Optimization of Decision Making in Multilayer Networks: The Role of Locus Coeruleus

Previous theoretical work has shown that a single layer neural network can implement the optimal decision process for simple, two alternative forced choice (2AFC) tasks. However, it is likely that the mammalian brain is comprised of multilayer networks, raising the question of whether and how optimal performance can be approximated in such an architecture. Here, we present theoretical work suggesting that the noradrenergic nucleus locus coeruleus (LC) may help optimize 2AFC decision making in the brain. This is based on the observations that neurons of the LC selectively fire following the presentation of salient stimuli in decision tasks, and that the corresponding release of norepinephrine can transiently increase the responsivity, or gain, of cortical processing units. We describe computational simulations that investigate the role of such gain changes in optimizing performance of 2AFC decision making. In the tasks we model, no prior cueing or knowledge of stimulus onset time is as...

• Type: Journal
• Year: 2008
• Where: NECO
• Authors: Eric Shea-Brown, Mark S. Gilzenrat, Jonathan D. Cohen
• Keywords: Decision Process, NECO 2008, Single Layer, Theoretical Work