Hemodynamic functional connectivity optimization of frequency EEG microstates enables attention LSTM framework to classify distinct temporal cortical communications of different cognitive tasks

Hemodynamic functional connectivity optimization of frequency EEG microstates enables attention LSTM framework to classify distinct temporal cortical communications of different cognitive tasks

Abstract Temporal analysis of global cortical communication of cognitive tasks in coarse EEG information is still challenging due to the underlying complex neural mechanisms. This study proposes an attention-based time-series deep learning framework that processes fMRI functional connectivity optimi...

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Bibliographic Details
Main Authors: Swati Agrawal, Vijayakumar Chinnadurai, Rinku Sharma
Format: Article
Language:English
Published: SpringerOpen 2022-10-01
Series:Brain Informatics
Subjects:
Attention-based deep learning
Frequency-microstates
Hemodynamic functional connectivity
EEG-informed fMRI. Multifrequency coupling
Target detection
Online Access:https://doi.org/10.1186/s40708-022-00173-5

Internet

https://doi.org/10.1186/s40708-022-00173-5

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