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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

Evolutionary robot systems offer two principal advantages: an advanced way of developing robots through evolutionary optimization and a special research platform to conduct what-if experiments regarding questions about evolution. Our study…

Robotics · Computer Science 2023-09-26 Jie Luo , Karine Miras , Jakub Tomczak , Agoston E. Eiben

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

The co-optimization of a robot's body and brain presents a coupled challenge: the morphology constrains which control strategies are effective, while the control determines how well the morphology performs. To address this, we combine…

Robotics · Computer Science 2026-05-18 K. Ege de Bruin , Kyrre Glette , Kai Olav Ellefsen

Lamarckian inheritance has been shown to be a powerful accelerator in systems where the joint evolution of robot morphologies and controllers is enhanced with individual learning. Its defining advantage lies in the offspring inheriting…

Robotics · Computer Science 2026-04-20 Jed R Muff , Karine Miras , A. E. Eiben

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

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

Instructive influence of environment on heredity has been a debated topic for centuries. Darwin's identification of natural selection coupled to chance variation as the driving force for evolution, against a formal interpretation proposed…

Genomics · Quantitative Biology 2007-05-23 Antoine Danchin

Handedness in humans - better performance using either the left or right hand - is personally familiar, moderately heritable, and regulated by many genes, including those involved in general body symmetry. But behavioral handedness, i.e.…

Neurons and Cognition · Quantitative Biology 2016-07-13 Sean Buchanan , Jamey Kain , Benjamin de Bivort

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

Current models of animal evolution focus on selection of individuals, ignoring the much faster selection of symbiotic bacteria. Here we take host-symbiont interactions into account by introducing a Population Genetics-like model of…

Populations and Evolution · Quantitative Biology 2016-12-28 Dino Osmanovic , David A Kessler , Yitzhak Rabin , Yoav Soen

The animals, in particular insects (Drosophila melanogaster), response towards odor stimuli in nature can be established by measuring the dynamic of the odor response. Such an approach is innovative since responses to odors were tested only…

Quantitative Methods · Quantitative Biology 2009-07-20 Agnieszka Ruebenbauer

Recordings from neurons in the insects' olfactory primary processing center, the antennal lobe (AL), reveal that the AL is able to process the input from chemical receptors into distinct neural activity patterns, called olfactory neural…

Neurons and Cognition · Quantitative Biology 2014-08-27 Eli Shlizerman , Jeffrey A. Riffell , J. Nathan Kutz

This study explores the integration of Lamarckian system into evolutionary robotics (ER), comparing it with the traditional Darwinian model across various environments. By adopting Lamarckian principles, where robots inherit learned traits,…

Robotics · Computer Science 2024-03-29 Jie Luo , Karine Miras , Carlo Longhi , Oliver Weissl , Agoston E. Eiben

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

In evolutionary robotics, robot morphologies are designed automatically using evolutionary algorithms. This creates a body-brain optimization problem, where both morphology and control must be optimized together. A common approach is to…

Robotics · Computer Science 2026-01-08 K. Ege de Bruin , Kyrre Glette , Kai Olav Ellefsen

Our understanding of the neural basis of locomotor behavior can be informed by careful quantification of animal movement. Classical descriptions of legged locomotion have defined discrete locomotor gaits, characterized by distinct patterns…

Neurons and Cognition · Quantitative Biology 2022-03-02 Ana I. Gonçalves , Jacob A. Zavatone-Veth , Megan R. Carey , Damon A. Clark

Associating multiple sensory cues with a single experience or object is a fundamental process that improves object recognition and memory performance. However, neural mechanisms that bind sensory features during learning and augment memory…

The mammalian olfactory system learns rapidly from very few examples, presented in unpredictable online sequences, and then recognizes these learned odors under conditions of substantial interference without exhibiting catastrophic…

Neural and Evolutionary Computing · Computer Science 2019-07-15 Ayon Borthakur , Thomas A. Cleland

Living systems continually respond to signals from the surrounding environment. Survival requires that their responses adapt quickly and robustly to the changes in the environment. One particularly challenging example is olfactory…

Neurons and Cognition · Quantitative Biology 2024-10-08 Kiri Choi , Will Rosenbluth , Isabella R. Graf , Nirag Kadakia , Thierry Emonet
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