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We investigate the dynamical role of inhibitory and highly connected nodes (hub) in synchronization and input processing of leaky-integrate-and-fire neural networks with short term synaptic plasticity. We take advantage of a heterogeneous…

Disordered Systems and Neural Networks · Physics 2017-01-25 Elena Bertolotti , Raffaella Burioni , Matteo di Volo , Alessandro Vezzani

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

An important idea in neural information processing is the communication-through-coherence hypothesis, according to which communication between two brain regions is effective only if they are phase-locked. Also of importance is neuronal…

This paper proposes a neuronal circuitry layout and synaptic plasticity principles that allow the (pyramidal) neuron to act as a "combinatorial switch". Namely, the neuron learns to be more prone to generate spikes given those combinations…

Biological Physics · Physics 2017-05-09 Marat M. Rvachev

Biological neurons and their in-silico emulations for neuromorphic artificial intelligence (AI) use extraordinarily energy-efficient mechanisms, such as spike-based communication and local synaptic plasticity. It remains unclear whether…

Neural and Evolutionary Computing · Computer Science 2021-06-17 Timoleon Moraitis , Abu Sebastian , Evangelos Eleftheriou

Collective rhythmic dynamics from neurons is vital for cognitive functions such as memory formation but how neurons self-organize to produce such activity is not well understood. Attractor-based models have been successfully implemented as…

Neurons and Cognition · Quantitative Biology 2013-03-22 Mark Niedringhaus , Xin Chen , Katherine Conant , Rhonda Dzakpasu

Brain plasticity refers to brain's ability to change neuronal connections, as a result of environmental stimuli, new experiences, or damage. In this work, we study the effects of the synaptic delay on both the coupling strengths and…

Neurons and Cognition · Quantitative Biology 2018-11-14 E. L. Lameu , E. E. N. Macau , F. S. Borges , K. C. Iarosz , I. L. Caldas , R. R. Borges , P. R. Protachevicz , R. L. Viana , A. M. Batista

In order to remain adaptable to a dynamic environment, neural activity must be simultaneously both sensitive and stable. To solve this problem, the brain has been hypothesised to sit near a critical boundary. Yet, precisely how criticality…

Neurons and Cognition · Quantitative Biology 2023-04-07 Brandon R. Munn , Eli J. Müller , James M. Shine

Networks of fast-spiking interneurons are crucial for the generation of neural oscillations in the brain. Here we study the synchronous behavior of interneuronal networks that are coupled by delayed inhibitory and fast electrical synapses.…

Neurons and Cognition · Quantitative Biology 2012-06-22 Daqing Guo , Qingyun Wang , Matjaz Perc

Neurons and networks in the cerebral cortex must operate reliably despite multiple sources of noise. To evaluate the impact of both input and output noise, we determine the robustness of single-neuron stimulus selective responses, as well…

Neurons and Cognition · Quantitative Biology 2018-01-24 Ran Rubin , L. F. Abbott , Haim Sompolinsky

Spiking Neural Networks (SNNs) offer energy-efficient and biologically plausible alternatives to traditional artificial neural networks, but their performance depends critically on the tuning of neuron model parameters. In this work, we…

Neural and Evolutionary Computing · Computer Science 2025-07-22 Szymon Mazurek , Jakub Caputa , Maciej Wielgosz

Neurons in the nervous system are submitted to distinct sources of noise, such as ionic-channel and synaptic noise, which introduces variability in their responses to repeated presentations of identical stimuli. This motivates the use of…

We present an unsupervised, local activation-dependent learning rule for intrinsic plasticity (IP) which affects the composition of ion channel conductances for single neurons in a use-dependent way. We use a single-compartment…

Neurons and Cognition · Quantitative Biology 2017-08-29 Gabriele Scheler

Even when driven by the same stimulus, neuronal responses are well-known to exhibit a striking level of spiking variability. In-vivo electrophysiological recordings also reveal a surprisingly large degree of variability at the subthreshold…

Neurons and Cognition · Quantitative Biology 2025-03-19 Logan A. Becker , Francois Baccelli , Thibaud Taillefumier

Synaptic connections are known to change dynamically. High-frequency presynaptic inputs induce decrease of synaptic weights. This process is known as short-term synaptic depression. The synaptic depression controls a gain for presynaptic…

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

Flexible modulation of temporal dynamics in neural sequences underlies many cognitive processes. For instance, we can adaptively change the speed of motor sequences and speech. While such flexibility is influenced by various factors such as…

Neurons and Cognition · Quantitative Biology 2025-04-15 Tomoki Kurikawa , Kunihiko Kaneko

The effects of spike timing precision and dynamical behavior on error correction in spiking neurons were investigated. Stationary discharges -- phase locked, quasiperiodic, or chaotic -- were induced in a simulated neuron by presenting…

Neurons and Cognition · Quantitative Biology 2007-05-23 Michael Stiber

The co-occurrence of action potentials of pairs of neurons within short time intervals is known since long. Such synchronous events can appear time-locked to the behavior of an animal and also theoretical considerations argue for a…

Neurons and Cognition · Quantitative Biology 2022-05-17 Moritz Helias , Tom Tetzlaff , Markus Diesmann

Author summary: Synchronization of neuronal spiking in the brain is related to cognitive functions, such as perception, attention, and memory. It is therefore important to determine which properties of neurons influence their collective…

Neurons and Cognition · Quantitative Biology 2013-11-06 Josef Ladenbauer , Moritz Augustin , LieJune Shiau , Klaus Obermayer

We investigate the efficient transmission and processing of weak, subthreshold signals in a realistic neural medium in the presence of different levels of the underlying noise. Assuming Hebbian weights for maximal synaptic conductances --…

Biological Physics · Physics 2015-08-19 Joaquin J. Torres , Irene Elices , J. Marro
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