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Neuronal Plasticity

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Automation of training and testing motor and related tasks in pre-clinical behavioural and rehabilitative neuroscience.

Experimental neurology
Testing and training animals in motor and related tasks is a cornerstone of pre-clinical behavioural and rehabilitative neuroscience. Yet manually testing and training animals in these tasks is time consuming and analyses are often subjective. Conseq...

Modulation of the dynamics of cerebellar Purkinje cells through the interaction of excitatory and inhibitory feedforward pathways.

PLoS computational biology
The dynamics of cerebellar neuronal networks is controlled by the underlying building blocks of neurons and synapses between them. For which, the computation of Purkinje cells (PCs), the only output cells of the cerebellar cortex, is implemented thro...

A computational framework for optimal control of a self-adjustive neural system with activity-dependent and homeostatic plasticity.

NeuroImage
The control of the brain system has received increasing attention in the domain of brain science. Most brain control studies have been conducted to explore the brain network's graph-theoretic properties or to produce the desired state based on neural...

Constraints on Hebbian and STDP learned weights of a spiking neuron.

Neural networks : the official journal of the International Neural Network Society
We analyse mathematically the constraints on weights resulting from Hebbian and STDP learning rules applied to a spiking neuron with weight normalisation. In the case of pure Hebbian learning, we find that the normalised weights equal the promotion p...

Noise suppression ability and its mechanism analysis of scale-free spiking neural network under white Gaussian noise.

PloS one
With the continuous improvement of automation and informatization, the electromagnetic environment has become increasingly complex. Traditional protection methods for electronic systems are facing with serious challenges. Biological nervous system ha...

A Novel Neural Model With Lateral Interaction for Learning Tasks.

Neural computation
We propose a novel neural model with lateral interaction for learning tasks. The model consists of two functional fields: an elementary field to extract features and a high-level field to store and recognize patterns. Each field is composed of some n...

NMDA Receptor Alterations After Mild Traumatic Brain Injury Induce Deficits in Memory Acquisition and Recall.

Neural computation
Mild traumatic brain injury (mTBI) presents a significant health concern with potential persisting deficits that can last decades. Although a growing body of literature improves our understanding of the brain network response and corresponding underl...

A Brain-Inspired Framework for Evolutionary Artificial General Intelligence.

IEEE transactions on neural networks and learning systems
From the medical field to agriculture, from energy to transportation, every industry is going through a revolution by embracing artificial intelligence (AI); nevertheless, AI is still in its infancy. Inspired by the evolution of the human brain, this...

Necessary conditions for STDP-based pattern recognition learning in a memristive spiking neural network.

Neural networks : the official journal of the International Neural Network Society
This work is aimed to study experimental and theoretical approaches for searching effective local training rules for unsupervised pattern recognition by high-performance memristor-based Spiking Neural Networks (SNNs). First, the possibility of weight...

Structural plasticity on an accelerated analog neuromorphic hardware system.

Neural networks : the official journal of the International Neural Network Society
In computational neuroscience, as well as in machine learning, neuromorphic devices promise an accelerated and scalable alternative to neural network simulations. Their neural connectivity and synaptic capacity depend on their specific design choices...