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Neurons

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Aperiodic switching event-triggered stabilization of continuous memristive neural networks with interval delays.

Neural networks : the official journal of the International Neural Network Society
The stabilization problem is studied for memristive neural networks with interval delays under aperiodic switching event-triggered control. Note that, most of delayed memristive neural networks models studied are discontinuous, which are not the real...

Automatized offline and online exploration to achieve a target dynamics in biohybrid neural circuits built with living and model neurons.

Neural networks : the official journal of the International Neural Network Society
Biohybrid circuits of interacting living and model neurons are an advantageous means to study neural dynamics and to assess the role of specific neuron and network properties in the nervous system. Hybrid networks are also a necessary step to build e...

Quantum spin models for numerosity perception.

PloS one
Humans share with animals, both vertebrates and invertebrates, the capacity to sense the number of items in their environment already at birth. The pervasiveness of this skill across the animal kingdom suggests that it should emerge in very simple po...

Memristor-Based Neural Network Circuit With Multimode Generalization and Differentiation on Pavlov Associative Memory.

IEEE transactions on cybernetics
Most of the classical conditioning laws implemented by existing circuits are involved in learning and forgetting between only three neurons, and the problems between multiple neurons are not considered. In this article, a multimode generalization and...

Complex computation from developmental priors.

Nature communications
Machine learning (ML) models have long overlooked innateness: how strong pressures for survival lead to the encoding of complex behaviors in the nascent wiring of a brain. Here, we derive a neurodevelopmental encoding of artificial neural networks th...

A Prediction Model Based on Gated Nonlinear Spiking Neural Systems.

International journal of neural systems
Nonlinear spiking neural P (NSNP) systems are one of neural-like membrane computing models, abstracted by nonlinear spiking mechanisms of biological neurons. NSNP systems have a nonlinear structure and can show rich nonlinear dynamics. In this paper,...

Stereology neuron counts correlate with deep learning estimates in the human hippocampal subregions.

Scientific reports
Hippocampal subregions differ in specialization and vulnerability to cell death. Neuron death and hippocampal atrophy have been a marker for the progression of Alzheimer's disease. Relatively few studies have examined neuronal loss in the human brain...

Interpretable machine learning approach for neuron-centric analysis of human cortical cytoarchitecture.

Scientific reports
The complexity of the cerebral cortex underlies its function and distinguishes us as humans. Here, we present a principled veridical data science methodology for quantitative histology that shifts focus from image-level investigations towards neuron-...

A deep learning network based on CNN and sliding window LSTM for spike sorting.

Computers in biology and medicine
Spike sorting plays an essential role to obtain electrophysiological activity of single neuron in the fields of neural signal decoding. With the development of electrode array, large numbers of spikes are recorded simultaneously, which rises the need...

Fully Complex-Valued Dendritic Neuron Model.

IEEE transactions on neural networks and learning systems
A single dendritic neuron model (DNM) that owns the nonlinear information processing ability of dendrites has been widely used for classification and prediction. Complex-valued neural networks that consist of a number of multiple/deep-layer McCulloch...