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Hippocampal CA3 is crucial for the formation of long-term associative memory. It has a heavily recurrent connectivity, and memories are thought to be stored as memory engrams in the CA3. However, despite its importance for memory storage…

Neurons and Cognition · Quantitative Biology 2017-04-26 Yansong Chua , Cheston Tan

Spike timing dependent plasticity (STDP) is believed to play an important role in shaping the structure of neural circuits. Here we show that STDP generates effective interactions between synapses of different neurons, which were neglected…

Neurons and Cognition · Quantitative Biology 2016-08-25 Neta Ravid Tannenbaum , Yoram Burak

This article underlines the learning and discrimination capabilities of a model of associative memory based on artificial networks of spiking neurons. Inspired from neuropsychology and neurobiology, the model implements top-down…

Neural and Evolutionary Computing · Computer Science 2016-08-16 Anthony Mouraud , Hélène Paugam-Moisy

Neuromodulation plays a fundamental role in the acquisition of new behaviours. Our experimental findings show that, whereas acetylcholine biases hippocampal synaptic plasticity towards depression, the subsequent application of dopamine can…

Neurons and Cognition · Quantitative Biology 2017-10-06 Sara Zannone , Zuzanna Brzosko , Ole Paulsen , Claudia Clopath

Short-term plasticity (STP) is fundamental to temporal information processing in biological neural systems but remains difficult to realize efficiently in neuromorphic hardware. Memristive electrochemical random-access memory (ECRAM)…

Neural and Evolutionary Computing · Computer Science 2026-05-13 Alex Currie , Sean Borkholder , Nithil Harris Manimaran , Huayuan Han , Cory Merkel , Ke Xu , Tejasvi Das

A fundamental feature of learning in animals is the "ability to forget" that allows an organism to perceive, model and make decisions from disparate streams of information and adapt to changing environments. Against this backdrop, we…

Neural and Evolutionary Computing · Computer Science 2018-06-12 Priyadarshini Panda , Jason M. Allred , Shriram Ramanathan , Kaushik Roy

Precise spatio-temporal patterns of neuronal action potentials underly e.g. sensory representations and control of muscle activities. However, it is not known how the synaptic efficacies in the neuronal networks of the brain adapt such that…

Neurons and Cognition · Quantitative Biology 2015-02-24 Christian Albers , Maren Westkott , Klaus Pawelzik

Spike-timing-dependent plasticity (STDP) provides a biologically-plausible learning mechanism for spiking neural networks (SNNs); however, Hebbian weight updates in architectures with recurrent connections suffer from pathological weight…

Neural and Evolutionary Computing · Computer Science 2026-01-14 Andreas Massey , Aliaksandr Hubin , Stefano Nichele , Solve Sæbø

The synaptic connectivity of cortex is plastic, with experience shaping the ongoing interactions between neurons. Theoretical studies of spike timing-dependent plasticity (STDP) have focused on either just pairs of neurons or large-scale…

Neurons and Cognition · Quantitative Biology 2016-08-02 Gabriel Koch Ocker , Brent Doiron

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

Late long-term potentiation (L-LTP) appears essential for the formation of long-term memory, with memories at least partly encoded by patterns of strengthened synapses. How memories are preserved for months or years, despite molecular…

Neurons and Cognition · Quantitative Biology 2015-05-13 Paul Smolen

Memory is a key component of biological neural systems that enables the retention of information over a huge range of temporal scales, ranging from hundreds of milliseconds up to years. While Hebbian plasticity is believed to play a pivotal…

Neural and Evolutionary Computing · Computer Science 2022-05-24 Thomas Limbacher , Ozan Özdenizci , Robert Legenstein

The compartmental model is a basic tool for studying signal propagation in neurons, and, if the model parameters are adequately defined, it can also be of help in the study of electrical or fluid transport. Here we show that the input…

Cell Behavior · Quantitative Biology 2007-05-23 E. Louis C. Degli Esposti Boschi G. J. Ortega E. Fernandez

We have added a simplified neuromorphic model of Spike Time Dependent Plasticity (STDP) to the Synapto-dendritic Kernel Adapting Neuron (SKAN). The resulting neuron model is the first to show synaptic encoding of afferent signal to noise…

Neural and Evolutionary Computing · Computer Science 2014-11-12 Saeed Afshar , Libin George , Jonathan Tapson , Andre van Schaik , Philip de Chazal , Tara Julia Hamilton

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

Many networks in the brain are sparsely connected, and the brain eliminates synapses during development and learning. How could the brain decide which synapses to prune? In a recurrent network, determining the importance of a synapse…

Neurons and Cognition · Quantitative Biology 2021-07-20 Eli Moore , Rishidev Chaudhuri

Within the complex neuroarchitecture of the brain, astrocytes play crucial roles in development, structure, and metabolism. These cells regulate neural activity through tripartite synapses, directly impacting cognitive processes such as…

Neural and Evolutionary Computing · Computer Science 2023-12-27 Guobin Shen , Dongcheng Zhao , Yiting Dong , Yang Li , Jindong Li , Kang Sun , Yi Zeng

Neural networks are composed of neurons and synapses, which are responsible for learning in a slow adaptive dynamical process. Here we experimentally show that neurons act like independent anisotropic multiplex hubs, which relay and mute…

Neurons and Cognition · Quantitative Biology 2017-07-21 Roni Vardi , Amir Goldental , Anton Sheinin , Shira Sardi , Ido Kanter

The spiking activity of principal cells in mammalian hippocampus encodes an internalized neuronal representation of the ambient space---a cognitive map. Once learned, such a map enables the animal to navigate a given environment for a long…

Neurons and Cognition · Quantitative Biology 2017-10-10 Andrey Babichev , Dmitriy Morozov , Yuri Dabaghian

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…

Neural and Evolutionary Computing · Computer Science 2015-05-19 Gerard David Howard , Larry Bull , Ben de Lacy Costello , Andrew Adamatzky , Ella Gale
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