Cross-hemispheric recruitment during action planning with increasing task demand.

The recruitment of cross-hemispheric counterparts of lateralized prefrontal brain regions with increasing processing demand is thought to increase memory performance despite cognitive aging, but was recently reported to be present also in young adults working at their capacity limit. Here we ask if cross-hemispheric recruitment is a general strategy of the adult brain in that executive task demand would modulate bilateral activation beyond prefrontal cortex and across cognitive tasks. We analyzed data sets from two fMRI experiments investigating retrospective working memory maintenance and prospective action planning. We confirmed a cross-hemispheric recruitment of prefrontal cortex across tasks and experiments. Changes in lateralization due to planning further surfaced in the cerebellum, dorsal premotor and posterior parietal cortex. Parietal cortex thereby exhibited cross-hemispheric recruitment also during spatial but not verbal working memory maintenance. Our results confirm a domain-general role of prefrontal cortex in cross-hemispheric recruitment. They further suggest that other task-specific brain regions also recruit their idling cross-hemispheric counterparts to relocate executive processing power.

Bounded rational decision-making models suggest capacity-limited concurrent motor planning in human posterior parietal and frontal cortex.

While traditional theories of sensorimotor processing have often assumed a serial decision-making pipeline, more recent approaches have suggested that multiple actions may be planned concurrently and vie for execution. Evidence for the latter almost exclusively stems from electrophysiological studies in posterior parietal and premotor cortex of monkeys. Here we study concurrent prospective motor planning in humans by recording functional magnetic resonance imaging (fMRI) during a delayed response task engaging movement sequences towards multiple potential targets. We find that also in human posterior parietal and premotor cortex delay activity modulates both with sequence complexity and the number of potential targets. We tested the hypothesis that this modulation is best explained by concurrent prospective planning as opposed to the mere maintenance of potential targets in memory. We devise a bounded rationality model with information constraints that optimally assigns information resources for planning and memory for this task and determine predicted information profiles according to the two hypotheses. When regressing delay activity on these model predictions, we find that the concurrent prospective planning strategy provides a significantly better explanation of the fMRI-signal modulations. Moreover, we find that concurrent prospective planning is more costly and thus limited for most subjects, as expressed by the best fitting information capacities. We conclude that bounded rational decision-making models allow relating both behavior and neural representations to utilitarian task descriptions based on bounded optimal information-processing assumptions.

Quantifying Motor Task Performance by Bounded Rational Decision Theory.

Expected utility models are often used as a normative baseline for human performance in motor tasks. However, this baseline ignores computational costs that are incurred when searching for the optimal strategy. In contrast, bounded rational decision-theory provides a normative baseline that takes computational effort into account, as it describes optimal behavior of an agent with limited information-processing capacity to change a prior motor strategy (before information-processing) into a posterior strategy (after information-processing). Here, we devised a pointing task where subjects had restricted reaction and movement time. In particular, we manipulated the permissible reaction time as a proxy for the amount of computation allowed for planning the movements. Moreover, we tested three different distributions over the target locations to induce different prior strategies that would influence the amount of required information-processing. We found that movement endpoint precision generally decreases with limited planning time and that non-uniform prior probabilities allow for more precise movements toward high-probability targets. Considering these constraints in a bounded rational decision model, we found that subjects were generally close to bounded optimal. We conclude that bounded rational decision theory may be a promising normative framework to analyze human sensorimotor performance.