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Neuromorphic computing which aims to mimic the collective and emergent behavior of the brain's neurons, synapses, axons, dendrites offers an intriguing, potentially disruptive solution to society's ever-growing computational needs. Although…

应用物理 · 物理学 2021-08-31 Uday S. Goteti , Ivan A. Zaluzhnyy , Shriram Ramanathan , Robert C. Dynes , Alex Frano

Signatures of glassy dynamics have been identified experimentally for a rich variety of materials in which molecular networks provide rigidity. Here we present a theoretical framework to study the glassy behavior of both passive and active…

统计力学 · 物理学 2013-03-26 Shenshen Wang , Peter G. Wolynes

Active systems of self-propelled agents, e.g., birds, fish, and bacteria, can organize their collective motion into myriad autonomous behaviors. Ubiquitous in nature and across length scales, such phenomena are also amenable to artificial…

软凝聚态物质 · 物理学 2024-04-17 Yuchen Xi , Trevor J. Jones , Richard Huang , Tom Marzin , P. -T. Brun

In vitro neuronal culture is an important research platform in cellular and network neuroscience. However, neurons cultured on a homogeneous scaffold form dense, randomly connected networks and display excessively synchronized activity;…

神经元与认知 · 定量生物学 2024-05-30 Hakuba Murota , Hideaki Yamamoto , Nobuaki Monma , Shigeo Sato , Ayumi Hirano-Iwata

Over the last two decades, network science has greatly advanced our understanding of how the collective behaviors of a complex system emerge from the interactions among its basic units. Multiplex networks, i.e. networks with many layers,…

We introduce NeuroPINNs, a neuroscience-inspired extension of Physics-Informed Neural Networks (PINNs) that incorporates biologically motivated spiking neuron models to achieve energy-efficient PDE solving. Unlike conventional PINNs, which…

计算物理 · 物理学 2025-11-11 Shailesh Garg , Souvik Chakraborty

At functional scales, cortical behavior results from the complex interplay of a large number of excitable cells operating in noisy environments. Such systems resist to mathematical analysis, and computational neurosciences have largely…

神经元与认知 · 定量生物学 2014-03-05 Mathieu Galtier , Jonathan Touboul

Self-organizing memristive networks are physical circuits that dynamically reconfigure their circuitry in response to external input signals. Their adaptive behavior arises from intrinsic neuro-synaptic dynamics combined with a…

无序系统与神经网络 · 物理学 2026-04-28 Yinhao Xu , Georg A. Gottwald , Zdenka Kuncic

Resistive switches are a class of emerging nanoelectronics devices that exhibit a wide variety of switching characteristics closely resembling behaviors of biological synapses. Assembled into random networks, such resistive switches produce…

新兴技术 · 计算机科学 2015-07-15 Jens Burger , Alireza Goudarzi , Darko Stefanovic , Christof Teuscher

The experimental study of neural networks requires simultaneous measurements of a massive number of neurons, while monitoring properties of the connectivity, synaptic strengths and delays. Current technological barriers make such a mission…

神经元与认知 · 定量生物学 2016-01-12 Amir Goldental , Pinhas Sabo , Shira Sardi , Roni Vardi , Ido Kanter

How the information microscopically processed by individual neurons is integrated and used in organizing the behavior of an animal is a central question in neuroscience. The coherence of neuronal dynamics over different scales has been…

无序系统与神经网络 · 物理学 2020-03-11 Takashi Hayakawa , Tomoki Fukai

Spin glasses, generally defined as disordered systems with randomized competing interactions, are a widely investigated complex system. Theoretical models describing spin glasses are broadly used in other complex systems, such as those…

Maximum entropy models are the least structured probability distributions that exactly reproduce a chosen set of statistics measured in an interacting network. Here we use this principle to construct probabilistic models which describe the…

神经元与认知 · 定量生物学 2014-01-28 Gašper Tkačik , Olivier Marre , Dario Amodei , Elad Schneidman , William Bialek , Michael J Berry

Characterizing the emergence of chaotic dynamics of complex networks is an essential task in nonlinear science with potential important applications in many fields such as neural control engineering, microgrid technologies, and ecological…

适应与自组织系统 · 物理学 2024-04-29 Ricardo Chacón , Pedro J. Martínez

Brain-inspired computing architectures attempt to emulate the computations performed in the neurons and the synapses in human brain. Memristors with continuously tunable resistances are ideal building blocks for artificial synapses. Through…

We present artificial neural network design using spin devices that achieves ultra low voltage operation, low power consumption, high speed, and high integration density. We employ spin torque switched nano-magnets for modelling neuron and…

无序系统与神经网络 · 物理学 2012-08-16 Mrigank Sharad , Charles Augustine , Georgios Panagopoulos , Kaushik Roy

Non-Boolean computing based on emerging post-CMOS technologies can potentially pave the way for low-power neural computing platforms. However, existing work on such emerging neuromorphic architectures have either focused on solely mimicking…

新兴技术 · 计算机科学 2016-11-15 Abhronil Sengupta , Yong Shim , Kaushik Roy

Mitochondrial networks exhibit a variety of complex behaviors, including coordinated cell-wide oscillations of energy states as well as a phase transition (depolarization) in response to oxidative stress. Since functional and structural…

A network of semiflexible biopolymers, known as the cytoskeleton, and molecular motors play fundamental mechanical roles in cellular activities. The cytoskeletal response to forces generated by molecular motors is profoundly linked to…

软凝聚态物质 · 物理学 2022-05-25 N. Honda , K. Shiraki , F. van Esterik , S. Inokuchi , H. Ebata , D. Mizuno

Many types of mammalian cells exert active contractile forces and mechanically deform their elastic substrate, to accomplish biological functions such as cell migration. These substrate deformations provide a mechanism by which cells can…

软凝聚态物质 · 物理学 2022-02-22 Subhaya Bose , Patrick S. Noerr , Ajay Gopinathan , Arvind Gopinath , Kinjal Dasbiswas
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