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Published September 20, 2019 | Supplemental Material + Submitted
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Neural precursors of deliberate and arbitrary decisions in the study of voluntary action

Abstract

The readiness potential (RP)--a key ERP correlate of upcoming action--is known to precede subjects' reports of their decision to move. Some view this as evidence against a causal role for consciousness in human decision-making and thus against free-will. Yet those studies focused on arbitrary decisions--purposeless, unreasoned, and without consequences. It remains unknown to what degree the RP generalizes to deliberate, more ecological decisions. We directly compared deliberate and arbitrary decision-making during a $1000-donation task to non-profit organizations. While we found the expected RPs for arbitrary decisions, they were strikingly absent for deliberate ones. Our results and drift-diffusion model are congruent with the RP representing accumulation of noisy, random fluctuations that drive arbitrary--but not deliberate--decisions. They further point to different neural mechanisms underlying deliberate and arbitrary decisions, challenging the generalizability of studies that argue for no causal role for consciousness in decision-making to real-life decisions.

Additional Information

The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. bioRxiv preprint first posted online Jan. 1, 2017. We thank Ralph Adolphs for his invaluable guidance and support in designing and running the experiment as well as for very useful discussions of the results. We thank Ram Rivlin for various conceptual discussions about deliberate versus arbitrary decision-making and about the initial experimental paradigm design. We thank Caitlin Duncan for her help in patiently and meticulously gathering the EEG data. We thank Daw-An Wu for discussions about EEG data collection and preprocessing and for his help with actual data collection. We thank Daniel Grossman for his help in carefully preprocessing the data and suggesting potential interpretations of it. We thank Aaron Schurger and Ueli Rutishauser for various discussions about the model and its simulations. We thank Shlomit Yuval-Greenberg and Leon Deouell for important discussions about EEG processing and analysis. Last, we thank the anonymous reviewers for their invaluable comments, which greatly improved this manuscript. Funding: This publication was made possible through the support of a joint grant from the John Templeton Foundation and the Fetzer Institute to U.M, L.M. and G.Y.. The opinions expressed in this publication are those of the author(s) and do not necessarily reflect the views of the John Templeton Foundation or the Fetzer Institute. This research was also supported by Florida State University's Big Questions in Free Will Initiative, funded by the John Templeton Foundation, to U.M., G.Y., and C.K.; by the Ralph Schlaeger Charitable Foundation to U.M.; by the Bial Foundation – Grant number 388/14 to U.M. and L.M.; and by the German-Israeli Foundation for Scientific Research and Development to L.M.. C.K. thanks the Allen Institute founders, Paul G. Allen and Jody Allen, for their vision, encouragement, and support. Author contributions: U.M, L.M, G.Y., and C.K. conceived the project and designed the experiments. L.M. and U.M. analyzed the results. U.M. designed and simulated the model. L.M. and U.M. wrote the manuscript. G.Y. and C.K. suggested revisions to the manuscript. The authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper. Additional data related to this paper may be requested from the authors.

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Supplemental Material - 097626-1.pdf

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Created:
September 15, 2023
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October 23, 2023