Vol. 7 No. 1 (2026)

Standard Journal Issues

Neural Signatures of Alcoholism Revealed by Event-Related Potential Analysis of Open EEG Data

Published 2026-03-03

  • Akash Rajak

Akash Rajak
Krishna Institute of Engineering & Technology (KIET), Ghaziabad, Delhi-NCR, Uttar Pradesh, India

Abstract

The event-related potential (ERP) analysis allows us to measure brain activity as it reflects sensory processing, attention, and a range of cognitive tasks. In this research article we introduce a comprehensive ERP-based approach for the identification of neurophysiological markers of alcoholism, using the open EEG dataset and the MNE-Python toolkit. All the EEG data recorded during a visual object recognition task were uniformly processed for both the alcoholic and control groups. After filtering and re-referencing, independent component analysis was applied, followed by segmenting the data into epochs and performing baseline correction. We focus on well-known ERP components, notably N2 and P300, occurring roughly 200-300 ms and 300-600 ms after the onset of the stimulus, respectively, which are associated with cognitive evaluation processes. We clearly see two distinct ERP profiles between the two groups. The alcoholic group shows reduced P300 and altered N2 compared with controls. This study presents a transparent and reproducible ERP analysis pipeline, developed solely with open-source tools and data, and highlights the potential of ERP markers as neurophysiological indicators of cognitive changes associated with alcohol use disorder.

Keywords

Event-Related Potential, Response Accuracy, MNE-Python, EEG Analysis, Neurophysiological Data, Comparative Study

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