Dynamic functional connectivity in temporal lobe epilepsy: a graph theoretical and machine learning approach.

Alireza FallahiMohammad PooyanNastaran LotfiFatemeh BaniasadLeili TapakNeda Mohammadi-MobarakehSeyed Sohrab Hashemi-FesharakiJafar Mehvari-HabibabadiMohammad Reza AyMohammad-Reza Nazem-Zadeh

Published in: Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology (2020)

Accounting for the non-stationary characteristics of functional connectivity, dynamic connectivity analysis of graph measures along with machine learning approach can identify the temporal trend of some specific network features. These network features may be used as potential imaging markers in determining the epileptogenic hemisphere in patients with TLE.

Keyphrases

functional connectivity
resting state
machine learning
temporal lobe epilepsy
artificial intelligence
convolutional neural network
big data
high resolution
deep learning
neural network
liquid chromatography
network analysis
human health
multiple sclerosis
risk assessment
mass spectrometry
photodynamic therapy