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At the level of individual neurons, various coding properties can be inferred from the input-output relationship of a cell. For small inputs, this relation is captured by the phase-response curve (PRC), which measures the effect of a small…

神经元与认知 · 定量生物学 2026-01-14 Janina Hesse , Susanne Schreiber

Regular firing neurons can be seen as oscillators. The phase-response curve (PRC) describes how such neurons will respond to small excitatory perturbations. Knowledge of the PRC is important as it is associated to the excitability type of…

神经元与认知 · 定量生物学 2010-01-05 Benjamin Torben-Nielsen , Marylka Uusisaari , Klaus M. Stiefel

The phase-response curve (PRC) is an important tool to determine the excitability type of single neurons which reveals consequences for their synchronizing properties. We review five methods to compute the PRC from both model data and…

定量方法 · 定量生物学 2010-03-29 Benjamin Torben-Nielsen , Marylka Uusisaari , Klaus M. Stiefel

Synchronized neural spiking is associated with many cognitive functions and thus, merits study for its own sake. The analysis of neural synchronization naturally leads to the study of repetitive spiking and consequently to the analysis of…

神经元与认知 · 定量生物学 2017-07-19 Youngmin Park , Stewart Heitmann , G. Bard Ermentrout

We present a study on the emergence of a variety of spatio temporal patterns among neurons that are connected in a multiplex framework, with neurons on two layers with different functional couplings. With the Hindmarsh-Rose model for the…

适应与自组织系统 · 物理学 2021-11-29 Umesh Kumar Verma , G. Ambika

The Phase Response Curve (PRC) is a tool used in neuroscience that measures the phase shift experienced by an oscillator due to a perturbation applied at different phases of the limit cycle. In this paper we present a new approach to PRCs…

动力系统 · 数学 2019-07-24 Alberto Pérez-Cervera , Tere M. Seara , Gemma Huguet

Brain rhythms emerge as a result of synchronization among interconnected spiking neurons. Key properties of such rhythms can be gleaned from the phase-resetting curve (PRC). Inferring the macroscopic PRC and developing a systematic phase…

神经元与认知 · 定量生物学 2022-10-12 Gregory Dumont , Alberto Pérez-Cervera , Boris Gutkin

Phase response curve (PRC) is an extremely useful tool for studying the response of oscillatory systems, e.g. neurons, to sparse or weak stimulation. Here we develop a framework for studying the response to a series of pulses which are…

数据分析、统计与概率 · 物理学 2017-09-13 Vladimir Klinshov , Serhiy Yanchuk , Artur Stephan , Vladimir Nekorkin

A simple model that replicates the dynamics of spiking and spiking-bursting activity of real biological neurons is proposed. The model is a two-dimensional map which contains one fast and one slow variable. The mechanisms behind generation…

混沌动力学 · 物理学 2009-11-07 Nikolai F. Rulkov

The well-studied Hindmarsh-Rose model of neural action potential is revisited from the point of view of global bifurcation analysis. This slow-fast system of three paremeterised differential equations is arguably the simplest reduction of…

动力系统 · 数学 2011-09-28 Daniele Linaro , Alan Champneys , Mathieu Desroches , Marco Storace

The describing function (DF) and phase response curve (PRC) are classical tools for the analysis of feedback oscillations and rhythmic behaviors, widely used across control engineering, biology, and neuroscience. These tools are known to…

系统与控制 · 电气工程与系统科学 2025-11-27 Robin Wroblowski , Rodolphe Sepulchre

The phase-resetting curve (PRC) describes the response of a neural oscillator to small perturbations in membrane potential. Its usefulness for predicting the dynamics of weakly coupled deterministic networks has been well characterized.…

动力系统 · 数学 2015-05-13 Aushra Abouzeid , Bard Ermentrout

We study the transition from a silent state to a bursting state by varying the dc stimulus in the Hindmarsh-Rose neuron under quasiperiodic stimulation. For this quasiperiodically forced case, a new type of strange nonchaotic (SN) bursting…

生物物理 · 物理学 2011-11-01 Woochang Lim , Sang-Yoon Kim

We report the emergent dynamics of a community structured modular network of chaotic Hindmarsh-Rose (HR) neurons with inhibitory synapses. We find the inhibitory coupling between the neuronal modules lead to complete synchronization of…

混沌动力学 · 物理学 2018-03-23 Kunal Mozumdar , G. Ambika

A new model of two coupled neurons is presented by the partly diffusive Hindmarsh-Rose equations. The solution semiflow exhibits globally absorbing characteristics. As the main result, the self-synchronization of the coupled neurons at a…

偏微分方程分析 · 数学 2019-10-31 Chi Phan , Yuncheng You

A theoretical analysis of two- and three-dimensional fractional-order Hindmarsh-Rose neuronal models is presented, focusing on stability properties and occurrence of Hopf bifurcations, with respect to the fractional order of the system…

动力系统 · 数学 2017-06-08 Eva Kaslik

Perturbation theory is an important tool in the analysis of oscillators and their response to external stimuli. It is predicated on the assumption that the perturbations in question are "sufficiently weak", an assumption that is not always…

神经元与认知 · 定量生物学 2012-01-19 Kevin K. Lin , Kyle C. A. Wedgwood , Stephen Coombes , Lai-Sang Young

Transport of neural signals in the brain is challenging, owing to neural interference and neural noise. There is experimental evidence of multiplexing of sensory information across population of neurons, particularly in the vertebrate…

信息论 · 计算机科学 2016-12-22 Nithin Nagaraj , K. R. Sahasranand

It is widely assumed that neural activity related to synchronous rhythms of large portions of neurons in specific locations of the brain is responsible for the pathology manifested in patients' uncontrolled tremor and other similar…

混沌动力学 · 物理学 2011-05-31 Aleksandar Gjurchinovski , Viktor Urumov , Zlatko Vasilkoski

A fundamental problem in neuroscience is to characterize the dynamics of spiking from the neurons in a circuit that is involved in learning about a stimulus or a contingency. A key limitation of current methods to analyze neural spiking…

统计方法学 · 统计学 2017-09-29 Yingzhuo Zhang , Noa Malem-Shinitski , Stephen A Allsop , Kay Tye , Demba Ba
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