Dynamic Trial-by-Trial Recoding of Task-Set Representations in the Frontoparietal Cortex Mediates Behavioral Flexibility

Abstract

Cognitive flexibility forms the core of the extraordinary ability of humans to adapt, but the precise neural mechanisms underlying our ability to nimbly shift between task sets remain poorly understood. Recent functional magnetic resonance imaging (fMRI) studies employing multivoxel pattern analysis (MVPA) have shown that a currently relevant task set can be decoded from activity patterns in the frontoparietal cortex, but whether these regions support the dynamic transformation of task sets from trial to trial is not clear. Here, we combined a cued task-switching protocol with human (both sexes) fMRI, and harnessed representational similarity analysis (RSA) to facilitate a novel assessment of trial-by-trial changes in neural task-set representations. We first used MVPA to define task-sensitive frontoparietal and visual regions and found that neural task-set representations on switch trials are less stably encoded than on repeat trials. We then exploited RSA to show that the neural representational pattern dissimilarity across consecutive trials is greater for switch trials than for repeat trials, and that the degree of this pattern dissimilarity predicts behavior. Moreover, the overall neural pattern of representational dissimilarities followed from the assumption that repeating sets, compared with switching sets, results in stronger neural task representations. Finally, when moving from cue to target phase within a trial, pattern dissimilarities tracked the transformation from previous-trial task representations to the currently relevant set. These results provide neural evidence for the longstanding assumptions of an effortful task-set reconfiguration process hampered by task-set inertia, and they demonstrate that frontoparietal and stimulus processing regions support "dynamic adaptive coding," flexibly representing changing task sets in a trial-by-trial fashion. Humans can fluently switch between different tasks, reflecting an ability to dynamically configure "task sets," rule representations that link stimuli to appropriate responses. Recent studies show that neural signals in frontal and parietal brain regions can tell us which of two tasks a person is currently performing. However, it is not known whether these regions are also involved in dynamically reconfiguring task-set representations when switching between tasks. Here we measured human brain activity during task switching and tracked the similarity of neural task-set representations from trial to trial. We show that frontal and parietal brain regions flexibly recode changing task sets in a trial-by-trial fashion, and that task-set similarity over consecutive trials predicts behavior.

Reward boosts neural coding of task rules to optimise cognitive flexibility

“…Consistent with the results of previous fMRI decoding studies (Etzel et al, 2016;Qiao, Zhang, Chen, & Egner, 2017;Woolgar et al, 2011;Waskom et al, 2014;Wisniewski et al, 2015), RSA successfully tracked neural representations for task rule information. In using this approach, our results replicate the fMRI findings of Etzel et al (2016) in human electroencephalographic data, showing that high reward prospect increased average task coding prior to target onset, and that the difference in task coding between reward conditions was associated with improvements in cognitive performance.…”

Transient and sustained control mechanisms supporting novel instructed behavior

“…We explored this using RSA focused on the CON and FPN ROIs. We computed a consistency index associated with the maintenance of multivoxel representation of instructions from encoding to implementation stages (Qiao et al 2017; see We first collapsed across novel and practiced trials, and observed that the CON's consistency index was higher than the FPN's one (T 34 = 9.34, P < .001), suggesting more persistent task-set representations in the former network. We then explored variations within ROIs of both subnetworks, with two additional repeated-measures ANOVAs.…”

“…We explored this using RSA focused on the CON and FPN ROIs. We computed a consistency index associated with the maintenance of multivoxel representation of instructions from encoding to implementation stages (Qiao et al 2017;see Fig. 2), in which larger values indicated a higher consistency along time (see fMRI analysis section).…”

Outcome contingency selectively affects the neural coding of outcomes but not of tasks

“…This finding informs current debates on the nature of task coding in the brain 27 . On the one hand, some have argued for flexible task coding especially in the fronto-parietal cortex 32,37 , often based on the multiple-demand network theory 31 . This account predicts that task coding should be stronger when task demands are high 32 , or when correct performance is rewarded 19 .…”