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Accession Number:
AD1105497
Title:
Stochastic Resonance and Perceptual Decision Making Inattention
Corporate Author:
University of California Los Angeles Los Angeles United States
Report Date:
2020-01-14
Abstract:
In this study, we empirically investigated to what extent the phenomenon of stochastic resonance under lack of attention generalizes to naturalistic stimuli and different contexts, and may work under different mechanismsSpecific Objectives 1 and 2. We also tried to understand the neurobiological mechanism behind this intriguing phenomenon, by means of computational modeling Specific Objectives 3. We found that people tend to confirm what they expect whenever they dont attend and that participants subjective sense of the visual surround is inflated. We also developed a simple leaky competing accumulator neural network model incorporating a known property of sensory neurons tuned normalization. We demonstrate that this biologically plausible model can account for several counterintuitive findings reported in the literature, where confidence and decision accuracy were shown to dissociate -- and that the differential contribution a neuron makes to decisions versus confidence judgments based on its normalization tuning is vital to capturing some of these effects.
Descriptive Note:
Technical Report,01 Apr 2015,31 Oct 2019
Pages:
0032
Distribution Statement:
Approved For Public Release;
File Size:
2.07MB
