AIMC Topic: Neuronal Plasticity

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Strong Allee Effect Synaptic Plasticity Rule in an Unsupervised Learning Environment.

Neural computation
Synaptic plasticity, or the ability of a brain to change one or more of its functions or structures at the synaptic level, has generated and is still generating a lot of interest from the scientific community especially from neuroscientists. These in...

An Area- and Energy-Efficient Spiking Neural Network With Spike-Time-Dependent Plasticity Realized With SRAM Processing-in-Memory Macro and On-Chip Unsupervised Learning.

IEEE transactions on biomedical circuits and systems
In this article, we present a spiking neural network (SNN) based on both SRAM processing-in-memory (PIM) macro and on-chip unsupervised learning with Spike-Time-Dependent Plasticity (STDP). Co-design of algorithm and hardware for hardware-friendly SN...

Fear memory-associated synaptic and mitochondrial changes revealed by deep learning-based processing of electron microscopy data.

Cell reports
Serial section electron microscopy (ssEM) can provide comprehensive 3D ultrastructural information of the brain with exceptional computational cost. Targeted reconstruction of subcellular structures from ssEM datasets is less computationally demandin...

The Role of Robotic Rehabilitation in Children with Neurodevelopmental Disorders.

Psychiatria Danubina
In the last years, traditional treatments have been combined with innovative therapies, such as robot-assisted training, an interesting new rehabilitation tool for children with neurologic impairment. The robots deliver a high dose of training and in...

Neuromorphic learning with Mott insulator NiO.

Proceedings of the National Academy of Sciences of the United States of America
Habituation and sensitization (nonassociative learning) are among the most fundamental forms of learning and memory behavior present in organisms that enable adaptation and learning in dynamic environments. Emulating such features of intelligence fou...

STDP Forms Associations between Memory Traces in Networks of Spiking Neurons.

Cerebral cortex (New York, N.Y. : 1991)
Memory traces and associations between them are fundamental for cognitive brain function. Neuron recordings suggest that distributed assemblies of neurons in the brain serve as memory traces for spatial information, real-world items, and concepts. Ho...

Robotic treatment of the upper limb in chronic stroke and cerebral neuroplasticity: a systematic review.

Journal of biological regulators and homeostatic agents
Stroke is the second cause of mortality and the third cause of long-term disability worldwide. Deficits in upper limb (UL) capacity persist at 6 months post-stroke in 30-66% of hemiplegic stroke patients with major limitations in activity of daily li...

Automatic Classification for the Type of Multiple Synapse Based on Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Recent studies have shown that the synaptic plasticity induced by development and learning can promote the formation of multiple synapse. With the rapid development of electron microscopy (EM) technology, we can closely observe the multiple synapse s...

[Brain-Machine Interface and Neuro-Rehabilitation].

Brain and nerve = Shinkei kenkyu no shinpo
Brain-Machine Interface (BMI) is a technology that enables users to control computers/machines intuitively via their volitional brain activities. Controlling robotic arms and tablet PCs, assisting the movement of paretic limbs through robotic action/...

[Artificial Intelligence and Cerebellar Motor Learning].

Brain and nerve = Shinkei kenkyu no shinpo
Half a century ago, cerebellar learning models based on a simple perceptron were proposed independently by Marr and Albus. Soon, these models were combined with Ito's flocculus hypothesis that the cerebellar flocculus controls the vestibulo-ocular re...