Morphological Homeostasis in Cortical Dendrites.
From: Krasnow Institute for Advanced Study and Department of Psychology, George Mason University, Fairfax, VA 22030, USA.
Proceedings of the National Academy of Sciences of the United States of America
- Publish Date: Jan 2006
- ISSN: 0027-8424
- Volume: 103
- Issue: 5
- Pages: 1569-74
- Medium: Print
- Language: English
- Citation (JAMA): Samsonovich Alexei V, Ascoli Giorgio A, et al. Morphological Homeostasis in Cortical Dendrites.. Proc. Natl. Acad. Sci. U.S.A. Jan 2006;103:1569-74
Abstract
Neurons have significant potential for the homeostatic regulation of a broad range of functional features, from gene expression to synaptic excitability. In this article, we show that dendritic morphology may also be under intrinsic homeostatic control. We present the results from a statistical analysis of a large collection of digitally reconstructed neurons, demonstrating that fluctuations in dendritic size in one given portion of a neuron are systematically counterbalanced by the remaining dendrites in the same cell. As a result, the total dendritic measure (e.g., number of branches, length, and surface area) of each neuron in a given morphological class is, on average, significantly less random than would be expected if trees (and their parts) were regulated independently during development. This observation is general across scales that range from gross basal/apical subdivisions to individual branches and bifurcations, and its statistical significance is robust among various brain regions, cell types, and experimental conditions. Given the pivotal dendritic role in signal integration, synaptic plasticity, and network connectivity, these findings add a dimension to the functional characterization of neuronal homeostasis.
Mesh Headings (Keywords): Aging, Animals, Cells, Cultured, Cerebral Cortex, Data Interpretation, Statistical, Dendrites, Dendritic Cells, Dentate Gyrus, Hippocampus, Homeostasis, Image Processing, Computer-Assisted, Imaging, Three-Dimensional, Models, Biological, Models, Neurological, Models, Statistical, Neural Pathways, Neurons, Pyramidal Cells, Rats, Synapses, Time Factors
Check for Full Text / PubMed Unique Identifier (PMID): 16418293
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