We present a novel method for the extraction of neuronal components showing cross-frequency phase synchronization.
In general the method can be applied for the detection of phase interactions between components with frequencies f1 and f2, where f2 ≈ rf1 and r is some integer. We refer to the method as cross-frequency decomposition (CFD), which consists of the following steps: (a) extraction of f1-oscillations with the spatio-spectral decomposition algorithm (SSD); (b) frequency modification of the f1-oscillations obtained with SSD; and (c) finding f2-oscillations synchronous with f1-oscillations using least-squares estimation.
Our simulations showed that CFD was capable of recovering interacting components even when the signal-to-noise ratio was as low as 0.01. An application of CFD to the real EEG data demonstrated that cross-frequency phase synchronization between alpha and beta oscillations can originate from the same or remote neuronal populations.
CFD allows a compact representation of the sets of interacting components. The application of CFD to EEG data allows differentiating cross-frequency synchronization arising due to genuine neurophysiological interactions from interactions occurring due to quasi-sinusoidal waveform of neuronal oscillations.
CFD is a method capable of extracting cross-frequency coupled neuronal oscillations even in the presence of strong noise.
Copyright © 2011 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
The performance of the three methods depends on the amount of averaged trials. Moreover, differences are found on both amplitude and latency of ERP components recorded in two environments (0 T vs 3 T). We showed that, while ERPs can be extracted from simultaneous EEG–fMRI data at 3 T, the static magnetic field might affect the physiological processes under investigation.The reproducibility of the ERPs in different recording environments (0 T vs 3 T) is a relevant issue that deserves further investigation to clarify the equivalence of cognitive processes in both behavioral and imaging studies.
Electrocorticography (ECoG) is a standard procedure for the localization of the epileptogeniczone during the surgical treatment of symptomatic epilepsy. The purpose of this study was to evaluate the diagnostic efficacy of intraoperative pre- and post-resective ECoG for the localization of the epileptogenic zone in patients with symptomatic epilepsy associated with supratentorial brain tumors. 1. In the surgical treatment of symptomatic epilepsy associated with intracerebral neoplasm, intraoperative ECG remains a relatively effective method. 2. The effectiveness of intraoperative pre- and post-resection ECoG is affected by factors associated with the performance of neurosurgical surgery (the influence of general anesthetics, mechanical effects on the brain, repeated electrocoagulation), which significantly alter the index of epileptiform activity.
Objective Removal of brain tissue generating pathological high-frequency oscillations (pHFOs) has been related to better seizure outcome than resection of seizure onset zone. However, there is still a lack of understanding what oscillations are to be considered pathological. Methods A female patient (age 53) with 10 year duration of temporal lobe tumor-related epilepsy was admitted to Polenov’s Neurosurgery Institute for tumor resection. The patient underwent a two-staged surgery with subdural implantation of a grid electrode (4 × 5) over the temporal lobe to identify the epileptogenic zone (EZ). During the second stage wideband intraoperative electrocorticography (iECoG) was recorded (up to 500 Hz, sampling frequency 2000 Hz, Mitsar-EEG 202 amplifier). Results Electrocorticographic monitoring data were subjected to visual analysis in traditional frequency range (0.5–70 Hz). Six of 20 electrodes were marked as EZ electrodes. The distance between tumor margin and EZ electrodes reached 1–2.5 cm. Subpial resection of this zone was arranged. During the surgery iECoG data in 0.5–70 Hz frequency band were uninformative, while in 80–500 Hz range bursts of fast ripples (250–500 Hz, 100 μV, extended up to 3 s) were recorded over the marked EZ electrodes. The tumor and EZ were completely resected. Discussion Observed data demonstrate that HFOs coincide with EZ marked during long-term monitoring. The patient is seizure-free for 5 months at the moment, though a more prolonged follow-up is required. Conclusion Wideband iECoG recordings might give us more essential information in case of tumor-related epilepsy. As is shown, fast ripples may be a valid marker of EZ. Significance Pathological HFOs show promise for optimising epilepsy surgery in tumor-related epilepsy.