References
- Altinok, D. C. A., Rajkumar, R., Nießen, D., Sbaihat, H., Kersey, M., Shah, N. J., Veselinović, T., & Neuner, I. (2021). Common neurobiological correlates of resilience and personality traits within the triple resting-state brain networks assessed by 7-Tesla ultra-high field MRI. Scientific Reports, 11(1), 1–15. https://doi.org/https://doi.org/10.1038/s41598-021-91056-y
- Andrews-Hanna, J. R. (2012). The brain’s default network and its adaptive role in internal mentation. The Neuroscientist, 18(3), 251–270. https://doi.org/https://doi.org/10.1177/1073858411403316
- Andrews-Hanna, J. R., Smallwood, J., & Spreng, R. N. (2014). The default network and self-generated thought: Component processes, dynamic control, and clinical relevance. Annals of the New York Academy of Sciences, 1316(1), 29. https://doi.org/https://doi.org/10.1111/nyas.12360
- Başar-Eroglu, C., Başar, E., Demiralp, T., & Schürmann, M. (1992). P300-response: Possible psychophysiological correlates in delta and theta frequency channels. A review. International Journal of Psychophysiology, 13(2), 161–179. https://doi.org/https://doi.org/10.1016/0167-8760(92)90055-G
- Başar, E., Başar-Eroğlu, C., Karakaş, S., & Schürmann, M. (1999). Are cognitive processes manifested in event-related gamma, alpha, theta and delta oscillations in the EEG? Neuroscience Letters, 259(3), 165–168. https://doi.org/https://doi.org/10.1016/S0304-3940(98)00934-3
- Bressler, S. L., & Menon, V. (2010). Large-scale brain networks in cognition: Emerging methods and principles. Trends in Cognitive Sciences, 14(6), 277–290. https://doi.org/https://doi.org/10.1016/j.tics.2010.04.004
- Brizi, A., Mannetti, L., & Kruglanski, A. W. (2016). The closing of open minds: Need for closure moderates the impact of uncertainty salience on outgroup discrimination. British Journal of Social Psychology, 55(2), 244–262. https://doi.org/https://doi.org/10.1111/bjso.12131
- Cai, H., Zhu, J., & Yu, Y. (2020). Robust prediction of individual personality from brain functional connectome. Social Cognitive and Affective Neuroscience, 15(3), 359–369. https://doi.org/https://doi.org/10.1093/scan/nsaa044
- Canuet, L., Ishii, R., Pascual-Marqui, R. D., Iwase, M., Kurimoto, R., Aoki, Y., Ikeda, S., Takahashi, H., Nakahachi, T., Takeda, M., & Maurits, N. M. (2011). Resting-state EEG source localization and functional connectivity in schizophrenia-like psychosis of epilepsy. PloS one, 6(11), e27863. https://doi.org/https://doi.org/10.1371/journal.pone.0027863
- Cohen, M. X. (2011). Hippocampal-prefrontal connectivity predicts midfrontal oscillations and long-term memory performance. Current Biology, 21(22), 1900–1905. https://doi.org/https://doi.org/10.1016/j.cub.2011.09.036
- Cole, M. W., & Schneider, W. (2007). The cognitive control network: Integrated cortical regions with dissociable functions. Neuroimage, 37(1), 343–360. https://doi.org/https://doi.org/10.1016/j.neuroimage.2007.03.071
- Crowne, D. P., & Marlowe, D. (1960). A new scale of social desirability independent of psychopathology. Journal of Consulting Psychology, 24(4), 349. https://doi.org/https://doi.org/10.1037/h0047358
