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Decoding and perturbing decision states in real time

Author

Listed:
  • Diogo Peixoto

    (Stanford University
    Champalimaud Neuroscience Programme
    Stanford University)

  • Jessica R. Verhein

    (Stanford University
    Stanford University
    Stanford University School of Medicine)

  • Roozbeh Kiani

    (New York University)

  • Jonathan C. Kao

    (Stanford University
    Stanford University
    University of California, Los Angeles
    University of California, Los Angeles)

  • Paul Nuyujukian

    (Stanford University
    Stanford University
    Stanford University
    Stanford University)

  • Chandramouli Chandrasekaran

    (Stanford University
    Stanford University
    Stanford University
    Boston University)

  • Julian Brown

    (Stanford University
    Stanford University)

  • Sania Fong

    (Stanford University
    Stanford University)

  • Stephen I. Ryu

    (Stanford University
    Palo Alto Medical Foundation)

  • Krishna V. Shenoy

    (Stanford University
    Stanford University
    Stanford University
    Stanford University)

  • William T. Newsome

    (Stanford University
    Stanford University
    Stanford University)

Abstract

In dynamic environments, subjects often integrate multiple samples of a signal and combine them to reach a categorical judgment1. The process of deliberation can be described by a time-varying decision variable (DV), decoded from neural population activity, that predicts a subject’s upcoming decision2. Within single trials, however, there are large moment-to-moment fluctuations in the DV, the behavioural significance of which is unclear. Here, using real-time, neural feedback control of stimulus duration, we show that within-trial DV fluctuations, decoded from motor cortex, are tightly linked to decision state in macaques, predicting behavioural choices substantially better than the condition-averaged DV or the visual stimulus alone. Furthermore, robust changes in DV sign have the statistical regularities expected from behavioural studies of changes of mind3. Probing the decision process on single trials with weak stimulus pulses, we find evidence for time-varying absorbing decision bounds, enabling us to distinguish between specific models of decision making.

Suggested Citation

  • Diogo Peixoto & Jessica R. Verhein & Roozbeh Kiani & Jonathan C. Kao & Paul Nuyujukian & Chandramouli Chandrasekaran & Julian Brown & Sania Fong & Stephen I. Ryu & Krishna V. Shenoy & William T. Newso, 2021. "Decoding and perturbing decision states in real time," Nature, Nature, vol. 591(7851), pages 604-609, March.
    • Handle: RePEc:nat:nature:v:591:y:2021:i:7851:d:10.1038_s41586-020-03181-9
    DOI: 10.1038/s41586-020-03181-9
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    Cited by:

    1. J. Tyler Boyd-Meredith & Alex T. Piet & Emily Jane Dennis & Ahmed El Hady & Carlos D. Brody, 2022. "Stable choice coding in rat frontal orienting fields across model-predicted changes of mind," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    2. Pierre O. Boucher & Tian Wang & Laura Carceroni & Gary Kane & Krishna V. Shenoy & Chandramouli Chandrasekaran, 2023. "Initial conditions combine with sensory evidence to induce decision-related dynamics in premotor cortex," Nature Communications, Nature, vol. 14(1), pages 1-28, December.

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