Hierarchical Classification of Event-Related Potentials for the Recognition of Gender Differences in the Attention Task.

Karina Maciejewska,Wojciech Froelich

doi:10.3390/e23111547

Abstract

Research on the functioning of human cognition has been a crucial problem studied for years. Electroencephalography (EEG) classification methods may serve as a precious tool for understanding the temporal dynamics of human brain activity, and the purpose of such an approach is to increase the statistical power of the differences between conditions that are too weak to be detected using standard EEG methods. Following that line of research, in this paper, we focus on recognizing gender differences in the functioning of the human brain in the attention task. For that purpose, we gathered, analyzed, and finally classified event-related potentials (ERPs). We propose a hierarchical approach, in which the electrophysiological signal preprocessing is combined with the classification method, enriched with a segmentation step, which creates a full line of electrophysiological signal classification during an attention task. This approach allowed us to detect differences between men and women in the P3 waveform, an ERP component related to attention, which were not observed using standard ERP analysis. The results provide evidence for the high effectiveness of the proposed method, which outperformed a traditional statistical analysis approach. This is a step towards understanding neuronal differences between men’s and women’s brains during cognition, aiming to reduce the misdiagnosis and adverse side effects in underrepresented women groups in health and biomedical research.

Highlights

The importance of recognizing gender differences in health and biomedical research, including neuroscience, has become a significant matter of concern, prompting new policies to be implemented at the funding agencies (Canadian Institutes of Health Research, European Commission, US National Institutes of Health or German Research Foundation) to supervise gender analysis [1,2,3,4].In recent decades, experiments in biomedical research were carried out without considering gender, resulting in more significant health risks for women due to their under-representation in the preclinical, clinical studies, and drug trials
While most EEG-based classification studies rely on resting-state EEG recording, in this work we focused on event-related potentials (ERPs) in reaction to visual stimuli as a result of neuronal activity related to the cognitive process, allowing for the isolation of specific cognitive functions of the human brain
We proposed a new combined empirical and theoretical approach for an efficient gender recognition based on ERPs, in order to better understand neuronal differences between men’s and women’s brains for the attention task

Summary

Introduction

The importance of recognizing gender differences in health and biomedical research, including neuroscience, has become a significant matter of concern, prompting new policies to be implemented at the funding agencies (Canadian Institutes of Health Research, European Commission, US National Institutes of Health or German Research Foundation) to supervise gender analysis [1,2,3,4]. Experiments in biomedical research were carried out without considering gender, resulting in more significant health risks for women due to their under-representation in the preclinical, clinical studies, and drug trials. We address this crucial research problem of cognitive neuroscience. We examine whether gender differences in human cognition can be recognized while performing the attention task. The method proposed here combines practical and theoretical efforts to solve the underlying stated problem. The contribution of this paper should be considered from empirical and theoretical perspectives:

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Conclusion