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Various neurophysiological and cognitive functions are based on transferring information between spiking neurons via a complex system of synaptic connections. In particular, the capacity of presynaptic inputs to influence the postsynaptic…

Neurons and Cognition · Quantitative Biology 2018-10-30 Y. Dabaghian

The behavior of active matter under confinement poses significant challenges due to the intricate coupling between dynamics near boundaries and those in the bulk. A defining feature of active matter systems is that a substantial portion of…

Analysis of PDEs · Mathematics 2025-08-25 Leonid Berlyand , Spencer Dang , Pierre-Emmanuel Jabin , Mykhailo Potomkin

We study the characteristics of weak signal detection by a recurrent neuronal network with plastic synaptic coupling. It is shown that in the presence of an asynchronous component in synaptic transmission, the network acquires selectivity…

Neurons and Cognition · Quantitative Biology 2015-05-13 Vladislav Volman , Herbert Levine

We report a detailed and systematic study of wave propagation through a stochastic absorbing random medium. Stochastic absorption is modeled by introducing an attenuation constant per unit length $\alpha$ in the free propagation region of…

Disordered Systems and Neural Networks · Physics 2009-10-31 Sandeep K. Joshi , Debendranath Sahoo , A. M. Jayannavar

Synaptic plasticity seems to be a capital aspect of the dynamics of neural networks. It is about the physiological modifications of the synapse, which have like consequence a variation of the value of the synaptic weight. The information…

Computer Vision and Pattern Recognition · Computer Science 2012-09-25 Tarek Behi , Najet Arous , Noureddine Ellouze

A mesoscopic continuum model is employed to analyse the transport mechanisms and structure formation during the redistribution stage of deposition experiments where organic molecules are deposited on a solid substrate with periodic…

Mesoscale and Nanoscale Physics · Physics 2018-07-24 Christoph Honisch , Te-Sheng Lin , Andreas Heuer , Uwe Thiele , Svetlana Gurevich

We study a neural network model in which both neurons and synaptic interactions evolve in time simultaneously. The time evolution of synaptic interactions is described by a Langevin equation including a Hebbian learning term, and a bias…

Biological Physics · Physics 2009-03-12 T. Uezu , K. Abe , S. Miyoshi , M. Okada

We present a method of estimating the gradient of an objective function with respect to the synaptic weights of a spiking neural network. The method works by measuring the fluctuations in the objective function in response to dynamic…

Neurons and Cognition · Quantitative Biology 2007-05-23 Ila R. Fiete , H. Sebastian Seung

Mathematical models of glucose, insulin, and pancreatic $\beta$-cell mass dynamics are essential for understanding the physiological basis of type 2 diabetes. This paper investigates the Topp model's discrete-time dynamics to represent…

Dynamical Systems · Mathematics 2024-05-02 Z. S. Boxonov , U. A. Rozikov

We utilize the externally forced linearized Navier-Stokes equations to study the receptivity of pre-transitional boundary layers to persistent sources of stochastic excitation. Stochastic forcing is used to model the effect of free-stream…

Fluid Dynamics · Physics 2019-09-09 Wei Ran , Armin Zare , M. J. Philipp Hack , Mihailo R. Jovanović

Recent biological experimental findings have shown that synaptic plasticity depends on the relative timing of pre- and post-synaptic spikes and this is called spike-timing-dependent plasticity (STDP). Many authors have claimed that a…

Disordered Systems and Neural Networks · Physics 2007-05-23 Narihisa Matsumoto , Masato Okada

We investigate the behaviour of the response function in the one dimensional trap model using scaling arguments that we confirm by numerical simulations. We study the average position of the random walk at time tw+t given that a small bias…

Disordered Systems and Neural Networks · Physics 2009-11-10 E. M. Bertin , J. -P. Bouchaud

Mixed-signal neuromorphic processors with brain-like organization and device physics offer an ultra-low-power alternative to the unsustainable developments of conventional deep learning and computing. However, realizing the potential of…

Neural and Evolutionary Computing · Computer Science 2022-08-05 Mattias Nilsson , Foteini Liwicki , Fredrik Sandin

In this paper we consider a multiparticle version of a recent probabilistic framework for studying diffusion-mediated surface reactions. The basic idea of the probabilistic approach is to consider the joint probability density or…

Statistical Mechanics · Physics 2022-10-19 Paul C Bressloff

We study reflection and transmission of waves in a random tight-binding system with absorption or gain for weak disorder, using a scattering matrix formalism. Our aim is to discuss analytically the effects of absorption or gain on the…

Mesoscale and Nanoscale Physics · Physics 2009-11-11 J. Heinrichs

Memories are stored, at least partly, as patterns of strong synapses. Given molecular turnover, how can synapses maintain strong for the years that memories can persist? Some models postulate that biochemical bistability maintains strong…

Neurons and Cognition · Quantitative Biology 2015-04-09 Paul Smolen

A position-dependent stochastic diffusion model of gating in ion channels is developed by considering the spatial variation of the diffusion coefficient between the closed and open states. It is assumed that a sensor which regulates the…

Mesoscale and Nanoscale Physics · Physics 2014-07-24 Samuel Robert Vaccaro

We present a computationally tractable scheme of time-dependent transport phenomena within open-boundary time-dependent density-functional-theory. Within this approach all the response properties of a system are determined from the…

Other Condensed Matter · Physics 2009-11-11 S. Kurth , G. Stefanucci , C. -O. Almbladh , A. Rubio , E. K. U. Gross

In this paper we develop an encounter-based model of reaction-subdiffusion in a domain $\Omega$ with a partially absorbing interior trap $\calU\subset \Omega$. We assume that the particle can freely enter and exit $\calU$, but is only…

Statistical Mechanics · Physics 2023-03-21 Paul C Bressloff

The N-methyl-D-aspartate receptor (NMDAR) is a crucial component of synaptic transmission, and its dysfunction is implicated in many neurological diseases and psychiatric conditions. NMDAR-based short-term postsynaptic plasticity (STPP) is…

Neurons and Cognition · Quantitative Biology 2023-09-28 Huilin Zhao , Sungchil Yang , Chi Chung Alan Fung