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Heterogeneity of EEG resting-state brain networks in absolute pitch

View ORCID ProfileMarielle Greber, Carina Klein, View ORCID ProfileSimon Leipold, View ORCID ProfileSilvano Sele, View ORCID ProfileLutz Jäncke
doi: https://doi.org/10.1101/2020.05.03.063206
Marielle Greber
1Division Neuropsychology, Department of Psychology, University of Zurich, Zurich, Switzerland
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  • For correspondence: marielle.greber@uzh.ch lutz.jaencke@uzh.ch
Carina Klein
1Division Neuropsychology, Department of Psychology, University of Zurich, Zurich, Switzerland
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Simon Leipold
1Division Neuropsychology, Department of Psychology, University of Zurich, Zurich, Switzerland
2Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, USA
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Silvano Sele
1Division Neuropsychology, Department of Psychology, University of Zurich, Zurich, Switzerland
3University Research Priority Program (URPP), Dynamics of Healthy Aging, University of Zurich, Zurich, Switzerland
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Lutz Jäncke
1Division Neuropsychology, Department of Psychology, University of Zurich, Zurich, Switzerland
3University Research Priority Program (URPP), Dynamics of Healthy Aging, University of Zurich, Zurich, Switzerland
4Department of Special Education, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia
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  • For correspondence: marielle.greber@uzh.ch lutz.jaencke@uzh.ch
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Abstract

The neural basis of absolute pitch (AP), the ability to effortlessly identify a musical tone without an external reference, is poorly understood. One of the key questions is whether perceptual or cognitive processes underlie the phenomenon as both sensory and higher-order brain regions have been associated with AP. One approach to elucidate the neural underpinnings of a specific expertise is the examination of resting-state networks.

Thus, in this paper, we report a comprehensive functional network analysis of intracranial resting-state EEG data in a large sample of AP musicians (n = 54) and non-AP musicians (n = 51). We adopted two analysis approaches: First, we applied an ROI-based analysis to examine the connectivity between the auditory cortex and the dorsolateral prefrontal cortex (DLPFC) using several established functional connectivity measures. This analysis is a replication of a previous study which reported increased connectivity between these two regions in AP musicians. Second, we performed a whole-brain network-based analysis on the same functional connectivity measures to gain a more complete picture of the brain regions involved in a possibly large-scale network supporting AP ability.

In our sample, the ROI-based analysis did not provide evidence for an AP-specific connectivity increase between the auditory cortex and the DLPFC. In contrast, the whole-brain analysis revealed three networks with increased connectivity in AP musicians comprising nodes in frontal, temporal, subcortical, and occipital areas. Commonalities of the networks were found in both sensory and higher-order brain regions of the perisylvian area. Further research will be needed to confirm these exploratory results.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted May 04, 2020.
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Heterogeneity of EEG resting-state brain networks in absolute pitch
Marielle Greber, Carina Klein, Simon Leipold, Silvano Sele, Lutz Jäncke
bioRxiv 2020.05.03.063206; doi: https://doi.org/10.1101/2020.05.03.063206
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Heterogeneity of EEG resting-state brain networks in absolute pitch
Marielle Greber, Carina Klein, Simon Leipold, Silvano Sele, Lutz Jäncke
bioRxiv 2020.05.03.063206; doi: https://doi.org/10.1101/2020.05.03.063206

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