Dataset Information

Operant matching is a generic outcome of synaptic plasticity based on the covariance between reward and neural activity.

ABSTRACT: The probability of choosing an alternative in a long sequence of repeated choices is proportional to the total reward derived from that alternative, a phenomenon known as Herrnstein's matching law. This behavior is remarkably conserved across species and experimental conditions, but its underlying neural mechanisms still are unknown. Here, we propose a neural explanation of this empirical law of behavior. We hypothesize that there are forms of synaptic plasticity driven by the covariance between reward and neural activity and prove mathematically that matching is a generic outcome of such plasticity. Two hypothetical types of synaptic plasticity, embedded in decision-making neural network models, are shown to yield matching behavior in numerical simulations, in accord with our general theorem. We show how this class of models can be tested experimentally by making reward not only contingent on the choices of the subject but also directly contingent on fluctuations in neural activity. Maximization is shown to be a generic outcome of synaptic plasticity driven by the sum of the covariances between reward and all past neural activities.

SUBMITTER: Loewenstein Y

PROVIDER: S-EPMC1622804 | biostudies-literature | 2006 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Operant matching is a generic outcome of synaptic plasticity based on the covariance between reward and neural activity.

Loewenstein Yonatan Y Seung H Sebastian HS

Proceedings of the National Academy of Sciences of the United States of America 20060928 41

The probability of choosing an alternative in a long sequence of repeated choices is proportional to the total reward derived from that alternative, a phenomenon known as Herrnstein's matching law. This behavior is remarkably conserved across species and experimental conditions, but its underlying neural mechanisms still are unknown. Here, we propose a neural explanation of this empirical law of behavior. We hypothesize that there are forms of synaptic plasticity driven by the covariance between ...[more]

PMID: 17008410

Similar Datasets

Project description:Reward-processing involves two temporal stages characterized by two distinct neural processes: reward-anticipation and reward-outcome. Intriguingly, very little research has examined the relationship between neural processes involved in reward-anticipation and reward-outcome. To investigate this, one needs to consider the heterogeneity of reward-processing within each stage. To identify different stages of reward processing, we adapted a reward time-estimation task. While EEG data were recorded, participants were instructed to button-press 3.5s after the onset of an Anticipation-Cue and received monetary reward for good time-estimation on the Reward trials, but not on No-Reward trials. We first separated reward-anticipation into event related potentials (ERPs) occurring at three sub-stages: reward/no-reward cue-evaluation, motor-preparation and feedback-anticipation. During reward/no-reward cue-evaluation, the Reward-Anticipation Cue led to a smaller N2 and larger P3. During motor-preparation, we report, for the first time, that the Reward-Anticipation Cue enhanced the Readiness Potential (RP), starting approximately 1s before movement. At the subsequent feedback-anticipation stage, the Reward-Anticipation Cue elevated the Stimulus-Preceding Negativity (SPN). We also separated reward-outcome ERPs into different components occurring at different time-windows: the Feedback-Related Negativity (FRN), Feedback-P3 (FB-P3) and Late-Positive Potentials (LPP). Lastly, we examined the relationship between reward-anticipation and reward-outcome ERPs. We report that individual-differences in specific reward-anticipation ERPs uniquely predicted specific reward-outcome ERPs. In particular, the reward-anticipation Early-RP (1-.8s before movement) predicted early reward-outcome ERPs (FRN and FB-P3), whereas, the reward-anticipation SPN most strongly predicted a later reward-outcome ERP (LPP). Results have important implications for understanding the nature of the relationship between reward-anticipation and reward-outcome neural-processes.

Dataset Information

Operant matching is a generic outcome of synaptic plasticity based on the covariance between reward and neural activity.

Publications

Operant matching is a generic outcome of synaptic plasticity based on the covariance between reward and neural activity.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets