Literature DB >> 21653845

Tracking the temporal evolution of a perceptual judgment using a compelled-response task.

Swetha Shankar1, Dino P Massoglia, Dantong Zhu, M Gabriela Costello, Terrence R Stanford, Emilio Salinas.   

Abstract

Choice behavior and its neural correlates have been intensely studied with tasks in which a subject makes a perceptual judgment and indicates the result with a motor action. Yet a question crucial for relating behavior to neural activity remains unresolved: what fraction of a subject's reaction time (RT) is devoted to the perceptual evaluation step, as opposed to executing the motor report? Making such timing measurements accurately is complicated because RTs reflect both sensory and motor processing, and because speed and accuracy may be traded. To overcome these problems, we designed the compelled-saccade task, a two-alternative forced-choice task in which the instruction to initiate a saccade precedes the appearance of the relevant sensory information. With this paradigm, it is possible to track perceptual performance as a function of the amount of time during which sensory information is available to influence a subject's choice. The result-the tachometric curve-directly reveals a subject's perceptual processing capacity independently of motor demands. Psychophysical data, together with modeling and computer-simulation results, reveal that task performance depends on three separable components: the timing of the motor responses, the speed of the perceptual evaluation, and additional cognitive factors. Each can vary quickly, from one trial to the next, or can show stable, longer-term changes. This novel dissociation between sensory and motor processes yields a precise metric of how perceptual capacity varies under various experimental conditions and serves to interpret choice-related neuronal activity as perceptual, motor, or both.

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Year:  2011        PMID: 21653845      PMCID: PMC3134312          DOI: 10.1523/JNEUROSCI.1419-11.2011

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  66 in total

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6.  Temporal resolution for the perception of features and conjunctions.

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Review 7.  The diffusion decision model: theory and data for two-choice decision tasks.

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Journal:  Psychol Rev       Date:  2007-04       Impact factor: 8.934

9.  Neural basis of a perceptual decision in the parietal cortex (area LIP) of the rhesus monkey.

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10.  Microstimulation of macaque area LIP affects decision-making in a motion discrimination task.

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  26 in total

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2.  Perceptual modulation of motor--but not visual--responses in the frontal eye field during an urgent-decision task.

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3.  Revisiting the evidence for collapsing boundaries and urgency signals in perceptual decision-making.

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Review 4.  Behavioural and computational varieties of response inhibition in eye movements.

Authors:  Vassilis Cutsuridis
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2017-04-19       Impact factor: 6.237

Review 5.  How mechanisms of perceptual decision-making affect the psychometric function.

Authors:  Joshua I Gold; Long Ding
Journal:  Prog Neurobiol       Date:  2012-05-17       Impact factor: 11.685

6.  All-or-None Context Dependence Delineates Limits of FEF Visual Target Selection.

Authors:  Veronica E Scerra; M Gabriela Costello; Emilio Salinas; Terrence R Stanford
Journal:  Curr Biol       Date:  2019-01-10       Impact factor: 10.834

7.  Comparing fixed and collapsing boundary versions of the diffusion model.

Authors:  Chelsea Voskuilen; Roger Ratcliff; Philip L Smith
Journal:  J Math Psychol       Date:  2016-05-24       Impact factor: 2.223

Review 8.  Under time pressure, the exogenous modulation of saccade plans is ubiquitous, intricate, and lawful.

Authors:  Emilio Salinas; Terrence R Stanford
Journal:  Curr Opin Neurobiol       Date:  2021-11-21       Impact factor: 6.627

9.  The countermanding task revisited: fast stimulus detection is a key determinant of psychophysical performance.

Authors:  Emilio Salinas; Terrence R Stanford
Journal:  J Neurosci       Date:  2013-03-27       Impact factor: 6.167

10.  Accuracy and response-time distributions for decision-making: linear perfect integrators versus nonlinear attractor-based neural circuits.

Authors:  Paul Miller; Donald B Katz
Journal:  J Comput Neurosci       Date:  2013-04-23       Impact factor: 1.621

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