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Synapses

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Biological batch normalisation: How intrinsic plasticity improves learning in deep neural networks.

PloS one
In this work, we present a local intrinsic rule that we developed, dubbed IP, inspired by the Infomax rule. Like Infomax, this rule works by controlling the gain and bias of a neuron to regulate its rate of fire. We discuss the biological plausibilit...

Turing Universality of Weighted Spiking Neural P Systems with Anti-spikes.

Computational intelligence and neuroscience
Weighted spiking neural P systems with anti-spikes (AWSN P systems) are proposed by adding anti-spikes to spiking neural P systems with weighted synapses. Anti-spikes behave like spikes of inhibition of communication between neurons. Both spikes and ...

Synaptic Iontronic Devices for Brain-Mimicking Functions: Fundamentals and Applications.

ACS applied bio materials
Inspired by the information transmission mechanism in the central nervous systems of life, synapse-mimicking devices have been designed and fabricated for the purpose of breaking the bottleneck of von Neumann architecture and realizing the constructi...

Spiking Neural P Systems with Extended Channel Rules.

International journal of neural systems
This paper discusses a new variant of spiking neural P systems (in short, SNP systems), spiking neural P systems with extended channel rules (in short, SNP-ECR systems). SNP-ECR systems are a class of distributed parallel computing models. In SNP-ECR...

Spiking Neural P Systems with Delay on Synapses.

International journal of neural systems
Based on the feature and communication of neurons in animal neural systems, spiking neural P systems (SN P systems) were proposed as a kind of powerful computing model. Considering the length of axons and the information transmission speed on synapse...

Exploiting defective RRAM array as synapses of HTM spatial pooler with boost-factor adjustment scheme for defect-tolerant neuromorphic systems.

Scientific reports
A crossbar array architecture employing resistive switching memory (RRAM) as a synaptic element accelerates vector-matrix multiplication in a parallel fashion, enabling energy-efficient pattern recognition. To implement the function of the synapse in...

NeuroConstruct-based implementation of structured-light stimulated retinal circuitry.

BMC neuroscience
BACKGROUND: Retinal circuitry provides a fundamental window to neural networks, featuring widely investigated visual phenomena ranging from direction selectivity to fast detection of approaching motion. As the divide between experimental and theoreti...

Experimental Demonstration of Supervised Learning in Spiking Neural Networks with Phase-Change Memory Synapses.

Scientific reports
Spiking neural networks (SNN) are computational models inspired by the brain's ability to naturally encode and process information in the time domain. The added temporal dimension is believed to render them more computationally efficient than the con...

Pippin: A random forest-based method for identifying presynaptic and postsynaptic neurotoxins.

Journal of bioinformatics and computational biology
Presynaptic and postsynaptic neurotoxins are two types of neurotoxins from venomous animals and functionally important molecules in the neurosciences; however, their experimental characterization is difficult, time-consuming, and costly. Therefore, b...

Dendrite P systems.

Neural networks : the official journal of the International Neural Network Society
It was recently found that dendrites are not just a passive channel. They can perform mixed computation of analog and digital signals, and therefore can be abstracted as information processors. Moreover, dendrites possess a feedback mechanism. Motiva...