Tests of human olfactory function: Principal components analysis suggests that most measure a common source of variance

Doty, Richard L.; Smith, Richard; McKeown, Donald A.; Raj, J.M.

doi:10.3758/bf03208363

Cited by 187 publications

(133 citation statements)

References 37 publications

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“…In free odor identification, young adults can name about 22-57% of the presented odors (Larsson, 1997), whereas in cued identification, performance can reach ceiling-levels (Doty et al, 1994). It is not surprising that subjects perform better in cued than in free odor identification.…”

Section: Odor Identificationmentioning

confidence: 99%

“…Also, a vast majority of findings have documented strong relationships between odor identification and odor recognition, such that a successfully identified odor is easier to recognize at a later occasion (Larsson & Bäckman, 1993;Larsson & Bäck-man, 1997;Murphy et al, 1991;Rabin & Cain, 1984). In a principal component analysis including olfactory tests of threshold, discrimination, recognition, and identification, Doty et al (1994) reported that olfactory tests share a common source of variance suggesting that olfactory function is multidimensional. For example, the act of detecting an odor also requires the ability to remember the odorant and to discriminate it from a blank.…”

Section: Relationships Among Olfactory Tasksmentioning

confidence: 99%

“…However, it is clear that sensory deficits alone cannot explain the age-related impairment in odor recognition memory and odor identification (Larsson & Bäckman, 1993;Larsson & Bäckman, 1997;Murphy et al, 1991). Given that olfactory tests share a common source of variance (Doty et al, 1994), and that cognitive abilities are recruited in olfactory tasks (Larsson, 1997;Richardsson & Zucco, 1989), performance across olfactory tasks may rely on a shared factor loading. For other sensory stimuli (hearing and vision) Baltes and Lindenberger (1997) reported a strong connection between sensory and cognitive functions that varies across the lifespan, such that the proportion of shared variance is amplified in older ages.…”

Section: Olfactory Function In Normal Agingmentioning

confidence: 99%

“…All methods have shown to yield reasonable good estimates of average threshold in an individual (Doty, Smith, Mckeown, & Raj, 1994;Wise, Bien, & Wysocki, 2007). In general, measurements of olfactory thresholds are thought to draw primarily on sensory processes.…”

Section: Odor Detectionmentioning

confidence: 99%

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Olfactory Function: The Influence of Demographic, Cognitive, and Genetic factors

Hedner¹

2013

PsycEXTRA Dataset

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Olfactory function is affected by demographic, cognitive, and genetic factors. In the present thesis, three empirical studies investigated individual differences in olfactory ability. Study I explored demographic and cognitive correlates in common olfactory tasks; odor detection, odor discrimination, and odor identification. The results indicated that old age influenced performance negatively in all tasks, and that semantic memory proficiency and executive functioning were related to odor discrimination and odor identification performance. No cognitive influence was observed for measurements of olfactory threshold. Using population-based data, Study II investigated a potential influence of the ApoE gene on olfactory identification after controlling for health status, semantic memory, and preclinical and clinical dementia. The main finding was that the ApoE-ɛ4 allele interacted with age, such that older ɛ4-carriers had an impaired odor identification performance relative to older non-carriers. Importantly, the negative ApoE-ɛ4 effect on olfactory proficiency was independent of clinical dementia conversion within five years. Study III investigated the effects of the BDNF val66met polymorphism on olfactory change over a five-year interval, in a communitydwelling sample of young and old age cohorts. The results showed that agerelated decline in olfactory identification was influenced by the BDNF val66met. In middle-aged subjects, no effect of BDNF val66met was observed although older val homozygote carriers showed a selectively larger olfactory decline than the older met carriers. Overall, results suggest that the relative influence of demographic and cognitive factors vary across different olfactory tasks and that two genes (ApoE and BDNF) impact age-related deficits in odor identification. Potential theoretical and practical implications of the findings are discussed as well as potential limitations of association studies in genomics research.

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Section: Odor Identificationmentioning

confidence: 99%

Section: Relationships Among Olfactory Tasksmentioning

confidence: 99%

Section: Olfactory Function In Normal Agingmentioning

confidence: 99%

Section: Odor Detectionmentioning

confidence: 99%

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Olfactory Function: The Influence of Demographic, Cognitive, and Genetic factors

Hedner¹

2013

PsycEXTRA Dataset

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“…Typical methods for dealing with the false thresholds have included correcting for the proportion of expected "guessers," which can be done at each concentration step or across the ranges of concentrations; or fitting psychometric functions to the data, which assumes a certain rate of false positives. Experiments comparing methods of threshold testing acknowledge that multiple tests, or even multiple methods, will give the most reliable data regarding an individual's true range of sensitivity, as the variance both among and within subjects in these datasets are high (Boesveldt, de Muinck Keizer, Knol, Wolters, & Berendse, 2009;Doty, McKeown, Lee, & Shaman, 1995;Doty, Smith, McKeown, & Raj, 1994;Haehner et al, 2009;Lotsch, Lange, & Hummel, 2004;Stevens, Cruz, Hoffman, & Patterson, 1995;. However, comparative data among a variety of testing methods are limited, and most naturally data arise from actual experiments designed to test specific stimuli.…”

Section: Introductionmentioning

confidence: 99%

High false positive rates in common sensory threshold tests

Running

2014

Atten Percept Psychophys

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Large variability in thresholds to sensory stimuli is observed frequently even in healthy populations. Much of this variability is attributed to genetics and day-to-day fluctuation in sensitivity. However, false positives are also contributing to the variability seen in these tests. In this study, random number generation was used to simulate responses in threshold methods using different "stopping rules": ascending 2-alternative forced choice (AFC) with 5 correct responses; ascending 3-AFC with 3 or 4 correct responses; staircase 2-AFC with 1 incorrect up and 2 incorrect down, as well as 1 up 4 down and 5 or 7 reversals; staircase 3-AFC with 1 up 2 down and 5 or 7 reversals. Formulas are presented for rates of false positives in the ascending methods, and curves were generated for the staircase methods. Overall, the staircase methods generally had lower false positive rates, but these methods were influenced even more by number of presentations than ascending methods. Generally, the high rates of error in all these methods should encourage researchers to conduct multiple tests per individual and/or select a method that can correct for false positives, such as fitting a logistic curve to a range of responses.

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