AIMC Topic: Neurons

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Inferring a network from dynamical signals at its nodes.

PLoS computational biology Nov 30, 2020
We give an approximate solution to the difficult inverse problem of inferring the topology of an unknown network from given time-dependent signals at the nodes. For example, we measure signals from individual neurons in the brain, and infer how they ...
Gene Regulatory Networks Action Potentials Neurons Proof of Concept Study Algorithms Brain Neural Networks, Computer
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Deep-learned spike representations and sorting via an ensemble of auto-encoders.

Neural networks : the official journal of the International Neural Network Society Nov 27, 2020
Spike sorting refers to the technique of detecting signals generated by single neurons from multi-neuron recordings and is a valuable tool for analyzing the relationships between individual neuronal activity patterns and specific behaviors. Since the...
Signal Processing, Computer-Assisted Deep Learning Neurons Algorithms Action Potentials Databases, Factual Machine Learning
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Necessary conditions for STDP-based pattern recognition learning in a memristive spiking neural network.

Neural networks : the official journal of the International Neural Network Society Nov 27, 2020
This work is aimed to study experimental and theoretical approaches for searching effective local training rules for unsupervised pattern recognition by high-performance memristor-based Spiking Neural Networks (SNNs). First, the possibility of weight...
Neuronal Plasticity Models, Neurological Pattern Recognition, Automated Neural Networks, Computer Neurons Algorithms
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The Relationship between Sparseness and Energy Consumption of Neural Networks.

Neural plasticity Nov 25, 2020
About 50-80% of total energy is consumed by signaling in neural networks. A neural network consumes much energy if there are many active neurons in the network. If there are few active neurons in a neural network, the network consumes very little ene...
Nerve Net Neurons Neural Networks, Computer Energy Metabolism Models, Neurological
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Detection of cellular micromotion by advanced signal processing.

Scientific reports Nov 18, 2020
Cellular micromotion-a tiny movement of cell membranes on the nm-µm scale-has been proposed as a pathway for inter-cellular signal transduction and as a label-free proxy signal to neural activity. Here we harness several recent approaches of signal p...
Cell Movement Imaging, Three-Dimensional Image Processing, Computer-Assisted Signal Processing, Computer-Assisted Neurons Video Recording Humans Computer Graphics Neural Networks, Computer
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DNN-assisted statistical analysis of a model of local cortical circuits.

Scientific reports Nov 18, 2020
In neuroscience, computational modeling is an effective way to gain insight into cortical mechanisms, yet the construction and analysis of large-scale network models-not to mention the extraction of underlying principles-are themselves challenging ta...
Cerebral Cortex Models, Neurological Data Interpretation, Statistical Neurons Mammals Animals Logistic Models Neural Networks, Computer Computer Simulation
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Dendrite P Systems Toolbox: Representation, Algorithms and Simulators.

International journal of neural systems Nov 16, 2020
Dendrite P systems (DeP systems) are a recently introduced neural-like model of computation. They provide an alternative to the more classical spiking neural (SN) P systems. In this paper, we present the first software simulator for DeP systems, and ...
Algorithms Computer Simulation Neural Networks, Computer Neurons Dendrites
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Introduction to part two of the special issue on computational models of hippocampus and related structures.

Hippocampus Nov 13, 2020
Extensive computational modeling has focused on the hippocampal formation and related cortical structures. This introduction describes the topics addressed by individual articles in part two of this special issue of the journal Hippocampus on the top...
Humans Neural Networks, Computer Animals Spatial Navigation Spatial Behavior Hippocampus Entorhinal Cortex Models, Neurological Neurons
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Neuromorphic Engineering: From Biological to Spike-Based Hardware Nervous Systems.

Advanced materials (Deerfield Beach, Fla.) Nov 9, 2020
The human brain is a sophisticated, high-performance biocomputer that processes multiple complex tasks in parallel with high efficiency and remarkably low power consumption. Scientists have long been pursuing an artificial intelligence (AI) that can ...
Neural Networks, Computer Artificial Intelligence Action Potentials Humans Neurons Brain Synapses Animals
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Evolution-Communication Spiking Neural P Systems.

International journal of neural systems Nov 7, 2020
Spiking neural P systems (SNP systems) are a class of distributed and parallel computation models, which are inspired by the way in which neurons process information through spikes, where the integrate-and-fire behavior of neurons and the distributio...
Models, Neurological Action Potentials Neurons Neural Networks, Computer
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