scholarly journals Periodic Non-Sinusoidal Activity Can Produce Cross-Frequency Coupling in Cortical Signals in the Absence of Functional Interaction Between Neural Sources

2016 ◽  
Author(s):  
Edden M. Gerber ◽  
Boaz Sadeh ◽  
Andrew Ward ◽  
Robert T. Knight ◽  
Leon Y. Deouell
Keyword(s):  
Frequency Component ◽  
High Frequency Component ◽  
Functional Interaction ◽  
Scalp Eeg ◽  
Periodic Potentials ◽  
Frequency Coupling ◽  
Eeg Recordings ◽  
Low Amplitude ◽  
Cross Frequency Coupling ◽  
Intracranial Recordings

AbstractThe analysis of cross-frequency coupling (CFC) has become popular in studies involving intracranial and scalp EEG recordings in humans. It has been argued that some cases where CFC is mathematically present may not reflect an interaction of two distinct yet functionally coupled neural sources with different frequencies. Here we provide two empirical examples from intracranial recordings where CFC can be shown to be driven by the shape of a periodic waveform rather than by a functional interaction between distinct sources. Using simulations, we also present a generalized and realistic scenario where such coupling may arise. This scenario, which we term waveform-dependent CFC, arises when sharp waveforms (e.g., cortical potentials) occur in a periodic manner throughout parts of the data. Since the waveforms are repeated periodically, they constitute a slow wave that is inherently phase-aligned with the high-frequency component carried by the same waveforms. We submit that such behavior of the data, which seems to be present in various cortical signals, cannot be interpreted as reflecting functional modulation between distinct neural sources without additional evidence. In addition, we show that even low amplitude periodic potentials that cannot be readily observed or controlled for, are sufficient for significant CFC to occur.

scholarly journals Zero-crossing patterns reveal subtle epileptiform discharges in the scalp EEG

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jan Pyrzowski ◽  
Jean- Eudes Le Douget ◽  
Amal Fouad ◽  
Mariusz Siemiński ◽  
Joanna Jędrzejczak ◽  
...  
Keyword(s):  
Normal Subjects ◽  
Intracranial Eeg ◽  
Zero Crossing ◽  
Temporal Precision ◽  
Scalp Eeg ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges ◽  
Eeg Recordings ◽  
Patients With Epilepsy ◽  
Low Amplitude

AbstractClinical diagnosis of epilepsy depends heavily on the detection of interictal epileptiform discharges (IEDs) from scalp electroencephalographic (EEG) signals, which by purely visual means is far from straightforward. Here, we introduce a simple signal analysis procedure based on scalp EEG zero-crossing patterns which can extract the spatiotemporal structure of scalp voltage fluctuations. We analyzed simultaneous scalp and intracranial EEG recordings from patients with pharmacoresistant temporal lobe epilepsy. Our data show that a large proportion of intracranial IEDs manifest only as subtle, low-amplitude waveforms below scalp EEG background and could, therefore, not be detected visually. We found that scalp zero-crossing patterns allow detection of these intracranial IEDs on a single-trial level with millisecond temporal precision and including some mesial temporal discharges that do not propagate to the neocortex. Applied to an independent dataset, our method discriminated accurately between patients with epilepsy and normal subjects, confirming its practical applicability.

scholarly journals Delta rhythm in wakefulness: evidence from intracranial recordings in human beings

2015 ◽  
Vol 114 (2) ◽  
pp. 1248-1254 ◽  
Author(s):  
Robert N. S. Sachdev ◽  
Nicolas Gaspard ◽  
Jason L. Gerrard ◽  
Lawrence J. Hirsch ◽  
Dennis D. Spencer ◽  
...  
Keyword(s):  
High Frequency ◽  
Nonhuman Primates ◽  
Human Beings ◽  
Seizure Onset ◽  
Intracranial Eeg ◽  
Quiet Wakefulness ◽  
Delta Rhythm ◽  
Eeg Recordings ◽  
Low Amplitude ◽  
Intracranial Recordings

A widely accepted view is that wakefulness is a state in which the entire cortical mantle is persistently activated, and therefore desynchronized. Consequently, the EEG is dominated by low-amplitude, high-frequency fluctuations. This view is currently under revision because the 1–4 Hz delta rhythm is often evident during “quiet” wakefulness in rodents and nonhuman primates. Here we used intracranial EEG recordings to assess the occurrence of delta rhythm in 18 awake human beings. Our recordings reveal rhythmic delta during wakefulness at 10% of all recording sites. Delta rhythm could be observed in a single cortical lobe or in multiple lobes. Sites with high delta could flip between high and low delta power or could be in a persistently high delta state. Finally, these sites were rarely identified as the sites of seizure onset. Thus rhythmic delta can dominate the background operation and activity of some neocortical circuits in awake human beings.

