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Genetic polymorphisms in COMT and BDNF influence synchronization dynamics of human neuronal oscillations

Cite this dataset

Simola, Jaana et al. (2023). Genetic polymorphisms in COMT and BDNF influence synchronization dynamics of human neuronal oscillations [Dataset]. Dryad.


Neuronal oscillations, their inter-areal synchronization, and scale-free dynamics constitute fundamental mechanisms for cognition by regulating communication in neuronal networks. These oscillatory dynamics have large inter-individual variability that is partly heritable. We hypothesized that this variability could be partially explained by genetic polymorphism in neuromodulatory genes. We recorded resting-state magnetoencephalography (MEG) from 82 healthy participants and investigated whether oscillation dynamics were influenced by genetic polymorphisms in Catechol-O-methyltransferase (COMT) Val158Met and brain-derived neurotrophic factor (BDNF) Val66Met. Both COMT and BDNF polymorphisms influenced local oscillation amplitudes and their long-range temporal correlations (LRTCs), while only BDNF polymorphism affected the strength of large-scale synchronization. Our findings demonstrate that COMT and BDNF genetic polymorphisms contribute to inter-individual variability in neuronal oscillation dynamics. Comparison of these results to computational modeling of near-critical synchronization dynamics further suggested that COMT and BDNF polymorphisms influenced local oscillations by modulating the excitation-inhibition balance according to the brain criticality framework.


Resting-state brain activity was recorded from healthy volunteers (N=82, 18–55 years of age; mean age: 29 years; 6 left-handed; 44 female) with 306-channel MEG (Vectorview, Elekta-Neuromag, LtD) at a sampling rate of 600 Hz. The subjects fixated on a central fixation cross throughout the ~8 min resting-state MEG-recording (duration 7.8 ± 2.9 min, mean ± standard deviation). MEG data was preprocessed using temporal signal-space separation with Maxfilter software and artifact removal was carried out using independent component analysis. MNE inverse operators were then computed for all wavelet frequencies and used to project the sensor-space data into source-space. Source-vertex time series were collapsed into cortical parcel time series with individual collapse operators that maximize source-reconstruction accuracy. A cortical parcellation in individual anatomy but with labels shared among the subject was obtained by iteratively splitting the 148-parcel Destrieux atlas into 400 parcels. The parcels were also assigned functional labels based on Yeo’s 7-functional-brain-systems atlas. 26 Morlet wavelets (log-spaced center frequencies 3-60 Hz) were used for obtaining the amplitude and phase time series of cortical parcels. LRTCs in amplitude time series were quantified with detrended fluctuation analysis (DFA) where the power-law-scaling exponent β is the slope of the DFA function and obtained with linear regression. Phase synchronization between parcels was computed using the weighted phase-lag index (wPLI). Amplitude, DFA, and phase synchonization values were then collapsed back to the 148-parcel Destrieux atlas, and phase synchonization also to the 7 systems (per hemisphere) of the Yeo atlas.

Usage notes

This data includes mean amplitudes, connectivity matrices, and detrended fluctuation analysis scaling exponents derived from 82 subjects' magnetoencephalographic resting-state recordings. The results of polymorphism analysis can be found, along with parcellation information, in the "settings" subfolder. This data can be used for replicating the main results from "Genetic polymorphisms in COMT and BDNF influence synchronization dynamics of human neuronal oscillations" with the python code in the associated code repository


Academy of Finland, Award: SA 1266402

Academy of Finland, Award: SA 1267030

Academy of Finland, Award: SA 1266745

Academy of Finland, Award: SA 1296304

Academy of Finland, Award: SA 1294761

Jane and Aatos Erkko Foundation

Jane ja Aatos Erkon Säätiö

Academy of Finland, Award: 1267030

Academy of Finland, Award: 1296304