Point-process deconvolution of fMRI reveals effective connectivity alterations in chronic pain patients

TL;DR

This paper introduces a novel blind deconvolution method to analyze effective brain connectivity from spontaneous fMRI activity, revealing changes in the Insula's connectivity in chronic pain patients.

Contribution

It presents a new approach for deconvolving hemodynamic responses without explicit event timings to study effective connectivity alterations in chronic pain.

Findings

Altered effective connectivity in the Insula of chronic pain patients

Method successfully deconvolved spontaneous neural events from fMRI data

Provides insights into brain function changes due to chronic pain

Abstract

It is now recognized that important information can be extracted from the brain spontaneous activity, as exposed by recent analysis using a repertoire of computational methods. In this context a novel method, based on a blind deconvolution technique, is used in this paper to analyze potential changes due to chronic pain in the brain pain matrix's effective connectivity. The approach is able to deconvolve the hemodynamic response function to spontaneous neural events, i.e., in the absence of explicit onset timings, and to evaluate information transfer between two regions as a joint probability of the occurrence of such spontaneous events. The method revealed that the chronic pain patients exhibit important changes in the Insula's effective connectivity which can be relevant to understand the overall impact of chronic pain on brain function.