AIMC Topic: Neurons

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Macroscopic dynamics of neural networks with heterogeneous spiking thresholds.

Physical review. E
Mean-field theory links the physiological properties of individual neurons to the emergent dynamics of neural population activity. These models provide an essential tool for studying brain function at different scales; however, for their application ...

Explaining the Neuroevolution of Fighting Creatures Through Virtual fMRI.

Artificial life
While interest in artificial neural networks (ANNs) has been renewed by the ubiquitous use of deep learning to solve high-dimensional problems, we are still far from general artificial intelligence. In this article, we address the problem of emergent...

Spiking Neural Networks and Mathematical Models.

Advances in experimental medicine and biology
Neural networks are applied in various scientific fields such as medicine, engineering, pharmacology, etc. Investigating operations of neural networks refers to estimating the relationship among single neurons and their contributions to the network a...

Neuron tracing from light microscopy images: automation, deep learning and bench testing.

Bioinformatics (Oxford, England)
MOTIVATION: Large-scale neuronal morphologies are essential to neuronal typing, connectivity characterization and brain modeling. It is widely accepted that automation is critical to the production of neuronal morphology. Despite previous survey pape...

Adaptive synapse-based neuron model with heterogeneous multistability and riddled basins.

Chaos (Woodbury, N.Y.)
Biological neurons can exhibit complex coexisting multiple firing patterns dependent on initial conditions. To this end, this paper presents a novel adaptive synapse-based neuron (ASN) model with sine activation function. The ASN model has time-varyi...

Neural Information Processing and Computations of Two-Input Synapses.

Neural computation
Information processing in artificial neural networks is largely dependent on the nature of neuron models. While commonly used models are designed for linear integration of synaptic inputs, accumulating experimental evidence suggests that biological n...

Nonlinear manipulation and analysis of large DNA datasets.

Nucleic acids research
Information processing functions are essential for organisms to perceive and react to their complex environment, and for humans to analyze and rationalize them. While our brain is extraordinary at processing complex information, winner-take-all, as a...

Permitted Sets and Convex Coding in Nonthreshold Linear Networks.

Neural computation
Hebbian theory proposes that ensembles of neurons form a basis for neural processing. It is possible to gain insight into the activity patterns of these neural ensembles through a binary analysis, regarding neurons as either active or inactive. The f...

Dynamics study on the effect of memristive autapse distribution on Hopfield neural network.

Chaos (Woodbury, N.Y.)
As the shortest feedback loop of the nervous system, autapse plays an important role in the mode conversion of neurodynamics. In particular, memristive autapses can not only facilitate the adjustment of the dynamical behavior but also enhance the com...