Ocular signatures of proactive versus reactive cognitive control in young adults

Abstract

During the execution of a cognitive task, the brain maintains contextual information to guide behavior and achieve desired goals. The AX-Continuous Performance Task is used to study proactive versus reactive cognitive control. Young adults tend to behave proactively in standard testing conditions. However, it remains unclear how interindividual variability (e.g., in cognitive and motivational factors) may drive people into more reactive or proactive control under the same task demands. We investigated the use of control strategies in a large population of healthy young adults. We computed the proactive behavioral index and consequently divided participants into proactive, reactive, and intermediate groups. We found that reactive participants were generally slower, presented lower context sensitivity, and larger response variability. Pupillary changes and blink rate index cognitive effort allocation. We measured, concomitantly to the task, the pupil size and frequency of blinks associated with the cue maintenance and response intervals. During the cue period, nonfrequent, nontarget cues led to increased pupil dilation and number of blinks in all participants. During the response interval, we found more errors and increased pupil dilation to the probe when all participants had to overcome a response bias generated by the frequent cue. Only reactive participants showed larger response-related pupil when they had to overcome a response bias related to the frequent probe. Contrary to expectations, groups did not differ in ocular measures in the cue period. In conclusion, interindividual differences in cognitive control between healthy adults can be mapped onto different patterns of effort allocation indexed by the pupil.

Decreased preparatory activation and inattention to cues suggest lower activation of proactive cognitive control among high procrastinating students

“…Moreover, this measure turned out to be negatively correlated with most behavioral and neurophysiological indices of proactive control, such as A-cue bias, d ’-context, CNV and P3b to B cues. It is in line with previous findings showing that higher RTV is linked with lower proactive responding (Mäki-Marttunen et al, 2018 ) and reduced CNV (Doehnert et al, 2013 ) and indicates that this measure might be considered as another index of proactive control engagement, reflecting processes involved in sustained attention. On the contrary, we did not observe significant correlations between RTV and PBIs.…”

Toward a formal theory of proactivity

“…This means that a participant might see an A cue and set the prepotent intention to report an AX trial in anticipation of an X probe and then inhibit that intention when they see the Y probe. In support of this view, the pupillometry findings of Mäki-Marttunen et al (2018) and the Locus Coeruleus and dlPFC activation found by Mäki-Marttunen et al (2019a, 2019b) support the involvement of inhibitory control in the AX-CPT. Furthermore, the especially long response times on AY trials might suggest that participants sometimes override their intention to report an AX pair when they see the Y probe (Mäki-Marttunen et al, 2018;Mäki-Marttunen et al, 2019b).…”

“…Recent physiological data and reaction time data suggest that there might be an additional control mechanism influencing people's responses in the AX-CPT, namely the inhibition of prepotent responses (Mäki-Marttunen et al, 2018;Mäki-Marttunen et al, 2019b). This means that a participant might see an A cue and set the prepotent intention to report an AX trial in anticipation of an X probe and then inhibit that intention when they see the Y probe.…”

“…Furthermore, it remains unclear how many and which meta-control decisions govern the variability in cognitive control within and across people. For instance, it is currently controversial whether people inhibit the intentions they have set in anticipation of one event when another event occurs that renders their intentions maladaptive (Mäki-Marttunen et al, 2018). The findings reviewed by Braver (2012) suggested that the frequency with which people engage proactive control increases with factors that make it more valuable (e.g., incentives) and decreases with factors that make it costlier (e.g., working memory load).…”

Effects of HF-rTMS over the left and right DLPFC on proactive and reactive cognitive control

“…In contrast, participants would show more reactive cognitive control after HF-rTMS over the right DLPFC ( Vanderhasselt et al., 2009 ). Previous studies have demonstrated that changes in pupil size can be used to investigate the allocation of cognitive resources or mental effort during the AX-CPT ( Chiew and Braver, 2013 , 2014 ; Mäki-Marttunen et al., 2018 ). Chiew and Braver (2013 ) showed that an increase in proactive control provokes a sustained increase in pupil size measured in the period immediately before the cue is presented, reflecting sustained resource allocation during the task.…”