PROJECT SUMMARY/ABSTRACT Humans have a uniquely developed ability to impose internal goals on how they interact with their environment. Referred to as “cognitive control”, this capacity includes two core components: (1) the ability to focus attention on currently goal-relevant stimulus features and responses (a “task set”) while ignoring task-irrelevant features (cognitive stability); and (2) the ability to switch to a different task set when circumstances change (cognitive flexibility). Crucially, to thrive in a dynamic environment, we need to continuously adapt our levels of cognitive stability and flexibility to suit changing demands. E.g., when cooking a meal, needs for stability (e.g., a strong task-focus when slicing onion) and flexibility (e.g., rapid shifting between recipe reading and stovetop monitoring) change frequently over time. The strategic regulation of stability and flexibility is thus fundamental for success in everyday life, and is in fact severely impaired in many clinical conditions. However, the underlying neurocognitive mechanisms are poorly understood. This is due to the fact that, while there are large literatures on cognitive stability (in the shape of conflict-control studies) and flexibility (in the shape of task-switching studies), these processes have been either investigated in isolation, conflated, or not interrogated in terms of their dynamic adaptation. The present proposal seeks to overcome these barriers to progress by combining a novel task protocol that assesses simultaneous and independent adaptive shifts in stability and flexibility with computational modeling, functional magnetic resonance imaging (fMRI), and intracranial electro- encephalography (iEEG). Our overall goal is to characterize the neurocognitive mechanisms of concurrent, strategic control over cognitive stability and flexibility. We triangulate this goal via three aims: Aim 1 seeks to establish the first computational model of concurrent stability and flexibility regulation by fitting and simulating behavioral data from protocols with time-varying demands on stability and flexibility (Studies 1 and 2). Our working model consists of two independent reinforcement learners making trial-by-trial predictions about forthcoming demands on stability (conflict- likelihood) and flexibility (switch-likelihood), which in turn modulate distinct within-trial drift-diffusion model parameters. Aim 2 employs the winning model to determine the neural mechanisms mediating these adjustments in stability and flexibility. Building on a large prior literature, we use complementary fMRI (Study 3) and iEEG (Study 4) approaches to test specific neuroanatomical hypotheses about the respective roles of the lateral prefrontal, posterior parietal, and anterior cingulate cortex, as well as the basal ganglia, in supporting the proactive adaptation of stability and flexibility to time-varying demands. Finally, Aim 3 will use fMRI to characterize the neural reinstatement of c...