AIMC Topic: Neurons

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Detection of cellular micromotion by advanced signal processing.

Scientific reports
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...

DNN-assisted statistical analysis of a model of local cortical circuits.

Scientific reports
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...

Dendrite P Systems Toolbox: Representation, Algorithms and Simulators.

International journal of neural systems
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 ...

Introduction to part two of the special issue on computational models of hippocampus and related structures.

Hippocampus
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...

Neuromorphic Engineering: From Biological to Spike-Based Hardware Nervous Systems.

Advanced materials (Deerfield Beach, Fla.)
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 ...

Evolution-Communication Spiking Neural P Systems.

International journal of neural systems
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...

Network structure of cascading neural systems predicts stimulus propagation and recovery.

Journal of neural engineering
OBJECTIVE: Many neural systems display spontaneous, spatiotemporal patterns of neural activity that are crucial for information processing. While these cascading patterns presumably arise from the underlying network of synaptic connections between ne...

Optical Axons for Electro-Optical Neural Networks.

Sensors (Basel, Switzerland)
Recently, neuromorphic sensors, which convert analogue signals to spiking frequencies, have ‎been reported for neurorobotics. In bio-inspired systems these sensors are connected to the main neural unit to perform ‎post-processing of the sensor data. ...

Pattern Recognition of Spiking Neural Networks Based on Visual Mechanism and Supervised Synaptic Learning.

Neural plasticity
Electrophysiological studies have shown that mammalian primary visual cortex are selective for the orientations of visual stimuli. Inspired by this mechanism, we propose a hierarchical spiking neural network (SNN) for image classification. Grayscale ...

Compressing Deep Networks by Neuron Agglomerative Clustering.

Sensors (Basel, Switzerland)
In recent years, deep learning models have achieved remarkable successes in various applications, such as pattern recognition, computer vision, and signal processing. However, high-performance deep architectures are often accompanied by a large stora...