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The sense of smell is achieved through the activities of the olfactory system. It starts when an airborne odorant enters the nasal cavity and reaches olfactory epithelium (OE). The OE is protected by a thin layer of mucus, which also serves the purpose of dissolving more complex compounds into simpler chemical odorants. The size of the OE and the density of sensory neurons varies among species; in humans, the OE is only about 9-10 cm2.
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The process of olfaction, also known as the sense of smell, is a sophisticated chemical response system. The specialized sensory neurons that facilitate this process, known as olfactory receptor neurons, are situated in an upper segment of the nasal cavity, known as the olfactory epithelium. Olfactory sensory neurons are bipolar, with their dendrites extending from the epithelium's apex into the mucus that lines the nasal cavity. Airborne molecules, when inhaled, traverse the olfactory...
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Humans detect odors with the help of specialized cells located in the upper part of the nasal cavity, called olfactory receptor neurons (ORNs). ORNs possess hair-like structures called cilia, which are receptive to sensations from the inhaled air. When an odorant molecule binds to a specific receptor on the cell of the cilia, it leads to a series of events that ultimately cause the ORN to send electrical signals to the olfactory bulb in the brain through the olfactory nerves.
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Gustation, or the sense of taste, is intrinsically linked to the anatomical structures located on the tongue. This organ's surface, along with the entirety of the oral cavity, is adorned with stratified squamous epithelium. Evident on the tongue are elevated structures known as papillae (singular = papilla), which house the mechanisms for the transduction of gustatory stimuli. Four distinct types of papillae exist, each identified by their unique morphological attributes: the circumvallate,...
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Updated: Apr 5, 2026

An Olfactory Preference Test for Measuring Olfactory Hedonic Biases in Mouse Models of Depression
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Decoding olfactory-depression-appetite pathways in nursing-home elderly: a knowledge multi-relational graph attention

Hye-Gyeong Cha1, Won-Jin Lee1, Yeon-Jin Noh2

  • 1Department of Nursing, Namseoul University, South Korea.

Psychiatry Research. Neuroimaging
|April 4, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces an AI model to understand sensory-affective patterns in the elderly. Depression mediates olfactory decline

Keywords:
Appetite pathwaysDepressionFisher mantis optimizerKnowledge graph and graph neural networkMulti-relational graph attention networksOlfactory function

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Area of Science:

  • Gerontology
  • Artificial Intelligence
  • Clinical Psychology

Background:

  • AI clinical systems require analytical frameworks for elderly sensory-affective patterns.
  • Olfactory decline, depression, and appetite loss are critical in nursing home residents.
  • Existing models lack integrated symbolic knowledge for sensory-psychological analysis.

Purpose of the Study:

  • To propose an AI-assisted sensory-psychological model, the Knowledge Multi-Relational Graph Attention Generative Neural Network (KMRG-GANN), incorporating symbolic knowledge.
  • To analyze the relationship between olfactory function, depression, and appetite in elderly populations.
  • To develop a predictive framework for sensory-affective patterns in nursing home residents.

Main Methods:

  • Utilized the Olfactory_Appetite_NursingHomes_Dataset (193 participants) with olfactory, gustatory, cognitive, depressive, anthropometric, and appetite-nutrition data.
  • Developed the Dual Selective Fusion Transformer Network (DSFTN) for cross-domain feature embedding and fusion.
  • Integrated Knowledge Graph and Graph Neural Network (KG-GNN) with Multi-Relation Graph Attention Networks (MRGAT), trained via Fisher Mantis Optimizer (FMO).

Main Results:

  • The KMRG-GANN achieved 99.9% predictive accuracy, outperforming baseline models.
  • Mediation analysis revealed depression as a key mediator (56.8%) in the olfactory effect on appetite control.
  • Identified symbolic, relation-sensitive pathways from olfactory deterioration to depressive symptoms and appetite loss.

Conclusions:

  • The KMRG-GANN provides a robust AI framework for interpreting complex sensory-affective patterns in the elderly.
  • Depression significantly mediates the impact of olfactory changes on appetite in nursing home residents.
  • The findings highlight the interconnectedness of sensory perception, mental health, and nutritional status in aging populations.