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Personality traits and the amplitude of spontaneous low-frequency oscillations during resting state
Neuroscience Letters 492 (2011) 109–113
Contents lists available at ScienceDirect
Neuroscience Letters journal homepage: www.elsevier.com/locate/neulet
Personality traits and the amplitude of spontaneous low-frequency oscillations during resting state Yoshihiko Kunisato a,b , Yasumasa Okamoto a,c , Go Okada a,c , Shiori Aoyama a,c , Yoshiko Nishiyama a , Keiichi Onoda d , Shigeto Yamawaki a,c,∗ a Department of Psychiatry and Neurosciences, Division of Frontier Medical Science, Graduate School of Biomedical Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima 734-8551, Japan b Japan Society for the Promotion of Science, 8 Ichibancho, Chiyoda-ku 102-8472, Japan c Core Research for Evolutional Science and Technology, 5 Sanbancho, Chiyoda-ku 102-0075, Japan d Department of Neurology, Faculty of Medicine, Shimane University, 89-1 Enyacho, Izumo 693-8501, Japan
a r t i c l e
i n f o
Article history: Received 15 November 2010 Received in revised form 11 January 2011 Accepted 25 January 2011 Keywords: Personality Big Five model Resting-state fMRI Fractional amplitude of low-frequency fluctuation
a b s t r a c t Recently, neural substrates of the Big Five personality model were investigated using neuroimaging. We examined the relationships between the amplitude of spontaneous low-frequency oscillations (LFO) and the Big Five traits using resting-state functional magnetic resonance imaging (R-fMRI). Twenty-four healthy right-handed undergraduates (23.13 ± 1.87 years, 9 males and 15 females) participated in 5min R-fMRI and completed the NEO Five-Factor Inventory. We observed that Neuroticism correlated negatively with regional activity of the middle frontal gyrus and precuneus; Extraversion correlated positively with regional activity of the striatum, precuneus, and superior frontal gyrus; Openness correlated positively with the thalamus and amygdala, and negatively with the superior frontal gyrus; Conscientiousness correlated positively with regional activity of the middle frontal gyrus and correlated negatively with the cerebellum. Our results revealed the neural substrates of Extraversion, Neuroticism, Openness, and Conscientiousness in the amplitude of spontaneous LFO. © 2011 Elsevier Ireland Ltd. All rights reserved.
Personality psychology has clarified that human personality is described by five personality traits: Extraversion, Neuroticism, Agreeableness, Conscientiousness, and Openness to experience [4]. This model was called the Big Five Model and a great deal of research has been conducted on personality psychology. DeYoung and Gray [8] proposed a biological model for the Big Five traits, in which Extraversion was associated with sensitivity to rewardrelated regions: nucleus accumbens, amygdala, and orbitofrontal cortex [7,25]; Neuroticism was associated with sensitivity to punishment regions: amygdala, anterior and middle cingulate cortex, medial prefrontal cortex, and hippocampus [13]; Agreeableness was associated with the theory of mind and empathy-related regions, including the superior temporal sulcus, temporo-parietal junction, and posterior cingulate cortex [23,26]; Conscientiousness was associated with inhibiting and constraining impulse-related regions, including the lateral prefrontal cortex [2]; and Openness to experience was associated with working memory, attention, and
∗ Corresponding author at: Department of Psychiatry and Neurosciences, Division of Frontier Medical Science, Graduate School of Biomedical Sciences, Hiroshima University, 1-2-3, Kasumi, Minami-ku, Hiroshima 734-8551, Japan. Tel.: +81 82 257 5208; fax: +81 82 257 5209. E-mail address: [email protected] (S. Yamawaki). 0304-3940/$ – see front matter © 2011 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.neulet.2011.01.067
reasoning-related regions, including the dorsolateral prefrontal cortex, anterior prefrontal cortex (frontal pole), and anterior parietal cortex [10]. DeYoung et al. [9] examined the relationship between individual differences in brain structure and the Big Five traits and partly confirmed the validity of their biological model. Some studies examined the relationship between resting state brain activity and the Big Five traits using positron emission tomography (PET) and electroencephalography (EEG) [6,18,29]. Especially, Extraversion and Neuroticism were associated with activity in specific brain regions, and these results agree with the biological model for the Big Five traits. Recently, there has been a great deal of interest in spontaneous low-frequency oscillations (LFO) measured by resting-state functional magnetic resonance imaging (R-fMRI) [3,11]. R-fMRI can detect functional networks of spontaneous LFO in brain regions, including the posterior cingulate cortex (PCC), precuneus, lateral parietal cortex, and medial prefrontal cortex (MPFC). The fractional amplitude of low-frequency fluctuation (fALFF) is one of the measures of spontaneous LFO that has been detected with R-fMRI and its reliability has been verified over time [31,32]. As the amplitude of spontaneous LFO is detected robustly and reliably over time, it seems that individual differences of spontaneous LFO are associated with individual differences in human traits, including
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Table 1 Regions in which fALFF correlated with the Big Five traits. Traits and predominant regions in cluster
Neuroticism Middle frontal gyrus Precuneus Extraversion Superior frontal gyrus Putamen and caudate Putamen Superior frontal gyrus Precuneus Precuneus Openness Superior frontal gyrus Thalamus and amygdala Agreeableness No region Conscientiousness Middle frontal gyrus Middle frontal gyrus Cerebellum and inferior temporal gyrus Cerebellum *
Side
BA
Voxels
Peak
Peak coordinates
Z-score
x
y
r z
R R
6 7
135 87
4.18 3.23
36 27
6 −45
54 42
−0.676* −0.676*
R R L R R L
10
219 291 170 195 73 84
4.33 4.23 3.98 3.79 3.65 3.38
21 18 −18 9 9 −9
57 12 18 24 −60 −54
15 −15 −9 66 54 21
0.666* 0.698* 0.681* 0.640* 0.561* 0.693*
6 7 31
R L
10
123 109
4.57 4.16
21 −15
63 −21
24 −3
−0.768* 0.711*
R L L R
6 8
176 79 121 167
4.64 3.41 4.50 3.73
51 −27 −51 15
0 33 −48 −72
54 54 −30 −30
0.669* 0.556* −0.779* −0.581*
p < 0.001.
