Cited by 1,721Visual perception and processing mechanismsNeural and Behavioral Psychology StudiesMotor Control and Adaptation

Neural correlates of decision variables in parietal cortex

Platt, Michael L., Glimcher, Paul W.·1999·Nature

Abstract

Decision theory proposes that humans and animals decide what to do in a given situation by assessing the relative value of each possible response. This assessment can be computed, in part, from the probability that each action will result in a gain and the magnitude of the gain expected. Here we show that the gain (or reward) a monkey can expect to realize from an eye-movement response modulates the activity of neurons in the lateral intraparietal area, an area of primate cortex that is thought to transform visual signals into eye-movement commands. We also show that the activity of these neurons is sensitive to the probability that a particular response will result in a gain. When animals can choose freely between two alternative responses, the choices subjects make and neuronal activation in this area are both correlated with the relative amount of gain that the animal can expect from each response. Our data indicate that a decision-theoretic model may provide a powerful new framework for studying the neural processes that intervene between sensation and action.

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Crossref · 10.1038/22268

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  • The dlPFC and parietal cortex have reciprocal projections with the dACC.

    “The dlPFC and parietal cortex have reciprocal projections with the dACC”
  • LIP neurons are hypothesized to encode the attentional salience or expected value of a visual saccade target, but these concepts cannot explain the pattern of LIP activity in the experiment.

    “LIP neurons are hypothesized to encode the attentional salience or expected value of a visual saccade target (52, 53, 63), but these concepts cannot explain the pattern of LIP activity in our experiment.”
  • The changes in sensory-driven LIP responses with training did not appear to reflect changes in other motor or motivational parameters known to modulate LIP activity.

    “The changes in sensory-driven LIP responses with training also did not appear to reflect changes in other motor (Fig. 5, middle) or motivational parameters (Fig. 5, right) known to modulate LIP activity21, 22.”
  • LIP plays a multitude of cognitive and sensory-motor roles.

    “LIP plays a multitude of cognitive and sensory-motor roles that could, in principle, change during training and account for the changes in LIP responses during motion viewing 20–22.”
  • Previous studies have shown that LIP responses are modulated by many factors, such as attention, expectation, time, motor intention, experienced value, reward, and the prior probability of making an eye movement.

    “In addition, previous studies have shown that LIP responses are modulated by many factors, such as attention, expectation, time, motor intention, experienced value, reward, and the prior probability of making an eye movement12,13,39–42.”

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Authors
Platt, M. L., & Glimcher, P. W.
Affiliations
New York University (US)
Corresponding author
Platt, Michael L.
Venue
Nature
Published
1999-07
Volume
400
Issue
6741
Pages
233-238
ISSN
  • 0028-0836 (ISSN-L)
  • 1476-4687
OpenAlex
W2107886772
Cited by
1,721
References
40
Citations by year
2026: 24 · 2025: 33 · 2024: 41 · 2023: 41 · 2022: 54 · 2021: 51 · 2020: 53 · 2019: 75 · 2018: 52 · 2017: 56 · 2016: 57 · 2015: 82 · 2014: 82 · 2013: 113 · 2012: 101
FWCI
14.32
Type
journal article
Language
en
Open access
closed
Locations
  • Nature (publishedVersion)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
Keywords
decision-making, lateral intraparietal area, parietal cortex, reward magnitude, response probability, eye movements, decision variables, decision-theoretic model
MeSH terms
Animals, Color Perception, Decision Making, Eye Movements, Fixation, Ocular, Macaca, Models, Neurological, Motor Neurons, Neurons, Neurons, Afferent, Parietal Lobe, Probability, Reward

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