Margarita Zachariou
A biophysical model of endocannabinoid-mediated short term depression in hippocampal inhibition
Zachariou, Margarita; Alexander, Stephen P.H.; Coombes, Stephen; Christodoulou, Chris
Authors
Stephen P.H. Alexander
Professor Stephen Coombes STEPHEN.COOMBES@NOTTINGHAM.AC.UK
PROFESSOR OF APPLIED MATHEMATICS
Chris Christodoulou
Abstract
Memories are believed to be represented in the synaptic pathways of vastly interconnected networks of neurons. The
plasticity of synapses, that is, their strengthening and weakening depending on neuronal activity, is believed to be the basis
of learning and establishing memories. An increasing number of studies indicate that endocannabinoids have a widespread
action on brain function through modulation of synap–tic transmission and plasticity. Recent experimental studies have
characterised the role of endocannabinoids in mediating both short- and long-term synaptic plasticity in various brain
regions including the hippocampus, a brain region strongly associated with cognitive functions, such as learning and
memory. Here, we present a biophysically plausible model of cannabinoid retrograde signalling at the synaptic level and
investigate how this signalling mediates depolarisation induced suppression of inhibition (DSI), a prominent form of shortterm
synaptic depression in inhibitory transmission in hippocampus. The model successfully captures many of the key
characteristics of DSI in the hippocampus, as observed experimentally, with a minimal yet sufficient mathematical
description of the major signalling molecules and cascades involved. More specifically, this model serves as a framework to
test hypotheses on the factors determining the variability of DSI and investigate under which conditions it can be evoked.
The model reveals the frequency and duration bands in which the post-synaptic cell can be sufficiently stimulated to elicit
DSI. Moreover, the model provides key insights on how the state of the inhibitory cell modulates DSI according to its firing
rate and relative timing to the post-synaptic activation. Thus, it provides concrete suggestions to further investigate
experimentally how DSI modulates and is modulated by neuronal activity in the brain. Importantly, this model serves as a
stepping stone for future deciphering of the role of endocannabinoids in synaptic transmission as a feedback mechanism
both at synaptic and network level.
Citation
Zachariou, M., Alexander, S. P., Coombes, S., & Christodoulou, C. (2013). A biophysical model of endocannabinoid-mediated short term depression in hippocampal inhibition. PLoS ONE, 8(3), Article e58296. https://doi.org/10.1371/journal.pone.0058926
Journal Article Type | Article |
---|---|
Publication Date | Mar 18, 2013 |
Deposit Date | Mar 26, 2014 |
Publicly Available Date | Mar 26, 2014 |
Journal | PLoS ONE |
Electronic ISSN | 1932-6203 |
Publisher | Public Library of Science |
Peer Reviewed | Peer Reviewed |
Volume | 8 |
Issue | 3 |
Article Number | e58296 |
DOI | https://doi.org/10.1371/journal.pone.0058926 |
Public URL | https://nottingham-repository.worktribe.com/output/713731 |
Publisher URL | http://www.plosone.org/article/info:doi/10.1371/journal.pone.0058926 |
Files
Coombes_Biophysical_Model.pdf
(1.2 Mb)
PDF
Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by/4.0
You might also like
Oscillatory networks: insights from piecewise-linear modelling
(2024)
Journal Article
Phase and amplitude responses for delay equations using harmonic balance
(2024)
Journal Article
Stability analysis of electrical microgrids and their control systems
(2024)
Journal Article
Insights into oscillator network dynamics using a phase-isostable framework
(2024)
Journal Article
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: discovery-access-systems@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search