Literature DB >> 26609110

Evidence against perfect integration of sensory information during perceptual decision making.

Matthew A Carland1, Encarni Marcos2, David Thura1, Paul Cisek3.   

Abstract

Perceptual decision making is often modeled as perfect integration of sequential sensory samples until the accumulated total reaches a fixed decision bound. In that view, the buildup of neural activity during perceptual decision making is attributed to temporal integration. However, an alternative explanation is that sensory estimates are computed quickly with a low-pass filter and combined with a growing signal reflecting the urgency to respond and it is the latter that is primarily responsible for neural activity buildup. These models are difficult to distinguish empirically because they make similar predictions for tasks in which sensory information is constant within a trial, as in most previous studies. Here we presented subjects with a variant of the classic constant-coherence motion discrimination (CMD) task in which we inserted brief motion pulses. We examined the effect of these pulses on reaction times (RTs) in two conditions: 1) when the CMD trials were blocked and subjects responded quickly and 2) when the same CMD trials were interleaved among trials of a variable-motion coherence task that motivated slower decisions. In the blocked condition, early pulses had a strong effect on RTs but late pulses did not, consistent with both models. However, when subjects slowed their decision policy in the interleaved condition, later pulses now became effective while early pulses lost their efficacy. This last result contradicts models based on perfect integration of sensory evidence and implies that motion signals are processed with a strong leak, equivalent to a low-pass filter with a short time constant.
Copyright © 2016 the American Physiological Society.

Entities:  

Keywords:  decision making; drift-diffusion model; urgency

Mesh:

Year:  2015        PMID: 26609110     DOI: 10.1152/jn.00264.2015

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  20 in total

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8.  A Dynamic Bayesian Observer Model Reveals Origins of Bias in Visual Path Integration.

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9.  A parameter recovery assessment of time-variant models of decision-making.

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10.  Dissociable mechanisms govern when and how strongly reward attributes affect decisions.

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