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Examining the Neurophysiology of Attentional Habituation to Repeated Presentations of Food and Non-Food Visual Stimuli

Duraisingam, Aruna, Soria, Daniele, Palaniappan, Ramaswamy (2025) Examining the Neurophysiology of Attentional Habituation to Repeated Presentations of Food and Non-Food Visual Stimuli. Algorithms, 18 (8). Article Number 525. ISSN 1999-4893. (doi:10.3390/a18080525) (KAR id:111103)

Abstract

Existing research shows that the human salivary response habituates to repeated presentation of visual, olfactory, or gustatory food cues in adults and children. The aim of this research is to examine the neurophysiological effects of attentional habituation within sessions toward repetition of the same high- and low-calorie food and non-food images. Participants’ event-related potential (ERP) responses were measured as they passively viewed the same food and non-food images repeatedly. The ERP analysis results from trial groups within a session over time indicated that repeated exposure to the same image has a distinct effect on the brain’s attentional responses to food and non-food images. The brain response modulated by motivation and attention decreases over time, and it is significant in the 170–300 ms onset time window for low-calorie images and 180–330 ms onset time window for non-food images in the parietal region of the brain. However, the modulation to high-calorie images remains sustained over time within the session. Furthermore, the ERP results show that high-calorie images have a slower rate of declination than low-calorie images, followed by non-food images. In conclusion, our ERP study showed that a habituation-like mechanism modulates attention to repeated low-calorie and non-food images, whereas high-calorie images have a negligible effect. High-energy foods have a larger reward value, which increases prolonged attention and reduces the process of habituation. This could be one of the reasons why a negligible neural attentional habituation and slow habituation rate to high-calorie diets could have negative health consequences.

Item Type: Article
DOI/Identification number: 10.3390/a18080525
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 08:50 UTC
Last Modified: 03 Sep 2025 02:46 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/111103 (The current URI for this page, for reference purposes)

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