2 new papers co-authored by CDB's Dr Gerold Baier published by Frontiers in Computational Neuroscience and Network Neuroscience
15 November 2017
Electro-cortical activity in patients with epilepsy may show abnormal rhythmic transients in response to stimulation.
Read full paper: Understanding epileptiform after-discharges as rhythmic oscillatory transients
Authors: Gerold Baier, Peter N. Taylor and Yujiang Wang
Electroencephalography (EEG) allows recording of cortical activity at high temporal resolution. EEG recordings can be summarised along different dimensions using network-level quantitative measures, e.g. channel-to-channel correlation, or band power distributions across channels. These reveal network patterns that unfold over a range of different time scales and can be tracked dynamically.
Here we describe the dynamics of network-state transitions in EEG recordings of spontaneous brain activity in normally developing infants and infants with severe early infantile epileptic encephalopathies (n=8, age: 1-8 months). We describe differences in measures of EEG dynamics derived from band power, and correlation-based summaries of network-wide brain activity.
We further show that EEGs from different patient groups and controls may be distinguishable based on a small set of the novel quantitative measures introduced here, which describe dynamic network state switching. Quantitative measures related to the sharpness of switching from one correlation pattern to another show the largest differences between groups.
These findings reveal that the early epileptic encephalopathies are associated with characteristic dynamic features at the network level. Quantitative network-based analyses like the one presented here may in future inform the clinical use of quantitative EEG for diagnosis.
Read full paper: Network dynamics in the healthy and epileptic developing brain
Authors: RE Rosch, T Baldeweg, F Moeller and G Baier