bioRxiv·Jul 14, 2020· 38 citations