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Electrotonic Signals along Intracellular Membranes May Interconnect Dendritic Spines and Nucleus

Overview of attention for article published in PLoS Computational Biology, March 2008
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Title
Electrotonic Signals along Intracellular Membranes May Interconnect Dendritic Spines and Nucleus
Published in
PLoS Computational Biology, March 2008
DOI 10.1371/journal.pcbi.1000036
Pubmed ID
Authors

Isaac Shemer, Björn Brinne, Jesper Tegnér, Sten Grillner

Abstract

Synapses on dendritic spines of pyramidal neurons show a remarkable ability to induce phosphorylation of transcription factors at the nuclear level with a short latency, incompatible with a diffusion process from the dendritic spines to the nucleus. To account for these findings, we formulated a novel extension of the classical cable theory by considering the fact that the endoplasmic reticulum (ER) is an effective charge separator, forming an intrinsic compartment that extends from the spine to the nuclear membrane. We use realistic parameters to show that an electrotonic signal may be transmitted along the ER from the dendritic spines to the nucleus. We found that this type of signal transduction can additionally account for the remarkable ability of the cell nucleus to differentiate between depolarizing synaptic signals that originate from the dendritic spines and back-propagating action potentials. This study considers a novel computational role for dendritic spines, and sheds new light on how spines and ER may jointly create an additional level of processing within the single neuron.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 3 7%
Chile 1 2%
Sweden 1 2%
United Kingdom 1 2%
Canada 1 2%
Japan 1 2%
Unknown 36 82%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 32%
Student > Ph. D. Student 8 18%
Professor 7 16%
Professor > Associate Professor 5 11%
Student > Master 2 5%
Other 4 9%
Unknown 4 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 41%
Neuroscience 7 16%
Medicine and Dentistry 3 7%
Engineering 2 5%
Computer Science 2 5%
Other 5 11%
Unknown 7 16%