It is well-known that food-cue reactivity (FCR) is positively associated with body mass index (BMI)1 and weight change2, but the mechanisms underlying these relationships are incompletely understood. One prominent theory of craving posits that the elaboration of a desired substance through sensory imagery intensifies cravings, thereby promoting consumption3. Olfaction is integral to food perception, yet the ability to imagine odours varies widely4. Here we test in a basic observational study whether this large variation in olfactory imagery drives FCR strength to promote adiposity in 45 adults (23 male). We define odour-imagery ability as the extent to which imagining an odour interferes with the detection of a weak incongruent odour (the ‘interference effect’5). As predicted in our preregistration, the interference effect correlates with the neural decoding of imagined, but not real, odours. These perceptual and neural measures of odour imagery are in turn associated with FCR, defined by the rated craving intensity of liked foods and cue-potentiated intake. Finally, odour imagery exerts positive indirect effects on changes in BMI and body-fat percentage over one year via its influences on FCR. These findings establish odour imagery as a driver of FCR that in turn confers risk for weight gain.
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The raw MRI data and sniff airflow traces can be downloaded from the OpenNEURO repository under accession no. ds004327 at: https://doi.org/10.18112/openneuro.ds004327.v1.0.1. Statistical maps of the human brain data are available on the NeuroVault repository at: https://neurovault.org/collections/14751/. Source data are provided with this paper.
Custom code used in data collection and analysis is available at: https://github.com/eeperszyk/odor-imagery.
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This work was supported by the National Science Foundation Graduate Research Fellowship under Grant No. 2139841 (E.E.P.), the National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health under Award No. F31DK130556 (E.E.P.), and the Modern Diet and Physiology Research Center (D.M.S.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Science Foundation or the National Institutes of Health. We would like to thank J. Avery for advice on the fMRI decoding methods; B. Kuzmanovic for guidance on the fMRI preprocessing pipeline; J. Howard for example code to perform the sniffing analyses; T. Hummel, J. Lundström, J. Mainland, and P. Wise for their thoughts on troubleshooting the odour-detection threshold testing; A. Dagher, R. DiLeone, and B. Green for their helpful suggestions on project design and analyses; and K. Martin for MR technical assistance.
The authors declare no competing interests.
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Extended Data Fig. 1 The perceptual measure of odour-imagery ability positively correlates with self-reported odour and flavor, but not visual, imagery ability.
a–c, The perceptual measure of odour-imagery ability (that is, the interference effect) positively correlated with self-reported odour (a) and flavor (b), but not visual (c), imagery ability. We note that the self-report and perceptual measures of odour-imagery ability did not vary by sex, age, household income, olfactory function or perception, sniff parameters, hunger, or dietary habits (Supplementary Table 4). Scatterplots depict single participants and the 95% CI around the line of best fit. Linear relationships were tested with two-tailed Pearson’s r correlations. p.p., percentage points, referring to the difference in odour detection accuracies (percentages) during matched versus mismatched trials of the odour-imagery condition from the perceptual task (see Fig. 1e,f); VOIQ, Vividness of Olfactory Imagery Questionnaire41; VFIQ, Vividness of Food Imagery Questionnaire8; VVIQ, Vividness of Visual Imagery Questionnaire7; *Pcorrected < 0.05 (3 tests comparing the interference effect to self-reported odour, flavor, or visual-imagery ability).
a, Control regions for the neural decoding analyses included the left and right primary visual cortices. b–c, SVM accuracies (b) and voxel correlations (c) were not significant for real, imagined, or cross-modal odours in either control region. Box-and-whisker plots represent single participants from the minimum to maximum (whiskers) around the 25th to 75th percentiles (box limits), along with the median (center line) and mean (+symbol) of the data. L, left; R, right; SVM, support vector machine; V1, primary visual cortex. See also Fig. 2 for additional details on the two decoding methods and significant effects in the piriform cortex regions of interest.
