AIMC Topic: Voltage-Sensitive Dye Imaging

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Optical Mapping-Validated Machine Learning Improves Atrial Fibrillation Driver Detection by Multi-Electrode Mapping.

Circulation. Arrhythmia and electrophysiology Sep 13, 2020
BACKGROUND: Atrial fibrillation (AF) can be maintained by localized intramural reentrant drivers. However, AF driver detection by clinical surface-only multielectrode mapping (MEM) has relied on subjective interpretation of activation maps. We hypoth...
Humans Machine Learning Reproducibility of Results Spectroscopy, Near-Infrared Time Factors Action Potentials Predictive Value of Tests Atrial Fibrillation Heart Rate Fourier Analysis Electrophysiologic Techniques, Cardiac Voltage-Sensitive Dye Imaging
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Modeling mesoscopic cortical dynamics using a mean-field model of conductance-based networks of adaptive exponential integrate-and-fire neurons.

Journal of computational neuroscience Nov 15, 2017
Voltage-sensitive dye imaging (VSDi) has revealed fundamental properties of neocortical processing at macroscopic scales. Since for each pixel VSDi signals report the average membrane potential over hundreds of neurons, it seems natural to use a mean...
Neural Networks, Computer Animals Male Models, Neurological Neurons Nonlinear Dynamics Synapses Cerebral Cortex Nerve Net Photic Stimulation Macaca mulatta Membrane Potentials Voltage-Sensitive Dye Imaging
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