AIMC Topic: Membrane Potentials

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Accuracy and Efficiency in Fixed-Point Neural ODE Solvers.

Neural computation Aug 27, 2015
Simulation of neural behavior on digital architectures often requires the solution of ordinary differential equations (ODEs) at each step of the simulation. For some neural models, this is a significant computational burden, so efficiency is importan...
Membrane Potentials Neural Networks, Computer Computer Simulation Synapses Humans
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Using Gene Ontology to describe the role of the neurexin-neuroligin-SHANK complex in human, mouse and rat and its relevance to autism.

BMC bioinformatics Jun 6, 2015
BACKGROUND: People with an autistic spectrum disorder (ASD) display a variety of characteristic behavioral traits, including impaired social interaction, communication difficulties and repetitive behavior. This complex neurodevelopment disorder is kn...
Social Behavior Membrane Potentials Cell Physiological Phenomena Cell Adhesion Molecules, Neuronal Neural Cell Adhesion Molecules Synaptic Potentials Nerve Tissue Proteins Humans Models, Molecular Gene Ontology Mice Synapses Phenotype High-Throughput Nucleotide Sequencing Genome Genomics Animals Calcium-Binding Proteins Rats Autistic Disorder
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Noninvasive reconstruction of cardiac transmembrane potentials using a kernelized extreme learning method.

Physics in medicine and biology Mar 27, 2015
Non-invasively reconstructing the cardiac transmembrane potentials (TMPs) from body surface potentials can act as a regression problem. The support vector regression (SVR) method is often used to solve the regression problem, however the computationa...
Models, Cardiovascular Image Processing, Computer-Assisted Software Humans Membrane Potentials Models, Theoretical Electrocardiography Algorithms Neural Networks, Computer Computer Simulation Regression Analysis Heart
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The Leaky Integrate-and-Fire Neuron Is a Change-Point Detector for Compound Poisson Processes.

Neural computation Apr 17, 2025
Animal nervous systems can detect changes in their environments within hundredths of a second. They do so by discerning abrupt shifts in sensory neural activity. Many neuroscience studies have employed change-point detection (CPD) algorithms to estim...
Humans Neural Networks, Computer Algorithms Poisson Distribution Neurons Membrane Potentials Animals Models, Neurological Action Potentials
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Collection of Simulated Data from a Thalamocortical Network Model.

Neuroinformatics Jan 1, 2017
A major challenge in experimental data analysis is the validation of analytical methods in a fully controlled scenario where the justification of the interpretation can be made directly and not just by plausibility. In some sciences, this could be a ...
Thalamus Membrane Potentials Models, Neurological Neurons Information Dissemination Datasets as Topic Cerebral Cortex Humans Software Neural Pathways Neural Networks, Computer Computer Simulation Animals
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Spiking neurons can discover predictive features by aggregate-label learning.

Science (New York, N.Y.) Mar 4, 2016
The brain routinely discovers sensory clues that predict opportunities or dangers. However, it is unclear how neural learning processes can bridge the typically long delays between sensory clues and behavioral outcomes. Here, I introduce a learning c...
Speech Models, Neurological Unsupervised Machine Learning Brain Learning Reinforcement, Psychology Formative Feedback Membrane Potentials Supervised Machine Learning Neurons Concept Formation Humans Neural Networks, Computer
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A Simple Network Architecture Accounts for Diverse Reward Time Responses in Primary Visual Cortex.

The Journal of neuroscience : the official journal of the Society for Neuroscience Sep 16, 2015
UNLABELLED: Many actions performed by animals and humans depend on an ability to learn, estimate, and produce temporal intervals of behavioral relevance. Exemplifying such learning of cued expectancies is the observation of reward-timing activity in ...
Reinforcement, Psychology Visual Cortex Membrane Potentials Neural Networks, Computer Reward Models, Neurological Computer Simulation Nerve Net Neurons Synaptic Transmission Learning Animals Neuronal Plasticity
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