Brain network segregation and integration during an epoch-related working memory fMRI experiment.

The characterization of brain subnetwork segregation and integration has previously focused on changes that are detectable at the level of entire sessions or epochs of imaging data. In this study, we applied time-varying functional connectivity analysis together with temporal network theory to calculate point-by-point estimates in subnetwork segregation and integration during an epoch-based (2-back, 0-back, baseline) working memory fMRI experiment as well as during resting-state. This approach allowed us to follow task-related changes in subnetwork segregation and integration at a high temporal resolution. At a global level, the cognitively more taxing 2-back epochs elicited an overall stronger response of integration between subnetworks compared to the 0-back epochs. Moreover, the visual, sensorimotor and fronto-parietal subnetworks displayed characteristic and distinct temporal profiles of segregation and integration during the 0- and 2-back epochs. During the interspersed epochs of baseline, several subnetworks, including the visual, fronto-parietal, cingulo-opercular and dorsal attention subnetworks showed pronounced increases in segregation. Using a drift diffusion model we show that the response time for the 2-back trials are correlated with integration for the fronto-parietal subnetwork and correlated with segregation for the visual subnetwork. Our results elucidate the fast-evolving events with regard to subnetwork integration and segregation that occur in an epoch-related task fMRI experiment. Our findings suggest that minute changes in subnetwork integration are of importance for task performance.

Memory-reliant Post-error Slowing Is Associated with Successful Learning and Fronto-occipital Activity.

Negative feedback after an action in a cognitive task can lead to devaluing that action on future trials as well as to more cautious responding when encountering that same choice again. These phenomena have been explored in the past by reinforcement learning theories and cognitive control accounts, respectively. Yet, how cognitive control interacts with value updating to give rise to adequate adaptations under uncertainty is less clear. In this fMRI study, we investigated cognitive control-based behavioral adjustments during a probabilistic reinforcement learning task and studied their influence on performance in a later test phase in which the learned value of items is tested. We provide support for the idea that functionally relevant and memory-reliant behavioral adjustments in the form of post-error slowing during reinforcement learning are associated with test performance. Adjusting response speed after negative feedback was correlated with BOLD activity in right inferior frontal gyrus and bilateral middle occipital cortex during the event of receiving the feedback. Bilateral middle occipital cortex activity overlapped partly with activity reflecting feedback deviance from expectations as measured by unsigned prediction error. These results suggest that cognitive control and feature processing cortical regions interact to implement feedback-congruent adaptations beneficial to learning.

The Sustained Influence of an Error on Future Decision-Making.

Post-error slowing (PES) is consistently observed in decision-making tasks after negative feedback. Yet, findings are inconclusive as to whether PES supports performance accuracy. We addressed the role of PES by employing drift diffusion modeling which enabled us to investigate latent processes of reaction times and accuracy on a large-scale dataset (>5,800 participants) of a visual search experiment with emotional face stimuli. In our experiment, post-error trials were characterized by both adaptive and non-adaptive decision processes. An adaptive increase in participants' response threshold was sustained over several trials post-error. Contrarily, an initial decrease in evidence accumulation rate, followed by an increase on the subsequent trials, indicates a momentary distraction of task-relevant attention and resulted in an initial accuracy drop. Higher values of decision threshold and evidence accumulation on the post-error trial were associated with higher accuracy on subsequent trials which further gives credence to these parameters' role in post-error adaptation. Finally, the evidence accumulation rate post-error decreased when the error trial presented angry faces, a finding suggesting that the post-error decision can be influenced by the error context. In conclusion, we demonstrate that error-related response adaptations are multi-component processes that change dynamically over several trials post-error.