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Title: A comprehensive analysis of the correlations between resting-state oscillations in multiple-frequency bands and Big Five traits
Authors: Ikeda, Shigeyuk
Takeuchi, Hikaru
Taki, Yasuyuki
Nouchi, Rui
Yokoyama, Ryoichi
Kotozaki, Yuka
Nakagawa, Seishu
Sekiguchi, Atsushi
Iizuka, Kunio
Yamamoto, Yuki
Hanawa, Sugiko
Araki, Tsuyoshi
Miyauchi, Carlos M.
Sakaki, Kohei
Nozawa, Takayuki
Yokota, Susumu
Magistro, Daniele
Kawashima, Ryuta
Keywords: Big Five traits
fALFF
Multiple-frequency bands
Extraversion
Multiple regression analysis
Issue Date: 2017
Publisher: Frontiers Media © The Authors
Citation: IKEDA, S. ... et al, 2017. A comprehensive analysis of the correlations between resting-state oscillations in multiple-frequency bands and Big Five traits. Frontiers in Human Neuroscience, 11, Article 321.
Abstract: Recently, the association between human personality traits and resting-state brain activity has gained interest in neuroimaging studies. However, it remains unclear if Big Five personality traits are represented in frequency bands (∼0.25 Hz) of resting-state functional magnetic resonance imaging (fMRI) activity. Based on earlier neurophysiological studies, we investigated the correlation between the five personality traits assessed by the NEO Five-Factor Inventory (NEO-FFI), and the fractional amplitude of low-frequency fluctuation (fALFF) at four distinct frequency bands (slow-5 (0.01–0.027 Hz), slow-4 (0.027–0.073 Hz), slow-3 (0.073–0.198 Hz) and slow-2 (0.198–0.25 Hz)). We enrolled 835 young subjects and calculated the correlations of resting-state fMRI signals using a multiple regression analysis. We found a significant and consistent correlation between fALFF and the personality trait of extraversion at all frequency bands. Furthermore, significant correlations were detected in distinct brain regions for each frequency band. This finding supports the frequency-specific spatial representations of personality traits as previously suggested. In conclusion, our data highlight an association between human personality traits and fALFF at four distinct frequency bands.
Description: This is an Open Access Article. Is it published by Frontiers Media under the Creative Commons Attribution 4.0 International Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/
Sponsor: This work was supported by JST/RISTEX, JST/CREST and a Grant-in-Aid for Young Scientists (B) (KAKENHI 23700306) and Young Scientists (A) (KAKENHI 25700012) from the Ministry of Education, Culture, Sports, Science and Technology.
Version: Published
DOI: 10.3389/fnhum.2017.00321
URI: https://dspace.lboro.ac.uk/2134/25629
Publisher Link: http://dx.doi.org/10.3389/fnhum.2017.00321
ISSN: 1662-5161
Appears in Collections:Published Articles (Sport, Exercise and Health Sciences)

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