personality and intelligence [11]. A few studies have examined the relationship between spontaneous LFO and IQ [28] or riskrelated personality [5]; however, no studies have investigated the relationship between the amplitude of spontaneous LFO and comprehensively measured personality on the basis of the Big Five model. This approach may contribute to the confirmation and elaboration of the biological model of personality or clarify individual differences in the amplitude of spontaneous LFO modulated by personality. In the present study, we investigated the relationships between fALFF and the Big Five traits using R-fMRI. Twenty-four healthy right-handed undergraduates (23.13 ± 1.87 years, range = 20–27 years, 9 males and 15 females) participated in the R-fMRI experiment. They gave informed written consent to participate in the experiment, which was conducted with the approval of the Ethics Committee of Hiroshima University. Trained psychiatrists and clinical psychologists interviewed each volunteer and screened them for previous psychiatric problems by using the MINI international neuropsychiatric interview [27]. We confirmed that no subjects had any previous psychiatric disorders, including mood or psychotic disorders or substance abuse. Before scanning, all participants completed the NEO Five Factor Inventory (NEO-FFI) [4,30] and the Japanese version of the National Adult Reading Test (NART) to assess their intellectual ability [21,22]. The NEO-FFI is a self-reported measure and consists of 60 items that assess the five personality factors of the Big Five model. Scanning took place on the GE Signa EXCITE HD 3.0T scanner (General Electric, Milwaukee, WI, USA) using an 8-channel brain array coil. Whole-brain 5-minute resting state fMRI scans were acquired with an echo-planar imaging sequence (TR = 2000 ms, TE = 27 ms, FA = 90◦ , matrix size = 64 × 64, FOV = 256 mm, 4 mm slice thickness, 32 slice, no gap, 150 acquisitions). Participants were instructed to close their eyes and remain awake. After the functional scan, anatomical images were acquired at 1 mm × 1 mm × 1 mm resolution (TR = 6.6 ms, TE = 1.4 ms, FA = 20◦ , matrix size = 256 × 256, FOV = 256 mm). The first 10 images were discarded to ensure steady-state MRI signals during acclimation of the subjects, and the subsequent 140 images were used for further analysis. Image preprocessing was carried out using Statistical Parametric Mapping (SPM8) software (Wellcome Department of Cognitive Neurology, London, UK). First, slice timing and head movement corrections were applied. After head movement correction, the values for translation and rotation
were obtained at each time point. All subjects had less than 1.5 mm maximum displacement in the x, y, and z axes and less than 1.5◦ angular motion during the scan. The images were then spatially normalized to the Montreal Neurological Institute functional template (resampling voxel size = 3 mm × 3 mm × 3 mm) and smoothed using an 8 mm FWHM Gaussian kernel. After preprocessing in SPM, the linear trend was removed and fALFF analysis was carried out using the resting-state fMRI data analysis toolkit (REST, http://restfmri.net/forum/) ver. 1.4. The analysis procedure for fALFF was carried out according to the method of Zou et al. [31,32]. For a time series in each voxel, the sum of amplitudes within a low frequency range (0.01–0.08 Hz) was calculated. The fALFF was then computed as the fractional sum of amplitudes within the low frequency range that was divided by the sum of amplitude across the entire frequency range (0–0.25 Hz) [32]. The subject-level voxel-wise fALFF maps were standardized into subject-level Z-score maps by subtracting the mean voxel-wise fALFF obtained for the entire brain and dividing by the standard deviation. We conducted a simple regression analysis to examine the correlation between the fALFF and the Big Five traits using SPM8. In this analysis, we included the IQ score estimated by the NART as a nuisance covariate to control for differences in intelligence. We conducted a Monte Carlo simulation to determine the combined threshold corresponding to a threshold of p < 0.05 (corrected) using AlphaSim (http://afni.nimh. nih.gov/pub/dist/doc/program help/AlphaSim.html). We then set significant correlations at the threshold of a voxel-wise p < 0.005 (uncorrected) that belonged to a cluster of activation with an extent of at least 66 voxels. Activated clusters were localized using Anatomical Automatic Labeling for SPM8 ver. 1 (http://www.cyceron.fr/web/aal anatomical automatic labeling.html). The average score for the Japanese version of NART was 112.82 (±5.82). The average NEO-FFI score showed an average profile: Neuroticism = 26.96 ± 6.08; Extraversion = 26.83 ± 4.84; Agreeableness = 30.17 ± 5.52: Conscientiousness = 24.92 ± 6.16; and Openness = 30.71 ± 5.30. The regions in which the fALFF significantly correlated with the Big Five traits are shown in Table 1. Neuroticism correlated negatively with fALFF in the right middle frontal gyrus (BA6) and right precuneus (BA7) (Fig. 1A). There was no significant positive cor-
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Fig. 1. Regions in which fALFF was significantly correlated with (A) Neuroticism, (B) Extraversion, (C) Openness to experience, and (D) Conscientiousness. The blue color bar shows the t values for negative correlations and the red color bar shows the t values for positive correlations.
