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Research paper

Culture shapes spontaneous brain dynamics – Shared versus idiosyncratic neural features among Chinese versus Canadian subjects

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Pages 312-330 | Received 22 Apr 2022, Published online: 16 Nov 2023

References

  • Alahmadi, N., Evdokimov, S. A., Kropotov, Y. J., Müller, A. M., & Jäncke, L. (2016). Different resting state EEG features in children from Switzerland and Saudi Arabia. Frontiers in Human Neuroscience, 10, 559. https://doi.org/10.3389/fnhum.2016.00559
  • Bai, Y., Nakao, T., Xu, J., Qin, P., Chaves, P., Heinzel, A., Duncan, N., Lane, T., Yen, N.-S., Tsai, S.-Y., & Northoff, G. (2016). Resting state glutamate predicts elevated pre-stimulus alpha during self-relatedness: A combined EEG-MRS study on “rest-self overlap”. Social Neuroscience, 11(3), 249–263. https://doi.org/10.1080/17470919.2015.1072582
  • Bartko, J. J. (1966). The intraclass correlation coefficient as a measure of reliability. Psychological Reports, 19(1), 3–11. https://doi.org/10.2466/pr0.1966.19.1.3
  • Benjamini, Y., & Yekutieli, D. (2001). The control of the false discovery rate in multiple testing under dependency. The Annals of Statistics, 29(4), 1165–1188. https://doi.org/10.1214/aos/1013699998
  • Benwell, C. S., Coldea, A., Harvey, M., & Thut, G. (2021). Low pre‐stimulus EEG alpha power amplifies visual awareness but not visual sensitivity. European Journal of Neuroscience, 55(11–12), 3125–3140. https://doi.org/10.1111/ejn.15166
  • Benwell, C. S., Tagliabue, C. F., Veniero, D., Cecere, R., Savazzi, S., & Thut, G. (2017). Prestimulus EEG power predicts conscious awareness but not objective visual performance. Eneuro, 4(6), e0182–17. https://doi.org/10.1523/ENEURO.0182-17.2017
  • Brown, M. B., & Forsythe, A. B. (1974). Robust tests for the equality of variances. Journal of the American Statistical Association, 69(346), 364–367. https://doi.org/10.1080/01621459.1974.10482955
  • Buzsaki, G. (2006). Rhythms of the brain. Oxford University Press.
  • Buzsáki, G., Logothetis, N., & Singer, W. (2013). Scaling brain size, keeping timing: Evolutionary preservation of brain rhythms. Neuron, 80(3), 751–764. https://doi.org/10.1016/j.neuron.2013.10.002
  • Caceres, A., Hall, D. L., Zelaya, F. O., Williams, S. C., & Mehta, M. A. (2009). Measuring fMRI reliability with the intra-class correlation coefficient. Neuroimage, 45(3), 758–768. https://doi.org/10.1016/j.neuroimage.2008.12.035
  • Cai, H., Gao, Y., Sun, S., Li, N., Tian, F., Xiao, H., Li, J., Yang, Z., Li, X., Zhao, Q., Liu, Z., Yao, Z., Yang, M., Peng, H., Zhu, J., Zhang, X., Gao, G., Zheng, F., Li, R., Guo, Z., Ma, R. (2020). MODMA dataset: A Multi-modal Open Dataset for Mental-disorder Analysis. ArXiv Preprint ArXiv:2002.09283.
