AIMC Topic: Neurons

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Oscillations in an artificial neural network convert competing inputs into a temporal code.

PLoS computational biology
The field of computer vision has long drawn inspiration from neuroscientific studies of the human and non-human primate visual system. The development of convolutional neural networks (CNNs), for example, was informed by the properties of simple and ...

Deep brain stimulation and lag synchronization in a memristive two-neuron network.

Neural networks : the official journal of the International Neural Network Society
In the pursuit of potential treatments for neurological disorders and the alleviation of patient suffering, deep brain stimulation (DBS) has been utilized to intervene or investigate pathological neural activities. To explore the exact mechanism of h...

A multiscale distributed neural computing model database (NCMD) for neuromorphic architecture.

Neural networks : the official journal of the International Neural Network Society
Distributed neuromorphic architecture is a promising technique for on-chip processing of multiple tasks. Deploying the constructed model in a distributed neuromorphic system, however, remains time-consuming and challenging due to considerations such ...

Rewireable Building Blocks for Enzyme-Powered DNA Computing Networks.

Journal of the American Chemical Society
Neural networks enable the processing of large, complex data sets with applications in disease diagnosis, cell profiling, and drug discovery. Beyond electronic computers, neural networks have been implemented using programmable biomolecules such as D...

Validation of neuron activation patterns for artificial intelligence models in oculomics.

Scientific reports
Recent advancements in artificial intelligence (AI) have prompted researchers to expand into the field of oculomics; the association between the retina and systemic health. Unlike conventional AI models trained on well-recognized retinal features, th...

Multistability and fixed-time multisynchronization of switched neural networks with state-dependent switching rules.

Neural networks : the official journal of the International Neural Network Society
This paper presents theoretical results on the multistability and fixed-time synchronization of switched neural networks with multiple almost-periodic solutions and state-dependent switching rules. It is shown herein that the number, location, and st...

Dissociative and prioritized modeling of behaviorally relevant neural dynamics using recurrent neural networks.

Nature neuroscience
Understanding the dynamical transformation of neural activity to behavior requires new capabilities to nonlinearly model, dissociate and prioritize behaviorally relevant neural dynamics and test hypotheses about the origin of nonlinearity. We present...

Optoelectronic neuron based on transistor combined with volatile threshold switching memristors for neuromorphic computing.

Journal of colloid and interface science
The human perception and learning heavily rely on the visual system, where the retina plays a vital role in preprocessing visual information. Developing neuromorphic vision hardware is based on imitating the neurobiological functions of the retina. I...

Memristive Circuit Implementation of Caenorhabditis Elegans Mechanism for Neuromorphic Computing.

IEEE transactions on neural networks and learning systems
To overcome the energy efficiency bottleneck of the von Neumann architecture and scaling limit of silicon transistors, an emerging but promising solution is neuromorphic computing, a new computing paradigm inspired by how biological neural networks h...

Backpropagation-Based Learning Techniques for Deep Spiking Neural Networks: A Survey.

IEEE transactions on neural networks and learning systems
With the adoption of smart systems, artificial neural networks (ANNs) have become ubiquitous. Conventional ANN implementations have high energy consumption, limiting their use in embedded and mobile applications. Spiking neural networks (SNNs) mimic ...