relation between fALFF and Neuroticism. Extraversion correlated positively with fALFF in the bilateral striatum (caudate and putamen), bilateral precuneus (BA7, 31), and right superior frontal gyrus (BA6, 10) (Fig. 1B). There was no significant negative correlation between fALFF and Extraversion. Openness correlated positively with the left thalamus and amygdala, and negatively with the right superior frontal gyrus (BA10) (Fig. 1C). Conscientiousness correlated positively with the bilateral middle frontal gyrus (BA6, 8) and negatively with the bilateral cerebellum (Fig. 1D). Agreeableness did not significantly correlate with fALFF in any brain region.
We tested the biological model for the Big Five traits by examining their relationship with the amplitude of spontaneous LFO during the resting state. We observed significant correlations between fALFF and four of the Big Five personality traits: Extraversion, Neuroticism, Openness, and Conscientiousness. These results partly supported the biological model for the Big Five traits. Individual differences in these personality traits were reflected in the amplitude of spontaneous LFO during the resting state. Neuroticism is considered to be related to punishment-related regions including the amygdala, anterior and middle cingulate
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cortices, medial prefrontal cortex, and hippocampus in the biological model for the Big Five traits [8,9]. However, we observed that Neuroticism was not correlated with such sensitivity to punishment-related regions, and was negatively correlated with the middle frontal gyrus and precuneus. This negative correlation between the precuneus and Neuroticism was in agreement with a previous fMRI study of anticipatory fear [20]. In addition, the precuneus plays a key role in emotional regulation by distancing an individual to emotional stimuli [19]. The relationship between the precuneus and Neuroticism may be modulated by a distancing strategy to emotional regulation. The negative correlation between Neuroticism and the dorsal premotor cortex (BA6) was also in agreement with previous studies [9,18]. Although the premotor cortex does not seem to be associated with emotional processing, the structural volume and regional activity of the premotor cortex has been reported to be correlated with Neuroticism [9,18]. Extraversion has been hypothesized to be associated with sensitivity to reward-related regions including the nucleus accumbens, amygdala, and orbitofrontal cortex in the biological model for the Big Five traits [9]. We observed that Extraversion was positively correlated with the striatum, dorsolateral prefrontal cortex, anterior prefrontal cortex, and precuneus. The nucleus accumbens is part of the striatum and is related to reward processing. The positive correlation between Extraversion and the striatum is consistent with the results of previous studies [14,18]. In addition, we also showed that Extraversion was positively correlated with the dorsolateral prefrontal cortex and precuneus, which regulate negative emotions, in contrast to Neuroticism. Therefore, we speculated that Extraversion was also associated with emotional regulation. We observed that Openness was positively correlated with the thalamus and amygdala, and negatively correlated with the right superior frontal gyrus, including the frontal pole (BA10). This result is not in agreement with the biological hypothesis for Openness, in which Openness is proposed to be associated with working memory, attention, and reasoning-related regions including the dorsolateral prefrontal cortex, anterior prefrontal cortex (frontal pole), and anterior parietal cortex [9]. The biological model for the Big Five traits emphasizes the intellectual and cognitive side of Openness, and this was partly confirmed in a previous study [10]; however, Openness is the most controversial trait and some researchers emphasize the unconventional, imaginative, and cultural side of Openness [17]. These inconsistencies may be the result of cultural differences in Openness or methodological differences; however, our findings indicate a specific ROI that can be tested in future studies. Conscientiousness is proposed to be associated with behavioral inhibition and constraining impulse-related regions, including the lateral prefrontal cortex, in the biological model for the Big Five traits. We observed that Conscientiousness was positively correlated with the bilateral middle frontal gyrus and negatively correlated with the bilateral cerebellum. Although this positive correlation between Conscientiousness and the middle frontal gyrus was in agreement with a previous study [9], our results show that the dorsal premotor cortex was primarily positively correlated with Conscientiousness. The dorsal premotor cortex has been regarded as a purely motor area, but accumulating evidence indicates that it plays a key role in working memory and executive function [1,15,24]. Conscientiousness is related to self-regulation, and high levels of Conscientiousness induce physical health and high job performance [12,16]. Conscientiousness may reflect the function of the dorsal premotor cortex in executive function. It is interesting that the fALFF of the right dorsal premotor cortex (BA6) was significantly correlated with Conscientiousness and Neuroticism, although in opposite directions. As described earlier, Neuroticism is defined as punishment sensitivity and emotional dysregulation, while Conscientiousness is defined as behavioral
