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Synapses

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A neural network model for online one-shot storage of pattern sequences.

PloS one
Based on the CRISP theory (Content Representation, Intrinsic Sequences, and Pattern completion), we present a computational model of the hippocampus that allows for online one-shot storage of pattern sequences without the need for a consolidation pro...

Spike-based dynamic computing with asynchronous sensing-computing neuromorphic chip.

Nature communications
By mimicking the neurons and synapses of the human brain and employing spiking neural networks on neuromorphic chips, neuromorphic computing offers a promising energy-efficient machine intelligence. How to borrow high-level brain dynamic mechanisms t...

Toward human-like adaptability in robotics through a retention-engineered synaptic control system.

Science advances
Although advanced robots can adeptly mimic human movement and aesthetics, they are still unable to adapt or evolve in response to external experiences. To address this limitation, we propose an innovative approach that uses parallel-processable reten...

Persistent spiking activity in neuromorphic circuits incorporating post-inhibitory rebound excitation.

Journal of neural engineering
. This study introduces a novel approach for integrating the post-inhibitory rebound excitation (PIRE) phenomenon into a neuronal circuit. Excitatory and inhibitory synapses are designed to establish a connection between two hardware neurons, effecti...

A Mean Field to Capture Asynchronous Irregular Dynamics of Conductance-Based Networks of Adaptive Quadratic Integrate-and-Fire Neuron Models.

Neural computation
Mean-field models are a class of models used in computational neuroscience to study the behavior of large populations of neurons. These models are based on the idea of representing the activity of a large number of neurons as the average behavior of ...

Neuromorphic learning and recognition in WOthin film-based forming-free flexible electronic synapses.

Nanotechnology
In pursuing advanced neuromorphic applications, this study introduces the successful engineering of a flexible electronic synapse based on WO, structured as W/WO/Pt/Muscovite-Mica. This artificial synapse is designed to emulate crucial learning behav...

Signatures of Bayesian inference emerge from energy-efficient synapses.

eLife
Biological synaptic transmission is unreliable, and this unreliability likely degrades neural circuit performance. While there are biophysical mechanisms that can increase reliability, for instance by increasing vesicle release probability, these mec...

Hydrogel-Based Artificial Synapses for Sustainable Neuromorphic Electronics.

Advanced materials (Deerfield Beach, Fla.)
Hydrogels find widespread applications in biomedicine because of their outstanding biocompatibility, biodegradability, and tunable material properties. Hydrogels can be chemically functionalized or reinforced to respond to physical or chemical stimul...

Deep brain stimulation and lag synchronization in a memristive two-neuron network.

Neural networks : the official journal of the International Neural Network Society
In the pursuit of potential treatments for neurological disorders and the alleviation of patient suffering, deep brain stimulation (DBS) has been utilized to intervene or investigate pathological neural activities. To explore the exact mechanism of h...

A multiscale distributed neural computing model database (NCMD) for neuromorphic architecture.

Neural networks : the official journal of the International Neural Network Society
Distributed neuromorphic architecture is a promising technique for on-chip processing of multiple tasks. Deploying the constructed model in a distributed neuromorphic system, however, remains time-consuming and challenging due to considerations such ...