Literature DB >> 9530966

Attention and the detectability of weak taste stimuli.

L E Marks1, M E Wheeler.   

Abstract

Subjects detected weak solutions of sucrose or citric acid under conditions in which attention was directed toward one of the tastants or the other. Detection thresholds were measured using an adaptive, forced-choice procedure, with a three-down one-up rule, which computer simulations suggest should be more reliable than the popular two-down one-up rule. The thresholds were modestly but systematically lower for attended tastants than for unattended ones. Similar results have been reported in other sense modalities, including vision (greater sensitivity to stimuli presented to attended versus unattended spatial locations) and hearing (greater sensitivity to stimuli presented at attended versus unattended sound frequencies). Taken together, the findings are consistent with a general hypothesis regarding attention in sensory systems: gains or losses in detectability occur when a central attentional mechanism (or, conceivably, a preattentive mechanism) selectively and preferentially monitors signals arising from particular subsets of peripheral neural inputs.

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Year:  1998        PMID: 9530966     DOI: 10.1093/chemse/23.1.19

Source DB:  PubMed          Journal:  Chem Senses        ISSN: 0379-864X            Impact factor:   3.160


  10 in total

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Journal:  Chem Senses       Date:  2016-01-31       Impact factor: 3.160

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3.  Modality-specific neural effects of selective attention to taste and odor.

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6.  An fMRI Study of the Interactions Between the Attention and the Gustatory Networks.

Authors:  Maria G Veldhuizen; Darren R Gitelman; Dana M Small
Journal:  Chemosens Percept       Date:  2012-03-01       Impact factor: 1.833

7.  The Effect of Swallowing Cues in Healthy Individuals: An Exploratory Study.

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8.  Orosensory and Homeostatic Functions of the Insular Taste Cortex.

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Review 9.  The tongue map and the spatial modulation of taste perception.

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Review 10.  Attention in Psychology, Neuroscience, and Machine Learning.

Authors:  Grace W Lindsay
Journal:  Front Comput Neurosci       Date:  2020-04-16       Impact factor: 2.380

  10 in total

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