inhibition and constraining impulsivity. That is, Neuroticism is related to a low ability of cognitive regulation and Conscientiousness is related to a high ability of cognitive regulation. We speculate that the activity of the dorsal premotor cortex reflects the level of cognitive regulation, which is closely related Neuroticism and Conscientiousness, although in opposite directions. In the biological model for the Big Five traits [9], Agreeableness is associated with the theory of mind and empathy-related regions, including the superior temporal sulcus, temporo-parietal junction, and posterior cingulate cortex. Agreeableness did not correlate to any region in our study with a relatively small sample size. To disclose the neural substrates of human personality traits using R-fMRI, a larger sample size may be needed [9]; however, our results showed a robust relationship between the Big Five traits and the amplitude of spontaneous LFO, and some of our results agreed with previous findings. We examined the relationships between the Big Five traits and the amplitude of spontaneous LFO using R-fMRI. Our results revealed the neural substrates of Extraversion, Neuroticism, Openness, and Conscientiousness in the amplitude of spontaneous LFO. Acknowledgments This work was supported by a Grant-in-Aid for Scientific Research (B) from the Ministry of Education, Culture, Sports, Science, and Technology of Japan. References [1] M. Abe, T. Hanakawa, Y. Takayama, C. Kuroki, S. Ogawa, H. Fukuyama, Functional coupling of human prefrontal and premotor areas during cognitive manipulation, J. Neurosci. 27 (2007) 3429–3438. [2] S. Asahi, Y. Okamoto, G. Okada, S. Yamawaki, N. Yokota, Negative correlation between right prefrontal activity during response inhibition and impulsiveness: a fMRI study, Eur. Arch. Psychiatry Clin. Neurosci. 254 (2004) 245–251. [3] B.B. Biswal, M. Mennes, X.N. Zuo, S. Gohel, C. Kelly, S.M. Smith, C.F. Beckmann, J.S. Adelstein, R.L. Buckner, S. Colcombe, A.M. Dogonowski, M. Ernst, D. Fair, M. Hampson, M.J. Hoptman, J.S. Hyde, V.J. Kiviniemi, R. Kotter, S.J. Li, C.P. Lin, M.J. Lowe, C. Mackay, D.J. Madden, K.H. Madsen, D.S. Margulies, H.S. Mayberg, K. McMahon, C.S. Monk, S.H. Mostofsky, B.J. Nagel, J.J. Pekar, S.J. Peltier, S.E. Petersen, V. Riedl, S.A. Rombouts, B. Rypma, B.L. Schlaggar, S. Schmidt, R.D. Seidler, G.J. Siegle, C. Sorg, G.J. Teng, J. Veijola, A. Villringer, M. Walter, L. Wang, X.C. Weng, S. Whitfield-Gabrieli, P. Williamson, C. Windischberger, Y.F. Zang, H.Y. Zhang, F.X. Castellanos, M.P. Milham, Toward discovery science of human brain function, Proc. Natl. Acad. Sci. U.S.A. 107 (2010) 4734–4739. [4] J.F. Costa, R.R. McCrae, Revised NEO Personality Inventory (NEO-PI) and NEO Five-Factor Inventory (NEO-FFI) Professional Manual, Psychological Assessment Resources, Odessa, FL, 1992. [5] C.L. Cox, K. Gotimer, A.K. Roy, F.X. Castellanos, M.P. Milham, C. Kelly, Your resting brain CAREs about your risky behavior, PLoS ONE 5 (2010) e12296. [6] T. Deckersbach, K.K. Miller, A. Klibanski, A. Fischman, D.D. Dougherty, M.A. Blais, D.B. Herzog, S.L. Rauch, Regional cerebral brain metabolism correlates of neuroticism and extraversion, Depress Anxiety 23 (2006) 133–138. [7] R.A. Depue, P.F. Collins, Neurobiology of the structure of personality: dopamine, facilitation of incentive motivation, and extraversion, Behav. Brain Sci. 22 (1999) 491–517. [8] C.G DeYoung, J.R. Gray, Personality neuroscience: explaining individual differences in affect, behavior and cognition, in: P.J. Corr, G. Matthews (Eds.), The Cambridge Handbook of Personality Psychology, Cambridge University Press, New York, 2009, pp. 323–346. [9] C.G. DeYoung, J.B. Hirsh, M.S. Shane, X. Papademetris, N. Rajeevan, J.R. Gray, Testing predictions from personality neuroscience: brain structure and the big five, Psychol. Sci. 21 (2010) 820–828. [10] C.G. DeYoung, N.A. Shamosh, A.E. Green, T.S. Braver, J.R. Gray, Intellect as distinct from openness: differences revealed by fMRI of working memory, J. Pers. Soc. Psychol. 97 (2009) 883–892. [11] M.D. Fox, M.E. Raichle, Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging, Nat. Rev. Neurosci. 8 (2007) 700–711. [12] R.D. Goodwin, H.S. Friedman, Health status and the five-factor personality traits in a nationally representative sample, J. Health Psychol. 11 (2006) 643–654. [13] J.A. Gray, N. McNaughton, The Neuropsychology of Anxiety, 2nd ed., Oxford University Press, New York, 2000. [14] T. Hahn, T. Dresler, A.C. Ehlis, M.M. Plichta, S. Heinzel, T. Polak, K.P. Lesch, F. Breuer, P.M. Jakob, A.J. Fallgatter, Neural response to reward anticipation is modulated by Gray’s impulsivity, Neuroimage 46 (2009) 1148–1153. [15] T. Hanakawa, M. Honda, N. Sawamoto, T. Okada, Y. Yonekura, H. Fukuyama, H. Shibasaki, The role of rostral Brodmann area 6 in mental-operation tasks: an integrative neuroimaging approach, Cereb. Cortex 12 (2002) 1157–1170.
