Interrelation of resting state functional connectivity, striatal GABA levels, and cognitive control processes

Abstract

Important issues for cognitive control are response selection processes, known to depend on fronto-striatal networks with recent evidence suggesting that striatal gamma-amino butyric acid (GABA) levels play an important role. Regional GABA concentrations have also been shown to modulate intrinsic connectivity, e.g. of the default mode network. However, the interrelation between striatal GABA levels, basal ganglia network (BGN) connectivity, and performance in cognitive control is elusive. In the current study, we measure striatal GABA levels using magnetic resonance spectroscopy (MRS) and resting state parameters using functional magnetic resonance imaging (fMRI). Resting state parameters include activity within the BGN, as determined by the low frequency power (LFP) within the network, and the functional connectivity between the BGN and somatomotor network (SMN). Specifically, we examine the interrelation between GABA, resting state parameters, and performance (i.e., accuracy) in conflict monitoring using a Simon task. Response control was affected by striatal GABA+ levels and activity within the BGN, especially when response selection was complicated by altered stimulus-response mappings. The data suggest that there are two mechanisms supporting response selection accuracy. One is related to resting state activity within the BGN and modulated by striatal GABA+ levels. The other is related to decreased cortico-striatal network connectivity, unrelated to the GABAergic system. The inclusion of all three factors (i.e., striatal GABA+ levels, activity within the BGN, and BGN-SMN network connectivity) explained a considerable amount of variance in task accuracy. Striatal neurobiochemical (GABA+) and parameters of the resting state BGN represent important modulators of response control.

On the relevance of EEG resting theta activity for the neurophysiological dynamics underlying motor inhibitory control

“…While this is increasingly recognized in the literature (Becker et al, 2018;Haag et al, 2015;Mahjoory et al, 2019;Tavor et al, 2016), the current study is the first to show this for the theta band oscillations in the context of inhibitory control. Notably, the data analysis of the PLF in Nogo trials revealed no differential effects between the high baseline group and the low baseline group, which was confirmed by Bayesian statistics.…”

“…In line with overarching theoretical conceptions concerning the function of the medial frontal cortex and theta band activity (Cavanagh & Frank, 2014), the increase in theta band power in Nogo trials has been suggested to reflect an "alarm" or "surprise signal," which is crucial for increasing cognitive control Dippel et al, 2017;Wessel, 2018). On the other hand, it is increasingly recognized that there are similarities between resting dynamics and activity related to cognitive control (Becker, Van de Ville, & Kleinschmidt, 2018;Haag et al, 2015;Mahjoory, Cesnaite, Hohlefeld, Villringer, & Nikulin, 2019;Tavor et al, 2016). Based on these findings, it could be assumed that the individual ability to increase theta activity beyond a certain resting state activity is essential for successful response inhibition performance.…”

“…Based on these findings, it could be assumed that the individual ability to increase theta activity beyond a certain resting state activity is essential for successful response inhibition performance. On the other hand, it is increasingly recognized that there are similarities between resting dynamics and activity related to cognitive control (Becker, Van de Ville, & Kleinschmidt, 2018;Haag et al, 2015;Mahjoory, Cesnaite, Hohlefeld, Villringer, & Nikulin, 2019;Tavor et al, 2016). Some findings suggest that resting state EEG activity can predict cognitive control (Nakao, Bai, Nashiwa, & Northoff, 2013) and that resting theta activity in the middle frontal gyrus is associated with modulations in the topography of EEG activity during response inhibition (Lansbergen, Schutter, & Kenemans, 2007;Schiller, Gianotti, Nash, & Knoch, 2014).…”

Acute Alcohol Effects on Response Inhibition Depend on Response Automatization, but not on GABA or Glutamate Levels in the ACC and Striatum

“…In the results section, the mean and standard errors of the mean (SEM) are reported as a measure of variance. MRS data were integrated with the behavioral and neurophysiological data by means of correlation [19,63,83,84]. For this, the individual GABA and glutamate concentrations in the ACC and striatum at baseline (i.e., in the sober state) were used to predict the behavioral differences between sober and intoxicated (i.e., sober-intoxicated) appointments for each combination of experimental conditions.…”

Effects of high‐dose ethanol intoxication and hangover on cognitive flexibility

“…Karayanidis et al ; Gehring et al ; Gajewski et al ) are reflected by the N2 ERP originating from the anterior cingulated cortex (ACC) (Folstein and Van Petten ). As these mechanisms represent important cognitive subprocesses during task switching (Gajewski et al ; Gajewski et al ) and are subject to modulation by the dopamine and the GABAergic system (Stock et al ; Steenbergen et al ; Haag et al ; Quetscher et al ; Beste et al ), these processes may be particularly affected by high‐dose ethanol intoxication and hangover. Furthermore, processes relating to updating of working memory processes, which are indexed by the P3 ERP (Polich and Kok ; Barceló ; Polich ) and are also strongly involved in memory‐based task switching, may be affected as well.…”