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Spiking Neural Network With Distributed Plasticity Reproduces Cerebellar Learning in Eye Blink Conditioning Paradigms.

IEEE transactions on bio-medical engineering
GOAL: In this study, we defined a realistic cerebellar model through the use of artificial spiking neural networks, testing it in computational simulations that reproduce associative motor tasks in multiple sessions of acquisition and extinction.

Impact of sub and supra-threshold adaptation currents in networks of spiking neurons.

Journal of computational neuroscience
Neuronal adaptation is the intrinsic capacity of the brain to change, by various mechanisms, its dynamical responses as a function of the context. Such a phenomena, widely observed in vivo and in vitro, is known to be crucial in homeostatic regulatio...

Rich spectrum of neural field dynamics in the presence of short-term synaptic depression.

Physical review. E, Statistical, nonlinear, and soft matter physics
In continuous attractor neural networks (CANNs), spatially continuous information such as orientation, head direction, and spatial location is represented by Gaussian-like tuning curves that can be displaced continuously in the space of the preferred...

Dynamic Behavior of Artificial Hodgkin-Huxley Neuron Model Subject to Additive Noise.

IEEE transactions on cybernetics
Motivated by neuroscience discoveries during the last few years, many studies consider pulse-coupled neural networks with spike-timing as an essential component in information processing by the brain. There also exists some technical challenges while...

Context-dependent coding and gain control in the auditory system of crickets.

The European journal of neuroscience
Sensory systems process stimuli that greatly vary in intensity and complexity. To maintain efficient information transmission, neural systems need to adjust their properties to these different sensory contexts, yielding adaptive or stimulus-dependent...

GABA diffusion across neuronal columns for efficient sensory tuning.

Biological cybernetics
Synaptic (phasic) lateral inhibition between neuronal columns mediated by GABAergic interneurons is, in general, essential for primary sensory cortices to respond selectively to elemental features. We propose here a neural network model with a nonsyn...

Employing TDMA Protocol in Neural Nanonetworks in Case of Neuron Specific Faults.

IEEE transactions on nanobioscience
Many neurodegenerative diseases arise from the malfunctioning neurons in the pathway where the signal is carried. In this paper, we propose neuron specific TDMA/multiplexing and demultiplexing mechanisms to convey the spikes of a receptor neuron over...

ECG Prediction Based on Classification via Neural Networks and Linguistic Fuzzy Logic Forecaster.

TheScientificWorldJournal
The paper deals with ECG prediction based on neural networks classification of different types of time courses of ECG signals. The main objective is to recognise normal cycles and arrhythmias and perform further diagnosis. We proposed two detection s...

The straintronic spin-neuron.

Nanotechnology
In artificial neural networks, neurons are usually implemented with highly dissipative CMOS-based operational amplifiers. A more energy-efficient implementation is a 'spin-neuron' realized with a magneto-tunneling junction (MTJ) that is switched with...

Speed-accuracy tradeoff by a control signal with balanced excitation and inhibition.

Journal of neurophysiology
A hallmark of flexible behavior is the brain's ability to dynamically adjust speed and accuracy in decision-making. Recent studies suggested that such adjustments modulate not only the decision threshold, but also the rate of evidence accumulation. H...