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Contents lists available at ScienceDirect
Neuroscience Letters journal homepage: www.elsevier.com/locate/neulet
Personality traits and the amplitude of spontaneous low-frequency oscillations during resting state Yoshihiko Kunisato a,b , Yasumasa Okamoto a,c , Go Okada a,c , Shiori Aoyama a,c , Yoshiko Nishiyama a , Keiichi Onoda d , Shigeto Yamawaki a,c,∗ a Department of Psychiatry and Neurosciences, Division of Frontier Medical Science, Graduate School of Biomedical Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima 734-8551, Japan b Japan Society for the Promotion of Science, 8 Ichibancho, Chiyoda-ku 102-8472, Japan c Core Research for Evolutional Science and Technology, 5 Sanbancho, Chiyoda-ku 102-0075, Japan d Department of Neurology, Faculty of Medicine, Shimane University, 89-1 Enyacho, Izumo 693-8501, Japan
a r t i c l e
i n f o
Article history: Received 15 November 2010 Received in revised form 11 January 2011 Accepted 25 January 2011 Keywords: Personality Big Five model Resting-state fMRI Fractional amplitude of low-frequency fluctuation
a b s t r a c t Recently, neural substrates of the Big Five personality model were investigated using neuroimaging. We examined the relationships between the amplitude of spontaneous low-frequency oscillations (LFO) and the Big Five traits using resting-state functional magnetic resonance imaging (R-fMRI). Twenty-four healthy right-handed undergraduates (23.13 ± 1.87 years, 9 males and 15 females) participated in 5min R-fMRI and completed the NEO Five-Factor Inventory. We observed that Neuroticism correlated negatively with regional activity of the middle frontal gyrus and precuneus; Extraversion correlated positively with regional activity of the striatum, precuneus, and superior frontal gyrus; Openness correlated positively with the thalamus and amygdala, and negatively with the superior frontal gyrus; Conscientiousness correlated positively with regional activity of the middle frontal gyrus and correlated negatively with the cerebellum. Our results revealed the neural substrates of Extraversion, Neuroticism, Openness, and Conscientiousness in the amplitude of spontaneous LFO. © 2011 Elsevier Ireland Ltd. All rights reserved.
Personality psychology has clarified that human personality is described by five personality traits: Extraversion, Neuroticism, Agreeableness, Conscientiousness, and Openness to experience [4]. This model was called the Big Five Model and a great deal of research has been conducted on personality psychology. DeYoung and Gray [8] proposed a biological model for the Big Five traits, in which Extraversion was associated with sensitivity to rewardrelated regions: nucleus accumbens, amygdala, and orbitofrontal cortex [7,25]; Neuroticism was associated with sensitivity to punishment regions: amygdala, anterior and middle cingulate cortex, medial prefrontal cortex, and hippocampus [13]; Agreeableness was associated with the theory of mind and empathy-related regions, including the superior temporal sulcus, temporo-parietal junction, and posterior cingulate cortex [23,26]; Conscientiousness was associated with inhibiting and constraining impulse-related regions, including the lateral prefrontal cortex [2]; and Openness to experience was associated with working memory, attention, and
∗ Corresponding author at: Department of Psychiatry and Neurosciences, Division of Frontier Medical Science, Graduate School of Biomedical Sciences, Hiroshima University, 1-2-3, Kasumi, Minami-ku, Hiroshima 734-8551, Japan. Tel.: +81 82 257 5208; fax: +81 82 257 5209. E-mail address: [email protected] (S. Yamawaki). 0304-3940/$ – see front matter © 2011 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.neulet.2011.01.067
reasoning-related regions, including the dorsolateral prefrontal cortex, anterior prefrontal cortex (frontal pole), and anterior parietal cortex [10]. DeYoung et al. [9] examined the relationship between individual differences in brain structure and the Big Five traits and partly confirmed the validity of their biological model. Some studies examined the relationship between resting state brain activity and the Big Five traits using positron emission tomography (PET) and electroencephalography (EEG) [6,18,29]. Especially, Extraversion and Neuroticism were associated with activity in specific brain regions, and these results agree with the biological model for the Big Five traits. Recently, there has been a great deal of interest in spontaneous low-frequency oscillations (LFO) measured by resting-state functional magnetic resonance imaging (R-fMRI) [3,11]. R-fMRI can detect functional networks of spontaneous LFO in brain regions, including the posterior cingulate cortex (PCC), precuneus, lateral parietal cortex, and medial prefrontal cortex (MPFC). The fractional amplitude of low-frequency fluctuation (fALFF) is one of the measures of spontaneous LFO that has been detected with R-fMRI and its reliability has been verified over time [31,32]. As the amplitude of spontaneous LFO is detected robustly and reliably over time, it seems that individual differences of spontaneous LFO are associated with individual differences in human traits, including
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Y. Kunisato et al. / Neuroscience Letters 492 (2011) 109–113
Table 1 Regions in which fALFF correlated with the Big Five traits. Traits and predominant regions in cluster
Neuroticism Middle frontal gyrus Precuneus Extraversion Superior frontal gyrus Putamen and caudate Putamen Superior frontal gyrus Precuneus Precuneus Openness Superior frontal gyrus Thalamus and amygdala Agreeableness No region Conscientiousness Middle frontal gyrus Middle frontal gyrus Cerebellum and inferior temporal gyrus Cerebellum *
Side
BA
Voxels
Peak
Peak coordinates
Z-score
x
y
r z
R R
6 7
135 87
4.18 3.23
36 27
6 −45
54 42
−0.676* −0.676*
R R L R R L
10
219 291 170 195 73 84
4.33 4.23 3.98 3.79 3.65 3.38
21 18 −18 9 9 −9
57 12 18 24 −60 −54
15 −15 −9 66 54 21
0.666* 0.698* 0.681* 0.640* 0.561* 0.693*
6 7 31
R L
10
123 109
4.57 4.16
21 −15
63 −21
24 −3
−0.768* 0.711*
R L L R
6 8
176 79 121 167
4.64 3.41 4.50 3.73
51 −27 −51 15
0 33 −48 −72
54 54 −30 −30
0.669* 0.556* −0.779* −0.581*
p < 0.001.
