The optimisation of functional brain network dynamics when learning to perform complex tasks

We present two novel self-ordered switching (SOS) fMRI paradigms designed to investigate how brain networks facilitate the establishment of structured human behaviour during the learning of complex tasks with multiple goals. In study 1, SOS was performed with minimal pretraining and detailed feedback to capture the learning process, while in study 2 substantial pretraining and minimal feedback were used as a control where the potential for ongoing optimisation of behaviour is reduced. Study 1 revealed changes in the learning process characterised by a decrease in task-switching frequency, resulting in superior task performance for individuals who minimised switch frequency and ordered their behaviour in simple structured routines. Additionally, with practice, multiple-demand cortex activation became less responsive, and the default mode network became more responsive when performing discrimination trials. Strikingly, the opposite pattern was observed for SOS events, with multiple-demand cortex activation becoming more responsive and default mode network activation becoming less responsive with practice. These neural changes correlated with the degree of structure of behavioural routines. The neural signatures of learning were less evident in study 2, where the task was practiced prior to entering the scanner. Our studies demonstrate that the default mode network and multiple demand cortex complement each other when people learn to perform complex tasks by becoming differentially fine-tuned to routine trial demands vs. executive-switching demands.