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Taking inspiration from how the brain coordinates multiple learning systems is an appealing strategy to endow robots with more flexibility. One of the expected advantages would be for robots to autonomously switch to the least costly system…

Robotics · Computer Science 2020-07-17 Rémi Dromnelle , Erwan Renaudo , Guillaume Pourcel , Raja Chatila , Benoît Girard , Mehdi Khamassi

In Rapela (2016) we reported traveling waves (TWs) on electrocorticographic (ECoG) recordings from an epileptic subject over speech processing brain regions, while the subject rhythmically produced consonant-vowel syllables (CVSs). In…

Neurons and Cognition · Quantitative Biology 2018-06-26 Joaquin Rapela

How can we build agents that keep learning from experience, quickly and efficiently, after their initial training? Here we take inspiration from the main mechanism of learning in biological brains: synaptic plasticity, carefully tuned by…

Neural and Evolutionary Computing · Computer Science 2018-08-01 Thomas Miconi , Jeff Clune , Kenneth O. Stanley

Spatiotemporal patterns such as traveling waves are frequently observed in recordings of neural activity. The mechanisms underlying the generation of such patterns are largely unknown. Previous studies have investigated the existence and…

Neurons and Cognition · Quantitative Biology 2022-09-16 Johanna Senk , Karolína Korvasová , Jannis Schuecker , Espen Hagen , Tom Tetzlaff , Markus Diesmann , Moritz Helias

As a person learns a new skill, distinct synapses, brain regions, and circuits are engaged and change over time. In this paper, we develop methods to examine patterns of correlated activity across a large set of brain regions. Our goal is…

Neurons and Cognition · Quantitative Biology 2013-10-31 Danielle S. Bassett , Nicholas F. Wymbs , M. Puck Rombach , Mason A. Porter , Peter J. Mucha , Scott T. Grafton

In this article we intoduce a novel stochastic Hebb-like learning rule for neural networks that is neurobiologically motivated. This learning rule combines features of unsupervised (Hebbian) and supervised (reinforcement) learning and is…

Disordered Systems and Neural Networks · Physics 2009-11-11 Frank Emmert-Streib

Learning and memory in the brain are implemented by complex, time-varying changes in neural circuitry. The computational rules according to which synaptic weights change over time are the subject of much research, and are not precisely…

Machine Learning · Statistics 2014-11-18 Scott W. Linderman , Christopher H. Stock , Ryan P. Adams

A family of three-dimensional travelling waves for flow through a pipe of circular cross section is identified. The travelling waves are dominated by pairs of downstream vortices and streaks. They originate in saddle-node bifurcations at…

Chaotic Dynamics · Physics 2009-11-10 H. Faisst , B. Eckhardt

We study the motion of an interface between two irrotational, incompressible fluids, with elastic bending forces present; this is the hydroelastic wave problem. We prove a global bifurcation theorem for the existence of families of…

Analysis of PDEs · Mathematics 2025-08-19 Benjamin F. Akers , David M. Ambrose , Davia W. Sulon

We investigate numerically a traveling wave pattern observed in experimental magnetized Taylor-Couette flow at low magnetic Reynolds number. By accurately modeling viscous and magnetic boundaries in all directions, we reproduce the…

Astrophysics · Physics 2008-11-26 Wei Liu , Jeremy Goodman , Hantao Ji

Correct prediction of particle transport by surface waves is crucial in many practical applications such as search and rescue or salvage operations and pollution tracking and clean-up efforts. Recent results have indicated transport by…

Fluid Dynamics · Physics 2023-01-26 D. Eeltink , R. Calvert , J. E. Swagemakers , Qian Xiao , T. S. van den Bremer

Thanks to novel, powerful brain activity recording techniques, we can create data-driven models from thousands of recording channels and large portions of the cortex, which can improve our understanding of brain-states neuromodulation and…

In marine plankton, many swimming species can perceive their environment with flow sensors. Can they use this flow information to travel faster in turbulence? To address this question, we consider plankters swimming at constant speed, whose…

Fluid Dynamics · Physics 2022-08-12 Rémi Monthiller , Aurore Loisy , Mimi A. R. Koehl , Benjamin Favier , Christophe Eloy

Update rules for learning in dynamic time warping spaces are based on optimal warping paths between parameter and input time series. In general, optimal warping paths are not unique resulting in adverse effects in theory and practice. Under…

Machine Learning · Computer Science 2018-03-05 Brijnesh J. Jain , David Schultz

Neural networks are composed of neurons and synapses, which are responsible for learning in a slow adaptive dynamical process. Here we experimentally show that neurons act like independent anisotropic multiplex hubs, which relay and mute…

Neurons and Cognition · Quantitative Biology 2017-07-21 Roni Vardi , Amir Goldental , Anton Sheinin , Shira Sardi , Ido Kanter

Synaptic plasticity, the dynamic tuning of signal transmission strength between neurons, serves as a fundamental basis for memory and learning in biological organisms. This adaptive nature of synapses is considered one of the key features…

Mesoscale and Nanoscale Physics · Physics 2024-11-11 Yechan Noh , Alex Smolyanitsky

We study the traveling wave solutions to a reaction diffusion system modeling the public goods game with altruistic behaviors. The existence of the waves is derived through monotone iteration of a pair of classical upper- and lower…

Analysis of PDEs · Mathematics 2009-09-09 Xiaojie Hou , Wei Feng

Biological neurons and their in-silico emulations for neuromorphic artificial intelligence (AI) use extraordinarily energy-efficient mechanisms, such as spike-based communication and local synaptic plasticity. It remains unclear whether…

Neural and Evolutionary Computing · Computer Science 2021-06-17 Timoleon Moraitis , Abu Sebastian , Evangelos Eleftheriou

We study traveling wave solutions of an equation for surface waves of moderate amplitude arising as a shallow water approximation of the Euler equations for inviscid, incompressible and homogenous fluids. We obtain solitary waves of…

Classical Analysis and ODEs · Mathematics 2013-12-06 Armengol Gasull , Anna Geyer

Efficient techniques to navigate networks with local information are fundamental to sample large-scale online social systems and to retrieve resources in peer-to-peer systems. Biased random walks, i.e. walks whose motion is biased on…

Physics and Society · Physics 2016-06-29 Federico Battiston , Vincenzo Nicosia , Vito Latora