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      Modeling Saccadic Action Selection: Cortical and Basal Ganglia Signals Coalesce in the Superior Colliculus

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          Abstract

          The distributed nature of information processing in the brain creates a complex variety of decision making behavior. Likewise, computational models of saccadic decision making behavior are numerous and diverse. Here we present a generative model of saccadic action selection in the context of competitive decision making in the superior colliculus (SC) in order to investigate how independent neural signals may converge to interact and guide saccade selection, and to test if systematic variations can better replicate the variability in responses that are part of normal human behavior. The model was tasked with performing pro- and anti-saccades in order to replicate specific attributes of healthy human saccade behavior. Participants (ages 18–39) were instructed to either look toward (pro-saccade, well-practiced automated response) or away from (anti-saccade, combination of inhibitory and voluntary responses) a peripheral visual stimulus. They generated express and regular latency saccades in the pro-saccade task. In the anti-saccade task, correct reaction times were longer and participants occasionally looked at the stimulus (direction error) at either express or regular latencies. To gain a better understanding of the underlying neural processes that lead to saccadic action selection and response inhibition, we implemented 8 inputs inspired by systems neuroscience. These inputs reflected known sensory, automated, voluntary, and inhibitory components of cortical and basal ganglia activity that coalesces in the intermediate layers of the SC (SCi). The model produced bimodal reaction time distributions, where express and regular latency saccades had distinct modes, for both correct pro-saccades and direction errors in the anti-saccade task. Importantly, express and regular latency direction errors resulted from interactions of different inputs in the model. Express latency direction errors were due to a lack of pre-emptive fixation and inhibitory activity, which aloud sensory and automated inputs to initiate a stimulus-driven saccade. Regular latency errors occurred when the automated motor signals were stronger than the voluntary motor signals. While previous models have emulated fewer aspects of these behavioral findings, the focus of the simulations here is on the interaction of a wide variety of physiologically-based information integration producing a richer set of natural behavioral variability.

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          Most cited references117

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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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            Dynamics of pattern formation in lateral-inhibition type neural fields.

            S Amari (1977)
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              Attention, intention, and priority in the parietal lobe.

              For many years there has been a debate about the role of the parietal lobe in the generation of behavior. Does it generate movement plans (intention) or choose objects in the environment for further processing? To answer this, we focus on the lateral intraparietal area (LIP), an area that has been shown to play independent roles in target selection for saccades and the generation of visual attention. Based on results from a variety of tasks, we propose that LIP acts as a priority map in which objects are represented by activity proportional to their behavioral priority. We present evidence to show that the priority map combines bottom-up inputs like a rapid visual response with an array of top-down signals like a saccade plan. The spatial location representing the peak of the map is used by the oculomotor system to target saccades and by the visual system to guide visual attention.
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                Author and article information

                Contributors
                Journal
                Front Syst Neurosci
                Front Syst Neurosci
                Front. Syst. Neurosci.
                Frontiers in Systems Neuroscience
                Frontiers Media S.A.
                1662-5137
                13 February 2019
                2019
                : 13
                : 3
                Affiliations
                [1] 1Centre for Neuroscience Studies, Queen's University , Kingston, ON, Canada
                [2] 2Faculty of Computer Science, Dalhousie University , Halifax, NS, Canada
                Author notes

                Edited by: Vassilis Cutsuridis, University of Lincoln, United Kingdom

                Reviewed by: Eduardo A. Aponte, ETH Zürich, Switzerland; Mazyar Fallah, York University, Canada

                *Correspondence: Brian C. Coe coe@ 123456queensu.ca ; dr.bcoe@ 123456gmail.com
                Article
                10.3389/fnsys.2019.00003
                6381059
                30814938
                86ac5d10-bca7-4ce4-a6a4-59a2acf3398a
                Copyright © 2019 Coe, Trappenberg and Munoz.

                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
                : 26 September 2018
                : 10 January 2019
                Page count
                Figures: 9, Tables: 5, Equations: 8, References: 141, Pages: 22, Words: 17741
                Categories
                Neuroscience
                Original Research

                Neurosciences
                eye movements,inhibition,anti-saccade,dynamic neural field model,reaction time,error rate,human behavior

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