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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

Learning is based on synaptic plasticity, which affects and is driven by neural activity. Because pre- and postsynaptic spiking activity is shaped by randomness, the synaptic weights follow a stochastic process, requiring a probabilistic…

Neurons and Cognition · Quantitative Biology 2026-01-14 Jakob Stubenrauch , Naomi Auer , Richard Kempter , Benjamin Lindner

Efficient continual learning in humans is enabled by a rich set of neurophysiological mechanisms and interactions between multiple memory systems. The brain efficiently encodes information in non-overlapping sparse codes, which facilitates…

Neural and Evolutionary Computing · Computer Science 2023-01-13 Fahad Sarfraz , Elahe Arani , Bahram Zonooz

The ability to predict future events or patterns based on previous experience is crucial for many applications such as traffic control, weather forecasting, or supply chain management. While modern supervised Machine Learning approaches…

Neurons and Cognition · Quantitative Biology 2024-10-16 Florian Feiler , Emre Neftci , Younes Bouhadjar

The sequential recommendation task aims to predict the item that user is interested in according to his/her historical action sequence. However, inevitable random action, i.e. user randomly accesses an item among multiple candidates or…

Information Retrieval · Computer Science 2024-04-09 Sirui Wang , Peiguang Li , Yunsen Xian , Hongzhi Zhang

Neural populations encode information about their stimulus in a collective fashion, by joint activity patterns of spiking and silence. A full account of this mapping from stimulus to neural activity is given by the conditional probability…

Neurons and Cognition · Quantitative Biology 2013-06-14 Einat Granot-Atedgi , Gašper Tkačik , Ronen Segev , Elad Schneidman

Rhythmic activity has been associated with a wide range of cognitive processes. Previous studies have shown that spike-timing-dependent plasticity can facilitate the transfer of rhythmic activity downstream the information processing…

Neurons and Cognition · Quantitative Biology 2020-09-09 Nimrod Sherf , Maoz Shamir

Habituation - a phenomenon in which a dynamical system exhibits a diminishing response to repeated stimulations that eventually recovers when the stimulus is withheld - is universally observed in living systems from animals to unicellular…

Adaptation and Self-Organizing Systems · Physics 2024-07-26 Matthew Smart , Stanislav Y. Shvartsman , Martin Mönnigmann

Time perception is the phenomenological experience of time by an individual. In this paper, we study how to replicate neural mechanisms involved in time perception, allowing robots to take a step towards temporal cognition. Our framework…

Systems and Control · Electrical Eng. & Systems 2019-12-24 Inês Lourenço , Bo Wahlberg , Rodrigo Ventura

Spikes are the currency in central nervous systems for information transmission and processing. They are also believed to play an essential role in low-power consumption of the biological systems, whose efficiency attracts increasing…

Neural and Evolutionary Computing · Computer Science 2020-05-05 Qiang Yu , Shenglan Li , Huajin Tang , Longbiao Wang , Jianwu Dang , Kay Chen Tan

Traditionally, the automatic recognition of human activities is performed with supervised learning algorithms on limited sets of specific activities. This work proposes to recognize recurrent activity patterns, called routines, instead of…

Machine Learning · Computer Science 2019-07-11 Paul Compagnon , Grégoire Lefebvre , Stefan Duffner , Christophe Garcia

This article underlines the learning and discrimination capabilities of a model of associative memory based on artificial networks of spiking neurons. Inspired from neuropsychology and neurobiology, the model implements top-down…

Neural and Evolutionary Computing · Computer Science 2016-08-16 Anthony Mouraud , Hélène Paugam-Moisy

Animals often receive information about errors and rewards after a significant delay. For example, there is typically a delay of tens to hundreds of milliseconds between motor actions and visual feedback. The standard approach to handling…

A hallmark of biological intelligence and control is combinatorial generalization: animals are able to learn various things, then piece them together in new combinations to produce appropriate outputs for new tasks. Inspired by the ability…

Neurons and Cognition · Quantitative Biology 2022-10-07 Sunny Duan , Mikail Khona , Adrian Bertagnoli , Sarthak Chandra , Ila Fiete

Agents that can learn to imitate given video observation -- \emph{without direct access to state or action information} are more applicable to learning in the natural world. However, formulating a reinforcement learning (RL) agent that…

Machine Learning · Computer Science 2023-07-14 Glen Berseth , Florian Golemo , Christopher Pal

"Monkey see monkey do" is an age-old adage, referring to na\"ive imitation without a deep understanding of a system's underlying mechanics. Indeed, if a demonstrator has access to information unavailable to the imitator (monkey), such as a…

Machine Learning · Computer Science 2022-08-15 Daniel Kumor , Junzhe Zhang , Elias Bareinboim

Precise spatio-temporal patterns of neuronal action potentials underly e.g. sensory representations and control of muscle activities. However, it is not known how the synaptic efficacies in the neuronal networks of the brain adapt such that…

Neurons and Cognition · Quantitative Biology 2015-02-24 Christian Albers , Maren Westkott , Klaus Pawelzik

Animals rely on different decision strategies when faced with ambiguous or uncertain cues. Depending on the context, decisions may be biased towards events that were most frequently experienced in the past, or be more explorative. A…

Neurons and Cognition · Quantitative Biology 2023-05-10 Younes Bouhadjar , Dirk J. Wouters , Markus Diesmann , Tom Tetzlaff

The occurrence of sleep passed through the evolutionary sieve and is widespread in animal species. Sleep is known to be beneficial to cognitive and mnemonic tasks, while chronic sleep deprivation is detrimental. Despite the importance of…

Neurons and Cognition · Quantitative Biology 2019-11-19 Cristiano Capone , Elena Pastorelli , Bruno Golosio , Pier Stanislao Paolucci

Behaviour change lies at the heart of many observable collective phenomena such as the transmission and control of infectious diseases, adoption of public health policies, and migration of animals to new habitats. Representing the process…

Quantitative Methods · Quantitative Biology 2025-09-03 Roben Delos Reyes , Hugo Lyons Keenan , Cameron Zachreson