Frequency-PCA improves EEG estimates in the EEG-ERP dynamics field
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1
University of Wollongong, School of Psychology, Australia
Aims: Our previous brain dynamics work investigated prestimulus EEG phase and amplitude effects upon behaviour and event-related potentials (ERPs) associated with stimulus processing. Frequency Principal Components Analysis (f-PCA) can identify data-driven EEG components, potentially paralleling our recent ERP move from peak-picked amplitudes to temporal PCA decomposition. Here we explored if f-PCA can provide insight to EEG analysis in the brain dynamics arena.
Method: Continuous EEG (19 sites) was recorded from 20 young adults during 3 minutes of eyes-closed (EC) and eyes-open (EO) resting, and a subsequent equiprobable auditory Go/NoGo task. Two second resting EC and EO epochs were windowed, and 0.5 s prestimulus Go and NoGo epochs were windowed and zero-padded, before undergoing Discrete Fourier Transformation (resolution 0.5 Hz). Mean spectral amplitudes in 61 frequencies (DC to 30 Hz) were reshaped for each subject and condition (EC, EO, Go, NoGo) and entered into a single unrestricted f-PCA using Promax rotation. Frequency components were explored as predictors of Go P3b and NoGo P3a amplitudes obtained from temporal PCA of the ERPs.
Results: EEG f-PCA yielded two components peaking in delta (0.5, 2.0 Hz), three in alpha (8.0, 9.0, 10.0 Hz), and two in the beta band (15.5, 24.5 Hz); these represented 91.3% of the variance. P3a amplitude was directly related to the 9.0 Hz alpha component, and inversely related to the 10.0 Hz component. P3b amplitude was inversely related to alpha components at 8.0 and 10.0 Hz, and directly related to the 9.0 Hz component.
Conclusions: The mid-frequency 9.0 Hz alpha component directly affected P3a and P3b amplitudes, confirming previous findings of the direct impact of prestimulus alpha on P3. In addition, f-PCA has added refinement in the subdivisions of the EEG bands, and done so in a data-driven decomposition of the EEG spectrum rather than depending on arbitrary frequency ranges.
Keywords:
Prestimulus EEG,
Frequency Principal Components Analysis (f-PCA),
event-related potentials (ERPs),
Brain Dynamics,
EEG-ERP relationships
Conference:
ASP2016 - The 26th Annual Meeting of the Australasian Society for Psychophysiology, Adelaide Australia, Adelaide,SA, Australia, 12 Dec - 14 Dec, 2016.
Presentation Type:
Oral Presentation
Topic:
Abstract (general)
Citation:
Barry
RJ and
De Blasio
FM
(2016). Frequency-PCA improves EEG estimates in the EEG-ERP dynamics field.
Conference Abstract:
ASP2016 - The 26th Annual Meeting of the Australasian Society for Psychophysiology, Adelaide Australia.
doi: 10.3389/conf.fnhum.2016.221.00013
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Received:
04 Nov 2016;
Published Online:
05 Dec 2016.
*
Correspondence:
Dr. Robert J Barry, University of Wollongong, School of Psychology, Wollongong, NSW, 2522, Australia, rbarry@uow.edu.au