Local diameter fully constrains dendritic size in basal but not apical trees of CA1 pyramidal neurons.
J Comput Neurosci
; 19(2): 223-38, 2005 Oct.
Article
em En
| MEDLINE
| ID: mdl-16133820
ABSTRACT
Computational modeling of dendritic morphology is a powerful tool for quantitatively describing complex geometrical relationships, uncovering principles of dendritic development, and synthesizing virtual neurons to systematically investigate cellular biophysics and network dynamics. A feature common to many morphological models is a dependence of the branching probability on local diameter. Previous models of this type have been able to recreate a wide variety of dendritic morphologies. However, these diameter-dependent models have so far failed to properly constrain branching when applied to hippocampal CA1 pyramidal cells, leading to explosive growth. Here we present a simple modification of this basic approach, in which all parameter sampling, not just bifurcation probability, depends on branch diameter. This added constraint prevents explosive growth in both apical and basal trees of simulated CA1 neurons, yielding arborizations with average numbers and patterns of bifurcations extremely close to those observed in real cells. However, simulated apical trees are much more varied in size than the corresponding real dendrites. We show that, in this model, the excessive variability of simulated trees is a direct consequence of the natural variability of diameter changes at and between bifurcations observed in apical, but not basal, dendrites. Conversely, some aspects of branch distribution were better matched by virtual apical trees than by virtual basal trees. Dendritic morphometrics related to spatial position, such as path distance from the soma or branch order, may be necessary to fully constrain CA1 apical tree size and basal branching pattern.
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Bases de dados:
MEDLINE
Assunto principal:
Células Piramidais
/
Dendritos
/
Tamanho Celular
/
Hipocampo
/
Modelos Neurológicos
Limite:
Animals
Idioma:
En
Revista:
J Comput Neurosci
Assunto da revista:
INFORMATICA MEDICA
/
NEUROLOGIA
Ano de publicação:
2005
Tipo de documento:
Article
País de afiliação:
Estados Unidos