Temporal Coding of Reward Value in Monkey Ventral Striatal Tonically Active Neurons

The Journal of Neuroscience : the Official Journal of the Society for Neuroscience
Rossella FalconeB J Richmond

Abstract

The rostromedioventral striatum is critical for behavior dependent on evaluating rewards. We asked what contribution tonically active neurons (TANs), the putative striatal cholinergic interneurons, make in coding reward value in this part of the striatum. Two female monkeys were given the option to accept or reject an offered reward in each trial, the value of which was signaled by a visual cue. Forty-five percent of the TANs use temporally modulated activity to encode information about discounted value. These responses were significantly better represented using principal component analysis than by just counting spikes. The temporal coding is straightforward: the spikes are distributed according to a sinusoidal envelope of activity that changes gain, ranging from positive to negative according to discounted value. Our results show that the information about the relative value of an offered reward is temporally encoded in neural spike trains of TANs. This temporal coding may allow well tuned, coordinated behavior to emerge.SIGNIFICANCE STATEMENT Ever since the discovery that neurons use trains of pulses to transmit information, it seemed self-evident that information would be encoded into the pattern of the spikes. However, the...Continue Reading

Related Concepts

Related Feeds

Basal Ganglia

Basal Ganglia are a group of subcortical nuclei in the brain associated with control of voluntary motor movements, procedural and habit learning, emotion, and cognition. Here is the latest research.

Related Papers

The Journal of Neuroscience : the Official Journal of the Society for Neuroscience
Simon Nougaret, Sabrina Ravel
The Journal of Neuroscience : the Official Journal of the Society for Neuroscience
Paul ApicellaEric Legallet
The Journal of Neuroscience : the Official Journal of the Society for Neuroscience
Eric Garr
© 2021 Meta ULC. All rights reserved