Orbitofrontal cortex computations in a systems-level perspective

Abstract

This chapter describes some of the computational approaches that are useful to understand the functions of the orbitofrontal cortex. Section 9.1 describes the operation of pattern association networks which may be used in the orbitofrontal cortex to associate the sight of a stimulus with its taste. Section 9.2 describes the operation of autoassociation or attractor networks which may be used in the orbitofrontal cortex to maintain a rule online by continuing neuronal firing. Section 9.3 describes the operation of the integrate-and-fire attractor network used to model probabilistic decision-making. Section 9.4 describes a neurophysiological and computational model for stimulus-reinforcer association learning and reversal in the orbitofrontal cortex. Section 9.5 describes a theory and model of how non-reward neurons are produced in the orbitofrontal cortex.