  • Carroll, G. R., & Harrison, J. R. (1998). Organizational demography and culture: Insights from a formal model and simulation. Administrative Science Quarterly, 43(3), 637–667. https://doi.org/10.2307/2393678
  • Chang, L., Mak, M. C., Li, T., Wu, B. P., Chen, B. B., & Lu, H. J. (2011). Cultural adaptations to environmental variability: An evolutionary account of East–west differences. Educational Psychology Review, 23(1), 99–129. https://doi.org/10.1007/s10648-010-9149-0
  • Chan, M. Y., Na, J., Agres, P. F., Savalia, N. K., Park, D. C., & Wig, G. S. (2018). Socioeconomic status moderates age-related differences in the brain’s functional network organization and anatomy across the adult lifespan. Proceedings of the National Academy of Sciences, 115(22), E5144–E5153. https://doi.org/10.1073/pnas.171402111
  • Chen, G., Taylor, P. A., Shin, Y.-W., Reynolds, R. C., & Cox, R. W. (2017). Untangling the relatedness among correlations, Part II: Inter-subject correlation group analysis through linear mixed-effects modeling. Neuroimage, 147, 825–840. https://doi.org/10.1016/j.neuroimage.2016.08.029
  • Chernyak, N., Kushnir, T., Sullivan, K. M., & Wang, Q. (2013). A Comparison of American and Nepalese children’s concepts of freedom of choice and social constraint. Cognitive Science, 37(7), 1343–1355. https://doi.org/10.1111/cogs.12046
  • Corcoran, A. W., Alday, P. M., Schlesewsky, M., & Bornkessel‐Schlesewsky, I. (2018). Toward a reliable, automated method of individual alpha frequency (IAF) quantification. Psychophysiology, 55(7), e13064. https://doi.org/10.1111/psyp.13064
  • Cui, L., Gong, X., Tang, Y., Kong, L., Chang, M., Geng, H., Xu, K., & Wang, F. (2016). Relationship between the LHPP gene polymorphism and resting-state brain activity in major depressive disorder. Neural Plasticity, 2016, 1–8. https://doi.org/10.1155/2016/9162590
  • De Bruin, D., van Baar, J. M., Rodríguez, P. L., & FeldmanHall, O. (2023). Shared neural representations and temporal segmentation of political content predict ideological similarity. Science Advances, 9(5), eabq5920. https://doi.org/10.1126/sciadv.abq5920
  • Delorme, A., & Makeig, S. (2004). EEGLAB: An open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. Journal of Neuroscience Methods, 134(1), 9–21. https://doi.org/10.1016/j.jneumeth.2003.10.009
  • Ding, J.-R., Liao, W., Zhang, Z., Mantini, D., Xu, Q., Wu, G.-R., Lu, G., & Chen, H. (2011). Topological fractionation of resting-state networks. PLoS One, 6(10), e26596. https://doi.org/10.1371/journal.pone.0026596
  • Dokmanic, I., Parhizkar, R., Ranieri, J., & Vetterli, M. (2015). Euclidean distance matrices: Essential theory, algorithms, and applications. IEEE Signal Processing Magazine, 32(6), 12–30. https://doi.org/10/10.1109/MSP.2015.2398954
  • Duncan, N. W., Hayes, D. J., Wiebking, C., Tiret, B., Pietruska, K., Chen, D. Q., Rainville, P., Marjańska, M., Ayad, O., Doyon, J., Hodaie, M., & Northoff, G. (2015). Negative childhood experiences alter a prefrontal-insular-motor cortical network in healthy adults: A preliminary multimodal rsfMRI-fMRI-MRS-dMRI study. Human Brain Mapping, 36(11), 4622–4637. https://doi.org/10.1002/hbm.22941
  • Feltz, C. J., & Miller, G. E. (1996). An asymptotic test for the equality of coefficients of variation from k populations. Statistics in Medicine, 15(6), 647–658. https://doi.org/10.1002/(SICI)1097-0258(19960330)15:6<647::AID-SIM184>3.0.CO;2-P
  • Fenigstein, A., Scheier, M. F., & Buss, A. H. (1975). Public and private self-consciousness: Assessment and theory. Journal of Consulting and Clinical Psychology, 43(4), 522–527. https://doi.org/10.1037/h0076760
  • Fisher, R. A. (1992). Statistical methods for research workers. In S. Kotz & N. L. Johnson (Eds.), Breakthroughs in statistics. Springer series in statistics (pp. 66–70). Springer. https://doi.org/10.1007/978-1-4612-4380-9_6
