Strategic down‐regulation of attentional resources as a mechanism of proactive response inhibition. (29th July 2016)

• Record Type: Journal Article
• Authors: Langford, Zachary D.; Krebs, Ruth M.; Talsma, Durk; Woldorff, Marty G.; Boehler, C. N.
• Editors: Foxe, John
• Is Part Of: European journal of neuroscience. Volume 44:Number 4(2016:Aug.)
• Page Start: 2095
• Page End: 2103
• Publication Date: 2016-07-29
• Subjects: attention -- drift diffusion models -- proactive control -- response inhibition -- single‐trial EEG; Nervous system -- Periodicals; 612.8
• DOI: 10.1111/ejn.13303
• Languages: English
• ISSNs: 0953-816X

Abstract

Abstract: Efficiently avoiding inappropriate actions in a changing environment is central to cognitive control. One mechanism contributing to this ability is the deliberate slowing down of responses in contexts where full response cancellation might occasionally be required, referred to as proactive response inhibition. The present electroencephalographic (EEG) study investigated the role of attentional processes in proactive response inhibition in humans. To this end, we compared data from a standard stop‐signal task, in which stop signals required response cancellation ('stop‐relevant'), to data where possible stop signals were task‐irrelevant ('stop‐irrelevant'). Behavioral data clearly indicated the presence of proactive slowing in the standard stop‐signal task. A novel single‐trial analysis was used to directly model the relationship between response time and the EEG data of the go‐trials in both contexts within a multilevel linear models framework. We found a relationship between response time and amplitude of the attention‐related N1 component in stop‐relevant blocks, a characteristic that was fully absent in stop‐irrelevant blocks. Specifically, N1 amplitudes were lower the slower the response time, suggesting that attentional resources were being strategically down‐regulated to control response speed. Drift diffusion modeling of the behavioral data indicated that multiple parameters differed across the two contexts, likely suggesting the contribution from independent brain mechanisms to proactive slowing. Hence, the attentional mechanism of proactive response control we report here might coexist with known mechanisms that are more directly tied to motoric response inhibition. As such, our study opens up new research avenues also concerning clinical conditions that feature deficits in proactive response inhibition. Abstract : A novel single‐trial EEG analysis was used to directly model the relationship between response time and the EEG data of the go‐trials when stopping was either contextually relevant, or not. In this multilevel linear models framework we found a relationship between response time and amplitude of the attention‐related N1 component in stop‐relevant blocks, a characteristic that was fully absent in stop‐irrelevant blocks. Bootstrap mean beta describing the positive relationship between the inferoposterior N1 and response time in the stop‐relevant stop signal task is shown.