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Dynamical wiring and rewiring in neural networks are carried out by activity-dependent growth and retraction of axons and dendrites, guided by gudance molecules, released by target cells. Experience-dependent structural changes in cortical…

神经元与认知 · 定量生物学 2007-05-23 Fail M. Gafarov

Brain can be represented as a network, where regions are the nodes and relations between the regions are edges. Within a network, co-existence of cooperative and competitive relationships between different nodes is called coopetition.…

神经元与认知 · 定量生物学 2018-02-13 Subhadip Paul , Satyam Mukherjee , Sagnik Bhattacharyya

Brain plasticity, also known as neuroplasticity, is a fundamental mechanism of neuronal adaptation in response to changes in the environment or due to brain injury. In this review, we show our results about the effects of synaptic…

Cortical network functioning critically depends on finely tuned interactions to afford neuronal activity propagation over long distances while avoiding runaway excitation. This importance is highlighted by the pathological consequences and…

神经元与认知 · 定量生物学 2022-10-12 Christian Meisel

Synaptic plasticity, the dynamic tuning of signal transmission strength between neurons, serves as a fundamental basis for memory and learning in biological organisms. This adaptive nature of synapses is considered one of the key features…

介观与纳米尺度物理 · 物理学 2024-11-11 Yechan Noh , Alex Smolyanitsky

Synaptic connections between neurons in the brain are dynamic because of continuously ongoing spine dynamics, axonal sprouting, and other processes. In fact, it was recently shown that the spontaneous synapse-autonomous component of spine…

神经元与认知 · 定量生物学 2018-01-08 David Kappel , Robert Legenstein , Stefan Habenschuss , Michael Hsieh , Wolfgang Maass

Many mathematical models of synaptic plasticity have been proposed to explain the diversity of plasticity phenomena observed in biological organisms. These models range from simple interpretations of Hebb's postulate, which suggests that…

神经元与认知 · 定量生物学 2025-08-05 Danil Tyulmankov

Cortical sensory neurons are known to be highly variable, in the sense that responses evoked by identical stimuli often change dramatically from trial to trial. The origin of this variability is uncertain, but it is usually interpreted as…

神经元与认知 · 定量生物学 2007-05-23 Gleb Basalyga , Emilio Salinas

Brain function results from communication between neurons connected by complex synaptic networks. Synapses are themselves highly complex and diverse signaling machines, containing protein products of hundreds of different genes, some in…

Cortical activity in-vivo displays relaxational time scales much longer than the membrane time constant of the neurons or the deactivation time of ionotropic synaptic conductances. The mechanisms responsible for such slow dynamics are not…

无序系统与神经网络 · 物理学 2025-08-07 Ferdinand Tixidre , Gianluigi Mongillo , Alessandro Torcini

Understanding how the brain learns to compute functions reliably, efficiently and robustly with noisy spiking activity is a fundamental challenge in neuroscience. Most sensory and motor tasks can be described as dynamical systems and could…

神经元与认知 · 定量生物学 2017-05-24 Sophie Denève , Alireza Alemi , Ralph Bourdoukan

We use a biophysical model of a local neuronal circuit to study the implications of synaptic plasticity for the detection of weak sensory stimuli. Networks with fast plastic coupling show behavior consistent with stochastic resonance.…

神经元与认知 · 定量生物学 2009-11-13 Vladislav Volman , Herbert Levine

The brain is an intricately structured organ responsible for the rich emergent dynamics that support the complex cognitive functions we enjoy as humans. With around $10^{11}$ neurons and $10^{15}$ synapses, understanding how the human brain…

神经元与认知 · 定量生物学 2019-02-12 Jason Z. Kim , Danielle S. Bassett

The brain is a nonlinear and highly Recurrent Neural Network (RNN). This RNN is surprisingly plastic and supports our astonishing ability to learn and execute complex tasks. However, learning is incredibly complicated due to the brain's…

神经与进化计算 · 计算机科学 2023-03-14 Mohammad Modiri

Neuromorphic computing is a brainlike information processing paradigm that requires adaptive learning mechanisms. A spiking neuro-evolutionary system is used for this purpose; plastic resistive memories are implemented as synapses in…

神经与进化计算 · 计算机科学 2015-05-19 Gerard David Howard , Larry Bull , Ben de Lacy Costello , Andrew Adamatzky , Ella Gale

We report a detailed study of neuromorphic switching behaviour in inherently complex percolating networks of self-assembled metal nanoparticles. We show that variation of the strength and duration of the electric field applied to this…

无序系统与神经网络 · 物理学 2019-03-06 S. K. Bose , S. Shirai , J. B. Mallinson , S. A. Brown

Neuromorphic engineering makes use of mixed-signal analog and digital circuits to directly emulate the computational principles of biological brains. Such electronic systems offer a high degree of adaptability, robustness, and energy…

系统与控制 · 电气工程与系统科学 2026-04-09 Loris Mendolia , Chenxi Wen , Elisabetta Chicca , Giacomo Indiveri , Rodolphe Sepulchre , Jean-Michel Redouté , Alessio Franci

Correlated electrical activity in neurons is a prominent characteristic of cortical microcircuits. Despite a growing amount of evidence concerning both spike-count and subthreshold membrane potential pairwise correlations, little is known…

神经元与认知 · 定量生物学 2019-07-29 Daniele Linaro , Gabriel K. Ocker , Brent Doiron , Michele Giugliano

Biological neural networks are characterized by their high degree of plasticity, a core property that enables the remarkable adaptability of natural organisms. Importantly, this ability affects both the synaptic strength and the topology of…

神经与进化计算 · 计算机科学 2024-06-17 Erwan Plantec , Joachin W. Pedersen , Milton L. Montero , Eleni Nisioti , Sebastian Risi

The inquiry into the origin of brain complexity remains a pivotal question in neuroscience. While synaptic stimuli are acknowledged as significant, their efficacy often falls short in elucidating the extensive interconnections of the brain…