  • Fleiss, J. L., & Shrout, P. E. (1978). Approximate interval estimation for a certain intraclass correlation coefficient. Psychometrika, 43(2), 259–262. https://doi.org/10.1007/BF02293867
  • Foo, H., Mather, K. A., Jiang, J., Thalamuthu, A., Wen, W., & Sachdev, P. S. (2020). Genetic influence on ageing-related changes in resting-state brain functional networks in healthy adults: A systematic review. Neuroscience & Biobehavioral Reviews, 113, 98–110. https://doi.org/10.1016/j.neubiorev.2020.03.011
  • Fox, M. D., Snyder, A. Z., Vincent, J. L., Corbetta, M., Van Essen, D. C., & Raichle, M. E. (2005). The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proceedings of the National Academy of Sciences, 102(27), 9673–9678. https://doi.org/10.1073/pnas.0504136102
  • Frossard, J., & Renaud, O. (2019). permuco: Permutation Tests for Regression, (Repeated Measures) ANOVA/ANCOVA and Comparison of Signals (1.1.0) [Computer software]. https://CRAN.R-project.org/package=permuco
  • Gabard-Durnam, L. J., Mendez Leal, A. S., Wilkinson, C. L., & Levin, A. R. (2018). The Harvard Automated Processing Pipeline for Electroencephalography (HAPPE): Standardized processing software for developmental and high-artifact data. Frontiers in Neuroscience, 12, 97. https://doi.org/10.3389/fnins.2018.00097
  • Gelfand, M. J., Raver, J. L., Nishii, L., Leslie, L. M., Lun, J., Lim, B. C., Duan, L., Almaliach, A., Ang, S., Arnadottir, J., Aycan, Z., Boehnke, K., Boski, P., Cabecinhas, R., Chan, D., Chhokar, J., D’Amato, A. Subirats, M., Fischlmayr, I. C. (2011). Differences between tight and loose cultures: A 33-nation study. Science, 332(6033), 1100–1104. https://doi.org/10.1126/science.1197754
  • Han, S., & Ma, Y. (2014). Cultural differences in human brain activity: A quantitative meta-analysis. NeuroImage, 99, 293–300. https://doi.org/10.1016/j.neuroimage.2014.05.062
  • Hasson, U., Nir, Y., Levy, I., Fuhrmann, G., & Malach, R. (2004). Intersubject synchronization of cortical activity during natural vision. Science, 303(5664), 1634–1640. https://doi.org/10.1126/science.1089506
  • Heine, S. J. (2001). Self as cultural product: An examination of East Asian and North American selves. Journal of Personality, 69(6), 881–905. https://doi.org/10.1111/1467-6494.696168
  • Henrich, J., Heine, S. J., & Norenzayan, A. (2010). The weirdest people in the world? Behavioral and Brain Sciences, 33(2–3), 61–83. https://doi.org/10.1017/s0140525x0999152x
  • Hofstede, G. (1984). Culture’s consequences: International differences in work-related values (Vol. 5). Sage.
  • Hook, J. N., Worthington, E. L., Jr., & Utsey, S. O. (2009). Collectivism, forgiveness, and social harmony. The Counseling Psychologist, 37(6), 821–847. https://doi.org/10.1177/0011000008326546
  • Hou, Y., Song, B., Hu, Y., Pan, Y., & Hu, Y. (2020). The averaged inter-brain coherence between the audience and a violinist predicts the popularity of violin performance. NeuroImage, 211, 116655. https://doi.org/10.1016/j.neuroimage.2020.116655
  • Huang, Z., Obara, N., Davis, H. H., IV, Pokorny, J., & Northoff, G. (2016). The temporal structure of resting-state brain activity in the medial prefrontal cortex predicts self-consciousness. Neuropsychologia, 82, 161–170. https://doi.org/10.1016/j.neuropsychologia.2016.01.025
  • Ishii, K., Miyamoto, Y., Rule, N. O., & Toriyama, R. (2014). Physical objects as vehicles of cultural transmission: Maintaining harmony and uniqueness through colored geometric patterns. Personality and Social Psychology Bulletin, 40(2), 175–188. https://doi.org/10.1177/0146167213508151
  • Kim, H., & Markus, H. R. (1999). Deviance or uniqueness, harmony or conformity? A cultural analysis. Journal of Personality and Social Psychology, 77(4), 785–800. https://doi.org/10.1037/0022-3514.77.4.785
  • Kitayama, S., Park, H., Sevincer, A. T., Karasawa, M., & Uskul, A. K. (2009). A cultural task analysis of implicit independence: Comparing North America, Western Europe, and East Asia. Journal of Personality and Social Psychology, 97(2), 236–255. https://doi.org/10.1037/a0015999
