Parsing Heterogeneous Striatal Activity

Kae Nakamura, Long Ding

The striatum is an input channel of the basal ganglia and is well known to be involved in reward-based decision making and learning. At the macroscopic level, the striatum has been postulated to contain parallel functional modules, each of which includes neurons that perform similar computations to support selection of appropriate actions for different task contexts. At the single-neuron level, however, recent studies in monkeys and rodents have revealed heterogeneity in neuronal activity even within restricted modules of the striatum. Looking for generality in the complex striatal activity patterns, here we briefly survey several types of striatal activity, focusing on their usefulness for mediating behaviors. In particular, we focus on two types of behavioral tasks: reward-based tasks that use salient sensory cues and manipulate outcomes associated with the cues; and perceptual decision tasks that manipulate the quality of noisy sensory cues and associate all correct decisions with the same outcome. Guided by previous insights on the modular organization and general selection-related functions of the basal ganglia, we relate striatal activity patterns on these tasks to two types of computations: implementation of selection and evaluation. We suggest that a parsing with the selection/evaluation categories encourages a focus on the functional commonalities revealed by studies with different animal models and behavioral tasks, instead of a focus on aspects of striatal activity that may be specific to a particular task setting. We then highlight several questions in the selection-evaluation framework for future explorations.