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Infant Auditory Processing and Event-related Brain Oscillations
Published on: July 1, 2015
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Analyzing the waveshape of brain oscillations with bicoherence
Sarah Bartz1, Forooz Shahbazi Avarvand2, Gregor Leicht3
1Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany; Berlin Institute of Technology, Machine Learning Laboratory, Berlin, Germany.
Neuroimage
|December 4, 2018
Summary
Brain oscillation waveshape analysis reveals neurophysiological insights. New methods using bispectrum and spatial filtering detect anomalies in conditions like schizophrenia, improving understanding beyond traditional frequency bands.
Area of Science:
- Neuroscience
- Signal Processing
Background:
- Brain activity is characterized by oscillations traditionally categorized by frequency bands.
- Non-sinusoidal waveshape features of brain oscillations can mislead cross-frequency coupling measures.
- Waveshape characteristics reflect neurophysiology and are altered in neurological conditions.
Purpose of the Study:
- To analyze brain oscillation waveshape properties using frequency and time domain methods.
- To introduce a waveshape-preserving spatial filter to mitigate distortions from bandpass filters.
- To investigate alpha and mu rhythms in resting-state and clinical conditions.
Main Methods:
- Utilized bispectrum analysis to reveal waveshape properties like phase differences and duration of crests/troughs.
- Introduced a novel waveshape-preserving spatial filter for accurate oscillation extraction.
- Applied bicoherence analysis to resting-state alpha rhythms and identified anomalies in schizophrenia.
Main Results:
- Bispectrum analysis directly reflects oscillation waveshape properties.
- Bandpass filters can distort waveshape; a spatial filter preserves these features.
- Alpha rhythm shape exists on a spectrum, and mu rhythm anomalies in schizophrenia are linked to waveshape.
Conclusions:
- Waveshape analysis provides complementary information to frequency domain analysis.
- Careful selection of signal processing methods is crucial for accurate waveshape analysis.
- Bispectral analysis offers novel insights into brain oscillations and their alterations in neurological disorders.
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