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The Drosophila mushroom body (MB) is known to be involved in olfactory learning and memory; the synaptic plasticity of the Kenyon cell (KC) to mushroom body output neuron (MBON) synapses plays a key role in the learning process. Previous…

Neurons and Cognition · Quantitative Biology 2025-09-25 Katherine Xie , Gabriel Koch Ocker

This study examines the modulatory effect of contextual hedonic olfactory stimuli on the visual processing of neutral faces using event-related potentials (ERPs) and effective connectivity analysis. The aim is to investigate how odors'…

In the principal cells of the insect mushroom body, the Kenyon cells (KC), olfactory information is represented by a spatially and temporally sparse code. Each odor stimulus will activate only a small portion of neurons and each stimulus…

Biological Physics · Physics 2010-07-21 Farzad Farkhooi , Eilif Muller , Martin P. Nawrot

Odor sensory evaluation has a broad application in food, clothing, cosmetics, and other fields. Traditional artificial sensory evaluation has poor repeatability, and the machine olfaction represented by the electronic nose (E-nose) is…

Artificial Intelligence · Computer Science 2023-11-27 Xiuxin Xia , Yuchen Guo , Yanwei Wang , Yuchao Yang , Yan Shi , Hong Men

Storing memory for molecular recognition is an efficient strategy for responding to external stimuli. Biological processes use different strategies to store memory. In the olfactory cortex, synaptic connections form when stimulated by an…

Biological Physics · Physics 2021-06-07 Oskar H Schnaack , Luca Peliti , Armita Nourmohammad

Animals smelling in the real world use a small number of receptors to sense a vast number of natural molecular mixtures, and proceed to learn arbitrary associations between odors and valences. Here, we propose a new interpretation of how…

Neurons and Cognition · Quantitative Biology 2017-07-10 Kamesh Krishnamurthy , Ann M Hermundstad , Thierry Mora , Aleksandra M Walczak , Vijay Balasubramanian

The insect olfactory system, which includes the antennal lobe (AL), mushroom body (MB), and ancillary structures, is a relatively simple neural system capable of learning. Its structural features, which are widespread in biological neural…

Neurons and Cognition · Quantitative Biology 2018-02-09 Charles B. Delahunt , Jeffrey A. Riffell , J. Nathan Kutz

This study investigates the dynamics of non-spatial specializations in hippocampal place cells during exposure to novel environments. Hippocampal place cells, known for their role in spatial mapping, exhibit multi-modal responses to sensory…

This article provides a background and descriptive analysis of insect memory and the coding of olfactory sensation in Drosophila, presenting graphs and summary statistics from a large dataset of neurons and synapses that was recently made…

Neurons and Cognition · Quantitative Biology 2022-09-07 Chris Rohlfs

Fruit flies are established model systems for studying olfactory learning as they will readily learn to associate odors with both electric shock or sugar rewards. The mechanisms of the insect brain apparently responsible for odor learning…

Machine Learning · Computer Science 2025-01-09 Jinyung Hong , Theodore P. Pavlic

We consider the problem of olfactory searches in a turbulent environment. We focus on agents that respond solely to odor stimuli, with no access to spatial perception nor prior information about the odor. We ask whether navigation to a…

Biological Physics · Physics 2025-01-29 Marco Rando , Martin James , Alessandro Verri , Lorenzo Rosasco , Agnese Seminara

The reshaping and decorrelation of similar activity patterns by neuronal networks can enhance their discriminability, storage, and retrieval. How can such networks learn to decorrelate new complex patterns, as they arise in the olfactory…

Neurons and Cognition · Quantitative Biology 2015-06-04 Siu-Fai Chow , Stuart D. Wick , Hermann Riecke

Continual learning in computational systems is challenging due to catastrophic forgetting. We discovered a two layer neural circuit in the fruit fly olfactory system that addresses this challenge by uniquely combining sparse coding and…

Machine Learning · Computer Science 2021-12-23 Yang Shen , Sanjoy Dasgupta , Saket Navlakha

Human learning and conceptual representation is grounded in sensorimotor experience, in contrast to state-of-the-art foundation models. In this paper, we investigate how well such large-scale models, trained on vast quantities of data,…

Computation and Language · Computer Science 2025-06-05 Dan Oneata , Desmond Elliott , Stella Frank

Multimodal wearable sensor data classification plays an important role in ubiquitous computing and has a wide range of applications in scenarios from healthcare to entertainment. However, most existing work in this field employs…

Computer Vision and Pattern Recognition · Computer Science 2018-05-02 Xiang Zhang , Lina Yao , Chaoran Huang , Sen Wang , Mingkui Tan , Guodong Long , Can Wang

In recent years, more machine learning algorithms have been applied to odor classification. These odor classification algorithms usually assume that the training datasets are static. However, for some odor recognition tasks, new odor…

Machine Learning · Computer Science 2019-04-30 Yu Cheng , Angus Wong , Kevin Hung , Zhizhong Li , Weitong Li , Jun Zhang

Studies of insect olfactory processing indicate that odors are represented by rich spatio-temporal patterns of neural activity. These patterns are very difficult to predict a priori, yet they are stimulus specific and reliable upon repeated…

Neurons and Cognition · Quantitative Biology 2007-05-23 M. I. Rabinovich , R. Huerta , A. Volkovskii , Henry D. I. Abarbanel , G. Laurent

A mechanism is proposed for increasing selectivity of olfactory bulb projection neurons as compared to the olfactory receptor neurons, which could operate under low odor concentration, when the lateral inhibition mechanism becomes…

Neurons and Cognition · Quantitative Biology 2021-11-09 Alexander Vidybida

It was observed before that due to convergence in the olfactory system a possible amplification can be as large as the degree of convergence. This is in the case when a single impulse from the converging inputs is enough to trigger the…

Neurons and Cognition · Quantitative Biology 2019-01-28 Alexander Vidybida

Associative learning allows animals to rapidly adapt to changes in the environment. Whether and what aspects of such acquired traits may be transmittable across generations remains unclear. Using prolonged olfactory training and subsequent…

Neurons and Cognition · Quantitative Biology 2013-12-30 Ziv M Williams
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