personality and intelligence [11]. A few studies have examined the relationship between spontaneous LFO and IQ [28] or riskrelated personality [5]; however, no studies have investigated the relationship between the amplitude of spontaneous LFO and comprehensively measured personality on the basis of the Big Five model. This approach may contribute to the confirmation and elaboration of the biological model of personality or clarify individual differences in the amplitude of spontaneous LFO modulated by personality. In the present study, we investigated the relationships between fALFF and the Big Five traits using R-fMRI. Twenty-four healthy right-handed undergraduates (23.13 ± 1.87 years, range = 20–27 years, 9 males and 15 females) participated in the R-fMRI experiment. They gave informed written consent to participate in the experiment, which was conducted with the approval of the Ethics Committee of Hiroshima University. Trained psychiatrists and clinical psychologists interviewed each volunteer and screened them for previous psychiatric problems by using the MINI international neuropsychiatric interview [27]. We confirmed that no subjects had any previous psychiatric disorders, including mood or psychotic disorders or substance abuse. Before scanning, all participants completed the NEO Five Factor Inventory (NEO-FFI) [4,30] and the Japanese version of the National Adult Reading Test (NART) to assess their intellectual ability [21,22]. The NEO-FFI is a self-reported measure and consists of 60 items that assess the five personality factors of the Big Five model. Scanning took place on the GE Signa EXCITE HD 3.0T scanner (General Electric, Milwaukee, WI, USA) using an 8-channel brain array coil. Whole-brain 5-minute resting state fMRI scans were acquired with an echo-planar imaging sequence (TR = 2000 ms, TE = 27 ms, FA = 90◦ , matrix size = 64 × 64, FOV = 256 mm, 4 mm slice thickness, 32 slice, no gap, 150 acquisitions). Participants were instructed to close their eyes and remain awake. After the functional scan, anatomical images were acquired at 1 mm × 1 mm × 1 mm resolution (TR = 6.6 ms, TE = 1.4 ms, FA = 20◦ , matrix size = 256 × 256, FOV = 256 mm). The first 10 images were discarded to ensure steady-state MRI signals during acclimation of the subjects, and the subsequent 140 images were used for further analysis. Image preprocessing was carried out using Statistical Parametric Mapping (SPM8) software (Wellcome Department of Cognitive Neurology, London, UK). First, slice timing and head movement corrections were applied. After head movement correction, the values for translation and rotation
were obtained at each time point. All subjects had less than 1.5 mm maximum displacement in the x, y, and z axes and less than 1.5◦ angular motion during the scan. The images were then spatially normalized to the Montreal Neurological Institute functional template (resampling voxel size = 3 mm × 3 mm × 3 mm) and smoothed using an 8 mm FWHM Gaussian kernel. After preprocessing in SPM, the linear trend was removed and fALFF analysis was carried out using the resting-state fMRI data analysis toolkit (REST, http://restfmri.net/forum/) ver. 1.4. The analysis procedure for fALFF was carried out according to the method of Zou et al. [31,32]. For a time series in each voxel, the sum of amplitudes within a low frequency range (0.01–0.08 Hz) was calculated. The fALFF was then computed as the fractional sum of amplitudes within the low frequency range that was divided by the sum of amplitude across the entire frequency range (0–0.25 Hz) [32]. The subject-level voxel-wise fALFF maps were standardized into subject-level Z-score maps by subtracting the mean voxel-wise fALFF obtained for the entire brain and dividing by the standard deviation. We conducted a simple regression analysis to examine the correlation between the fALFF and the Big Five traits using SPM8. In this analysis, we included the IQ score estimated by the NART as a nuisance covariate to control for differences in intelligence. We conducted a Monte Carlo simulation to determine the combined threshold corresponding to a threshold of p < 0.05 (corrected) using AlphaSim (http://afni.nimh. nih.gov/pub/dist/doc/program help/AlphaSim.html). We then set significant correlations at the threshold of a voxel-wise p < 0.005 (uncorrected) that belonged to a cluster of activation with an extent of at least 66 voxels. Activated clusters were localized using Anatomical Automatic Labeling for SPM8 ver. 1 (http://www.cyceron.fr/web/aal anatomical automatic labeling.html). The average score for the Japanese version of NART was 112.82 (±5.82). The average NEO-FFI score showed an average profile: Neuroticism = 26.96 ± 6.08; Extraversion = 26.83 ± 4.84; Agreeableness = 30.17 ± 5.52: Conscientiousness = 24.92 ± 6.16; and Openness = 30.71 ± 5.30. The regions in which the fALFF significantly correlated with the Big Five traits are shown in Table 1. Neuroticism correlated negatively with fALFF in the right middle frontal gyrus (BA6) and right precuneus (BA7) (Fig. 1A). There was no significant positive cor-
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Fig. 1. Regions in which fALFF was significantly correlated with (A) Neuroticism, (B) Extraversion, (C) Openness to experience, and (D) Conscientiousness. The blue color bar shows the t values for negative correlations and the red color bar shows the t values for positive correlations.
