Stimulus-Response Mappings Shape Inhibition Processes: A Combined EEG-fMRI Study of Contextual Stopping

Abstract

Humans are rarely faced with one simple task, but are typically confronted with complex stimulus constellations and varying stimulus-relevance in a given situation. Through modifying the prototypical stop-signal task and by combined recording and analysis of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), we studied the effects of stimulus relevance for the generation of a response or its inhibition. Stimulus response mappings were modified by contextual cues, indicating which of two different stimuli following a go stimulus was relevant for stopping. Overall, response inhibition, that is comparing successful stopping to a stop-signal against go-signal related processes, was associated with increased activity in right inferior and left midfrontal regions, as well as increased EEG delta and theta power; however, stimulus-response conditions in which the most infrequent stop-signal was relevant for inhibition, were associated with decreased activity in regions typically involved in response inhibition, as well as decreased activity in the delta and theta bands as compared to conditions wherein the relevant stop-signal frequency was higher. Behaviorally, this (aforementioned) condition, which demanded inhibition only from the most infrequent stimulus, was also associated with reduced reaction times and lower error rates. This pattern of results does not align with typical stimulus frequency-driven findings and suggests interplay between task relevance and stimulus frequency of the stop-signal. Moreover, with a multimodal EEG-fMRI analysis, we demonstrated significant parameterization for response inhibition with delta, theta and beta time-frequency values, which may be interpreted as reflecting conflict monitoring, evaluative and/or motor processes as suggested by previous work (Huster et al., 2013; Aron, 2011). Further multimodal results suggest a possible neurophysiological and behavioral benefit under conditions whereby the most infrequent stimulus demanded inhibition, indicating that the frequency of the stop-signal interacts with the current stimulus-response contingency. These results demonstrate that response inhibition is prone to influence from other cognitive functions, making it difficult to dissociate real inhibitory capabilities from the influence of moderating mechanisms.

Inhibitory motor control based on complex stopping goals relies on the same brain network as simple stopping

“…Converging evidence from studies with more spatially precise methods such as fMRI (Curtis et al, 2005; Li et al, 2006; Rubia et al, 2001; Swann et al, 2012a) and intracranial recordings (Swann et al, 2009; Swann et al, 2012b) point towards critical roles of pre-SMA and rIFC in simple stopping, in addition to the basal ganglia (Aron and Poldrack, 2006; Ray et al, 2012; Zandbelt and Vink, 2010). Regarding scalp EEG, the majority of studies of successful stopping in the SST reported activity with a fronto-central voltage distribution, similar to what we report here (Etchell et al, 2012; Greenhouse and Wessel, 2013; Johnstone et al, 2007; Kok et al, 2004; Kramer et al, 2011; Lavallee et al, 2014; Nigbur et al, 2011; Schmiedt-Fehr and Basar-Eroglu, 2011; Wessel and Aron, 2013; Yamanaka and Yamamoto, 2010). However, due to the inverse problem, it is still unclear which exact anatomical brain regions generate this fronto-central activity.…”

“…Activity within this stopping network has been found across several brain imaging modalities. In the human scalp electroencephalogram (EEG), time-frequency analyses show a signature of successful action-stopping at fronto-central scalp sites, specifically within the theta- (5–8Hz) and delta-frequency bands (1–4Hz) (Lavallee et al, 2014; Nigbur et al, 2011; Schmiedt-Fehr and Basar-Eroglu, 2011; Wessel and Aron, 2013; Yamanaka and Yamamoto, 2010). …”

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

“…Processes related to the conflict monitoring modulate theta activity (Cohen & Donner, 2013;Lavallee et al, 2014;Tang et al, 2013;Wang et al, 2014). In the high baseline group, no such differences between compatible and incompatible Nogo trials were observed.…”

Spurious correlations in simultaneous EEG-fMRI driven by in-scanner movement

“…The relationship between motion and EEG power might explain the lack of distinct correlation patterns found between specific frequency bands and BOLD responses (de Munck et al, 2009;Lavallee et al, 2014;Mantini et al, 2007), the lack of correlation of oscillatory EEG power in taskactive regions (Ritter et al, 2009;Scheeringa et al, 2009), and the high variability in correlation patterns across participants (de Munck et al, 2007;de Munck et al, 2009;Goncalves et al, 2006;Laufs et al, 2006a;Meyer et al, 2013). In particular, we suggest that EEG-fMRI studies investigating the relationship between oscillatory EEG power and BOLD responses in resting state are particularly susceptible to spurious correlations, since in resting state studies, continuous power time series are typically correlated with BOLD time series similar to the analysis presented here.…”