A model of activity-dependent changes in dendritic spine density and spine structure

Sharon Crook, M. Dur-E-Ahmad, Steven Baer

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

Recent evidence indicates that the morphology and density of dendritic spines are regulated during synaptic plasticity. See, for instance, a review by Hayashi and Majewska [9]. In this work, we extend previous modeling studies [27] by combining a model for activity-dependent spine density with one for calcium-mediated spine stem restructuring. The model is based on the standard dimensionless cable equation, which represents the change in the membrane potential in a passive dendrite. Additional equations characterize the change in spine density along the dendrite, the current balance equation for an individual spine head, the change in calcium concentration in the spine head, and the dynamics of spine stem resistance. We use computational studies to investigate the changes in spine density and structure for differing synaptic inputs and demonstrate the effects of these changes on the input-output properties of the dendritic branch. Moderate amounts of high-frequency synaptic activation to dendritic spines result in an increase in spine stem resistance that is correlated with spine stem elongation. In addition, the spine density increases both inside and outside the input region. The model is formulated so that this long-term potentiation-inducing stimulus eventually leads to structural stability. In contrast, a prolonged low-frequency stimulation paradigm that would typically induce long-term depression results in a decrease in stem resistance (correlated with stem shortening) and an eventual decrease in spine density.

Original languageEnglish (US)
Pages (from-to)617-631
Number of pages15
JournalMathematical Biosciences and Engineering
Volume4
Issue number4
DOIs
StatePublished - Oct 2007

Keywords

  • Dendritic plasticity
  • Dendritic spine
  • Long-term potentiation
  • Structural plasticity

ASJC Scopus subject areas

  • Modeling and Simulation
  • Agricultural and Biological Sciences(all)
  • Computational Mathematics
  • Applied Mathematics

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