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      Choice history biases subsequent evidence accumulation

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          Abstract

          Perceptual choices depend not only on the current sensory input but also on the behavioral context, such as the history of one’s own choices. Yet, it remains unknown how such history signals shape the dynamics of later decision formation. In models of decision formation, it is commonly assumed that choice history shifts the starting point of accumulation toward the bound reflecting the previous choice. We here present results that challenge this idea. We fit bounded-accumulation decision models to human perceptual choice data, and estimated bias parameters that depended on observers’ previous choices. Across multiple task protocols and sensory modalities, individual history biases in overt behavior were consistently explained by a history-dependent change in the evidence accumulation, rather than in its starting point. Choice history signals thus seem to bias the interpretation of current sensory input, akin to shifting endogenous attention toward (or away from) the previously selected interpretation.

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          Most cited references76

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          Noise in the nervous system.

          Noise--random disturbances of signals--poses a fundamental problem for information processing and affects all aspects of nervous-system function. However, the nature, amount and impact of noise in the nervous system have only recently been addressed in a quantitative manner. Experimental and computational methods have shown that multiple noise sources contribute to cellular and behavioural trial-to-trial variability. We review the sources of noise in the nervous system, from the molecular to the behavioural level, and show how noise contributes to trial-to-trial variability. We highlight how noise affects neuronal networks and the principles the nervous system applies to counter detrimental effects of noise, and briefly discuss noise's potential benefits.
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            The time course of perceptual choice: the leaky, competing accumulator model.

            The time course of perceptual choice is discussed in a model of gradual, leaky, stochastic, and competitive information accumulation in nonlinear decision units. Special cases of the model match a classical diffusion process, but leakage and competition work together to address several challenges to existing diffusion, random walk, and accumulator models. The model accounts for data from choice tasks using both time-controlled (e.g., response signal) and standard reaction time paradigms and its adequacy compares favorably with other approaches. A new paradigm that controls the time of arrival of information supporting different choice alternatives provides further support. The model captures choice behavior regardless of the number of alternatives, accounting for the log-linear relation between reaction time and number of alternatives (Hick's law) and explains a complex pattern of visual and contextual priming in visual word identification.
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              Probabilistic decision making by slow reverberation in cortical circuits.

              Recent physiological studies of alert primates have revealed cortical neural correlates of key steps in a perceptual decision-making process. To elucidate synaptic mechanisms of decision making, I investigated a biophysically realistic cortical network model for a visual discrimination experiment. In the model, slow recurrent excitation and feedback inhibition produce attractor dynamics that amplify the difference between conflicting inputs and generates a binary choice. The model is shown to account for salient characteristics of the observed decision-correlated neural activity, as well as the animal's psychometric function and reaction times. These results suggest that recurrent excitation mediated by NMDA receptors provides a candidate cellular mechanism for the slow time integration of sensory stimuli and the formation of categorical choices in a decision-making neocortical network.
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                Author and article information

                Contributors
                Role: Reviewing Editor
                Role: Senior Editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                02 July 2019
                2019
                : 8
                : e46331
                Affiliations
                [1 ]deptDepartment of Neurophysiology and Pathophysiology University Medical Center Hamburg-Eppendorf HamburgGermany
                [2 ]deptDepartment of Psychology University of Amsterdam AmsterdamNetherlands
                [3 ]deptAmsterdam Brain and Cognition University of Amsterdam AmsterdamNetherlands
                Carnegie Mellon University United States
                Carnegie Mellon University United States
                Carnegie Mellon University United States
                Carnegie Mellon University United States
                Author notes
                [†]

                Cold Spring Harbor Laboratory, Cold Spring Harbor, United States.

                [‡]

                Department of Neuroscience, Baylor College of Medicine, Houston, United States.

                Author information
                https://orcid.org/0000-0001-5270-6513
                https://orcid.org/0000-0002-5875-8282
                https://orcid.org/0000-0003-2709-7634
                https://orcid.org/0000-0002-7559-6019
                Article
                46331
                10.7554/eLife.46331
                6606080
                31264959
                5ab26331-0d2f-4105-ab83-f990ba438a14
                © 2019, Urai et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 28 February 2019
                : 11 June 2019
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001654, German Academic Exchange Service London;
                Award ID: A/13/70362
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft;
                Award ID: DO 1240/2-1
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft;
                Award ID: DO 1240/3-1
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft;
                Award ID: SFB 936/A7
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft;
                Award ID: SFB 936/Z1
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100010665, H2020 Marie Skłodowska-Curie Actions;
                Award ID: 658581
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Research Article
                Neuroscience
                Custom metadata
                Choice history signals bias the interpretation of current sensory input, akin to shifting endogenous attention toward (or away from) the previously selected interpretation.

                Life sciences
                decision-making,choice history,sequential sampling model,human
                Life sciences
                decision-making, choice history, sequential sampling model, human

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