Tracking EEG Network Dynamics

Epilepsy in the neonatal period and in childhood can often profoundly disrupt normal brain function. We can use EEG to characterise these disruptions, but visual EEG analysis, particularly in young children is time-consuming and challenging. Furthermore, certain features of the EEG that describe the relationship between multiple challenge are difficult to appreciate by visual analysis alone. 

In this work stream, we are exploring the use of computational analysis of clinical EEG recordings to track dynamic network changes in patients with a range of different epilepsies. This work aims to identify both biomarkers that can support the diagnostic process in the clinical setting, and dynamic features that may point to a new understanding of underlying disease mechanism. 

Collaborators

Gerold Baier
Senior Research Associate
University College London, 

London (UK)

Torsten Baldeweg
Professor of Developmental Cognitive Neuroscience
University College London,
London (UK)

Friederike Moeller
Consultant Neurophysiologist
Great Ormond Street Hospital,
London (UK)

Rachel Thornton
Consultant Neurophysiologist
Great Ormond Street Hospital, 
London (UK)

 


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In this paper we illustrate how summary measures of network dynamics can separate subgroups of epilepsies in early infancy. 

Rosch et al (2017) Net Neurosci: 10.1162/netn_a_00026

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This code applies dynamic network analysis on clinical EEG recordings, using a dynamic delay-delay matrix approach. 

Github: Dynamics Matrices