How Do Brain Areas Communicate During the Processing of Noxious Stimuli? An Analysis of Laser-Evoked Event-Related Potentials Using the Granger Causality Index

Abstract

Several imaging techniques have identified different brain areas involved in the processing of noxious stimulation and thus in the constitution of pain. However, only little is known how these brain areas communicate with one another after activation by stimulus processing and which areas directionally affect or modulate the activity of succeeding areas. One measure for the analysis of such interactions is represented by the Granger Causality Index (GCI). In applying time-varying bivariate and partial variants of this concept (tvGCI), the aim of the present study was to investigate the interaction of neural activities between a set of scalp electrodes that best represent the brain electrical neural activity of major cortical areas involved in the processing of noxious laser-heat stimuli and their variation in time. Bivariate and partial tvGCIs were calculated within four different intervals of laser-evoked event-related potentials (LEPs) including a baseline period prior to stimulus application and three intervals immediately following stimulus application, i.e., between 170 and 200 ms (at the N2 component), between 260 and 320 ms (P2 component), and between 320 and 400 ms (P3 component of LEPs). Results show some similarities, but also some striking differences between bivariate and partial tvGCIs. These differences might be explained by the nature of bivariate and partial tvGCIs. However, both tvGCI approaches revealed a directed interaction between medial and lateral electrodes of the centroparietal region. This result was interpreted as a directed interaction between the anterior cingulate cortex and the secondary somatosensory cortex and the insula, structures that are significantly involved in the constitution of pain.

A time-varying source connectivity approach to reveal human somatosensory information processing

“…4). However, the effective connectivity from ipsilateral SII to CC was not reported in their study (Weiss et al, 2008), which may be caused by the relatively weaker effective connectivity strength (smaller tvPDC values in this study) (D, Fig. 4).…”

“…Previously, the identification of the tvMVAR model (i.e., the estimation of tvMVAR coefficients a(n)) from multiple trials of source waveforms was achieved by the recursive least-squares (Arnold et al, 1998;Ding et al, 2000;Milde et al, 2010;Moller et al, 2001) or Kalman filtering (Kaminski et al, 2001;Milde et al, 2010;Weiss et al, 2008). In the present study, we employed a Kalman smoother method to obtain a more accurate tvMVAR model estimation for estimating the tvMVAR coefficients from Eq.…”

“…The variations of these singletrial source waveforms can be described by a P-order tvMVAR model (Milde et al, 2010;Moller et al, 2001;Weiss et al, 2008) as:…”

“…Some tracking methods (Arnold et al, 1998;Ding et al, 2000;Kaminski et al, 2001;Milde et al, 2010;Moller et al, 2001;Weiss et al, 2008), e.g. recursive least-squares and Kalman filtering, have been applied to estimate the tvMVAR coefficients in effective connectivity studies.…”

“…insula, somatosensory cortex, and motor and premotor cortices) and send back projections to most of them (Baleydier and Mauguiere, 1980;Frot et al, 2008;Morecraft and Van Hoesen, 1992;Morecraft et al, 2000Morecraft et al, , 2004. In addition, by assessing the effective connectivity of cortical responses to laser stimuli between pairs of scalp EEG electrodes, Weiss et al (2008) reported an "unexpected" effective connectivity from CC to the SII/insula of each hemisphere. The effective connectivity from CC to the SII/insula is in accord with the strong tvPDC from CC to bilateral SII observed in this study (E and G, Fig.…”