Influence of Dendritic Morphology on Neuronal Electrophysiology
Why is it so important to model neuronal anatomy in detail?
are convinced that dendritic morphology plays an important role in
computation, but there are very few attempts to investigate this role
We are systematically studying the effect of the geometry and topology
of neurons on their electrical behavior by means of computational
We took several experimentally traced neurons from a public electronic archive, converted them for use with the GENESIS simulator, and loaded them with a standard model for their morphological class (CA3 pyramidal cell's Traub model). We paid special attention in setting the exact same distributions of electrophysiological properties (e.g. ionic concentrations and conductances) in all the neurons. Then we started stimulating them (with somatic current injections) with an identical protocol for all of the cells. Thus, every single parameter was constant across these neurons, aside from their dendritic morphology. This variability was sufficient to cause both qualitative and quantitative differences in the firing output of the neurons. Different qualitative behaviors were observed as distinct types of firing modes (regular spiking, as for the two top cells, or train bursting, as in the two bottom cells). Within each mode, there were dramatic quantitative differences (as in the spiking rate between the two top cells, or in the baseline within a burst, in the bottom cells). This project aims at quantifying the exact relationships between morphological and physiological parameters.
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