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Synapses

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Modeling mesoscopic cortical dynamics using a mean-field model of conductance-based networks of adaptive exponential integrate-and-fire neurons.

Journal of computational neuroscience
Voltage-sensitive dye imaging (VSDi) has revealed fundamental properties of neocortical processing at macroscopic scales. Since for each pixel VSDi signals report the average membrane potential over hundreds of neurons, it seems natural to use a mean...

The role of neuron-glia interactions in the emergence of ultra-slow oscillations.

Biological cybernetics
Ultra-slow cortical oscillatory activity of 1-100 mHz has been recorded in human by electroencephalography and in dissociated cultures of cortical rat neurons, but the underlying mechanisms remain to be elucidated. This study presents a computational...

Mechanism-Based and Input-Output Modeling of the Key Neuronal Connections and Signal Transformations in the CA3-CA1 Regions of the Hippocampus.

Neural computation
This letter examines the results of input-output (nonparametric) modeling based on the analysis of data generated by a mechanism-based (parametric) model of CA3-CA1 neuronal connections in the hippocampus. The motivation is to obtain biological insig...

Stochastic spike synchronization in a small-world neural network with spike-timing-dependent plasticity.

Neural networks : the official journal of the International Neural Network Society
We consider the Watts-Strogatz small-world network (SWN) consisting of subthreshold neurons which exhibit noise-induced spikings. This neuronal network has adaptive dynamic synaptic strengths governed by the spike-timing-dependent plasticity (STDP). ...

SNAVA-A real-time multi-FPGA multi-model spiking neural network simulation architecture.

Neural networks : the official journal of the International Neural Network Society
Spiking Neural Networks (SNN) for Versatile Applications (SNAVA) simulation platform is a scalable and programmable parallel architecture that supports real-time, large-scale, multi-model SNN computation. This parallel architecture is implemented in ...

Flexible three-dimensional artificial synapse networks with correlated learning and trainable memory capability.

Nature communications
If a three-dimensional physical electronic system emulating synapse networks could be built, that would be a significant step toward neuromorphic computing. However, the fabrication complexity of complementary metal-oxide-semiconductor architectures ...

Robust spike-train learning in spike-event based weight update.

Neural networks : the official journal of the International Neural Network Society
Supervised learning algorithms in a spiking neural network either learn a spike-train pattern for a single neuron receiving input spike-train from multiple input synapses or learn to output the first spike time in a feedforward network setting. In th...

Synaptic convergence regulates synchronization-dependent spike transfer in feedforward neural networks.

Journal of computational neuroscience
Correlated neural activities such as synchronizations can significantly alter the characteristics of spike transfer between neural layers. However, it is not clear how this synchronization-dependent spike transfer can be affected by the structure of ...

Global and local excitation and inhibition shape the dynamics of the cortico-striatal-thalamo-cortical pathway.

Scientific reports
The cortico-striatal-thalamo-cortical (CSTC) pathway is a brain circuit that controls movement execution, habit formation and reward. Hyperactivity in the CSTC pathway is involved in obsessive compulsive disorder (OCD), a neuropsychiatric disorder ch...

Memristive neural network for on-line learning and tracking with brain-inspired spike timing dependent plasticity.

Scientific reports
Brain-inspired computation can revolutionize information technology by introducing machines capable of recognizing patterns (images, speech, video) and interacting with the external world in a cognitive, humanlike way. Achieving this goal requires fi...