a, BOLD responses to smelling odours (rose and cookie) > smelling clean air were significant in the bilateral insula, piriform/amygdala, orbitofrontal cortices, cerebellum, and middle frontal and cingulate gyri, among other regions (Supplementary Table 10). Whole-brain statistical map can be viewed at: https://neurovault.org/images/798927/. b, BOLD responses to imagining odours > imagining clean air (while sniffing) were significant in the bilateral insula, right putamen, and left cerebellum (Supplementary Table 11). Whole-brain statistical map can be viewed at: https://neurovault.org/images/798926/. c, BOLD responses to imagining odours > smelling clean air were significant in the bilateral insula, putamen extending into the piriform cortices, pallidum, and orbitofrontal, middle frontal, and precentral gyri, among other regions (Supplementary Table 12). Whole-brain statistical map can be viewed at: https://neurovault.org/images/798923/. d, BOLD responses in the conjunction of smelling odours > smelling clean air and imagining odours > imagining clean air were significant in the bilateral insula and putamen extending into the piriform cortices, along with the left precentral gyrus (Supplementary Table 13). Whole-brain statistical map can be viewed at: https://neurovault.org/images/798917/. e, BOLD responses to smelling odours > imagining odours were significant in the bilateral insula and amygdala along with the right uncus and orbitofrontal cortex, among other regions (Supplementary Table 13). Those to imagining odours > smelling odours were significant in the left supplementary motor area (Supplementary Table 13). Whole-brain statistical map can be viewed at: https://neurovault.org/images/798924/. Brain sections show the SPM t-map (Puncorrected < 0.005, clusters of at least 5 voxels) overlaid onto an anatomical template in MNI coordinates for illustrative purposes. In each panel, the top row depicts 3D coronal sections (18–mm thick) evenly spanning y = 56 to –88 mm (for a–c) or y = 56 to –16 mm (for d–e), and the bottom row highlights important areas of activation with custom coordinates (see Supplementary Tables 10–13). Color bars depict t values. L, left; R, right; Amyg, amygdala; Ins, insula; OFC, orbitofrontal cortex; Pir, piriform cortex; Put, putamen; SMA, supplementary motor area.
a–c, Neither the self-report (a), perceptual (b), nor neural (c) measure of odour-imagery ability predicted changes in BMI over one year from the baseline to follow-up sessions. d–f, Neither the self-report (d), perceptual (e), nor neural (f) measure of odour-imagery ability predicted changes in body-fat percentage over one year from the baseline to follow-up sessions. Scatterplots depict single participants and the 95% CI around the line of best fit. Linear relationships were tested with two-tailed Pearson’s r correlations. As no effects were significant, all P-values were left uncorrected. a.u., arbitrary units, referring to sex-adjusted changes in body-fat percentage over one year; p.p., percentage points, referring to the difference in odour detection accuracies (percentages) during matched versus mismatched trials of the odour-imagery condition from the perceptual task (see Fig. 1e,f); VOIQ, Vividness of Olfactory Imagery Questionnaire41; R, right; Pir, piriform.
Flow diagram depicting the number of individuals at each stage of the study.
a–d, The cookie odour was rated to be significantly more intense (a), familiar (b), and edible (c) than the rose odour in two-sided paired samples t-tests. There was no significant difference in liking (d). However, the cookie minus rose odour ratings were not correlated with any measure of odour-imagery ability (Supplementary Table 4). Truncated violin plots depict single participants (n = 44) with shading to represent the density of the points around the median line. R, rose; C, cookie; gLMS, general Labeled Magnitude Scale37,38,39; VAS, visual analogue scale; LHS, Labeled Hedonic Scale40; n.s., not significant. *Pcorrected < 0.05 (4 tests).
a–d, Normalized sniff traces (mean ± s.e.m.) for smelling the rose (a) and cookie (b) odours and imagining the rose (c) and cookie (d) odours. e–j, Sniff amplitude (e), latency (f), volume (g), duration (h), peak airflow rate (i), and mean airflow rate (j) while smelling and imagining the rose and cookie odours. Differences in the sniff parameters for imagining the cookie minus rose odour were not correlated with any measure of odour-imagery ability (Supplementary Table 4). ANOVAs also revealed no main effects or interactions of modality (smell/imagine), odour (rose/cookie), or the perceptual measure of odour-imagery ability (the interference effect) on any sniff parameter (Supplementary Table 9). Truncated violin plots depict single participants (n = 44) with shading to represent the density of the points around the median line. S, smell; I, imagine; R, rose; C, cookie; a.u., arbitrary units.
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Perszyk, E.E., Davis, X.S., Djordjevic, J. et al. Odour-imagery ability is linked to food craving, intake, and adiposity change in humans. Nat Metab 5, 1483–1493 (2023). https://doi.org/10.1038/s42255-023-00874-z