Literature DB >> 25411459

Dopamine neurons encode errors in predicting movement trigger occurrence.

Benjamin Pasquereau1, Robert S Turner2.   

Abstract

The capacity to anticipate the timing of events in a dynamic environment allows us to optimize the processes necessary for perceiving, attending to, and responding to them. Such anticipation requires neuronal mechanisms that track the passage of time and use this representation, combined with prior experience, to estimate the likelihood that an event will occur (i.e., the event's "hazard rate"). Although hazard-like ramps in activity have been observed in several cortical areas in preparation for movement, it remains unclear how such time-dependent probabilities are estimated to optimize response performance. We studied the spiking activity of dopamine neurons in the substantia nigra pars compacta of monkeys during an arm-reaching task for which the foreperiod preceding the "go" signal varied randomly along a uniform distribution. After extended training, the monkeys' reaction times correlated inversely with foreperiod duration, reflecting a progressive anticipation of the go signal according to its hazard rate. Many dopamine neurons modulated their firing rates as predicted by a succession of hazard-related prediction errors. First, as time passed during the foreperiod, slowly decreasing anticipatory activity tracked the elapsed time as if encoding negative prediction errors. Then, when the go signal appeared, a phasic response encoded the temporal unpredictability of the event, consistent with a positive prediction error. Neither the anticipatory nor the phasic signals were affected by the anticipated magnitudes of future reward or effort, or by parameters of the subsequent movement. These results are consistent with the notion that dopamine neurons encode hazard-related prediction errors independently of other information.
Copyright © 2015 the American Physiological Society.

Entities:  

Keywords:  anticipation; dopamine; hazard rate; prediction error

Mesh:

Year:  2014        PMID: 25411459      PMCID: PMC4329436          DOI: 10.1152/jn.00401.2014

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  82 in total

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  10 in total

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Review 5.  Model-based predictions for dopamine.

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Review 7.  What does dopamine mean?

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8.  Tamping Ramping: Algorithmic, Implementational, and Computational Explanations of Phasic Dopamine Signals in the Accumbens.

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Review 10.  Synchronicity: The Role of Midbrain Dopamine in Whole-Brain Coordination.

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  10 in total

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