  • Kitayama, S., Yu, Q., King, A. P., Yoon, C., & Liberzon, I. (2020). The gray matter volume of the temporoparietal junction varies across cultures: A moderating role of the dopamine D4 receptor gene (DRD4). Social Cognitive and Affective Neuroscience, 15(2), 193–202. https://doi.org/10.1093/scan/nsaa032
  • Klimesch, W. (2012). α-band oscillations, attention, and controlled access to stored information. Trends in Cognitive Sciences, 16(12), 606–617. https://doi.org/10.1016/j.tics.2012.10.007
  • Knyazev, G. G., Savostyanov, A. N., Bocharov, A. V., & Merkulova, E. A. (2018). Resting state connectivity mediates the relationship between collectivism and social cognition. International Journal of Psychophysiology, 123, 17–24. https://doi.org/10.1016/j.ijpsycho.2017.12.002
  • Knyazev, G. G., Savostyanov, A. N., Volf, N. V., Liou, M., & Bocharov, A. V. (2012). EEG correlates of spontaneous self-referential thoughts: A cross-cultural study. International Journal of Psychophysiology, 86(2), 173–181. https://doi.org/10.1016/j.ijpsycho.2012.09.002
  • Kolvoort, I. R., Wainio‐Theberge, S., Wolff, A., & Northoff, G. (2020). Temporal integration as “common currency” of brain and self - scale-free activity in resting-state EEG correlates with temporal delay effects on self-relatedness. Human Brain Mapping, 41(15), 4355–4374. https://doi.org/10.1002/hbm.25129
  • Koopmans, L. H., Owen, D. B., & Rosenblatt, J. I. (1964). Confidence intervals for the coefficient of variation for the normal and log normal distributions. Biometrika, 51(1–2), 25–32. https://doi.org/10.1093/biomet/51.1-2.25
  • Kothe, C. A. E., & Jung, T.-P. (2016). Artifact removal techniques with signal reconstruction. WO-2015047462-A3. https://patents.google.com/patent/WO2015047462A3
  • Kraus, B., Salvador, C. E., Kamikubo, A., Hsiao, N.-C., Hu, J.-F., Karasawa, M., & Kitayama, S. (2021). Oscillatory alpha power at rest reveals an independent self: A cross-cultural investigation. Biological Psychology, 163, 108118. https://doi.org/10.1016/j.biopsycho.2021.108118
  • Li, L., Huang, X., Xiao, J., Zheng, Q., Shan, X., He, C., Liao, W., Chen, H., Menon, V., & Duan, X. (2022). Neural synchronization predicts marital satisfaction. Proceedings of the National Academy of Sciences, 119(34), e2202515119. https://doi.org/10.1073/pnas.2202515119
  • Liu, W., Kohn, N., & Fernández, G. (2019). Intersubject similarity of personality is associated with intersubject similarity of brain connectivity patterns. Neuroimage, 186, 56–69. https://doi.org/10.1016/j.neuroimage.2018.10.062
  • Lu, S., Gao, W., Wei, Z., Wang, D., Hu, S., Huang, M., Xu, Y., & Li, L. (2017). Intrinsic brain abnormalities in young healthy adults with childhood trauma: A resting-state functional magnetic resonance imaging study of regional homogeneity and functional connectivity. Australian & New Zealand Journal of Psychiatry, 51(6), 614–623. https://doi.org/10.1177/0004867416671
  • Luo, S., Zhu, Y., Fan, L., Gao, D., & Han, S. (2020). Resting-state brain network properties mediate the association between the oxytocin receptor gene and interdependence. Social Neuroscience, 15(3), 296–310. https://doi.org/10.1080/17470919.2020.1714718
  • Maguire, M. J., & Schneider, J. M. (2019). Socioeconomic status related differences in resting state EEG activity correspond to differences in vocabulary and working memory in grade school. Brain and Cognition, 137, 103619. https://doi.org/10.1016/j.bandc.2019.103619
  • Mantini, D., Perrucci, M. G., Del Gratta, C., Romani, G. L., & Corbetta, M. (2007). Electrophysiological signatures of resting state networks in the human brain. Proceedings of the National Academy of Sciences, 104(32), 13170–13175. https://doi.org/10.1073/pnas.0700668104
  • Markus, H. R., & Kitayama, S. (1991). Culture and the self: Implications for cognition, emotion, and motivation. Psychological Review, 98(2), 224–253. https://doi.org/10.1037/0033-295x.98.2.224
