On the Neurophysiological Mechanisms Underlying the Adaptability to Varying Cognitive Control Demands

Abstract

Cognitive control processes are advantageous when routines would not lead to the desired outcome, but this can be ill-advised when automated behavior is advantageous. The aim of this study was to identify neural dynamics related to the ability to adapt to different cognitive control demands – a process that has been referred to as ‘metacontrol.’ A sample of N = 227 healthy subjects that was split in a ‘high’ and ‘low adaptability’ group based on the behavioral performance in a task with varying control demands. To examine the neurophysiological mechanisms, we combined event-related potential (ERP) recordings with source localization and machine learning approaches. The results show that individuals who are better at strategically adapting to different cognitive control demands benefit from automatizing their response processes in situations where little cognitive control is needed. On a neurophysiological level, neither perceptual/attentional selection processes nor conflict monitoring processes paralleled the behavioral data, although the latter showed a descriptive trend. Behavioral differences in metacontrol abilities were only significantly mirrored by the modulation of response-locked P3 amplitudes, which were accompanied by activation differences in insula (BA13) and middle frontal gyrus (BA9). The machine learning result corroborated this by identifying a predictive/classification feature near the peak of the response-locked P3, which arose from the anterior cingulate cortex (BA24; BA33). In short, we found that metacontrol is associated to the ability to manage response selection processes, especially the ability to effectively downregulate cognitive control under low cognitive control requirements, rather than the ability to upregulate cognitive control.

Resting-state BOLD signal variability is associated with individual differences in metacontrol

“…How might signal variability in the brain translate into metacontrol biases towards persistence or exibility? Researchers have proposed that dopamine (DA) and inter-individual differences in DA levels and/or the dynamics of these levels over time are promising candidates for linking characteristics of neural processing, like differences in neural variability, to behavior 3,47−49 and some evidence suggests that dopaminergic (or catecholamine system activity) is associated with metacontrol [50][51][52][53] .…”

Alpha ERS-ERD Pattern during Divergent and Convergent Thinking Depends on Individual Differences on Metacontrol

“…High-metacontrol individuals may flexibly switch between persistent and flexible states to accommodate the current task, while low-metacontrol individuals cannot. For instance, high-metacontrol individuals exert more "persistent" automatic control with low cognitive control demands; in turn, they allow more "flexible" cognitive control under high cognitive demands (Zink et al 2018). There has been evidence that a high-metacontrol group (i.e., high adaptive ability) can cope with varying levels of cognitive control demands with superior performance than a low-metacontrol group when it comes to low control requirements (Zink et al 2018).…”

“…For instance, high-metacontrol individuals exert more "persistent" automatic control with low cognitive control demands; in turn, they allow more "flexible" cognitive control under high cognitive demands (Zink et al 2018). There has been evidence that a high-metacontrol group (i.e., high adaptive ability) can cope with varying levels of cognitive control demands with superior performance than a low-metacontrol group when it comes to low control requirements (Zink et al 2018). Concerning the neural mechanism for adaptive control, response-locked P3 amplitude had striking differences between the high-and low-metacontrol groups, which reflected the response selection adaptation to changing cognitive control needs (Stock et al 2016;Twomey et al 2015;Verleger et al 2005;Zink et al 2018).…”

“…There has been evidence that a high-metacontrol group (i.e., high adaptive ability) can cope with varying levels of cognitive control demands with superior performance than a low-metacontrol group when it comes to low control requirements (Zink et al 2018). Concerning the neural mechanism for adaptive control, response-locked P3 amplitude had striking differences between the high-and low-metacontrol groups, which reflected the response selection adaptation to changing cognitive control needs (Stock et al 2016;Twomey et al 2015;Verleger et al 2005;Zink et al 2018). There is no significant difference in either bottom-up perceptual and attentional selection processes (P1 and N1 ERPs), nor in conflict monitoring processes (N2 and N450 ERPs) (Zink et al 2018).…”

The Role of DRD1 and DRD2 Receptors for Response Selection Under Varying Complexity Levels: Implications for Metacontrol Processes

“…In summary, our study investigated the effects of DRD1 and DRD2 receptor genotypes in 195 healthy individuals, who were assessed with an experiment consisting of 2 complementary tasks (Bocanegra and Hommel, 2014; Zink et al, 2018a, 2018b). Subjects responded to the same set of stimuli in both tasks, but the demand for cognitive control was manipulated by asking them to either follow a less complex rule (easy task/low cognitive control requirement) or a more complex rule (hard task/high cognitive control requirement).…”