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Imperfect integration: Congruency between multiple sensory sources modulates decision-making processes

Dominik Krzemiński Orcid Logo, Jiaxiang Zhang Orcid Logo

Attention, Perception, & Psychophysics, Volume: 84, Issue: 5, Pages: 1566 - 1582

Swansea University Author: Jiaxiang Zhang Orcid Logo

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Abstract

Decision-making on the basis of multiple information sources is common. However, to what extent such decisions differ from those with a single source remains unclear. We combined cognitive modelling and neural-mass modelling to characterise the neurocognitive process underlying perceptual decision-m...

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Published in: Attention, Perception, & Psychophysics
ISSN: 1943-3921 1943-393X
Published: Springer Science and Business Media LLC 2022
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa61202
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Abstract: Decision-making on the basis of multiple information sources is common. However, to what extent such decisions differ from those with a single source remains unclear. We combined cognitive modelling and neural-mass modelling to characterise the neurocognitive process underlying perceptual decision-making with single or double information sources. Ninety-four human participants performed binary decisions to discriminate the coherent motion direction averaged across two independent apertures. Regardless of the angular distance of the apertures, separating motion information into two apertures resulted in a reduction in accuracy. Our cognitive and neural-mass modelling results are consistent with the hypotheses that the addition of the second information source led to a lower signal-to-noise ratio of evidence accumulation with two congruent information sources, and a change in the decision strategy of speed–accuracy trade-off with two incongruent sources. Thus, our findings support a robust behavioural change in relation to multiple information sources, which have congruency-dependent impacts on selective decision-making subcomponents.
Keywords: Decision-making; Multiple sources; Attention; Speed–accuracy trade-off; Cognitive model; Neural-mass; model
College: Faculty of Science and Engineering
Funders: DK was supported by Engineering and Physical Sciences Research Council PhD Scholarship (EP/N509449/1). JZ was supported by European Research Council (716321).
Issue: 5
Start Page: 1566
End Page: 1582