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Evidence accumulation occurs locally in the parietal cortex

Author

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  • Zhewei Zhang

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Chaoqun Yin

    (Chinese Academy of Sciences)

  • Tianming Yang

    (Chinese Academy of Sciences)

Abstract

Decision making often entails evidence accumulation, a process that is represented by neural activities in a network of multiple brain areas. Yet, it has not been identified where exactly the accumulation originates. We reason that a candidate brain area should both represent evidence accumulation and information that is used to compute evidence. Therefore, we designed a two-stage probabilistic reasoning task in which the evidence for accumulation had to be first determined from sensory signals orthogonal to decisions. With a linear encoding model, we decomposed the responses of posterior parietal neurons to each stimulus into an early and a late component that represented two dissociable stages of decision making. The former reflected the transformation from sensory inputs to accumulable evidence, and the latter reflected the accumulation of evidence and the formation of decisions. The presence of both computational stages indicates that evidence accumulation signal in the parietal cortex is computed locally.

Suggested Citation

  • Zhewei Zhang & Chaoqun Yin & Tianming Yang, 2022. "Evidence accumulation occurs locally in the parietal cortex," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-32210-6
    DOI: 10.1038/s41467-022-32210-6
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    References listed on IDEAS

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    1. Joshua I. Gold & Michael N. Shadlen, 2000. "Representation of a perceptual decision in developing oculomotor commands," Nature, Nature, vol. 404(6776), pages 390-394, March.
    2. Tianming Yang & Michael N. Shadlen, 2007. "Probabilistic reasoning by neurons," Nature, Nature, vol. 447(7148), pages 1075-1080, June.
    3. Michael L. Platt & Paul W. Glimcher, 1999. "Neural correlates of decision variables in parietal cortex," Nature, Nature, vol. 400(6741), pages 233-238, July.
    4. Camillo Padoa-Schioppa & John A. Assad, 2006. "Neurons in the orbitofrontal cortex encode economic value," Nature, Nature, vol. 441(7090), pages 223-226, May.
    5. Louis J. Toth & John A. Assad, 2002. "Dynamic coding of behaviourally relevant stimuli in parietal cortex," Nature, Nature, vol. 415(6868), pages 165-168, January.
    6. Mattia Rigotti & Omri Barak & Melissa R. Warden & Xiao-Jing Wang & Nathaniel D. Daw & Earl K. Miller & Stefano Fusi, 2013. "The importance of mixed selectivity in complex cognitive tasks," Nature, Nature, vol. 497(7451), pages 585-590, May.
    7. A. B. Sereno & J. H. R. Maunsell, 1998. "Shape selectivity in primate lateral intraparietal cortex," Nature, Nature, vol. 395(6701), pages 500-503, October.
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