Dissociable forms of uncertainty-driven representational change across the human brain.

Environmental change can lead decision makers to shift rapidly among different behavioral regimes. These behavioral shifts can be accompanied by rapid changes in the firing pattern of neural networks. However, it is unknown what the populations of neurons that participate in such "network reset" phenomena are representing. Here we examined 1) whether and where rapid changes in multivariate activity patterns are observable with fMRI during periods of rapid behavioral change, and 2) what types of representations give rise to these phenomena. We did so by examining fluctuations in multi-voxel patterns of BOLD activity from male and female human subjects making sequential inferences about the state of a partially observable and discontinuously changing variable. We found that, within the context of this sequential inference task, the multivariate patterns of activity in a number of cortical regions contain representations that change more rapidly during periods of uncertainty following a change in behavioral context. In motor cortex, this phenomenon was indicative of discontinuous change in behavioral outputs, whereas in visual regions the same basic phenomenon was evoked by tracking of salient environmental changes. In most other cortical regions, including dorsolateral prefrontal and anterior cingulate cortex, the phenomenon was most consistent with directly encoding the degree of uncertainty. However, in a few other regions, including orbitofrontal cortex, the phenomenon was best explained by representations of a shifting context that evolve more rapidly during periods of rapid learning. These representations may provide a dynamic substrate for learning that facilitates rapid disengagement from learned responses during periods of change. SIGNIFICANCE STATEMENT Brain activity patterns tend to change more rapidly during periods of uncertainty and behavioral adjustment, yet the computational role of such rapid transitions is poorly understood. Here we identify brain regions with fMRI BOLD activity patterns that change more rapidly during periods of behavioral adjustment and use computational modeling to attribute the phenomenon to specific causes. We demonstrate that the phenomenon emerges in different brain regions for different computational reasons, the most common being the representation of uncertainty itself, but that in a selective subset of regions including orbitofrontal cortex the phenomenon was best explained as a shifting latent state signal that may serve to control the degree to which recent temporal context affects ongoing expectations.