A biophysical model of endocannabinoid-mediated short term depression in hippocampal inhibition

Zachariou, Margarita and Alexander, Stephen P.H. and Coombes, Stephen and Christodoulou, Chris (2013) A biophysical model of endocannabinoid-mediated short term depression in hippocampal inhibition. PLoS ONE, 8 (3). e58296/1-e58296/23. ISSN 1932-6203

[img] PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Available under Licence Creative Commons Attribution.
Download (1MB)

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.

Item Type: Article
Schools/Departments: University of Nottingham UK Campus > Faculty of Science > School of Mathematical Sciences
Depositing User: de Sousa, Mrs Shona
Date Deposited: 26 Mar 2014 13:24
Last Modified: 13 Sep 2016 19:18
URI: http://eprints.nottingham.ac.uk/id/eprint/2669

Actions (Archive Staff Only)

Edit View Edit View