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Neuronal Plasticity

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A 0.086-mm 12.7-pJ/SOP 64k-Synapse 256-Neuron Online-Learning Digital Spiking Neuromorphic Processor in 28-nm CMOS.

IEEE transactions on biomedical circuits and systems
Shifting computing architectures from von Neumann to event-based spiking neural networks (SNNs) uncovers new opportunities for low-power processing of sensory data in applications such as vision or sensorimotor control. Exploring roads toward cogniti...

On String Languages Generated by Spiking Neural P Systems With Structural Plasticity.

IEEE transactions on nanobioscience
Spiking neural P systems (SNP systems) are parallel and non-deterministic models of computation, inspired by the neural system of the brain. A variant of SNP systems known as SNP systems with structural plasticity (SNPSP systems) includes the feature...

Emergence of spontaneous assembly activity in developing neural networks without afferent input.

PLoS computational biology
Spontaneous activity is a fundamental characteristic of the developing nervous system. Intriguingly, it often takes the form of multiple structured assemblies of neurons. Such assemblies can form even in the absence of afferent input, for instance in...

The Combined Use of Transcranial Direct Current Stimulation and Robotic Therapy for the Upper Limb.

Journal of visualized experiments : JoVE
Neurologic disorders such as stroke and cerebral palsy are leading causes of long-term disability and can lead to severe incapacity and restriction of daily activities due to lower and upper limb impairments. Intensive physical and occupational thera...

Emergence of Binocular Disparity Selectivity through Hebbian Learning.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Neural selectivity in the early visual cortex strongly reflects the statistics of our environment (Barlow, 2001; Geisler, 2008). Although this has been described extensively in literature through various encoding hypotheses (Barlow and Földiák, 1989;...

The impact of encoding-decoding schemes and weight normalization in spiking neural networks.

Neural networks : the official journal of the International Neural Network Society
Spike-timing Dependent Plasticity (STDP) is a learning mechanism that can capture causal relationships between events. STDP is considered a foundational element of memory and learning in biological neural networks. Previous research efforts endeavore...

Born to learn: The inspiration, progress, and future of evolved plastic artificial neural networks.

Neural networks : the official journal of the International Neural Network Society
Biological neural networks are systems of extraordinary computational capabilities shaped by evolution, development, and lifelong learning. The interplay of these elements leads to the emergence of biological intelligence. Inspired by such intricate ...

An open-source tool for analysis and automatic identification of dendritic spines using machine learning.

PloS one
Synaptic plasticity, the cellular basis for learning and memory, is mediated by a complex biochemical network of signaling proteins. These proteins are compartmentalized in dendritic spines, the tiny, bulbous, post-synaptic structures found on neuron...

Effect of inhibitory spike-timing-dependent plasticity on fast sparsely synchronized rhythms in a small-world neuronal network.

Neural networks : the official journal of the International Neural Network Society
We consider the Watts-Strogatz small-world network (SWN) consisting of inhibitory fast spiking Izhikevich interneurons. This inhibitory neuronal population has adaptive dynamic synaptic strengths governed by the inhibitory spike-timing-dependent plas...

A self-organizing short-term dynamical memory network.

Neural networks : the official journal of the International Neural Network Society
Working memory requires information about external stimuli to be represented in the brain even after those stimuli go away. This information is encoded in the activities of neurons, and neural activities change over timescales of tens of milliseconds...