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Corresponding Author

Akash Rajak

Subject Area

Computer Science

Article Type

Original Study

Abstract

Event-Related Potentials (ERPs) are extensively employed in the examination of neural responses linked with cognitive processing and changes in brain activity. In this work, we conducted a comparative analysis of ERPs on a publicly available EEG dataset (122 subjects, alcoholic and control groups) with the help of the MNE-Python framework. The 64 electrodes for EEG were placed according to the international 10 - 20 system, and EEG was sampled at a 256 Hz sampling rate over 1-second epochs. The preprocessing pipeline consisted of 1 - 40 Hz bandpass filtering, noise reduction, spectral computation, and ERP waveform analysis. Temporal neural activity variations between the subject groups were analyzed using representative ERP waveforms visualized at the Cz electrode. The Power Spectral Density (PSD) analysis showed that the power of the EEG signals was higher in the low frequency band (< 15 Hz), and the Inter-Channel Correlation (ICC) analysis indicated strong positive correlation between frontal electrodes such as FP1 - FP2 (r = 0.94) and F3 - F4 (r = 0.91). When comparing amplitude dynamics and waveforms between control and alcoholic EEG signals, there were noticeable differences in the neural signals in the 200-600 ms window associated with FRN-related and P300-related ERP activity.

Keywords

Event-Related Potential; MNE-Python; EEG Analysis; Cognitive Neuroscience; Neural Signal Processing; Alcoholism EEG

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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