Workshop 3, How should a neuron be modeled: Biophysical detail vs. abstraction

Arnd Roth

Title: Biophysically detailed neuron models: a challenge

University College London, London, UK

Abstract: Biophysically realistic compartmental models of neurons have a long tradition in computational neuroscience, beginning with the first compartmental model of a neuron constructed by Wilfrid Rall in 1964. Due to the large number of free parameters in the most detailed models, their identification and fitting to experimental data has always been a challenge. We review recent developments in this area and discuss the challenges ahead, focusing on strategies for automated optimization, error functions, reduced models and benchmarks for a quantitative comparison of models.

Reference

Arnd Roth and Armin Bahl (2009) Divide et impera: optimizing compartmental models of neurons step by step. J. Physiol. 587:1369-1370. http://jp.physoc.org/content/587/7/1369.long

Bio sketch: Arnd Roth studied physics at the University of Heidelberg, Germany, and did his PhD with Bert Sakmann at the Max Planck Institute for Medical Research in Heidelberg. Currently he is a Senior Research Fellow at the Wolfson Institute for Biomedical Research at University College London. He is co-investigator in a collaborative project, "A novel computing architecture for cognitive systems based on the laminar microcircuitry of the neocortex," funded by the Novel Computation Initiative of the UK Engineering and Physical Sciences Research Council. Arnd's research interests include models of the anatomy and function of synaptic connections in the neocortex and cerebellum, biophysical models of spike generation in the dendrites and axons of neurons, and the role of single neurons in neural computation. He is particularly interested in linking new types of anatomical, electrophysiological and imaging data to biophysically realistic models of neurons and neural circuits, and in turn to more abstract theories of information processing in the brain.