[Zurück]

M. Fuchs, Z. Zimmer, R. Grosu, R. Hasani:
"Searching for Biophysically Realistic Parameters for Dynamic Neuron Models by Genetic Algorithms from Calcium Imaging Recording";
Poster: Workshop on Worm´s Neural Information Processing at the 31st Neural Information Processing Systems (NIPS) Conference, 2017, Long Beach, CA, USA; 08.12.2017; in: "Proceedings of the Workshop on Worm´s Neural Information Processing at the 31st Neural Information Processing Systems (NIPS) Conference, 2017", (2017), 6 S.

Individual neurons in the nervous systems exploit various dynamics. To capture

these dynamics for single neurons, we tune the parameters of an electrophysiologi-
cal model of nerve cells, to fit experimental data obtained by calcium imaging. A

search for the biophysical parameters of this model is performed by means of a
genetic algorithm, where the model neuron is exposed to a predefined input current
representing overall inputs from other parts of the nervous system. The algorithm
is then constrained for keeping the ion-channel currents within reasonable ranges,

while producing the best fit to a calcium imaging time series of the AVA interneu-
ron, from the brain of the soil-worm, C. elegans . Our settings enable us to project

a set of biophysical parameters to the the neuron kinetics observed in neuronal
imaging.

http://publik.tuwien.ac.at/files/publik_265630.pdf