Artificial neural networks applied to somatosensory evoked potentials for migraine classification.

ABSTRACT:

Background

Finding a biomarker to diagnose migraine remains a significant challenge in the headache field. Migraine patients exhibit dynamic and recurrent alterations in the brainstem-thalamo-cortical loop, including reduced thalamocortical activity and abnormal habituation during the interictal phase. Although these insights into migraine pathophysiology have been valuable, they are not currently used in clinical practice. This study aims to evaluate the potential of Artificial Neural Networks (ANNs) in distinguishing migraine patients from healthy individuals using neurophysiological recordings.

Methods

We recorded Somatosensory Evoked Potentials (SSEPs) to gather electrophysiological data from low- and high-frequency signal bands in 177 participants, comprising 91 migrain

SUBMITTER: Sebastianelli G 

PROVIDER: S-EPMC11970013 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature