Title |
A Comprehensive Analysis of the Correlations between Resting-State Oscillations in Multiple-Frequency Bands and Big Five Traits
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Published in |
Frontiers in Human Neuroscience, June 2017
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DOI | 10.3389/fnhum.2017.00321 |
Pubmed ID | |
Authors |
Shigeyuki Ikeda, Hikaru Takeuchi, Yasuyuki Taki, Rui Nouchi, Ryoichi Yokoyama, Yuka Kotozaki, Seishu Nakagawa, Atsushi Sekiguchi, Kunio Iizuka, Yuki Yamamoto, Sugiko Hanawa, Tsuyoshi Araki, Carlos Makoto Miyauchi, Kohei Sakaki, Takayuki Nozawa, Susumu Yokota, Daniele Magistro, Ryuta Kawashima |
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. |
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France | 1 | 11% |
United Kingdom | 1 | 11% |
Switzerland | 1 | 11% |
Spain | 1 | 11% |
Unknown | 3 | 33% |
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Scientists | 1 | 11% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 57 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 8 | 14% |
Researcher | 8 | 14% |
Student > Master | 6 | 11% |
Student > Doctoral Student | 5 | 9% |
Professor > Associate Professor | 4 | 7% |
Other | 10 | 18% |
Unknown | 16 | 28% |
Readers by discipline | Count | As % |
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Psychology | 14 | 25% |
Neuroscience | 11 | 19% |
Medicine and Dentistry | 6 | 11% |
Engineering | 2 | 4% |
Sports and Recreations | 2 | 4% |
Other | 4 | 7% |
Unknown | 18 | 32% |