English
Related papers

Related papers: Stroboscopic motion reversals in delay-coupled neu…

200 papers

We study two delay-coupled FitzHugh-Nagumo systems, introducing a mismatch between the delay times, as the simplest representation of interacting neurons. We demonstrate that the presence of delays can cause periodic oscillations which…

Adaptation and Self-Organizing Systems · Physics 2009-11-12 Anastasiia Panchuk , Markus Dahlem , Eckehard Schöll

Both a good understanding of geometrical concepts and a broad familiarity with objects lead to our excellent perception of moving objects. The human ability to detect and segment moving objects works in the presence of multiple objects,…

Computer Vision and Pattern Recognition · Computer Science 2022-03-02 Pia Bideau , Erik Learned-Miller , Cordelia Schmid , Karteek Alahari

To gain insight into the neural events responsible for visual perception of static and dynamic optical patterns, we study how neural activation spreads in arrays of inhibition-stabilized neural networks with nearest-neighbor coupling. The…

Neurons and Cognition · Quantitative Biology 2016-09-02 Sergey Savel'ev , Sergei Gepshtein

Model Predictive Controllers (MPC) require a good model for the controlled process. In this paper I infer inductive biases about a physical system. I use these biases to derive a new neural network architecture that can model this real…

Machine Learning · Computer Science 2021-04-26 Cristian Vicas

This paper exploits the fact that the variability in the inter-spike intervals, in the spike train issuing from a neuron, carries substantial information regarding the input to the neuron. A framework for neuronal information processing is…

Neurons and Cognition · Quantitative Biology 2008-08-04 Balaram Das

Networks of neural mass nodes with delayed interactions are increasingly being used as models for large-scale brain activity. To complement the growing number of computational studies of such networks, it is timely to develop new…

Dynamical Systems · Mathematics 2025-09-29 S Coombes , H G E Meijer

Sensory perception originates from the responses of sensory neurons, which react to a collection of sensory signals linked to various physical attributes of a singular perceptual object. Unraveling how the brain extracts perceptual…

Neurons and Cognition · Quantitative Biology 2025-10-27 Zhichao Zhu , Yang Qi , Wenlian Lu , Jianfeng Feng

Neural style transfer is an emerging technique which is able to endow daily-life images with attractive artistic styles. Previous work has succeeded in applying convolutional neural networks (CNNs) to style transfer for monocular images or…

Computer Vision and Pattern Recognition · Computer Science 2018-07-30 Xinyu Gong , Haozhi Huang , Lin Ma , Fumin Shen , Wei Liu , Tong Zhang

Why do moving objects appear rigid when projected retinal images are deformed nonrigidly? We used rotating rigid objects that can appear rigid or non-rigid to test whether shape features contribute to rigidity perception. When two circular…

Neurons and Cognition · Quantitative Biology 2023-04-12 Akihito Maruya , Qasim Zaidi

This paper gives an in-depth theoretical analysis of the direction and speed selectivity properties of idealized models of the spatio-temporal receptive fields of simple cells and complex cells, based on the generalized Gaussian derivative…

Neurons and Cognition · Quantitative Biology 2026-01-15 Tony Lindeberg

Biological nervous systems constitute important sources of inspiration towards computers that are faster, cheaper, and more energy efficient. Neuromorphic disciplines view the brain as a coevolved system, simultaneously optimizing the…

Neural and Evolutionary Computing · Computer Science 2025-09-18 Jens Egholm Pedersen , Jörg Conradt , Tony Lindeberg

We consider the problem of the limit of bio-inspired spatially extended neuronal networks including an infinite number of neuronal types (space locations), with space-dependent propagation delays modeling neural fields. The propagation of…

Probability · Mathematics 2016-05-30 Jonathan Touboul

Learning how complex dynamical systems evolve over time is a key challenge in system identification. For safety critical systems, it is often crucial that the learned model is guaranteed to converge to some equilibrium point. To this end,…

Machine Learning · Computer Science 2021-12-13 Andreas Schlaginhaufen , Philippe Wenk , Andreas Krause , Florian Dörfler

In this work we extend and improve the results done in a previous work on simulating Spiking Neural P systems (SNP systems in short) with delays using SNP systems without delays. We simulate the former with the latter over sequential,…

Neural and Evolutionary Computing · Computer Science 2012-12-12 Francis George C. Cabarle , Kelvin C. Buño , Henry N. Adorna

Representational drift refers to over-time changes in neural activation accompanied by a stable task performance. Despite being observed in the brain and in artificial networks, the mechanisms of drift and its implications are not fully…

Disordered Systems and Neural Networks · Physics 2023-06-07 Farhad Pashakhanloo , Alexei Koulakov

The distinct timescales of synaptic plasticity and neural activity dynamics play an important role in the brain's learning and memory systems. Activity-dependent plasticity reshapes neural circuit architecture, determining spontaneous and…

Neurons and Cognition · Quantitative Biology 2023-06-30 Heather L Cihak , Zachary P Kilpatrick

Networks of fast-spiking interneurons are crucial for the generation of neural oscillations in the brain. Here we study the synchronous behavior of interneuronal networks that are coupled by delayed inhibitory and fast electrical synapses.…

Neurons and Cognition · Quantitative Biology 2012-06-22 Daqing Guo , Qingyun Wang , Matjaz Perc

Neural representations of visual perception are affected by mental imagery and attention. Although attention is known to modulate neural representations, it is unknown how imagery changes neural representations when imagined and perceived…

Simulating trajectories of dynamical systems is a fundamental problem in a wide range of fields such as molecular dynamics, biochemistry, and pedestrian dynamics. Machine learning has become an invaluable tool for scaling physics-based…

Machine Learning · Computer Science 2026-05-28 Kiet Bennema ten Brinke , Koen Minartz , Vlado Menkovski

Previously we showed how delay communication between globally coupled self-propelled agents causes new spatio-temporal patterns to arise when the delay coupling is fixed among all agents \cite{Forgoston08}. In this paper, we show how…

Pattern Formation and Solitons · Physics 2012-04-23 Brandon Lindley , Luis Mier-y-Teran-Romero , Ira B. Schwartz