AIMC Topic: Action Potentials

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Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning.

Journal of neural engineering Feb 1, 2018
OBJECTIVE: Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit h...
Animals Male Computer Systems Neural Networks, Computer Learning Cerebellum Blinking Neural Prostheses Rats Rats, Sprague-Dawley Action Potentials
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SPICODYN: A Toolbox for the Analysis of Neuronal Network Dynamics and Connectivity from Multi-Site Spike Signal Recordings.

Neuroinformatics Jan 1, 2018
We implemented an automated and efficient open-source software for the analysis of multi-site neuronal spike signals. The software package, named SPICODYN, has been developed as a standalone windows GUI application, using C# programming language with...
Microelectrodes Software Animals Neural Networks, Computer Action Potentials Rats Neurons Cerebral Cortex
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Competitive Spiking Neural P Systems With Rules on Synapses.

IEEE transactions on nanobioscience Dec 1, 2017
This paper proposes an extension of spiking neural P systems with rules on synapses (SNP-RS systems) working in competitive strategy, called competitive SNP-RS (CSNP-RS systems). In CSNP-RS systems, the spikes are viewed as a kind of competitive reso...
Action Potentials Synapses Computers, Molecular Neural Networks, Computer Computer Simulation Models, Neurological
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Augmenting intracortical brain-machine interface with neurally driven error detectors.

Journal of neural engineering Dec 1, 2017
OBJECTIVE: Making mistakes is inevitable, but identifying them allows us to correct or adapt our behavior to improve future performance. Current brain-machine interfaces (BMIs) make errors that need to be explicitly corrected by the user, thereby con...
Action Potentials Principal Component Analysis Brain-Computer Interfaces Animals Male Support Vector Machine Macaca mulatta Acoustic Stimulation Electrodes, Implanted Photic Stimulation Motor Cortex
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Biological modelling of a computational spiking neural network with neuronal avalanches.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences Jun 28, 2017
In recent years, an increasing number of studies have demonstrated that networks in the brain can self-organize into a critical state where dynamics exhibit a mixture of ordered and disordered patterns. This critical branching phenomenon is termed ne...
Neuronal Plasticity Action Potentials Biomimetics Nerve Net Feedback, Physiological Biological Clocks Machine Learning Learning Animals Humans Neural Networks, Computer
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Improving odorant chemical class prediction with multi-layer perceptrons using temporal odorant spike responses from drosophila melanogaster olfactory receptor neurons.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2016
In this work, we examine the possibility of improving the prediction performance of an olfactory biosensor through the use of temporal spiking data. We present an Artificial Neural Network (ANN), in the form of an optimal hybrid Multi-Layer Perceptro...
Drosophila melanogaster Receptors, Odorant Olfactory Receptor Neurons Neural Networks, Computer Action Potentials Animals Odorants Smell Time Factors
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A supervised learning rule for classification of spatiotemporal spike patterns.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2016
This study introduces a novel supervised algorithm for spiking neurons that take into consideration synapse delays and axonal delays associated with weights. It can be utilized for both classification and association and uses several biologically inf...
Algorithms Models, Neurological Action Potentials Supervised Machine Learning Neurons Synapses
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Application of cross-correlated delay shift rule in spiking neural networks for interictal spike detection.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2016
This study proposes a Cross-Correlated Delay Shift (CCDS) supervised learning rule to train neurons with associated spatiotemporal patterns to classify spike patterns. The objective of this study was to evaluate the feasibility of using the CCDS rule...
Algorithms Electroencephalography Humans Models, Theoretical Epilepsy Action Potentials Neural Networks, Computer Neurons Machine Learning
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Homeostatic Activity-Dependent Tuning of Recurrent Networks for Robust Propagation of Activity.

The Journal of neuroscience : the official journal of the Society for Neuroscience Mar 30, 2016
UNLABELLED: Developing neuronal networks display spontaneous bursts of action potentials that are necessary for circuit organization and tuning. While spontaneous activity has been shown to instruct map formation in sensory circuits, it is unknown wh...
Neuronal Plasticity Nerve Net Models, Neurological Humans Periodicity Action Potentials Neurons Locomotion Homeostasis Neural Networks, Computer Computer Simulation Animals
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A cardiac electrical activity model based on a cellular automata system in comparison with neural network model.

Pakistan journal of pharmaceutical sciences Mar 1, 2016
Cardiac Electrical Activity is commonly distributed into three dimensions of Cardiac Tissue (Myocardium) and evolves with duration of time. The indicator of heart diseases can occur randomly at any time of a day. Heart rate, conduction and each elect...
Action Potentials Heart Rate Heart Conduction System Humans Arrhythmias, Cardiac Computer Simulation Models, Cardiovascular Neural Networks, Computer Animals Time Factors
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