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Spiking neural networks have shown great promise for the design of low-power sensory-processing and edge-computing hardware platforms. However, implementing on-chip learning algorithms on such architectures is still an open challenge,…

Neural and Evolutionary Computing · Computer Science 2021-04-13 Matteo Cartiglia , Germain Haessig , Giacomo Indiveri

Kirigami offers unique opportunities for guided morphing by leveraging the geometry of the cuts. This work presents inflatable kirigami crawlers created by introducing cut patterns into heat-sealable textiles to achieve locomotion upon…

Robotics · Computer Science 2025-06-06 Burcu Seyidoğlu , Aida Parvaresh , Bahman Taherkhani , Ahmad Rafsanjani

With the rising societal demand for more information-processing capacity with lower power consumption, alternative architectures inspired by the parallelism and robustness of the human brain have recently emerged as possible solutions. In…

Neurons and Cognition · Quantitative Biology 2019-07-02 Emily Toomey , Ken Segall , Karl K. Berggren

Beyond providing accurate movements, achieving smooth motion trajectories is a long-standing goal of robotics control theory for arms aiming to replicate natural human movements. Drawing inspiration from biological agents, whose reaching…

Robotics · Computer Science 2023-03-09 Ioannis Polykretis , Lazar Supic , Andreea Danielescu

Self-organized robots may develop attracting states within the sensorimotor loop, that is within the phase space of neural activity, body, and environmental variables. Fixpoints, limit cycles, and chaotic attractors correspond in this…

Adaptation and Self-Organizing Systems · Physics 2019-01-18 Bulcsú Sándor , Michael Nowak , Tim Koglin , Laura Martin , Claudius Gros

We construct a two-dimensional electric circuit model for creeping discharge. Two types of discharge, surface corona and surface leader, are modeled by a two-step function of conductance. Branched patterns of surface leaders surrounded by…

Pattern Formation and Solitons · Physics 2010-04-08 Hidetsugu Sakaguchi , Sahim M. Kourkouss

Simulation speed matters for neuroscientific research: this includes not only how quickly the simulated model time of a large-scale spiking neuronal network progresses, but also how long it takes to instantiate the network model in computer…

Air hockey demands split-second decisions at high puck velocities, a challenge we address with a compact network of spiking neurons running on a mixed-signal analog/digital neuromorphic processor. By co-designing hardware and learning…

The critical state is assumed to be optimal for any computation in recurrent neural networks, because criticality maximizes a number of abstract computational properties. We challenge this assumption by evaluating the performance of a…

Emerging Technologies · Computer Science 2020-11-05 Benjamin Cramer , David Stöckel , Markus Kreft , Michael Wibral , Johannes Schemmel , Karlheinz Meier , Viola Priesemann

Rectilinear crawling locomotion is a primitive and common mode of locomotion in slender, soft-bodied animals. It requires coordinated contractions that propagate along a body that interacts frictionally with its environment. We propose a…

Biological Physics · Physics 2021-08-31 Shruti Mishra , Wim M. van Rees , L. Mahadevan

We describe a chain of unidirectionally coupled adaptive excitable elements slowly driven by a stochastic process from one end and open at the other end, as a minimal toy model of unresolved irreducible uncertainty in a system performing…

Neurons and Cognition · Quantitative Biology 2022-09-14 Mario Martinez-Saito

In this paper, we study the impact of electrical and memristor-based couplings on some neuron-like spiking regimes, previously observed in the ensemble of two identical FitzHugh-Nagumo elements with chemical excitatory coupling. We…

Chaotic Dynamics · Physics 2019-10-23 Alexander G. Korotkov , Tatiana A. Levanova , Alexey O. Kazakov

Many central neurons, and in particular certain brainstem aminergic neurons exhibit spontaneous and fairly regular spiking with frequencies of order a few Hz. A large number of ion channel types contribute to such spiking so that accurate…

Neurons and Cognition · Quantitative Biology 2015-08-25 Henry C. Tuckwell , Ying Zhou , Nicholas J. Penington

We apply the framework of optimal nonlinear control to steer the dynamics of a whole-brain network of FitzHugh-Nagumo oscillators. Its nodes correspond to the cortical areas of an atlas-based segmentation of the human cerebral cortex, and…

Neurons and Cognition · Quantitative Biology 2021-09-08 Teresa Chouzouris , Nicolas Roth , Caglar Cakan , Klaus Obermayer

The dynamic membrane potential threshold, as one of the essential properties of a biological neuron, is a spontaneous regulation mechanism that maintains neuronal homeostasis, i.e., the constant overall spiking firing rate of a neuron. As…

Robotics · Computer Science 2023-06-21 Jianchuan Ding , Bo Dong , Felix Heide , Yufei Ding , Yunduo Zhou , Baocai Yin , Xin Yang

We demonstrate a spiking neural network for navigation motivated by the chemotaxis network of Caenorhabditis elegans. Our network uses information regarding temporal gradients in the tracking variable's concentration to make navigational…

Neural and Evolutionary Computing · Computer Science 2014-10-30 Shibani Santurkar , Bipin Rajendran

Artificial spiking neural networks have found applications in areas where the temporal nature of activation offers an advantage, such as time series prediction and signal processing. To improve their efficiency, spiking architectures often…

This work presents an event-triggered controller for spacecraft rendezvous hovering phases. The goal is to maintain the chaser within a bounded region with respect to the target. The main assumption is that the chaser vehicle has impulsive…

Systems and Control · Electrical Eng. & Systems 2025-01-22 Julio C. Sanchez , Christophe Louembet , Francisco Gavilan , Rafael Vazquez

Recently, researchers have explored control methods that embrace nonlinear dynamic coupling instead of suppressing it. Such designs leverage dynamical coupling for communication between different parts of the robot. Morphological…

Neural and Evolutionary Computing · Computer Science 2025-08-28 Matthew Meek , Guy Tallent , Thomas Breimer , James Gaskell , Abhay Kashyap , Atharv Tekurkar , Jonathan Fischman , Luodi Wang , Viet-Dung Nguyen , John Rieffel

Future developments in artificial intelligence will profit from the existence of novel, non-traditional substrates for brain-inspired computing. Neuromorphic computers aim to provide such a substrate that reproduces the brain's capabilities…

Neural and Evolutionary Computing · Computer Science 2019-10-02 Timo C. Wunderlich , Akos F. Kungl , Eric Müller , Johannes Schemmel , Mihai Petrovici
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