A DecisionMaking Model Based on Basal Ganglia Account of Action Prediction Reinforcement learning offers robotics a framework for the design of sophisticated behaviors. The theory of it is deeply rooted in psychological and neuroscientific perspectives. The basal ganglia, thalamus and cerebral cortex constitute an important neural decision circuit involving in the behavioral choice of reinforcement learning. However, the influence of the changes of various nucleuses in the basal ganglia on decisionmaking is still unclear. Considering the complexity and difficulty of brain experiments on both animals and humans, it is necessary to establish a neural computing model. This paper builds a decisionmaking model based on physiology and anatomy of basal ganglia. The feasibility of the model was verified by comparing the behavior data from experiments and simulated by the model as well as readiness potentials and discharges rate of nucleus. Moreover, the simulation data were then used to further analyze the effects of conflict, dopamine, and subthalamic nucleus changes on behavioral accuracy and response. The results show this model opens a window for exploring specific neural mechanisms associated with basal gangliarelated decisions.

Anterior insula reflects surprise in valuebased decisionmaking and perception Abstract   The brain has been theorized to employ inferential processes to overcome the problem of uncertainty. Inference is thought to underlie neural processes, including in disparate domains such as valuebased decisionmaking and perception. Valuebased decisionmaking commonly involves deliberation, a timeconsuming process that requires conscious consideration of decision variables. Perception, by contrast, is thought to be automatic and effortless. Both processes may call on a general neural system to resolve for uncertainty however. We addressed this question by directly comparing uncertainty signals in visual perception and an economic task using fMRI. We presented the same individuals with different versions of a bistable figure (Neckeru0027s cube) and with a gambling task during fMRI acquisition. We experimentally varied uncertainty, either on perceptual state or financial outcome. We found that inferential errors indexed by a formal account of surprise in the gambling task yielded BOLD responses in the anterior insula, in line with earlier findings. Moreover, we found perceptual uncertainty and surprise in the Necker Cube task yielded similar responses in the anterior insula. These results suggest that uncertainty, irrespective of domain, correlates to a common brain region, the anterior insula. These findings provide empirical evidence that the brain interacts with its environment through inferential processes.