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The Habituation-Dishabituation ERP Responses to Repeated Visual Food Cues

Duraisingam, Aruna, Soria, Daniele, Palaniappan, Ramaswamy (2025) The Habituation-Dishabituation ERP Responses to Repeated Visual Food Cues. In: IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES). 2024 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES). . pp. 413-418. IEEE ISBN 979-8-3503-8341-6. (doi:10.1109/IECBES61011.2024.10990932) (KAR id:111081)

Abstract

Existing research indicates that human salivary responses habituate to repeated food cues. This study examines the neurophysiological dynamics of within-session habituation and dishabituation to high/low-calorie food and non-food images, with Event-Related Potentials (ERPs) measured as participants viewed these images, including distractors. The analysis showed significant habituation (decreased response) and dishabituation (response recovery) in the parietal area, particularly within the 160–290 ms time window. The non-food image exhibited a linear decrease with repetition, and responses recovered when novel stimuli were introduced. High and low calorie images did not show significant linear habituation, maintaining sustained attention and motivation instead. However, both food image types displayed a recovery response during the dishabituation phase. The ERP results also indicated that food images have a slower rate of decline compared to non-food images. In conclusion, our ERP study demonstrated that a habituation-like mechanism influences attention in response to repeated non-food images, while food images had minimal impact. Food images, with their higher reward value, led to prolonged attention and hindered habituation. These reduced neural attentional habituation and a slower rate of habituation to food stimuli could have negative health consequences. Furthermore, the dishabituation effect observed across all images underscores that the habituation phenomena are not simply due to mental fatigue.

Item Type: Conference or workshop item (Proceeding)
DOI/Identification number: 10.1109/IECBES61011.2024.10990932
Institutional Unit: Schools > School of Computing
Former Institutional Unit:
There are no former institutional units.
Funders: University of Kent (https://ror.org/00xkeyj56)
Depositing User: Aruna Duraisingam
Date Deposited: 30 Aug 2025 09:13 UTC
Last Modified: 03 Sep 2025 02:43 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/111081 (The current URI for this page, for reference purposes)

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