Detecting gustatory-olfactory flavor mixtures: models of probability summation.

Abstract:

:Odorants and flavorants typically contain many components. It is generally easier to detect multicomponent stimuli than to detect a single component, through either neural integration or probability summation (PS) (or both). PS assumes that the sensory effects of 2 (or more) stimulus components (e.g., gustatory and olfactory components of a flavorant) are detected in statistically independent channels, that each channel makes a separate decision whether a component is detected, and that the behavioral response depends solely on the separate decisions. Models of PS traditionally assume high thresholds for detecting each component, noise being irrelevant. The core assumptions may be adapted, however, to signal-detection theory, where noise limits detection. The present article derives predictions of high-threshold and signal-detection models of independent-decision PS in detecting gustatory-olfactory flavorants, comparing predictions in yes/no and 2-alternative forced-choice tasks using blocked and intermixed stimulus designs. The models also extend to measures of response times to suprathreshold flavorants. Predictions derived from high-threshold and signal-detection models differ markedly. Available empirical evidence on gustatory-olfactory flavor detection suggests that neither the high-threshold nor the signal-detection versions of PS can readily account for the results, which likely reflect neural integration in the flavor system.

journal_name

Chem Senses

journal_title

Chemical senses

authors

Marks LE,Veldhuizen MG,Shepard TG,Shavit AY

doi

10.1093/chemse/bjr103

subject

Has Abstract

pub_date

2012-03-01 00:00:00

pages

263-77

issue

3

eissn

0379-864X

issn

1464-3553

pii

bjr103

journal_volume

37

pub_type

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