AIMC Topic: Neuronal Plasticity

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State of the Art of Brain Function Detection Technologies in Robot-Assisted Lower Limb Rehabilitation.

Brain connectivity
With an aging population, the prevalence of neurological disorders is increasing, leading to a rise in lower limb movement disorders and, in turn, a growing need for rehabilitation training. Previous neuroimaging studies have shown a growing scienti...

Leveraging spiking neural networks for topic modeling.

Neural networks : the official journal of the International Neural Network Society
This article investigates the application of spiking neural networks (SNNs) to the problem of topic modeling (TM): the identification of significant groups of words that represent human-understandable topics in large sets of documents. Our research i...

A neural network model for online one-shot storage of pattern sequences.

PloS one
Based on the CRISP theory (Content Representation, Intrinsic Sequences, and Pattern completion), we present a computational model of the hippocampus that allows for online one-shot storage of pattern sequences without the need for a consolidation pro...

Robot-assisted gait training improves walking and cerebral connectivity in children with unilateral cerebral palsy.

Pediatric research
BACKGROUND: Robot-assisted gait training (RAGT) is promising to help walking rehabilitation in cerebral palsy, but training-induced neuroplastic effects have little been investigated.

Hypergraph-Based Numerical Spiking Neural Membrane Systems with Novel Repartition Protocols.

International journal of neural systems
The classic spiking neural P (SN P) systems abstract the real biological neural network into a simple structure based on graphs, where neurons can only communicate on the plane. This study proposes the hypergraph-based numerical spiking neural membra...

A sparse quantized hopfield network for online-continual memory.

Nature communications
An important difference between brains and deep neural networks is the way they learn. Nervous systems learn online where a stream of noisy data points are presented in a non-independent, identically distributed way. Further, synaptic plasticity in t...

Minicolumn-Based Episodic Memory Model With Spiking Neurons, Dendrites and Delays.

IEEE transactions on neural networks and learning systems
Episodic memory is fundamental to the brain's cognitive function, but how neuronal activity is temporally organized during its encoding and retrieval is still unknown. In this article, combining hippocampus structure with a spiking neural network (SN...

Using deep learning to quantify neuronal activation from single-cell and spatial transcriptomic data.

Nature communications
Neuronal activity-dependent transcription directs molecular processes that regulate synaptic plasticity, brain circuit development, behavioral adaptation, and long-term memory. Single cell RNA-sequencing technologies (scRNAseq) are rapidly developing...

Inferring neural activity before plasticity as a foundation for learning beyond backpropagation.

Nature neuroscience
For both humans and machines, the essence of learning is to pinpoint which components in its information processing pipeline are responsible for an error in its output, a challenge that is known as 'credit assignment'. It has long been assumed that c...