Statistical analysis of dendritic spine distributions in rat hippocampal cultures

BMC Bioinformatics

Aruna Jammalamadaka¹  Sourav Banerjee²  Bangalore S Manjunath¹  Kenneth S Kosik² 

[1] Department of Electrical and Computer Engineering, University of California Santa Barbara, Santa Barbara, CA, USA

[2] Department of Molecular and Cellular Neurobiology, University of California Santa Barbara, Santa Barbara, CA, USA

关键词: Neuronal growth;    Point processes;    Spatial statistics;    Morphological modeling;    Linear network K-function;    Rat hippocampal culture;    Dendritic spines;   

Others  :  1087748
DOI  :  10.1186/1471-2105-14-287

 received in 2013-02-07, accepted in 2013-09-16,  发布年份 2013

【 摘 要 】

Background

Dendritic spines serve as key computational structures in brain plasticity. Much remains to be learned about their spatial and temporal distribution among neurons. Our aim in this study was to perform exploratory analyses based on the population distributions of dendritic spines with regard to their morphological characteristics and period of growth in dissociated hippocampal neurons. We fit a log-linear model to the contingency table of spine features such as spine type and distance from the soma to first determine which features were important in modeling the spines, as well as the relationships between such features. A multinomial logistic regression was then used to predict the spine types using the features suggested by the log-linear model, along with neighboring spine information. Finally, an important variant of Ripley’s K-function applicable to linear networks was used to study the spatial distribution of spines along dendrites.

Results

Our study indicated that in the culture system, (i) dendritic spine densities were "completely spatially random", (ii) spine type and distance from the soma were independent quantities, and most importantly, (iii) spines had a tendency to cluster with other spines of the same type.

Conclusions

Although these results may vary with other systems, our primary contribution is the set of statistical tools for morphological modeling of spines which can be used to assess neuronal cultures following gene manipulation such as RNAi, and to study induced pluripotent stem cells differentiated to neurons.

【 授权许可】

   
2013 Jammalamadaka et al.; licensee BioMed Central Ltd.

【 图 表 】

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