Optimisation of functional network resources when learning behavioural strategies for performing complex tasks

Abstract

We designed two novel fMRI paradigms to investigate how people self-optimise performance when managing competing demands. We hypothesised that the brain adopts distinct functional states to support different tasks, that switching between them involves a costly process of collapse and reconfiguration of the functional connectome, and that this process is optimised with practice. Accordingly, self-ordered switches (SOS) were associated with transient states of low-connectivity and high-activation. Individuals progressively improved their performance with practice. This learning behaviour was reflected by an ongoing redeployment of the neural resources supporting switching and routine behaviour.Furthermore, those who developed more structured behaviours also scored more points, showed a greater deepening of switching-dysconnectivity and a greater tuning of activity within dorsal frontoparietal cortex to switching events with practice. These results demonstrate that a fundamental property of human neurocognitive systems is concurrent self-optimisation to maximise behavioural outcomes and minimise the use of neural resources.Study 1: Feedback guided SOS. While in the MRI scanner, 16 healthy individuals performed SOS for 20 minutes while being guided by response feedback (Figure 2b-d). Visual discriminations were made on each trial using left or right button presses. Switches between tasks and rules were made using up or down button presses. Response feedback occurred after each trial and consisted of a set of hierarchically organised meters and an overall score.Each task had an overall progress meter, and two subordinal meters corresponding to the discrimination rules. To increment the task meters, both rule meters for that task had to progress, which occurred when a correct response was made for a corresponding trial. To score maximum points, both task meters had to progress. Response errors, or making too many responses on a particular rule or task, resulted in penalties that hindered progress (see

Increased global integration in the brain after psilocybin therapy for depression

“…The EN and SN have been associated with tasks requiring cognitive flexibility such as learning and task switching 18,19,46,47 ; impaired functioning of these networks have been reported in depression 14,17 and other disorders exhibiting cognitive inflexibility such as autism spectrum disorder 48 and obsessive-compulsive disorder 49 . Our results suggest that decreased modularity or increased flexibility of these networks following psilocybin therapy is a key component of its therapeutic mechanism of action.…”

“…In addition to the DMN, other higher-order brain networks such as the executive network (EN) and salience network (SN) have been implicated in depression 14,17 . These networks are associated with 'cognitive control' and internal versus external attention switching [18][19][20] . Such attentional switching is often impaired in depression 21 .…”

Quantifying brain state transition cost via Schrödinger bridge

“…However, few studies have quantified the switch cost from brain activity. A recent work suggests that task switching involves the reconfiguration of brain-wide functional connectivity 46 . Our framework may be used as a quantitative method for measuring switch cost.…”

Decreased brain modularity after psilocybin therapy for depression.

“…The EN and SN have been associated with tasks requiring cognitive exibility such as, planning 65 , learning 66 and task-switching 24,25 ; impaired functioning of these networks have been reported in depression 21,53 , and other disorders exhibiting cognitive in exibility such as traumatic brain injury 67 , autism spectrum disorder 68 and obsessive-compulsive disorder 69 . Our results suggest that decreased modularity, or increased exibility, of EN regions, following psilocybin therapy, is a key component of its therapeutic mechanism of action.…”

“…In addition to the DMN, other higher-order brain networks such as the executive (EN) and salience networks (SN) have been implicated in depression [21][22][23] . These networks are associated with the 'cognitive control' of thoughts and attention switching 24,25 between introspective thought and an external focus 26 . Such attentional switching is impaired in depression 27 .…”