Context-Sensitive Computational Mechanisms of Decision Making

Abstract

Real-world information is primarily sensory in nature, and understandably people attach value to the sensory information to prepare for appropriate behavioral responses. This review presents research from value-based, perceptual, and social decision-making domains, so far studied using isolated paradigms and their corresponding computational models. For example, in perceptual decision making, the sensory evidence accumulation rather than value computation becomes central to choice behavior. Furthermore, we identify cross-linkages between the perceptual and value-based domains to help us better understand generic processes pertaining to individual decision making. The purpose of this review is 2-fold. First, we identify the need for integrated study of different domains of decision making. Second, given that both our perception and valuation are influenced by the surrounding context, we suggest the integration of different types of information in decision making could be done by studying contextual influences in decision making. Future research needs to attempt toward a system-level understanding of various subprocesses involved in decision making.

Keywords: Decision making; computational models; neuroeconomics.

Figure 1.

Neural model of decision making. Adapted from Levy and Glimcher.

Figure 2.

Schematic diagram of a drift diffusion model.

Figure 3.

Context gambles. Adapted from Nieuwenhuis et al.