  • Mars, R. B., Neubert, F.-X., Noonan, M. P., Sallet, J., Toni, I., & Rushworth, M. F. (2012). On the relationship between the “default mode network” and the “social brain”. Frontiers in Human Neuroscience, 6, 189. https://doi.org/10.3389/fnhum.2012.00189
  • Marwick, B., & Krishnamoorthy, K. (2019). Cvequality: Tests for the equality of coefficients of variation from multiple groups (0.2.0) [Computer software]. https://CRAN.R-project.org/package=cvequality
  • Matz, S. C., Hyon, R., Baek, E. C., Parkinson, C., & Cerf, M. (2022). Personality similarity predicts synchronous neural responses in fMRI and EEG data. Scientific Reports, 12(1), 14325. https://doi.org/10.1038/s41598-022-18237-1
  • Menon, V. (2011). Large-scale brain networks and psychopathology: A unifying triple network model. Trends in Cognitive Sciences, 15(10), 483–506. https://doi.org/10.1016/j.tics.2011.08.003
  • Mesoudi, A., Chang, L., Murray, K., & Lu, H. J. (2015). Higher frequency of social learning in China than in the West shows cultural variation in the dynamics of cultural evolution. Proceedings of the Royal Society Series B: Biological Sciences, 282(1798), 20142209. https://doi.org/10.1098/rspb.2014.2209
  • Murray, R. J., Debbané, M., Fox, P. T., Bzdok, D., & Eickhoff, S. B. (2015). Functional connectivity mapping of regions associated with self‐and other‐processing. Human Brain Mapping, 36(4), 1304–1324. https://doi.org/10.1002/hbm.22703
  • Nastase, S. A., Gazzola, V., Hasson, U., & Keysers, C. (2019). Measuring shared responses across subjects using intersubject correlation. Social Cognitive and Affective Neuroscience, 14(6), 667–685. https://doi.org/10.1093/scan/nsz037
  • Nguyen, M., Vanderwal, T., & Hasson, U. (2019). Shared understanding of narratives is correlated with shared neural responses. NeuroImage, 184, 161–170. https://doi.org/10.1016/j.neuroimage.2018.09.010
  • Northoff, G. (2012). Immanuel Kant’s mind and the brain’s resting state. Trends in Cognitive Sciences, 16(7), 356–359. https://doi.org/10.1016/j.tics.2012.06.001
  • Northoff, G. (2013a). Unlocking the brain: Volume 1: Coding. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199826988.001.0001
  • Northoff, G. (2013b). Unlocking the brain: Volume 2: Consciousness. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199826995.001.0001
  • Northoff, G. (2016). Is the self a higher-order or fundamental function of the brain? The “basis model of self-specificity” and its encoding by the brain’s spontaneous activity. Cognitive Neuroscience, 7(1–4), 203–222. https://doi.org/10.1080/17588928.2015.1111868
  • Northoff, G. (2018). The spontaneous brain: From the mind-body to the world-brain problem. MIT Press.
  • Northoff, G. (2021). 4 Embrainment and enculturation: Culture, brain, and self. In J. Y. Chiao, S. Li, R. Turner, S. Y. Lee-Tauler, & B. A. Pringle (Eds.), The oxford handbook of cultural neuroscience and global mental health (pp. 75–96). Oxford University Press.
  • Northoff, G., Heinzel, A., de Greck, M., Bermpohl, F., Dobrowolny, H., & Panksepp, J. (2006). Self-referential processing in our brain—A meta-analysis of imaging studies on the self. NeuroImage, 31(1), 440–457. https://doi.org/10.1016/j.neuroimage.2005.12.002
  • Northoff, G., Wainio-Theberge, S., & Evers, K. (2020). Is temporo-spatial dynamics the “common currency” of brain and mind? In Quest of “Spatiotemporal Neuroscience”. Physics of Life Reviews, 33, 34–54. https://doi.org/10.1016/j.plrev.2019.05.002
  • Northoff, G., & Zilio, F. (2022). Temporo-spatial theory of consciousness (TTC) – bridging the gap of neuronal activity and phenomenal states. Behavioural Brain Research, 424, 113788. https://doi.org/10.1016/j.bbr.2022.113788
  • Oostenveld, R., Fries, P., Maris, E., & Schoffelen, J.-M. (2011). FieldTrip: Open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data. Computational Intelligence and Neuroscience, 2011, 156869. https://doi.org/10.1155/2011/156869
