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

Journal: The journal of headache and pain
PMID: 40186113

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.

Authors

  • Gabriele Sebastianelli
    Department of Medico-Surgical Sciences and Biotechnologies, Sapienza University of Rome Polo Pontino ICOT, Latina, Italy.
  • Daniele Secci
    Department of Engineering and Architecture, University of Parma, Parma, Italy.
  • Francesco Casillo
    Department of Medico-Surgical Sciences and Biotechnologies, Sapienza University of Rome Polo Pontino ICOT, Via Franco Faggiana 1668, Latina, 04100, Italy.
  • Chiara Abagnale
    Department of Medico-Surgical Sciences and Biotechnologies, Sapienza University of Rome Polo Pontino ICOT, Via Franco Faggiana 1668, Latina, 04100, Italy.
  • Cherubino Di Lorenzo
    Department of Medico-Surgical Sciences and Biotechnologies, University of Rome Sapienza, Latina, Italy.
  • Mariano Serrao
    Department of Medico-Surgical Sciences and Biotechnologies, University of Rome Sapienza, Latina, Italy.
  • Shuu-Jiun Wang
    Brain Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan.
  • Fu-Jung Hsiao
    Brain Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan.
  • Gianluca Coppola
    Department of Medico-Surgical Sciences and Biotechnologies, University of Rome Sapienza, Latina, Italy.

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