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This article is part of the supplement: Twenty First Annual Computational Neuroscience Meeting: CNS*2012

Open Access Poster presentation

Automated model optimization to study spike shape modulation in Layer 2/3 cortical pyramidal neurons

Michael Vella* and Hugh PC Robinson

Author Affiliations

Department of Physiology,Development and Neuroscience, University of Cambridge, Cambridge, CB2 3DY, UK

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BMC Neuroscience 2012, 13(Suppl 1):P57  doi:10.1186/1471-2202-13-S1-P57


The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1471-2202/13/S1/P57


Published:16 July 2012

© 2012 Vella and Robinson; licensee BioMed Central Ltd.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Poster presentation

It has been proposed that, contrary to the “classical” view in which cortical action potentials are encoded as purely digital, all-or-none events, action potential (AP) shape may be used by the brain for representing and processing information [1-4]. Cortical pyramidal neurons of Layer 2/3 show prominent variations in AP waveform during sustained depolarizing responses, which may lead to different levels of synaptic output at proximal axonal synaptic terminals, and different patterns of invasion of the dendrites by back-propagating APs. A range of membrane ionic channels probably plays an important part in this phenomenon. We carried out electrical recording during conductance injection, combined with morphological reconstruction and multicompartmental modelling of Layer II/III pyramidal neurons in rat and mouse cortical slices, to investigate the mechanism of AP waveform modulation. Evolutionary optimization techniques [5-7] were implemented and a computational cluster architecture was designed for searching the parameter space of ion channel distributions and properties efficiently in parallel, to fit models to experimental data. As a test of the fitting process, we assessed its ability to detect point voltage-dependent conductances of different types, introduced at the soma by conductance injection (dynamic clamp). Using the available evidence, we describe how the inactivation kinetics of voltage-dependent potassium channels appears to play a particularly important role in the modulation of action potential waveform of these neurons.

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