  • Ouyang, G., Hildebrandt, A., Schmitz, F., & Herrmann, C. S. (2020). Decomposing alpha and 1/f brain activities reveals their differential associations with cognitive processing speed. NeuroImage, 205, 116304. https://doi.org/10.1016/j.neuroimage.2019.116304
  • Parkinson, C., Kleinbaum, A. M., & Wheatley, T. (2018). Similar neural responses predict friendship. Nature Communications, 9(1), 332. https://doi.org/10.1038/s41467-017-02722-7
  • Pascual-Marqui, R. D., Lehmann, D., Koukkou, M., Kochi, K., Anderer, P., Saletu, B., Tanaka, H., Hirata, K., John, E. R., Prichep, L., Biscay-Lirio, R., & Kinoshita, T. (2011). Assessing interactions in the brain with exact low-resolution electromagnetic tomography. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 369(1952), 3768–3784. https://doi.org/10.1098/rsta.2011.0081
  • Pei, L., Zhou, X., Leung, F. K. S., & Ouyang, G. (2023). Differential associations between scale-free neural dynamics and different levels of cognitive ability. Psychophysiology, 60(6), e14259. https://doi.org/10.1111/psyp.14259
  • Qin, P., Wang, M., & Northoff, G. (2020). Linking bodily, environmental and mental states in the self—A three-level model based on a meta-analysis. Neuroscience & Biobehavioral Reviews, 115, 77–95. https://doi.org/10.1016/j.neubiorev.2020.05.004
  • Raichle, M. E. (2015). The restless brain: How intrinsic activity organizes brain function. Philosophical Transactions of the Royal Society B: Biological Sciences, 370(1668), 20140172. https://doi.org/10.1098/rstb.2014.0172
  • Ramphal, B., Whalen, D. J., Kenley, J. K., Yu, Q., Smyser, C. D., Rogers, C. E., & Sylvester, C. M. (2020). Brain connectivity and socioeconomic status at birth and externalizing symptoms at age 2 years. Developmental Cognitive Neuroscience, 45, 100811. https://doi.org/10.1016/j.dcn.2020.100811
  • Ramsay, I. S., Lynn, P. A., Schermitzler, B., & Sponheim, S. R. (2021). Individual alpha peak frequency is slower in schizophrenia and related to deficits in visual perception and cognition. Scientific Reports, 11(1), 17852. https://doi.org/10.1038/s41598-021-00055-6
  • Reinero, D. A., Dikker, S., & Van Bavel, J. J. (2021). Inter-brain synchrony in teams predicts collective performance. Social Cognitive and Affective Neuroscience, 16(1–2), 43–57. https://doi.org/10.1093/scan/nsaa135
  • Richiardi, J., Altmann, A., Milazzo, A.-C., Chang, C., Chakravarty, M. M., Banaschewski, T., Barker, G. J., Bokde, A. L., Bromberg, U., Büchel, C., Conrod, P., Fauth-Bühler, M., Flor, H., Frouin, V., Gallinat, J., Garavan, H., Gowland, P., Heinz, A., Lemaître, H., Mann, K. F. (2015). Correlated gene expression supports synchronous activity in brain networks. Science, 348(6240), 1241–1244. https://doi.org/10.1126/science.1255905
  • Saha, S., & Baumert, M. (2020). Intra-and inter-subject variability in EEG-based sensorimotor brain computer interface: A review. Frontiers in Computational Neuroscience, 13, 87. https://doi.org/10.3389/fncom.2019.00087
  • Salkind, N. (2010). Encyclopedia of Research design. SAGE. https://doi.org/10.4135/9781412961288
  • Sampedro-Piquero, P., Álvarez-Suárez, P., Moreno-Fernández, R. D., García-Castro, G., Cuesta, M., & Begega, A. (2018). Environmental enrichment results in both brain connectivity efficiency and selective improvement in different behavioral tasks. Neuroscience, 388, 374–383. https://doi.org/10.1016/j.neuroscience.2018.07.036
  • Sarkar, S., Jun, S., Rellick, S., Quintana, D. D., Cavendish, J. Z., & Simpkins, J. W. (2016). Expression of microRNA-34a in Alzheimer’s disease brain targets genes linked to synaptic plasticity, energy metabolism, and resting state network activity. Brain Research, 1646, 139–151. https://doi.org/10.1016/j.brainres.2016.05.026
  • Scalabrini, A., Ebisch, S. J., Huang, Z., DiPlinio, S., Perrucci, M. G., Romani, G. L., Mucci, C., & Northoff, G. (2019). Spontaneous brain activity predicts task-evoked activity during animate versus inanimate touch. Cerebral Cortex, 29(11), 4628–4645. https://doi.org/10.1093/cercor/bhy340
