gms | German Medical Science

60. Jahrestagung der Deutschen Gesellschaft für Neuropathologie und Neuroanatomie (DGNN)

Deutsche Gesellschaft für Neuropathologie und Neuroanatomie

26. - 28.08.2015, Berlin

Power spectral density (PSD) of brain signal differs between genders and networks

Meeting Abstract

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  • corresponding author presenting/speaker Gianluca Mingoia - University hospital RWTH Aachen, IZKF Aachen, Aachen, Germany
  • Igor Nenadic - University hospital of Jena, Clinic of Psychiatry and Psychotherapy, Jena, Germany

Deutsche Gesellschaft für Neuropathologie und Neuroanatomie. 60th Annual Meeting of the German Society for Neuropathology and Neuroanatomy (DGNN). Berlin, 26.-28.08.2015. Düsseldorf: German Medical Science GMS Publishing House; 2015. Doc15dgnnP36

doi: 10.3205/15dgnn60, urn:nbn:de:0183-15dgnn604

Veröffentlicht: 25. August 2015

© 2015 Mingoia et al.
Dieser Artikel ist ein Open-Access-Artikel und steht unter den Lizenzbedingungen der Creative Commons Attribution 4.0 License (Namensnennung). Lizenz-Angaben siehe



Background: Recent studies demonstrate significant functional connectivity gender differences in resting state networks, but did not provide clues about the temporal dynamics of resting state fMRI. He et al. (2011) founded that the fMRI signal consists of scale free dynamics and its power-law exponent differentiates between brain areas. Frequency power distribution was also found to differ in newborns compare to adults (Fransson, 2012). Both studies focus their investigation on single areas and their time courses. The goal of our study was to compare the PSD in resting state fMRI networks between men and women across 11 well-known brain networks.

Methods: We obtained RS fMRI series in 83 women and 73 men, all right handed and healthy. Data were pre-processed and high-pass filtered. We applied FSL MELODIC, and an automated routine to select the components matching the anatomical definition of well-known networks (Damoiseaux et al. 2006, Seeley et al. 2007). Power spectrum of the fMRI signal was computed for each individual’s networks component using the Welch method for power spectrum density estimation. The frequency spectrum functions were fitted with a power-law function y. The power slope α was entered into ANOVA with network and gender as main factors.

Results: ANOVA with network as the main factor showed a significant power-law exponent dependence with network (women: p<0.0001; men: p<0.0001). The mean slope of frequency power spectra (α) was higher in men (α=0.91) compared to women (α=0.76) p<0.001; following networks exhibited significant differences between genders: auditory, frontoparietal1, Sensorimotor, Visual1, Visual2, Visual3 (see Figure 1 [Fig. 1]).

Conclusions: To the best of our knowledge this study is the first comparing the PSD of well-known resting state network between gender. Results show strong differences in the frequency power distribution of spontaneous bold signal fluctuation inter gender and between networks suggesting the possibility to investigate brain networks and their rule in clinical process in frequency domain too.