- Davey, J., Thompson, H. E., Hallam, G., Karapanagiotidis, T., Murphy, C., De Caso, I., Krieger-Redwood, K., Bernhardt, B. C., Smallwood, J., & Jefferies, E. (2016). Exploring the role of the posterior middle temporal gyrus in semantic cognition: Integration of anterior temporal lobe with executive processes. Neuroimage, 137, 165–177. https://doi.org/https://doi.org/10.1016/j.neuroimage.2016.05.051
- Dubois, J., Galdi, P., Han, Y., Paul, L. K., & Adolphs, R. (2018). Resting-state functional brain connectivity best predicts the personality dimension of openness to experience. Personality Neuroscience, 1, 1–21. https://doi.org/https://doi.org/10.1017/pen.2018.8
- Elton, A., & Gao, W. (2015). Task-positive functional connectivity of the default mode network transcends task domain. Journal of Cognitive Neuroscience, 27(12), 2369–2381. https://doi.org/https://doi.org/10.1162/jocn_a_00859
- Faul, F., Erdfelder, E., Buchner, A., & Lang, A. G. (2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41(4), 1149–1160. https://doi.org/https://doi.org/10.3758/BRM.41.4.1149
- Hampshire, A., Chamberlain, S. R., Monti, M. M., Duncan, J., & Owen, A. M. (2010). The role of the right inferior frontal gyrus: Inhibition and attentional control. Neuroimage, 50(3), 1313–1319. https://doi.org/https://doi.org/10.1016/j.neuroimage.2009.12.109
- Hata, M., Hayashi, N., Ishii, R., Canuet, L., Pascual-Marqui, R. D., Aoki, Y., Ikeda, S., Sakamoto, T., Iwata, M., Kimura, K., Iwase, M., Ikeda, M., & Ito, T. (2019). Short-term meditation modulates EEG activity in subjects with post-traumatic residual disabilities. Clinical Neurophysiology Practice, 4, 30–36. https://doi.org/https://doi.org/10.1016/j.cnp.2019.01.003
- Hata, M., Kazui, H., Tanaka, T., Ishii, R., Canuet, L., Pascual-Marqui, R. D., Aoki, Y., Ikeda, S., Kanemoto, H., Yoshiyama, K., Iwase, M., & Takeda, M. (2016). Functional connectivity assessed by resting state EEG correlates with cognitive decline of Alzheimer’s disease–An eLORETA study. Clinical Neurophysiology, 127(2), 1269–1278. https://doi.org/https://doi.org/10.1016/j.clinph.2015.10.030
- Imperatori, C., Brunetti, R., Farina, B., Speranza, A. M., Losurdo, A., Testani, E., Contardi, A., & Della Marca, G. (2014). Modification of EEG power spectra and EEG connectivity in autobiographical memory: A sLORETA study. Cognitive Processing, 15(3), 351–361. https://doi.org/https://doi.org/10.1007/s10339-014-0605-5
- Imperatori, C., Della Marca, G., Amoroso, N., Maestoso, G., Valenti, E. M., Massullo, C., Carbone, G. A., Contardi, A., & Farina, B. (2017). Alpha/Theta neurofeedback increases mentalization and default mode network connectivity in a non-clinical sample. Brain Topography, 30(6), 822–831. https://doi.org/https://doi.org/10.1007/s10548-017-0593-8
- Imperatori, C., Farina, B., Valenti, E. M., Di Poce, A., D’Ari, S., De Rossi, E., Murgia, C., Carbone, G. A., Massullo, C., & Della Marca, G. (2019). Is resting state frontal alpha connectivity asymmetry a useful index to assess depressive symptoms? A preliminary investigation in a sample of university students. Journal of Affective Disorders, 257, 152–159. https://doi.org/https://doi.org/10.1016/j.jad.2019.07.034
- Jann, K., Koenig, T., Dierks, T., Boesch, C., & Federspiel, A. (2010). Association of individual resting state EEG alpha frequency and cerebral blood flow. Neuroimage, 51(1), 365–372. https://doi.org/https://doi.org/10.1016/j.neuroimage.2010.02.024
