Abstract
Often, when animals encounter an unexpected sensory event, they transition from executing a variety of movements to repeating the movement(s) that may have caused the event. According to a recent theory of action discovery (Redgrave and Gurney, 2006), repetition allows the animal to represent those movements, and the outcome, as an action for later recruitment. The transition from variation to repetition often follows a non-random, structured, pattern. While the structure of the pattern can be explained by sophisticated cognitive mechanisms, simpler mechanisms based on dopaminergic modulation of basal ganglia (BG) activity are thought to underlie action discovery (Redgrave and Gurney, 2006). In this paper we ask the question: can simple BG-mediated mechanisms account for a structured transition from variation to repetition, or are more sophisticated cognitive mechanisms always necessary? To address this question, we present a computational model of BG-mediated biasing of behavior. In our model, unlike most other models of BG function, the BG biases behavior through modulation of cortical response to excitation; many possible movements are represented by the cortical area; and excitation to the cortical area is topographically-organized. We subject the model to simple reaching tasks, inspired by behavioral studies, in which a location to which to reach must be selected. Locations within a target area elicit a reinforcement signal. A structured transition from variation to repetition emerges from simple BG-mediated biasing of cortical response to excitation. We show how the structured pattern influences behavior in simple and complicated tasks. We also present analyses that describe the structured transition from variation to repetition due to BG-mediated biasing and from biasing that would be expected from a type of cognitive biasing, allowing us to compare behavior resulting from these types of biasing and make connections with future behavioral experiments.
Highlights
Animals are capable of executing a huge variety of movements but, importantly, they can discover the specific movements that affect the environment in predictable ways and represent them as actions for later recruitment
In this paper we ask the question, can simple basal ganglia (BG)-mediated mechanisms guide a structured transition from variation to repetition, or must sophisticated cognitive mechanisms always be recruited? To address this question, we present a computational model of BG-mediated biasing of behavior
In this paper we use a biologically-plausible computational model to demonstrate that a structured transition from variation to repetition can emerge from processing within such simple mechanisms
Summary
Animals are capable of executing a huge variety of movements but, importantly, they can discover the specific movements that affect the environment in predictable ways and represent them as actions for later recruitment. Through its influence on the basal ganglia (BG)—a group of interconnected subcortical structures which, in turn, influence cortical activity—the increase in DA activity can help bias the animal to repeat the movements that preceded the unexpected sensory event under the same contextual circumstances. This repetition bias (Redgrave and Gurney, 2006) allows associative networks in the brain to learn and encode the movements as an action because it causes a frequent and reliable presentation of context, movements, and the sensory event as the outcome of those movements
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