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We study numerically and analytically first- and second-order phase transitions in neuronal networks stimulated by shot noise (a flow of random spikes bombarding neurons). Using an exactly solvable cortical model of neuronal networks on…

Neurons and Cognition · Quantitative Biology 2015-08-25 K. -E. Lee , M. A. Lopes , J. F. F. Mendes , A. V. Goltsev

In neurosciences, the brain processes information via the firing patterns of connected neurons operating across a spectrum of frequencies. To better understand the effects of these frequencies in the neuron dynamics, we have simulated a…

Neurons and Cognition · Quantitative Biology 2025-11-21 Gabriel Marghoti , Thiago L. Prado , Miguel A. F. Sanjuán , Sergio R. Lopes

Neuronal voltage dynamics of regularly firing neurons typically has one stable attractor: either a fixed point (like in the subthreshold regime) or a limit cycle that defines the tonic firing of action potentials (in the suprathreshold…

Neurons and Cognition · Quantitative Biology 2021-01-20 Jan-Hendrik Schleimer , Janina Hesse , Susana Andrea Contreras , Susanne Schreiber

The timing of individual neuronal spikes is essential for biological brains to make fast responses to sensory stimuli. However, conventional artificial neural networks lack the intrinsic temporal coding ability present in biological…

Neural and Evolutionary Computing · Computer Science 2020-11-18 Iulia M. Comsa , Krzysztof Potempa , Luca Versari , Thomas Fischbacher , Andrea Gesmundo , Jyrki Alakuijala

It has long been debated whether information in the brain is coded at the rate of neuronal spiking or at the precise timing of single spikes. Although this issue is essential to the understanding of neural signal processing, it is not…

Neurons and Cognition · Quantitative Biology 2014-02-17 Yasuhiro Mochizuk , Shigeru Shinomoto

Neural coding is a field of study that concerns how sensory information is represented in the brain by networks of neurons. The link between external stimulus and neural response can be studied from two parallel points of view. The first,…

Neurons and Cognition · Quantitative Biology 2012-03-07 Shinsuke Koyama

The success of deep learning in the past decade is partially shrouded in the shadow of adversarial attacks. In contrast, the brain is far more robust at complex cognitive tasks. Utilizing the advantage that neurons in the brain communicate…

Neurons and Cognition · Quantitative Biology 2023-06-12 Jianhao Ding , Zhaofei Yu , Tiejun Huang , Jian K. Liu

Information encoding in the nervous system is supported through the precise spike-timings of neurons; however, an understanding of the underlying processes by which such representations are formed in the first place remains unclear. Here we…

Neural and Evolutionary Computing · Computer Science 2015-12-01 Brian Gardner , Ioana Sporea , André Grüning

In this paper, we investigate saddle-node to saddle separatrix--loops that we term SNICeroclinic bifurcations. They are generic codimension-two bifurcations involving a heteroclinic loop between one non-hyperbolic and one hyperbolic saddle.…

Dynamical Systems · Mathematics 2025-10-20 Kateryna Nechyporenko , Peter Ashwin , Krasimira Tsaneva-Atanasova

Understanding how the dynamics of neural networks is shaped by the computations they perform is a fundamental question in neuroscience. Recently, the framework of efficient coding proposed a theory of how spiking neural networks can compute…

Neurons and Cognition · Quantitative Biology 2022-10-25 Veronika Koren , Stefano Panzeri

Human cognition emerges from coordinated spiking dynamics in distributed neural circuits, where information is encoded via both firing rates and precise spike timing determined by brain rhythms. Inspired by this notion, we propose a…

Neurons and Cognition · Quantitative Biology 2026-05-05 Tingting Dan , Guorong Wu

Recent experimental and theoretical studies have indicated that the putative criticality of cortical dynamics may corresponds to a synchronization phase transition. The critical dynamics near such a critical point needs further…

Disordered Systems and Neural Networks · Physics 2022-05-04 Mahsa Khoshkhou , Afshin Montakhab

Neuromorphic computing has recently gained momentum with the emergence of various neuromorphic processors. As the field advances, there is an increasing focus on developing training methods that can effectively leverage the unique…

Emerging Technologies · Computer Science 2025-04-15 Sanaz Mahmoodi Takaghaj , Jack Sampson

We consider the effect on tipping from an additive periodic forcing in a canonical model with a saddle node bifurcation and a slowly varying bifurcation parameter. Here tipping refers to the dramatic change in dynamical behavior…

Classical Analysis and ODEs · Mathematics 2015-08-28 Jielin Zhu , Rachel Kuske , Thomas Erneux

Neuromorphic computing, inspired by the functionality and efficiency of biological neural systems, holds promise for advancing artificial intelligence and computational paradigms. Resonant tunneling diodes (RTDs), thanks to their ability to…

We demonstrate that the information contained in the spike occurrence times of a population of neurons can be broken up into a series of terms, each of which reflect something about potential coding mechanisms. This is possible in the…

Biological Physics · Physics 2007-05-23 S. Panzeri , S. R. Schultz

Although temporal coding through spike-time patterns has long been of interest in neuroscience, the specific structures that could be useful for spike-time codes remain highly unclear. Here, we introduce a new analytical approach, using…

Neurons and Cognition · Quantitative Biology 2022-11-15 Federico W. Pasini , Alexandra N. Busch , Ján Mináč , Krishnan Padmanabhan , Lyle Muller

The saddle-node bifurcation on an invariant circle (SNIC) is one of the codimension-one routes to creation or destruction of a periodic orbit in a continuous-time dynamical system. It governs the transition from resting behaviour to…

Dynamical Systems · Mathematics 2015-06-17 Claude Baesens , Robert S. MacKay

Spikes are the currency in central nervous systems for information transmission and processing. They are also believed to play an essential role in low-power consumption of the biological systems, whose efficiency attracts increasing…

Neural and Evolutionary Computing · Computer Science 2020-05-05 Qiang Yu , Shenglan Li , Huajin Tang , Longbiao Wang , Jianwu Dang , Kay Chen Tan

Repeating spatiotemporal spike patterns exist and carry information. Here we investigated how a single spiking neuron can optimally respond to one given pattern (localist coding), or to either one of several patterns (distributed coding,…

Neural and Evolutionary Computing · Computer Science 2018-09-24 Timothée Masquelier , Saeed Reza Kheradpisheh
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