EEG based functional connectivity in resting and emotional states may identify major depressive disorder using machine learning.

Journal: Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
PMID: 38870669

Abstract

OBJECTIVE: Disrupted brain network connectivity underlies major depressive disorder (MDD). Altered EEG based Functional connectivity (FC) with Emotional stimuli in major depressive disorder (MDD) in addition to resting state FC may help in improving the diagnostic accuracy of machine learning classification models. We explored the potential of EEG-based FC during resting state and emotional processing, for diagnosing MDD using machine learning approach.

Authors

  • Estelle Havilla Earl
    Department of Physiology, All India Institute of Medical Sciences, Bhubaneswar, Odisha, India.
  • Manish Goyal
    Department of Computer Science and Engineering, University of Connecticut, Storrs, CT 06269, USA.
  • Shree Mishra
    Department of Psychiatry, All India Institute of Medical Sciences, Bhubaneswar, Odisha, India.
  • Balakrishnan Kannan
    Department of Physiology, All India Institute of Medical Sciences, Bhubaneswar, Odisha, India.
  • Anushree Mishra
    Department of Psychiatry, All India Institute of Medical Sciences, Bhubaneswar, Odisha, India.
  • Nilotpal Chowdhury
    Department of Pathology, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India.
  • Priyadarshini Mishra
    Department of Physiology, All India Institute of Medical Sciences, Bhubaneswar, Odisha, India. Electronic address: pmishra2789@gmail.com.

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