TY - JOUR
T1 - Decoding and perturbing decision states in real time
AU - Peixoto, Diogo
AU - Verhein, Jessica R.
AU - Kiani, Roozbeh
AU - Kao, Jonathan C.
AU - Nuyujukian, Paul
AU - Chandrasekaran, Chandramouli
AU - Brown, Julian
AU - Fong, Sania
AU - Ryu, Stephen I.
AU - Shenoy, Krishna V.
AU - Newsome, William T.
N1 - Funding Information:
Acknowledgements We thank all members of the Newsome and Shenoy labs at Stanford University for comments on the methods and results throughout the execution of the project. D.P. was supported by the Champalimaud Foundation, Portugal and Howard Hughes Medical Institute. J.R.V. was supported by Stanford MSTP NIH training grant 4T32GM007365 and supported by the Howard Hughes Medical Institute. R.K. was supported by Simons Collaboration on the Global Brain grant 542997, Pew Scholarship in Biomedical Sciences, National Institutes of Health Award R01MH109180 and a McKnight Scholars Award. J.C.K. was supported by NSF graduate research fellowship. P.N. was supported by NIDCD award R01DC014034. C.C. was supported by K99NS092972 and 4R00NS092972-03 award from the NINDS and supported as a research specialist by the Howard Hughes Medical Institute. J.B. and S.F. were supported by the Howard Hughes Medical Institute. K.V.S. was supported by the following awards: NIH Director’s Pioneer Award 8DP1HD075623, DARPA-BTO ‘NeuroFAST’ award W911NF-14-2-0013, the Simons Foundation Collaboration on the Global Brain awards 325380 and 543045, and ONR award N000141812158. W.T.N. and K.V.S. were supported by the Howard Hughes Medical Institute.
Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Nature Limited.
PY - 2021/3/25
Y1 - 2021/3/25
N2 - 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.
AB - 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.
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U2 - 10.1038/s41586-020-03181-9
DO - 10.1038/s41586-020-03181-9
M3 - Article
C2 - 33473215
AN - SCOPUS:85099533909
SN - 1465-7392
VL - 591
SP - 604
EP - 609
JO - Nature Cell Biology
JF - Nature Cell Biology
IS - 7851
ER -