  • Scheier, M. F., & Carver, C. S. (1985). The self‐Consciousness Scale: A revised version for use with general populations. Journal of Applied Social Psychology, 15(8), 687–699. https://doi.org/10.1111/j.1559-1816.1985.tb02268.x
  • Schultz, B. B. (1985). Levene’s test for relative variation. Systematic Biology, 34(4), 449–456. https://doi.org/10.1093/sysbio/34.4.449
  • Seghier, M. L., & Price, C. J. (2018). Interpreting and utilising intersubject variability in brain function. Trends in Cognitive Sciences, 22(6), 517–530. https://doi.org/10.1016/j.tics.2018.03.003
  • Singelis, T. M. (1994). The measurement of independent and interdependent self-construals. Personality and Social Psychology Bulletin, 20(5), 580–591. https://doi.org/10.1177/0146167294205014
  • Singelis, T. M., Triandis, H., Bhawuk, D. P., & Gelfand, M. J. (1995). Horizontal and vertical dimensions of individualism and collectivism: A theoretical and measurement refinement. Cross-Cultural Research, 29(3), 240–275. https://doi.org/10.1177/106939719502900302
  • Smulders, F. T., Ten Oever, S., Donkers, F. C., Quaedflieg, C. W., & Van de Ven, V. (2018). Single‐trial log transformation is optimal in frequency analysis of resting EEG alpha. European Journal of Neuroscience, 48(7), 2585–2598. https://doi.org/10.1111/ejn.13854
  • Spreng, R. N., & Andrews-Hanna, J. R. (2015). The default network and social cognition. Brain Mapping: An Encyclopedic Reference, 1316, 165–169. https://doi.org/10.1016/B978-0-12-397025-1.00173-1
  • Spreng, R. N., Dimas, E., Mwilambwe-Tshilobo, L., Dagher, A., Koellinger, P., Nave, G., Ong, A., Kernbach, J. M., Wiecki, T. V., Ge, T., Li, Y., Holmes, A. J., Yeo, B. T., Turner, G. R., Dunbar, R. I., & Bzdok, D. (2020). The default network of the human brain is associated with perceived social isolation. Nature Communications, 11(1), 6393. https://doi.org/10.1038/s41467-020-20039-w
  • Sugimura, K., Iwasa, Y., Kobayashi, R., Honda, T., Hashimoto, J., Kashihara, S., Zhu, J., Yamamoto, K., Kawahara, T., Anno, M., Nakagawa, R., Hatano, K., & Nakao, T. (2021). Association between long-range temporal correlations in intrinsic EEG activity and subjective sense of identity. Scientific Reports, 11(1), 422. https://doi.org/10.1038/s41598-020-79444-2
  • Teeuw, J., Brouwer, R. M., Guimarães, J. P., Brandner, P., Koenis, M. M., Swagerman, S. C., Verwoert, M., Boomsma, D. I., & Pol, H. E. H. (2019). Genetic and environmental influences on functional connectivity within and between canonical cortical resting-state networks throughout adolescent development in boys and girls. NeuroImage, 202, 116073. https://doi.org/10.1016/j.neuroimage.2019.116073
  • Tilman, D. (2000). Causes, consequences and ethics of biodiversity. Nature, 405(6783), 208–211. https://doi.org/10.1038/35012217
  • Tooley, U. A., Mackey, A. P., Ciric, R., Ruparel, K., Moore, T. M., Gur, R. C., Gur, R. E., Satterthwaite, T. D., & Bassett, D. S. (2020). Associations between neighborhood SES and functional brain network development. Cerebral Cortex, 30(1), 1–19. https://doi.org/10.1093/cercor/bhz066
  • Torelli, C. J. (2006). Individuality or conformity? The effect of independent and interdependent self-concepts on public judgments. Journal of Consumer Psychology, 16(3), 240–248. https://doi.org/10.1207/s15327663jcp1603_6
  • Triandis, H. (1988). Collectivism v. Individualism: A reconceptualisation of a basic concept in cross-cultural social psychology. In G. K. Verma & C. Bagley (Eds.), Cross-cultural studies of personality, attitudes and cognition (pp. 60–95). Macmillan Press. https://doi.org/10.1007/978-1-349-08120-2_3
  • Triandis, H. (1993). Collectivism and individualism as cultural Syndromes. Cross-Cultural Research, 27(3–4), 155–180. https://doi.org/10.1177/106939719302700301
