Automatic Construction of Predictive Neuron Models through Large Scale Assimilation of Electrophysiological Data.
We report on the construction of neuron models by assimilating electrophysiological data with large-scale constrained nonlinear optimization. The method implements interior point line parameter search to determine parameters from the responses to intracellular current injections of zebra finch HVC neurons. We incorporated these parameters into a nine ionic channel conductance model to obtain completed models which we then use to predict the state of the neuron under arbitrary current stimulation. Each model was validated by successfully predicting the dynamics of the membrane potential induced by 20-50 different current protocols. The dispersion of parameters extracted from different assimilation windows was studied. Differences in constraints from current protocols, stochastic variability in neuron output, and noise behave as a residual temperature which broadens the global minimum of the objective function to an ellipsoid domain whose principal axes follow an exponentially decaying distribution. The maximum likelihood expectation of extracted parameters was found to provide an excellent approximation of the global minimum and yields highly consistent kinetics for both neurons studied. Large scale assimilation absorbs the intrinsic variability of electrophysiological data over wide assimilation windows. It builds models in an automatic manner treating all data as equal quantities and requiring minimal additional insight.
Department of Physics, University of Bath, Bath BA2 7AY, UK.
Alain
A
Nogaret
Department of Psychology, University of Virginia, Charlottesville, VA 22904, USA.
C Daniel
CD
Meliza
Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL 60637, USA.
Daniel
D
Margoliash
Department of Physics, University of California San Diego, La Jolla, CA 92093, USA.|Scripps Institution for Oceanography, Marine Physical Laboratory, La Jolla, CA 92093, USA.
Henry D I
HD
Abarbanel
D000818:Animals; D001499:Bayes Theorem; D001921:Brain / Q000502:physiology*; D004594:Electrophysiology / Q000379:methods*; D046369:Finches; D007473:Ion Channels / Q000502:physiology; D008297:Male; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology; D015203:Reproducibility of Results
D007473:Ion Channels