Multiple Functional Brain Networks Related to Pain Perception Revealed by fMRI

Autor: Nicole Sanford, Ryan Lim, Matteo Damascelli, John L.K. Kramer, Hafsa B Zahid, Todd S. Woodward, Alex Scott
Rok vydání: 2021
Předmět:
Zdroj: Neuroinformatics. 20(1)
ISSN: 1559-0089
Popis: The rise of functional magnetic resonance imaging (fMRI) has led to a deeper understanding of cortical processing of pain. Central to these advances has been the identification and analysis of “functional networks”, often derived from groups of pre-selected pain regions. In this study our main objective was to identify functional brain networks related to pain perception by examining whole-brain activation, avoiding the need for a priori selection of regions. We applied a data-driven technique—Constrained Principal Component Analysis for fMRI (fMRI-CPCA)—that identifies networks without assuming their anatomical or temporal properties. Open-source fMRI data collected during a thermal pain task (33 healthy participants) were subjected to fMRI-CPCA for network extraction, and networks were associated with pain perception by modelling subjective pain ratings as a function of network activation intensities. Three functional networks emerged: a sensorimotor response network, a salience-mediated attention network, and the default-mode network. Together, these networks constituted a brain state that explained variability in pain perception, both within and between individuals, demonstrating the potential of data-driven, whole-brain functional network techniques for the analysis of pain imaging data.
Databáze: OpenAIRE