  • Uddin, L. Q. (2020). Bring the noise: Reconceptualizing spontaneous neural activity. Trends in Cognitive Sciences, 24(9), 734–746. https://doi.org/10.1016/j.tics.2020.06.003
  • Van Dam, W. O., Decker, S. L., Durbin, J. S., Vendemia, J. M. C., & Desai, R. H. (2015). Resting state signatures of domain and demand-specific working memory performance. NeuroImage, 118, 174–182. https://doi.org/10.1016/j.neuroimage.2015.05.017
  • Van Essen, D. C., Glasser, M. F., Dierker, D. L., Harwell, J., & Coalson, T. (2012). Parcellations and hemispheric asymmetries of human cerebral cortex analyzed on surface-based atlases. Cerebral Cortex, 22(10), 2241–2262. https://doi.org/10.1093/cercor/bhr291
  • Wang, G.-Z., Belgard, T. G., Mao, D., Chen, L., Berto, S., Preuss, T. M., Lu, H., Geschwind, D. H., & Konopka, G. (2015). Correspondence between resting-state activity and brain gene expression. Neuron, 88(4), 659–666. https://doi.org/10.1016/j.neuron.2015.10.022
  • Wang, C., Oyserman, D., Liu, Q., Li, H., & Han, S. (2013). Accessible cultural mind-set modulates default mode activity: Evidence for the culturally situated brain. Social Neuroscience, 8(3), 203–216. https://doi.org/10.1080/17470919.2013.775966
  • Welch, P. (1967). The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms. IEEE Transactions on Audio and Electroacoustics, 15(2), 70–73. https://doi.org/10.1109/TAU.1967.1161901
  • Wens, V., Bourguignon, M., Goldman, S., Marty, B., De Beeck, M. O., Clumeck, C., Mary, A., Peigneux, P., Van Bogaert, P., Brookes, M. J., & De Tiège, X. (2014). Inter-and intra-subject variability of neuromagnetic resting state networks. Brain Topography, 27(5), 620–634. https://doi.org/10.1007/s10548-014-0364-8
  • Winkler, I., Haufe, S., & Tangermann, M. (2011). Automatic classification of artifactual ICA-Components for artifact removal in EEG signals. Behavioral and Brain Functions, 7(1), 30. https://doi.org/10.1186/1744-9081-7-30
  • Wolff, A., de la Salle, S., Sorgini, A., Lynn, E., Blier, P., Knott, V., & Northoff, G. (2019). Atypical temporal dynamics of resting state shapes stimulus-evoked activity in depression—an EEG study on rest–stimulus interaction. Frontiers in Psychiatry, 10, 719. https://doi.org/10.3389/fpsyt.2019.00719
  • Wolff, A., DiGiovanni, D. A., Gómez‐Pilar, J., Nakao, T., Huang, Z., Longtin, A., & Northoff, G. (2019). The temporal signature of self: Temporal measures of resting‐state EEG predict self‐consciousness. Human Brain Mapping, 40(3), 789–803. https://doi.org/10.1002/hbm.24412
  • Yeshurun, Y., Nguyen, M., & Hasson, U. (2021). The default mode network: Where the idiosyncratic self meets the shared social world. Nature Reviews Neuroscience, 22(3), 181–192. https://doi.org/10.1038/s41583-020-00420-w
  • Yu, K., Guo, G.-D., Li, J., & Lin, S. (2020). Quantum algorithms for similarity measurement based on Euclidean distance. International Journal of Theoretical Physics, 59(10), 3134–3144. https://doi.org/10.1007/s10773-020-04567-1
  • Zhang, W., Andrews-Hanna, J. R., Mair, R. W., Goh, J. O. S., & Gutchess, A. (2022). Functional connectivity with medial temporal regions differs across cultures during post-encoding rest. Cognitive, Affective, & Behavioral Neuroscience, 22(6), 1334–1348. https://doi.org/10.3758/s13415-022-01027-7
  • Zhang, J., Huang, Z., Tumati, S., & Northoff, G. (2020). Rest-task modulation of fMRI-derived global signal topography is mediated by transient coactivation patterns. PLoS Biology, 18(7), e3000733. https://doi.org/10.1371/journal.pbio.3000733
  • Zilio, F., Gomez-Pilar, J., Cao, S., Zhang, J., Zang, D., Qi, Z., Tan, J., Hiromi, T., Wu, X., Fogel, S., Huang, Z., Hohmann, M. R., Fomina, T., Synofzik, M., Grosse-Wentrup, M., Owen, A. M., & Northoff, G. (2021). Are intrinsic neural timescales related to sensory processing? Evidence from abnormal behavioral states. NeuroImage, 226, 117579. https://doi.org/10.1016/j.neuroimage.2020.117579

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