relation between fALFF and Neuroticism. Extraversion correlated positively with fALFF in the bilateral striatum (caudate and putamen), bilateral precuneus (BA7, 31), and right superior frontal gyrus (BA6, 10) (Fig. 1B). There was no significant negative correlation between fALFF and Extraversion. Openness correlated positively with the left thalamus and amygdala, and negatively with the right superior frontal gyrus (BA10) (Fig. 1C). Conscientiousness correlated positively with the bilateral middle frontal gyrus (BA6, 8) and negatively with the bilateral cerebellum (Fig. 1D). Agreeableness did not significantly correlate with fALFF in any brain region.
We tested the biological model for the Big Five traits by examining their relationship with the amplitude of spontaneous LFO during the resting state. We observed significant correlations between fALFF and four of the Big Five personality traits: Extraversion, Neuroticism, Openness, and Conscientiousness. These results partly supported the biological model for the Big Five traits. Individual differences in these personality traits were reflected in the amplitude of spontaneous LFO during the resting state. Neuroticism is considered to be related to punishment-related regions including the amygdala, anterior and middle cingulate
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cortices, medial prefrontal cortex, and hippocampus in the biological model for the Big Five traits [8,9]. However, we observed that Neuroticism was not correlated with such sensitivity to punishment-related regions, and was negatively correlated with the middle frontal gyrus and precuneus. This negative correlation between the precuneus and Neuroticism was in agreement with a previous fMRI study of anticipatory fear [20]. In addition, the precuneus plays a key role in emotional regulation by distancing an individual to emotional stimuli [19]. The relationship between the precuneus and Neuroticism may be modulated by a distancing strategy to emotional regulation. The negative correlation between Neuroticism and the dorsal premotor cortex (BA6) was also in agreement with previous studies [9,18]. Although the premotor cortex does not seem to be associated with emotional processing, the structural volume and regional activity of the premotor cortex has been reported to be correlated with Neuroticism [9,18]. Extraversion has been hypothesized to be associated with sensitivity to reward-related regions including the nucleus accumbens, amygdala, and orbitofrontal cortex in the biological model for the Big Five traits [9]. We observed that Extraversion was positively correlated with the striatum, dorsolateral prefrontal cortex, anterior prefrontal cortex, and precuneus. The nucleus accumbens is part of the striatum and is related to reward processing. The positive correlation between Extraversion and the striatum is consistent with the results of previous studies [14,18]. In addition, we also showed that Extraversion was positively correlated with the dorsolateral prefrontal cortex and precuneus, which regulate negative emotions, in contrast to Neuroticism. Therefore, we speculated that Extraversion was also associated with emotional regulation. We observed that Openness was positively correlated with the thalamus and amygdala, and negatively correlated with the right superior frontal gyrus, including the frontal pole (BA10). This result is not in agreement with the biological hypothesis for Openness, in which Openness is proposed to be associated with working memory, attention, and reasoning-related regions including the dorsolateral prefrontal cortex, anterior prefrontal cortex (frontal pole), and anterior parietal cortex [9]. The biological model for the Big Five traits emphasizes the intellectual and cognitive side of Openness, and this was partly confirmed in a previous study [10]; however, Openness is the most controversial trait and some researchers emphasize the unconventional, imaginative, and cultural side of Openness [17]. These inconsistencies may be the result of cultural differences in Openness or methodological differences; however, our findings indicate a specific ROI that can be tested in future studies. Conscientiousness is proposed to be associated with behavioral inhibition and constraining impulse-related regions, including the lateral prefrontal cortex, in the biological model for the Big Five traits. We observed that Conscientiousness was positively correlated with the bilateral middle frontal gyrus and negatively correlated with the bilateral cerebellum. Although this positive correlation between Conscientiousness and the middle frontal gyrus was in agreement with a previous study [9], our results show that the dorsal premotor cortex was primarily positively correlated with Conscientiousness. The dorsal premotor cortex has been regarded as a purely motor area, but accumulating evidence indicates that it plays a key role in working memory and executive function [1,15,24]. Conscientiousness is related to self-regulation, and high levels of Conscientiousness induce physical health and high job performance [12,16]. Conscientiousness may reflect the function of the dorsal premotor cortex in executive function. It is interesting that the fALFF of the right dorsal premotor cortex (BA6) was significantly correlated with Conscientiousness and Neuroticism, although in opposite directions. As described earlier, Neuroticism is defined as punishment sensitivity and emotional dysregulation, while Conscientiousness is defined as behavioral
