AI Medical Compendium Topic:
Neurons

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Toward Fast Neural Computing using All-Photonic Phase Change Spiking Neurons.

Scientific reports
The rapid growth of brain-inspired computing coupled with the inefficiencies in the CMOS implementations of neuromrphic systems has led to intense exploration of efficient hardware implementations of the functional units of the brain, namely, neurons...

Domain Wall Motion-Based Dual-Threshold Activation Unit for Low-Power Classification of Non-Linearly Separable Functions.

IEEE transactions on biomedical circuits and systems
Recently, a great deal of scientific endeavour has been devoted to developing spin-based neuromorphic platforms owing to the ultra-low-power benefits offered by spin devices and the inherent correspondence between spintronic phenomena and the desired...

Monostable multivibrators as novel artificial neurons.

Neural networks : the official journal of the International Neural Network Society
Retriggerable and non-retriggerable monostable multivibrators are simple timers with a single characteristic, their period. Motivated by the fact that monostable multivibrators are implementable in large quantities as counters in digital programmable...

Handwritten-Digit Recognition by Hybrid Convolutional Neural Network based on HfO Memristive Spiking-Neuron.

Scientific reports
Although there is a huge progress in complementary-metal-oxide-semiconductor (CMOS) technology, construction of an artificial neural network using CMOS technology to realize the functionality comparable with that of human cerebral cortex containing 1...

Estimation of neural connections from partially observed neural spikes.

Neural networks : the official journal of the International Neural Network Society
Plasticity is one of the most important properties of the nervous system, which enables animals to adjust their behavior to the ever-changing external environment. Changes in synaptic efficacy between neurons constitute one of the major mechanisms of...

Novel deep generative simultaneous recurrent model for efficient representation learning.

Neural networks : the official journal of the International Neural Network Society
Representation learning plays an important role for building effective deep neural network models. Deep generative probabilistic models have shown to be efficient in the data representation learning task which is usually carried out in an unsupervise...

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 ...

Evolving Spiking Neural Networks for online learning over drifting data streams.

Neural networks : the official journal of the International Neural Network Society
Nowadays huge volumes of data are produced in the form of fast streams, which are further affected by non-stationary phenomena. The resulting lack of stationarity in the distribution of the produced data calls for efficient and scalable algorithms fo...

Network-Based Drug Discovery: Coupling Network Pharmacology with Phenotypic Screening for Neuronal Excitability.

Journal of molecular biology
Diseases such as chronic pain with complex etiologies are unlikely to respond to single, target-specific therapeutics but rather require intervention at multiple points within a perturbed disease system. Such approaches are being enabled by the rise ...

Organization of Neural Population Code in Mouse Visual System.

eNeuro
The mammalian visual system consists of several anatomically distinct areas, layers, and cell types. To understand the role of these subpopulations in visual information processing, we analyzed neural signals recorded from excitatory neurons from var...