Integrated workflows for spiking neuronal network simulations [PDF]
Frontiers in Neuroinformatics, 2013 The increasing availability of computational resources is enabling more detailed, realistic modelling in computational neuroscience, resulting in a shift towards more heterogeneous models of neuronal circuits, and employment of complex experimental ...
Ján eAntolík, Andrew P Davison
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Piecewise quadratic neuron model: A tool for close-to-biology spiking neuronal network simulation on dedicated hardware [PDF]
Frontiers in Neuroscience, 2023 Spiking neuron models simulate neuronal activities and allow us to analyze and reproduce the information processing of the nervous system. However, ionic-conductance models, which can faithfully reproduce neuronal activities, require a huge computational
Takuya Nanami, Takashi Kohno
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Linear Response of General Observables in Spiking Neuronal Network Models. [PDF]
Entropy (Basel), 2021 We establish a general linear response relation for spiking neuronal networks, based on chains with unbounded memory. This relation allows us to predict the influence of a weak amplitude time-dependent external stimuli on spatio-temporal spike ...
Cessac B, Ampuero I, Cofré R.
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Training a spiking neuronal network model of visual-motor cortex to play a virtual racket-ball game using reinforcement learning. [PDF]
PLoS ONE, 2022 Recent models of spiking neuronal networks have been trained to perform behaviors in static environments using a variety of learning rules, with varying degrees of biological realism.
Haroon Anwar +12 more
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Autapses enable temporal pattern recognition in spiking neural networks. [PDF]
PLoS ONEMost sensory stimuli are temporal in structure. How action potentials encode the information incoming from sensory stimuli remains one of the central research questions in neuroscience.
Muhammad Yaqoob +2 more
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Spiking dynamics of individual neurons reflect changes in the structure and function of neuronal networks [PDF]
Nature CommunicationsBrain networks exhibit diverse topological structures to adapt and support brain functions. The changes in neuronal network architecture can lead to alterations in neuronal spiking activity, yet how individual neuronal behavior reflects network structure
Ruochen Yang +4 more
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Conditions for replay of neuronal assemblies. [PDF]
PLoS Computational BiologyFrom cortical synfire chains to hippocampal replay, the idea that neural populations can be activated sequentially with precise spike timing is thought to be essential for several brain functions.
Gaspar Cano, Richard Kempter
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A lightweight data-driven spiking neuronal network model of Drosophila olfactory nervous system with dedicated hardware support [PDF]
Frontiers in NeuroscienceData-driven spiking neuronal network (SNN) models enable in-silico analysis of the nervous system at the cellular and synaptic level. Therefore, they are a key tool for elucidating the information processing principles of the brain.
Takuya Nanami +7 more
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Memristive Izhikevich Spiking Neuron Model and Its Application in Oscillatory Associative Memory
Frontiers in Neuroscience, 2022 The Izhikevich (IZH) spiking neuron model can display spiking and bursting behaviors of neurons. Based on the switching property and bio-plausibility of the memristor, the memristive Izhikevich (MIZH) spiking neuron model is built.
Xiaoyan Fang, Shukai Duan, Lidan Wang
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Partial coupling delay induced multiple spatiotemporal orders in a modular neuronal network. [PDF]
PLoS ONE, 2017 The influence of partial coupling delay on the spatiotemporal spiking dynamics is explored in a modular neuronal network. The modular neuronal network is composed of two subnetworks which present the small-world property and scale-free property ...
XiaoLi Yang, HuiDan Li, ZhongKui Sun
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