» Articles » PMID: 32431963

Integrated Development Environment for EEG-Driven Cognitive-Neuropsychological Research

Overview
Date 2020 May 21
PMID 32431963
Citations 1
Authors
Affiliations
Soon will be listed here.
Abstract

EEG-driven research is paramount in cognitive-neuropsychological studies, as it provides a non-invasive window to the underlying neural mechanisms of cognition and behavior. A myriad collection of software and hardware frameworks has been developed to alleviate some of the technical barriers involved in EEG-driven research. we propose an integrated development environment which encompasses the entire technical "data-collection pipeline" of cognitive-neuropsychological research, including experiment design, data acquisition, data exploration and analysis in a state-of-the-art user interface. Our framework is based on a unique integration between a python-based web framework, time-oriented databases and object-based data schemes. we demonstrated our framework with the recording and analysis of an n-Back task completed by 15 elderly (ages 50 to 80) participants. This case study demonstrates the highly utilized nature of our integrated framework with a challenging target population. Furthermore, our results may provide new insights into the correlation between brain activity and working memory performance in elderly people, who are prone to experience accelerated decline in executive prefrontal cortex functioning. our framework extends the range of EEG-driven experimental methods for assessing cognition available for cognitive-neuroscientists, allowing them to concentrate on the creative part of their work instead of technical aspects.

Citing Articles

Virtual Intelligence: A Systematic Review of the Development of Neural Networks in Brain Simulation Units.

Zavala Hernandez J, Barbosa-Santillan L Brain Sci. 2022; 12(11).

PMID: 36421877 PMC: 9688651. DOI: 10.3390/brainsci12111552.

References
1.
Klimesch W . EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis. Brain Res Brain Res Rev. 1999; 29(2-3):169-95. DOI: 10.1016/s0165-0173(98)00056-3. View

2.
Hassan M, Shamas M, Khalil M, El Falou W, Wendling F . EEGNET: An Open Source Tool for Analyzing and Visualizing M/EEG Connectome. PLoS One. 2015; 10(9):e0138297. PMC: 4574940. DOI: 10.1371/journal.pone.0138297. View

3.
von Bastian C, Locher A, Ruflin M . Tatool: a Java-based open-source programming framework for psychological studies. Behav Res Methods. 2012; 45(1):108-15. DOI: 10.3758/s13428-012-0224-y. View

4.
Babiloni C, Lizio R, Vecchio F, Frisoni G, Pievani M, Geroldi C . Reactivity of cortical alpha rhythms to eye opening in mild cognitive impairment and Alzheimer's disease: an EEG study. J Alzheimers Dis. 2010; 22(4):1047-64. DOI: 10.3233/JAD-2010-100798. View

5.
Barham M, Clark G, Hayden M, Enticott P, Conduit R, Lum J . Acquiring research-grade ERPs on a shoestring budget: A comparison of a modified Emotiv and commercial SynAmps EEG system. Psychophysiology. 2017; 54(9):1393-1404. DOI: 10.1111/psyp.12888. View