Can we “find the beat”? Searching the beta band in the human EEG as a function of acoustic rhythmic regularity and in correlation with behaviour.

Research output: Contribution to conferencePosterResearchpeer-review

  • Manon Grube
  • Stephanie Brandl, Machine Learning Group, TU Berlin, Germany, GermanyPieter-Jan Kindermans, Machine Learning Group, TU Berlin, Germany, GermanyBenjamin Blankertz, Neurotechnology Group, TU Berlin, Germany, GermanySven Daehne, Machine Learning Group, TU Berlin, Germany, GermanyKlaus-Robert Mueller, Machine Learning Group, TU Berlin, Germany, Germany
AIMS. This work aims at beat-based entrainment mechanisms in the human brain. It examines the effect of rhythmic regularity on beta-band activity in the electroencephalogram (EEG). Motivated by previous demonstrations of beta power modulation by a regular beat (Fujioka et al., 2012; Chang et al., 2014; Cirelli et al., 2014), we employ state-of-the-art machine-learning techniques (Nikulin et al., 2011; Daehne et al., 2014; Haufe et al., 2014) to track the activity of relevant components in source space, and test for links with behaviour. METHODS. In an active listening experiment (Bekius et al., 2015), participants (n=26) were asked to rate the degree of regularity of sequences of 9-11 tones, with an underlying beat period of 340, 400 or 460 ms inter-onset-interval, and different degree of irregularity (0 vs. 30% jitter). Continuous EEG was epoched into 2-beat periods, wavelet analysis applied to calculate spectrograms, and Fourier transformation to obtain modulation power as a function of frequency, with focus on the beat period. RESULTS. Running the analysis in on more traditional formats (single channel, Laplace, beam former) yield very limited results. Plugging in our customized pipeline that combines spatio-spectral decomposition with a novel source separation framework allows extracting components with a beat-related modulation of beta-band specific activity and correlation with behavior (Spearman’s rho >0.5, p<0.01). CONCLUSION. Initial results look promising, in terms of EEG beta band power and even a possible link with perceptual performance, but with limitations in statistical stability and consistency with pre-existing work, warranting further testing and critical discussion. References: Bekius, A., Cope, T., Sturm, I., Müller, K.-R., Grube, M. (2015) Systematic investigation of the “feeling of a beat”: auditory regularity processing in behaviour and EEG. Rhythm Perception & Production Workshop (RPPW). Chang, A., Bosnyak, D. J., & Trainor, L. J. (2016). Unpredicted Pitch Modulates Beta Oscillatory Power during Rhythmic Entrainment to a Tone Sequence. Front Psychol, 7, 327. doi:10.3389/fpsyg.2016.00327 Cirelli, L. K., Bosnyak, D., Manning, F. C., Spinelli, C., Marie, C., Fujioka, T., . . . Trainor, L. J. (2014). Beat-induced fluctuations in auditory cortical beta-band activity: using EEG to measure age-related changes. Front Psychol, 5, 742. doi:10.3389/fpsyg.2014.00742 Dahne, S., Meinecke, F. C., Haufe, S., Hohne, J., Tangermann, M., Muller, K. R., & Nikulin, V. V. (2014). SPoC: A novel framework for relating the amplitude of neuronal oscillations to behaviorally relevant parameters. Neuroimage, 86, 111-122. doi:10.1016/j.neuroimage.2013.07.079 Fujioka, T., Trainor, L. J., Large, E. W., & Ross, B. (2012). Internalized timing of isochronous sounds is represented in neuromagnetic beta oscillations. J Neurosci, 32(5), 1791-1802. doi:10.1523/JNEUROSCI.4107-11.2012 Haufe, S., Meinecke, F., Gorgen, K., Dahne, S., Haynes, J. D., Blankertz, B., & Biessmann, F. (2014). On the interpretation of weight vectors of linear models in multivariate neuroimaging. Neuroimage, 87, 96-110. doi:10.1016/j.neuroimage.2013.10.067 Nikulin, V. V., Nolte, G., & Curio, G. (2011). A novel method for reliable and fast extraction of neuronal EEG/MEG oscillations on the basis of spatio-spectral decomposition. Neuroimage, 55(4), 1528-1535. doi:10.1016/j.neuroimage.2011.01.057
Original languageEnglish
Publication year9 Jul 2018
Number of pages1
Publication statusPublished - 9 Jul 2018
Event11th FENS Forum of Neuroscience: Federation of European Neuroscience Societies - CityCube Berlin, Berlin, Germany
Duration: 7 Jul 201811 Jul 2018
http://www.fens.org

Conference

Conference11th FENS Forum of Neuroscience
LocationCityCube Berlin
CountryGermany
CityBerlin
Period07/07/201811/07/2018
Internet address

Bibliographical note

Also presented at the first edition of the Auditory EEG Signal Processing (AESoP) symposium, 21/05/2018 - 23/05/2018 in Leuven, Belgium.

    Research areas

  • auditory, rhythm, regularity, beat, beta band, EEG.

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