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      Adaptive Choice Biases in Mice and Humans

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          Abstract

          The contribution of non-sensory information processing to perceptual decision making is not fully understood. Choice biases have been described for mice and humans and are highly prevalent even if they decrease rewarding outcomes. Choice biases are usually reduced by discriminability because stimulus strength directly enables the adjustments in the decision strategies used by decision-makers. However, choice biases could also derive from functional asymmetries in sensory processing, decision making, or both. Here, we tested how particular experimental contingencies influenced the production of choice biases in mice and humans. Our main goal was to establish the tasks and methods to jointly characterize psychometric performance and innate side-choice behavior in mice and humans. We implemented forced and un-forced visual tasks and found that both species displayed stable levels of side-choice biases, forming continuous distributions from low to high levels of choice stereotypy. Interestingly, stimulus discriminability reduced the side-choice biases in forced-choice, but not in free-choice tasks. Choice biases were stable in appearance and intensity across experimental days and could be employed to identify mice and human participants. Additionally, side- and alternating choices could be reinforced for both mice and humans, implying that choice biases were adaptable to non-visual manipulations. Our results highlight the fact that internal and external elements can influence the production of choice biases. Adaptations of our tasks could become a helpful diagnostic tool to detect aberrant levels of choice variability.

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          Most cited references40

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          Mapping Sub-Second Structure in Mouse Behavior.

          Complex animal behaviors are likely built from simpler modules, but their systematic identification in mammals remains a significant challenge. Here we use depth imaging to show that 3D mouse pose dynamics are structured at the sub-second timescale. Computational modeling of these fast dynamics effectively describes mouse behavior as a series of reused and stereotyped modules with defined transition probabilities. We demonstrate this combined 3D imaging and machine learning method can be used to unmask potential strategies employed by the brain to adapt to the environment, to capture both predicted and previously hidden phenotypes caused by genetic or neural manipulations, and to systematically expose the global structure of behavior within an experiment. This work reveals that mouse body language is built from identifiable components and is organized in a predictable fashion; deciphering this language establishes an objective framework for characterizing the influence of environmental cues, genes and neural activity on behavior.
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            Serial dependence in visual perception

            Visual input often arrives in a noisy and discontinuous stream, owing to head and eye movements, occlusion, lighting changes, and many other factors. Yet the physical world is generally stable—objects and physical characteristics rarely change spontaneously. How then does the human visual system capitalize on continuity in the physical environment over time? Here we show that visual perception is serially dependent, using both prior and present input to inform perception at the present moment. Using an orientation judgment task, we found that even when visual input changes randomly over time, perceived orientation is strongly and systematically biased toward recently seen stimuli. Further, the strength of this bias is modulated by attention and tuned to the spatial and temporal proximity of successive stimuli. These results reveal a serial dependence in perception characterized by a spatiotemporally tuned, orientation-selective operator—which we call a continuity field—that may promote visual stability over time.
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              Matching behavior and the representation of value in the parietal cortex.

              Psychologists and economists have long appreciated the contribution of reward history and expectation to decision-making. Yet we know little about how specific histories of choice and reward lead to an internal representation of the "value" of possible actions. We approached this problem through an integrated application of behavioral, computational, and physiological techniques. Monkeys were placed in a dynamic foraging environment in which they had to track the changing values of alternative choices through time. In this context, the monkeys' foraging behavior provided a window into their subjective valuation. We found that a simple model based on reward history can duplicate this behavior and that neurons in the parietal cortex represent the relative value of competing actions predicted by this model.
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                Author and article information

                Contributors
                Journal
                Front Behav Neurosci
                Front Behav Neurosci
                Front. Behav. Neurosci.
                Frontiers in Behavioral Neuroscience
                Frontiers Media S.A.
                1662-5153
                14 July 2020
                2020
                : 14
                : 99
                Affiliations
                Laboratorio de Plasticidad Cortical y Aprendizaje Perceptual, Instituto de Neurociencias, Universidad de Guadalajara , Guadalajara, Mexico
                Author notes

                Edited by: Jonathan L. Brigman, University of New Mexico School of Medicine, United States

                Reviewed by: Lindsay Halladay, Santa Clara University, United States; Anna K. Radke, Miami University, United States

                *Correspondence: Mario Treviño, mariomtv@ 123456hotmail.com

                This article was submitted to Motivation and Reward, a section of the journal Frontiers in Behavioral Neuroscience

                Article
                10.3389/fnbeh.2020.00099
                7372118
                32760255
                335c81e2-ed87-42e9-b182-a0f0a9ca32d9
                Copyright © 2020 Treviño, Medina-Coss y León and Haro.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 24 March 2020
                : 22 May 2020
                Page count
                Figures: 8, Tables: 0, Equations: 0, References: 42, Pages: 16, Words: 0
                Categories
                Neuroscience
                Original Research

                Neurosciences
                mouse,human,choice-bias,discriminability,two-alternative choice
                Neurosciences
                mouse, human, choice-bias, discriminability, two-alternative choice

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