Persistent coding of outcome-predictive cue features in the rat nucleus accumbens
Abstract
The nucleus accumbens (NAc) is important for learning from feedback, and for biasing and invigorating behavior in response to cues that predict motivationally relevant outcomes. NAc encodes outcome-related cue features such as the magnitude and identity of reward. However, little is known about how features of cues themselves are encoded. We designed a decision making task where rats learned multiple sets of outcome-predictive cues, and recorded single-unit activity in the NAc during performance. We found that coding of cue identity and location occurred alongside coding of expected outcome. Furthermore, this coding persisted both during a delay period, after the rat made a decision and was waiting for an outcome, and after the outcome was revealed. Encoding of cue features in the NAc may enable contextual modulation of ongoing behavior, and provide an eligibility trace of outcome-predictive stimuli for updating stimulus-outcome associations to inform future behavior.
Data availability
Preprocessed data and data analysis code, sufficient to reproduce the results in the paper, are available on this public GitHub repository: https://github.com/jgmaz/vStrCueCodingPaper (commit 56c5f52).
Article and author information
Author details
Funding
Natural Sciences and Engineering Research Council of Canada
- James E Carmichael
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: All experimental procedures were approved by the the University of Waterloo Animal Care Committee (protocol# 11-06) and carried out in accordance with Canadian Council for Animal Care (CCAC) guidelines.
Copyright
© 2018, Gmaz et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 1,928
- views
Views, downloads and citations are aggregated across all versions of this paper published by eLife.