AIMC Topic: Neurons

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A unifying framework for functional organization in early and higher ventral visual cortex.

Neuron
A key feature of cortical systems is functional organization: the arrangement of functionally distinct neurons in characteristic spatial patterns. However, the principles underlying the emergence of functional organization in the cortex are poorly un...

Hspb1 and Lgals3 in spinal neurons are closely associated with autophagy following excitotoxicity based on machine learning algorithms.

PloS one
Excitotoxicity represents the primary cause of neuronal death following spinal cord injury (SCI). While autophagy plays a critical and intricate role in SCI, the specific mechanism underlying the relationship between excitotoxicity and autophagy in S...

Machine learning decoding of single neurons in the thalamus for speech brain-machine interfaces.

Journal of neural engineering
. Our goal is to decode firing patterns of single neurons in the left ventralis intermediate nucleus (Vim) of the thalamus, related to speech production, perception, and imagery. For realistic speech brain-machine interfaces (BMIs), we aim to charact...

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...

SSTE: Syllable-Specific Temporal Encoding to FORCE-learn audio sequences with an associative memory approach.

Neural networks : the official journal of the International Neural Network Society
The circuitry and pathways in the brains of humans and other species have long inspired researchers and system designers to develop accurate and efficient systems capable of solving real-world problems and responding in real-time. We propose the Syll...

Multi-level feature interaction image super-resolution network based on convolutional nonlinear spiking neural model.

Neural networks : the official journal of the International Neural Network Society
Image super-resolution (ISR) is designed to recover lost detail information from low-resolution images, resulting in high-quality and high-definition high-resolution images. In the existing single ISR (SISR) methods based on convolutional neural netw...

Improved weight initialization for deep and narrow feedforward neural network.

Neural networks : the official journal of the International Neural Network Society
Appropriate weight initialization settings, along with the ReLU activation function, have become cornerstones of modern deep learning, enabling the training and deployment of highly effective and efficient neural network models across diverse areas o...

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...

An artificial visual neuron with multiplexed rate and time-to-first-spike coding.

Nature communications
Human visual neurons rely on event-driven, energy-efficient spikes for communication, while silicon image sensors do not. The energy-budget mismatch between biological systems and machine vision technology has inspired the development of artificial v...

Binary matrix factorization via collaborative neurodynamic optimization.

Neural networks : the official journal of the International Neural Network Society
Binary matrix factorization is an important tool for dimension reduction for high-dimensional datasets with binary attributes and has been successfully applied in numerous areas. This paper presents a collaborative neurodynamic optimization approach ...