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Models of Neocortical Layer 5b Pyramidal Cells Capturing a Wide Range of Dendritic and Perisomatic Active Properties

Overview of attention for article published in PLoS Computational Biology, July 2011
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Title
Models of Neocortical Layer 5b Pyramidal Cells Capturing a Wide Range of Dendritic and Perisomatic Active Properties
Published in
PLoS Computational Biology, July 2011
DOI 10.1371/journal.pcbi.1002107
Pubmed ID
Authors

Etay Hay, Sean Hill, Felix Schürmann, Henry Markram, Idan Segev

Abstract

The thick-tufted layer 5b pyramidal cell extends its dendritic tree to all six layers of the mammalian neocortex and serves as a major building block for the cortical column. L5b pyramidal cells have been the subject of extensive experimental and modeling studies, yet conductance-based models of these cells that faithfully reproduce both their perisomatic Na(+)-spiking behavior as well as key dendritic active properties, including Ca(2+) spikes and back-propagating action potentials, are still lacking. Based on a large body of experimental recordings from both the soma and dendrites of L5b pyramidal cells in adult rats, we characterized key features of the somatic and dendritic firing and quantified their statistics. We used these features to constrain the density of a set of ion channels over the soma and dendritic surface via multi-objective optimization with an evolutionary algorithm, thus generating a set of detailed conductance-based models that faithfully replicate the back-propagating action potential activated Ca(2+) spike firing and the perisomatic firing response to current steps, as well as the experimental variability of the properties. Furthermore, we show a useful way to analyze model parameters with our sets of models, which enabled us to identify some of the mechanisms responsible for the dynamic properties of L5b pyramidal cells as well as mechanisms that are sensitive to morphological changes. This automated framework can be used to develop a database of faithful models for other neuron types. The models we present provide several experimentally-testable predictions and can serve as a powerful tool for theoretical investigations of the contribution of single-cell dynamics to network activity and its computational capabilities.

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Geographical breakdown

Country Count As %
United States 9 3%
Germany 4 1%
Netherlands 4 1%
Japan 4 1%
United Kingdom 4 1%
France 3 <1%
Switzerland 3 <1%
Israel 2 <1%
Brazil 1 <1%
Other 10 3%
Unknown 304 87%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 90 26%
Researcher 71 20%
Student > Master 37 11%
Professor 28 8%
Student > Bachelor 28 8%
Other 53 15%
Unknown 41 12%
Readers by discipline Count As %
Neuroscience 99 28%
Agricultural and Biological Sciences 80 23%
Engineering 30 9%
Computer Science 27 8%
Physics and Astronomy 20 6%
Other 37 11%
Unknown 55 16%