AIMC Topic: Synapses

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

Journal of nanoscience and nanotechnology Dec 1, 2018
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...
Neurons Electronics Synapses Humans Neural Networks, Computer Neuronal Plasticity
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Propagation delays determine neuronal activity and synaptic connectivity patterns emerging in plastic neuronal networks.

Chaos (Woodbury, N.Y.) Oct 1, 2018
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...
Dendrites Nonlinear Dynamics Synapses Nerve Net Normal Distribution Oscillometry Synaptic Transmission Plastics Neurons Axons Models, Neurological Action Potentials Neural Networks, Computer Algorithms Brain Computer Simulation Time Factors Humans Neuronal Plasticity
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Global firing rate contrast enhancement in E/I neuronal networks by recurrent synchronized inhibition.

Chaos (Woodbury, N.Y.) Oct 1, 2018
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...
Neural Networks, Computer Animals Models, Neurological Humans Electronic Data Processing Synaptic Transmission Neural Inhibition Action Potentials Neurons Synapses Sensory Receptor Cells
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Chaos versus noise as drivers of multistability in neural networks.

Chaos (Woodbury, N.Y.) Oct 1, 2018
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...
Ion Channels Magnetic Resonance Imaging Magnetoencephalography Cluster Analysis Neural Conduction Models, Neurological Data Collection Stochastic Processes Neural Networks, Computer Nonlinear Dynamics Humans Oscillometry Algorithms Synapses Temperature
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Correlations between synapses in pairs of neurons slow down dynamics in randomly connected neural networks.

Physical review. E Jun 1, 2018
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...
Neural Networks, Computer Animals Time Factors Models, Neurological Action Potentials Neurons Synapses
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Two artificial synapses are better than one.

Nature Jun 1, 2018
Neural Networks, Computer Synapses
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Competitive Spiking Neural P Systems With Rules on Synapses.

IEEE transactions on nanobioscience Dec 1, 2017
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...
Computers, Molecular Neural Networks, Computer Models, Neurological Computer Simulation Action Potentials Synapses
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A biologically inspired neurocomputational model for audiovisual integration and causal inference.

The European journal of neuroscience Nov 1, 2017
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...
Humans Neural Networks, Computer Visual Perception Brain Auditory Perception Models, Neurological Illusions Synapses
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[Not Available].

Revue medicale suisse Apr 19, 2017
Electronic Nicotine Delivery Systems Humans France Artificial Intelligence Vaping New Zealand Synapses
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A supervised learning rule for classification of spatiotemporal spike patterns.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2016
This study introduces a novel supervised algorithm for spiking neurons that take into consideration synapse delays and axonal delays associated with weights. It can be utilized for both classification and association and uses several biologically inf...
Synapses Action Potentials Algorithms Supervised Machine Learning Models, Neurological Neurons
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