Abstracts

Rationale: High-frequency oscillations (HFOs, >80Hz) different have proven important and useful. Classical studies in this field were focused on the spatial relationship of ictal activity with the rhythms in each of limited frequency bands, not to address the temporal relationship of HFOs for seizure activity. However, it is revealed that further examining the relation and interaction between the nonstationary oscillations in different bands, can be informative in understanding epileptogenesis. Methods: Recent studies suggest that cross-frequency coupling play a functional role in neuronal computation, communication and learning. Here we proposed a new analytical tool to compute the coupling between the amplitudes of different oscillatory components at different frequencies. We analyzed intracranial EEG signals of seizure activity to investigate the dynamics of HFOs. We first utilize empirical mode decomposition (EMD) to extract nonlinear oscillations at different frequencies. All EMD components of a signal, called intrinsic mode functions (IMFs) are unique to the signal, allowing for frequency and amplitude changes at timescales close to the sampling rate of the data. Then we use Hilbert transform to obtain instantaneous amplitude of each IMF — amplitude envelop. In order to quantify amplitude-amplitude coupling (AAC) between two oscillatory components over a specific range of frequencies range, we used EMD to extract oscillatory components (IMFs) of the amplitude envelopes in the given frequency region. After evaluating the standard deviation (SD) of each IMFs extracted from the given amplitude envelops, by taking the amplitude envelop from one of the 1st extracted IMFs and the phase from the 2nd extracted IMFs (the frequency of the 1st IMFs we applied to decompose 2nd times must lower than the one we taken as the amplitude envelop), we can therefore quantify their AAC using an index named modulation index (MI) and weighted via their SD values. Finally, we can calculate AAC between IMFs over different frequency ranges. Results: Eleven ictal ECoGs from 5 epileptic patients that were acquired in 512Hz sampling were analyzed. There were common features of seizure dynamics. During an epileptic seizure, the dynamic of phase-amplitude coupling showed a drifting on the on the amplitude-given frequency (β or ϒ wave) to its lower frequency approximately in the middle of the dynamic process, while the dynamic of AAC further shows that the coupling behavior become more center to a certain point gradually. Both PAC and AAC show stronger energy in approximately the middle of the seizure dynamic. HFOs (100-300Hz) within individual channel were consistantly nested by lower frequency waves. Conclusions: Not like interictal or preictal stage, HFOs not only remain during a seizure but also tightly coupled with dynamic changes of lower frequency oscillations. Our findings further support that cross-frequency coupling serve as a mechanism of large-scale brain networks operating at seizure and HFOs are critical signs of epileptogenesis.