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Individual odor hedonic perception is coded in temporal joint network activity

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INTRO The human sense of smell is highly individual and characterized by a strong variability in the perception and evaluation of olfactory stimuli, depending on cultural imprint and current physiological… Click to show full abstract

INTRO The human sense of smell is highly individual and characterized by a strong variability in the perception and evaluation of olfactory stimuli, depending on cultural imprint and current physiological conditions. Since this individual perspective has often been neglected in fMRI studies on olfactory hedonic coding, this study focuses on the neuronal activity and connectivity patterns resulting from subject-specific olfactory stimulation. METHODS Thirty-one normosmic participants took part in a fMRI block designed paradigm consisting of three olfactory stimulation sessions. The most pleasant and unpleasant odors were individually specified during a pre-test for each participant and validated in the main experiment. Mean activation and functional connectivity analysis focusing on the right and left piriform cortex were performed for the predefined olfactory regions-of-interest (ROIs) and compared between the three olfactory conditions. RESULTS Individual unpleasant olfactory stimulation as compared to pleasant or neutral did not alter mean BOLD activation in the predefined olfactory ROIs but led to a change in connectivity pattern in the right piriform cortex. CONCLUSION Our data suggests that the individual pleasantness of odors is not detectable by average BOLD magnitude changes in primary or secondary olfactory brain areas, but reflected in temporal patterns of joint activation that create a network between the right piriform cortex, the left insular cortex, the orbitofrontal cortex, and the precentral gyrus. This network may serve the evolutionary defense mechanism of olfaction by preparing goal-directed action.

Keywords: network; piriform cortex; perception; activity; olfactory stimulation

Journal Title: NeuroImage
Year Published: 2021

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