AIMC Topic: Synapses

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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...

Chaos versus noise as drivers of multistability in neural networks.

Chaos (Woodbury, N.Y.)
The multistable behavior of neural networks is actively being studied as a landmark of ongoing cerebral activity, reported in both functional Magnetic Resonance Imaging (fMRI) and electro- or magnetoencephalography recordings. This consists of a cont...

Correlations between synapses in pairs of neurons slow down dynamics in randomly connected neural networks.

Physical review. E
Networks of randomly connected neurons are among the most popular models in theoretical neuroscience. The connectivity between neurons in the cortex is however not fully random, the simplest and most prominent deviation from randomness found in exper...

Competitive Spiking Neural P Systems With Rules on Synapses.

IEEE transactions on nanobioscience
This paper proposes an extension of spiking neural P systems with rules on synapses (SNP-RS systems) working in competitive strategy, called competitive SNP-RS (CSNP-RS systems). In CSNP-RS systems, the spikes are viewed as a kind of competitive reso...

A biologically inspired neurocomputational model for audiovisual integration and causal inference.

The European journal of neuroscience
Recently, experimental and theoretical research has focused on the brain's abilities to extract information from a noisy sensory environment and how cross-modal inputs are processed to solve the causal inference problem to provide the best estimate o...