Year: 2022
Type: article
Abstract: Prospect theory, arguably the most prominent theory of choice, is an obvious candidate for neural valuation models. How the activity of individual neurons, a possible computational unit, obeys prospect theory remains unknown. Here, we show, with theoretical accuracy equivalent to that of human neuroimaging studies, that single-neuron activity in four core reward-related cortical and subcortical regions represents the subjective valuation of risky gambles in monkeys. The activity of individual neurons in monkeys passively viewing a lottery reflects the desirability of probabilistic rewards parameterized as a multiplicative combination of utility and probability weighting functions, as in the prospect theory framework. The diverse patterns of valuation signals were not localized but distributed throughout most parts of the reward circuitry. A network model aggregating these signals reconstructed the risk preferences and subjective probability weighting revealed by the animals' choices. Thus, distributed neural coding explains the computation of subjective valuations under risk.
Source: Nature Communications
Language: English
Subfield: General Decision Sciences
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $5,890
Awards: G4133443254, Neural mehcanisms underlying behavioral regulation based on physiological needs: model animal study, G6246161379, Neural basis for value-based decision making and physiological needs, Neural Implementation of Dynamic Probabilistic Information Processing in Irregular Sensorimotor Synchronization, Neuroeconomic foundations of probability and value perception, Microscopic probabilistic information processing inferred from a macroscopic bias in sensory-motor interaction, G8980086550
OpenAlex ID: W4301395244