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- W4319036617 abstract "Epilepsy is a multiscale disease in which small alterations at the cellular scale affect the electroencephalogram (EEG). We use a computational model to bridge the cellular scale to EEG by evaluating the ionic conductance of the Hodkin–Huxley (HH) membrane model and comparing the EEG in response to intermittent photic stimulation (IPS) for epilepsy and normal subjects. Modeling is sectioned into IPS encoding, determination of an LTI system, and modifying ionic conductance to generate epilepsy signals. Machine learning is employed where it results in 0.6 (mScm2) ionic conductance in epilepsy. This ionic conductance is lower than the unitary conductance for normal subjects." @default.
- W4319036617 created "2023-02-03" @default.
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- W4319036617 date "2023-02-01" @default.
- W4319036617 modified "2023-10-01" @default.
- W4319036617 title "A Computational Model to Determine Membrane Ionic Conductance Using Electroencephalography in Epilepsy" @default.
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- W4319036617 doi "https://doi.org/10.3390/psf2022005045" @default.
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