Bayesian inference for biophysical neuron models enables stimulus optimization for retinal neuroprosthetics

Bayesian inference for biophysical neuron models enables stimulus optimization for retinal neuroprosthetics

While multicompartment models have long been used to study the biophysics of neurons, it is still challenging to infer the parameters of such models from data including uncertainty estimates. Here, we performed Bayesian inference for the parameters of detailed neuron models of a photoreceptor and an...

Full description

Bibliographic Details
Main Authors: Jonathan Oesterle, Christian Behrens, Cornelius Schröder, Thoralf Hermann, Thomas Euler, Katrin Franke, Robert G Smith, Günther Zeck, Philipp Berens
Format: Article
Language:English
Published: eLife Sciences Publications Ltd 2020-10-01
Series:eLife
Subjects:
biophysical model
retina
bipolar cell
neuroprosthetics
bayesian inference
two-photon imaging
Online Access:https://elifesciences.org/articles/54997

Internet

https://elifesciences.org/articles/54997

Similar Items