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Synapses

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Memristive synapses with high reproducibility for flexible neuromorphic networks based on biological nanocomposites.

Nanoscale
Memristive synapses from biomaterials are promising for building flexible and implantable artificial neuromorphic systems due to their remarkable mechanical and biological properties. However, these biological devices have relatively poor memristive ...

Analysis of the Memristor-Based Crossbar Synapse for Neuromorphic Systems.

Journal of nanoscience and nanotechnology
In this study, we analyzed the memristor device typically used as a synapse in neuromorphic architecture and confirmed that the synaptic memristor device can be adopted to perform the machine learning algorithm. The nonlinear characteristics of the m...

Automatic Classification for the Type of Multiple Synapse Based on Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Recent studies have shown that the synaptic plasticity induced by development and learning can promote the formation of multiple synapse. With the rapid development of electron microscopy (EM) technology, we can closely observe the multiple synapse s...

[Artificial Intelligence and Cerebellar Motor Learning].

Brain and nerve = Shinkei kenkyu no shinpo
Half a century ago, cerebellar learning models based on a simple perceptron were proposed independently by Marr and Albus. Soon, these models were combined with Ito's flocculus hypothesis that the cerebellar flocculus controls the vestibulo-ocular re...

Gradient and Hamiltonian coupled systems on undirected networks.

Mathematical biosciences and engineering : MBE
Many real world applications are modelled by coupled systems on undirected networks. Two striking classes of such systems are the gradient and the Hamiltonian systems. In fact, within these two classes, coupled systems are admissible only by the undi...

Computing of temporal information in spiking neural networks with ReRAM synapses.

Faraday discussions
Resistive switching random-access memory (ReRAM) is a two-terminal device based on ion migration to induce resistance switching between a high resistance state (HRS) and a low resistance state (LRS). ReRAM is considered one of the most promising tech...

Recent Progress on Neuromorphic Synapse Electronics: From Emerging Materials, Devices, to Neural Networks.

Journal of nanoscience and nanotechnology
To realize intelligent functions in electronic devices like a human brain, it is important to develop the electronic devices that can imitate biological neurons and synapses (synaptic electronics). In this paper, we review the critical learning mecha...

Propagation delays determine neuronal activity and synaptic connectivity patterns emerging in plastic neuronal networks.

Chaos (Woodbury, N.Y.)
In plastic neuronal networks, the synaptic strengths are adapted to the neuronal activity. Specifically, spike-timing-dependent plasticity (STDP) is a fundamental mechanism that modifies the synaptic strengths based on the relative timing of pre- and...

Global firing rate contrast enhancement in E/I neuronal networks by recurrent synchronized inhibition.

Chaos (Woodbury, N.Y.)
Inhibitory synchronization is commonly observed and may play some important functional roles in excitatory/inhibitory (E/I) neuronal networks. The firing rate contrast enhancement is a general feature of information processing in sensory pathways, an...