inhibition and constraining impulsivity. That is, Neuroticism is related to a low ability of cognitive regulation and Conscientiousness is related to a high ability of cognitive regulation. We speculate that the activity of the dorsal premotor cortex reflects the level of cognitive regulation, which is closely related Neuroticism and Conscientiousness, although in opposite directions. In the biological model for the Big Five traits [9], Agreeableness is associated with the theory of mind and empathy-related regions, including the superior temporal sulcus, temporo-parietal junction, and posterior cingulate cortex. Agreeableness did not correlate to any region in our study with a relatively small sample size. To disclose the neural substrates of human personality traits using R-fMRI, a larger sample size may be needed [9]; however, our results showed a robust relationship between the Big Five traits and the amplitude of spontaneous LFO, and some of our results agreed with previous findings. We examined the relationships between the Big Five traits and the amplitude of spontaneous LFO using R-fMRI. Our results revealed the neural substrates of Extraversion, Neuroticism, Openness, and Conscientiousness in the amplitude of spontaneous LFO. Acknowledgments This work was supported by a Grant-in-Aid for Scientific Research (B) from the Ministry of Education, Culture, Sports, Science, and Technology of Japan. References [1] M. Abe, T. Hanakawa, Y. Takayama, C. Kuroki, S. Ogawa, H. Fukuyama, Functional coupling of human prefrontal and premotor areas during cognitive manipulation, J. Neurosci. 27 (2007) 3429–3438. [2] S. Asahi, Y. Okamoto, G. Okada, S. Yamawaki, N. Yokota, Negative correlation between right prefrontal activity during response inhibition and impulsiveness: a fMRI study, Eur. Arch. Psychiatry Clin. Neurosci. 254 (2004) 245–251. [3] B.B. Biswal, M. Mennes, X.N. Zuo, S. Gohel, C. Kelly, S.M. Smith, C.F. Beckmann, J.S. Adelstein, R.L. Buckner, S. Colcombe, A.M. Dogonowski, M. Ernst, D. Fair, M. Hampson, M.J. Hoptman, J.S. Hyde, V.J. Kiviniemi, R. Kotter, S.J. Li, C.P. Lin, M.J. Lowe, C. Mackay, D.J. Madden, K.H. Madsen, D.S. Margulies, H.S. Mayberg, K. McMahon, C.S. Monk, S.H. Mostofsky, B.J. Nagel, J.J. Pekar, S.J. Peltier, S.E. Petersen, V. Riedl, S.A. Rombouts, B. Rypma, B.L. Schlaggar, S. Schmidt, R.D. Seidler, G.J. Siegle, C. Sorg, G.J. Teng, J. Veijola, A. Villringer, M. Walter, L. Wang, X.C. Weng, S. Whitfield-Gabrieli, P. Williamson, C. Windischberger, Y.F. Zang, H.Y. Zhang, F.X. Castellanos, M.P. Milham, Toward discovery science of human brain function, Proc. Natl. Acad. Sci. U.S.A. 107 (2010) 4734–4739. [4] J.F. Costa, R.R. McCrae, Revised NEO Personality Inventory (NEO-PI) and NEO Five-Factor Inventory (NEO-FFI) Professional Manual, Psychological Assessment Resources, Odessa, FL, 1992. [5] C.L. Cox, K. Gotimer, A.K. Roy, F.X. Castellanos, M.P. Milham, C. Kelly, Your resting brain CAREs about your risky behavior, PLoS ONE 5 (2010) e12296. [6] T. Deckersbach, K.K. Miller, A. Klibanski, A. Fischman, D.D. Dougherty, M.A. Blais, D.B. Herzog, S.L. Rauch, Regional cerebral brain metabolism correlates of neuroticism and extraversion, Depress Anxiety 23 (2006) 133–138. [7] R.A. Depue, P.F. Collins, Neurobiology of the structure of personality: dopamine, facilitation of incentive motivation, and extraversion, Behav. Brain Sci. 22 (1999) 491–517. [8] C.G DeYoung, J.R. Gray, Personality neuroscience: explaining individual differences in affect, behavior and cognition, in: P.J. Corr, G. Matthews (Eds.), The Cambridge Handbook of Personality Psychology, Cambridge University Press, New York, 2009, pp. 323–346. [9] C.G. DeYoung, J.B. Hirsh, M.S. Shane, X. Papademetris, N. Rajeevan, J.R. Gray, Testing predictions from personality neuroscience: brain structure and the big five, Psychol. Sci. 21 (2010) 820–828. [10] C.G. DeYoung, N.A. Shamosh, A.E. Green, T.S. Braver, J.R. Gray, Intellect as distinct from openness: differences revealed by fMRI of working memory, J. Pers. Soc. Psychol. 97 (2009) 883–892. [11] M.D. Fox, M.E. Raichle, Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging, Nat. Rev. Neurosci. 8 (2007) 700–711. [12] R.D. Goodwin, H.S. Friedman, Health status and the five-factor personality traits in a nationally representative sample, J. Health Psychol. 11 (2006) 643–654. [13] J.A. Gray, N. McNaughton, The Neuropsychology of Anxiety, 2nd ed., Oxford University Press, New York, 2000. [14] T. Hahn, T. Dresler, A.C. Ehlis, M.M. Plichta, S. Heinzel, T. Polak, K.P. Lesch, F. Breuer, P.M. Jakob, A.J. Fallgatter, Neural response to reward anticipation is modulated by Gray’s impulsivity, Neuroimage 46 (2009) 1148–1153. [15] T. Hanakawa, M. Honda, N. Sawamoto, T. Okada, Y. Yonekura, H. Fukuyama, H. Shibasaki, The role of rostral Brodmann area 6 in mental-operation tasks: an integrative neuroimaging approach, Cereb. Cortex 12 (2002) 1157–1170.
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