Paper Info
Title
Tracking slow modulations in synaptic gain using dynamic causal modelling: Validation in epilepsy.
Abstract
In this work we propose a proof of principle that dynamic causal modelling can identify plausible mechanisms at the synaptic level underlying brain state changes over a timescale of seconds. As a benchmark example for validation we used intracranial electroencephalographic signals in a human subject. These data were used to infer the (effective connectivity) architecture of synaptic connections among neural populations assumed to generate seizure activity. Dynamic causal modelling allowed us to quantify empirical changes in spectral activity in terms of a trajectory in parameter space — identifying key synaptic parameters or connections that cause observed signals. Using recordings from three seizures in one patient, we considered a network of two sources (within and just outside the putative ictal zone). Bayesian model selection was used to identify the intrinsic (within-source) and extrinsic (between-source) connectivity. Having established the underlying architecture, we were able to track the evolution of key connectivity parameters (e.g., inhibitory connections to superficial pyramidal cells) and test specific hypotheses about the synaptic mechanisms involved in ictogenesis. Our key finding was that intrinsic synaptic changes were sufficient to explain seizure onset, where these changes showed dissociable time courses over several seconds. Crucially, these changes spoke to an increase in the sensitivity of principal cells to intrinsic inhibitory afferents and a transient loss of excitatory–inhibitory balance.
Year
DOI
Venue
2015
10.1016/j.neuroimage.2014.12.007
NeuroImage
Keywords
DocType
Volume
DCM,SOZ,EEG,CSD
Journal
107
ISSN
Citations 
PageRank 
1053-8119
7
0.47
References 
Authors
13
7
Name
Order
Citations
PageRank
Margarita Papadopoulou170.47
Marco Leite2183.39
Pieter van Mierlo3101.56
Kristl Vonck470.47
Louis Lemieux543979.68
K. J. Friston6430321.24
Daniele Marinazzo7112.90