scholarly journals Classification of Pre-Clinical Seizure States Using Scalp EEG Cross-Frequency Coupling Features

2018 ◽  
Vol 65 (11) ◽  
pp. 2440-2449 ◽  
Author(s):  
Daniel Jacobs ◽  
Trevor Hilton ◽  
Martin del Campo ◽  
Peter L. Carlen ◽  
Berj L. Bardakjian
Keyword(s):  
Scalp Eeg ◽  
Clinical Seizure ◽  
Frequency Coupling ◽  
Cross Frequency Coupling

scholarly journals Non-Sinusoidal Activity Can Produce Cross-Frequency Coupling in Cortical Signals in the Absence of Functional Interaction between Neural Sources

PLoS ONE ◽  
2016 ◽  
Vol 11 (12) ◽  
pp. e0167351 ◽  
Author(s):  
Edden M. Gerber ◽  
Boaz Sadeh ◽  
Andrew Ward ◽  
Robert T. Knight ◽  
Leon Y. Deouell
Keyword(s):  
Functional Interaction ◽  
Frequency Coupling ◽  
Cross Frequency Coupling

scholarly journals From thoughtless awareness to effortful cognition: alpha - theta cross-frequency dynamics in experienced meditators during meditation, rest and arithmetic

2020 ◽  
Author(s):  
Julio Rodriguez-Larios ◽  
Pascal Faber ◽  
Peter Achermann ◽  
Shisei Tei ◽  
Kaat Alaerts
Keyword(s):  
Cognitive Processing ◽  
Information Integration ◽  
Recent Theory ◽  
Harmonic Frequency ◽  
Arithmetic Task ◽  
Continuous Eeg ◽  
Frequency Coupling ◽  
Eeg Recordings ◽  
Cross Frequency Coupling ◽  
The Brain

AbstractNeural activity is known to oscillate within discrete frequency bands and the synchronization between these rhythms is hypothesized to underlie information integration in the brain. Since strict synchronization is only possible for harmonic frequencies, a recent theory proposes that the interaction between different brain rhythms is facilitated by transient harmonic frequency arrangements. In this line, it has been recently shown that the transient occurrence of 2:1 harmonic cross-frequency relationships between alpha and theta rhythms (i.e. falpha≈12 Hz; ftheta≈6 Hz) is enhanced during effortful cognition. In this study, we tested whether achieving a state of ‘mental emptiness’ during meditation is accompanied by a relative decrease in the occurrence of 2:1 harmonic cross-frequency relationships between alpha and theta rhythms. Continuous EEG recordings (19 electrodes) were obtained from 43 highly experienced meditators during meditation practice, rest and an arithmetic task. We show that the occurrence of transient alpha:theta 2:1 harmonic relationships increased linearly from a meditative to an active cognitive processing state (i.e. meditation< rest< arithmetic task). It is argued that transient EEG cross-frequency arrangements that prevent alpha:theta cross-frequency coupling could facilitate the experience of ‘mental emptiness’ by avoiding the interaction between the memory and executive components of cognition.

scholarly journals Mutual Information of Multiple Rhythms for EEG Signals

2020 ◽  
Vol 14 ◽  
Author(s):  
Antonio José Ibáñez-Molina ◽  
María Felipa Soriano ◽  
Sergio Iglesias-Parro
Keyword(s):  
Time Series ◽  
Mutual Information ◽  
A Priori ◽  
Basic Mechanism ◽  
Frequency Component ◽  
Brain Functioning ◽  
Single Method ◽  
Spatiotemporal Scales ◽  
Frequency Coupling ◽  
Cross Frequency Coupling

Electroencephalograms (EEG) are one of the most commonly used measures to study brain functioning at a macroscopic level. The structure of the EEG time series is composed of many neural rhythms interacting at different spatiotemporal scales. This interaction is often named as cross frequency coupling, and consists of transient couplings between various parameters of different rhythms. This coupling has been hypothesized to be a basic mechanism involved in cognitive functions. There are several methods to measure cross frequency coupling between two rhythms but no single method has been selected as the gold standard. Current methods only serve to explore two rhythms at a time, are computationally demanding, and impose assumptions about the nature of the signal. Here we present a new approach based on Information Theory in which we can characterize the interaction of more than two rhythms in a given EEG time series. It estimates the mutual information of multiple rhythms (MIMR) extracted from the original signal. We tested this measure using simulated and real empirical data. We simulated signals composed of three frequencies and background noise. When the coupling between each frequency component was manipulated, we found a significant variation in the MIMR. In addition, we found that MIMR was sensitive to real EEG time series collected with open vs. closed eyes, and intra-cortical recordings from epileptic and non-epileptic signals registered at different regions of the brain. MIMR is presented as a tool to explore multiple rhythms, easy to compute and without a priori assumptions.

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