AIMC Topic: Neuronal Plasticity

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A bi-functional three-terminal memristor applicable as an artificial synapse and neuron.

Nanoscale Nov 2, 2023
Due to their significant resemblance to the biological brain, spiking neural networks (SNNs) show promise in handling spatiotemporal information with high time and energy efficiency. Two-terminal memristors have the capability to achieve both synapti...
Neural Networks, Computer Neurons Synapses Neuronal Plasticity Brain
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Signatures of task learning in neural representations.

Current opinion in neurobiology Sep 12, 2023
While neural plasticity has long been studied as the basis of learning, the growth of large-scale neural recording techniques provides a unique opportunity to study how learning-induced activity changes are coordinated across neurons within the same ...
Neural Networks, Computer Learning Neurons Neuronal Plasticity
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Synchronization in STDP-driven memristive neural networks with time-varying topology.

Journal of biological physics Sep 1, 2023
Synchronization is a widespread phenomenon in the brain. Despite numerous studies, the specific parameter configurations of the synaptic network structure and learning rules needed to achieve robust and enduring synchronization in neurons driven by s...
Synapses Neurons Brain Neural Networks, Computer Models, Neurological Neuronal Plasticity
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Representational drift as a window into neural and behavioural plasticity.

Current opinion in neurobiology Jun 29, 2023
Large-scale recordings of neural activity over days and weeks have revealed that neural representations of familiar tasks, precepts and actions continually evolve without obvious changes in behaviour. We hypothesise that this steady drift in neural a...
Neuronal Plasticity Learning Neural Networks, Computer
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Coherent noise enables probabilistic sequence replay in spiking neuronal networks.

PLoS computational biology May 2, 2023
Animals rely on different decision strategies when faced with ambiguous or uncertain cues. Depending on the context, decisions may be biased towards events that were most frequently experienced in the past, or be more explorative. A particular type o...
Memory Mental Recall Neurons Neuronal Plasticity Action Potentials Models, Neurological Learning Neural Networks, Computer Animals
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Meta-learning biologically plausible plasticity rules with random feedback pathways.

Nature communications Mar 31, 2023
Backpropagation is widely used to train artificial neural networks, but its relationship to synaptic plasticity in the brain is unknown. Some biological models of backpropagation rely on feedback projections that are symmetric with feedforward connec...
Feedback Models, Neurological Neuronal Plasticity Neural Networks, Computer Learning Brain
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Forgetting memristor based STDP learning circuit for neural networks.

Neural networks : the official journal of the International Neural Network Society Nov 19, 2022
The circuit implementation of STDP based on memristor is of great significance for the application of neural network. However, recent research shows that the research on the pure circuit implementation of forgetting memristor and STDP is still rare. ...
Learning Neural Networks, Computer Memory, Short-Term Neuronal Plasticity Synapses
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Complementary Memtransistor-Based Multilayer Neural Networks for Online Supervised Learning Through (Anti-)Spike-Timing-Dependent Plasticity.

IEEE transactions on neural networks and learning systems Oct 27, 2022
We propose a complete hardware-based architecture of multilayer neural networks (MNNs), including electronic synapses, neurons, and periphery circuitry to implement supervised learning (SL) algorithm of extended remote supervised method (ReSuMe). In ...
Neuronal Plasticity Models, Neurological Neural Networks, Computer Synapses Supervised Machine Learning
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TripleBrain: A Compact Neuromorphic Hardware Core With Fast On-Chip Self-Organizing and Reinforcement Spike-Timing Dependent Plasticity.

IEEE transactions on biomedical circuits and systems Oct 12, 2022
Human brain cortex acts as a rich inspiration source for constructing efficient artificial cognitive systems. In this paper, we investigate to incorporate multiple brain-inspired computing paradigms for compact, fast and high-accuracy neuromorphic ha...
Computers Neural Networks, Computer Humans Neurons Neuronal Plasticity Algorithms
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Spike-Timing-Dependent Plasticity With Activation-Dependent Scaling for Receptive Fields Development.

IEEE transactions on neural networks and learning systems Oct 5, 2022
Spike-timing-dependent plasticity (STDP) is one of the most popular and deeply biologically motivated forms of unsupervised Hebbian-type learning. In this article, we propose a variant of STDP extended by an additional activation-dependent scale fact...
Models, Neurological Neural Networks, Computer Neurons Neuronal Plasticity Learning
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