- Jastorff, J., Clavagnier, S., Gergely, G., & Orban, G. A. (2011). Neural mechanisms of understanding rational actions: Middle temporal gyrus activation by contextual violation. Cerebral Cortex, 21(2), 318–329. https://doi.org/https://doi.org/10.1093/cercor/bhq098
- Kitaura, Y., Nishida, K., Yoshimura, M., Mii, H., Katsura, K., Ueda, S., Ikeda, S., Pascual-Marqui, R. D., Ishii, R., & Kinoshita, T. (2017). Functional localization and effective connectivity of cortical theta and alpha oscillatory activity during an attention task. Clinical Neurophysiology Practice, 2, 193–200. https://doi.org/https://doi.org/10.1016/j.cnp.2017.09.002
- Klimesch, W., Sauseng, P., & Hanslmayr, S. (2007). EEG alpha oscillations: The inhibition–timing hypothesis. Brain Research Reviews, 53(1), 63–88. https://doi.org/https://doi.org/10.1016/j.brainresrev.2006.06.003
- Knyazev, G. G. (2012). EEG delta oscillations as a correlate of basic homeostatic and motivational processes. Neuroscience and Biobehavioral Reviews, 36(1), 677–695. https://doi.org/https://doi.org/10.1016/j.neubiorev.2011.10.002
- Kossowska, M. (2007). The role of cognitive inhibition in motivation toward closure. Personality and Individual Differences, 42(6), 1117–1126. https://doi.org/https://doi.org/10.1016/j.paid.2006.09.026
- Kossowska, M., Czarnek, G., Wronka, E., Wyczesany, M., & Bukowski, M. (2014). Individual differences in epistemic motivation and brain conflict monitoring activity. Neuroscience Letters, 570, 38–41. https://doi.org/https://doi.org/10.1016/j.neulet.2014.04.002
- Kossowska, M., Czarnek, G., Wyczesany, M., Wronka, E., Szwed, P., & Bukowski, M. (2015). Electrocortical indices of attention correlate with the need for closure. NeuroReport, 26(5), 285–290. https://doi.org/https://doi.org/10.1097/WNR.0000000000000345
- Kossowska, M., Szwed, P., & Wyczesany, M. (2019). Motivational effects on brain activity: Need for closure moderates the impact of task uncertainty on engagement-related P3b. NeuroReport, 30(17), 1179–1183. https://doi.org/https://doi.org/10.1097/WNR.0000000000001334
- Kruglanski, A. W. (2013). The psychology of closed mindedness. Psychology Press.
- Kruglanski, A. W., Dechesne, M., Orehek, E., & Pierro, A. (2009). Three decades of lay epistemics: The why, how, and who of knowledge formation. European Review of Social Psychology, 20(1), 146–191. https://doi.org/https://doi.org/10.1080/10463280902860037
- Kruglanski, A. W., & Webster, D. M. (1996). Motivated closing of the mind:” Seizing” and” freezing.”. Psychological Review, 103(2), 263. https://doi.org/https://doi.org/10.1037/0033-295X.103.2.263
- Kruglanski, A. W., Webster, D. M., & Klem, A. (1993). Motivated resistance and openness to persuasion in the presence or absence of prior information. Journal of Personality and Social Psychology, 65(5), 861. https://doi.org/https://doi.org/10.1037/0022-3514.65.5.861
- Lamm, C., Fischmeister, F. P., & Bauer, H. (2005). Individual differences in brain activity during visuo-spatial processing assessed by slow cortical potentials and LORETA. Cognitive Brain Research, 25(3), 900–912. https://doi.org/https://doi.org/10.1016/j.cogbrainres.2005.09.025
- Leech, R., Braga, R., & Sharp, D. J. (2012). Echoes of the brain within the posterior cingulate cortex. Journal of Neuroscience, 32(1), 215–222. https://doi.org/https://doi.org/10.1523/JNEUROSCI.3689-11.2012
- Liakakis, G., Nickel, J., & Seitz, R. (2011). Diversity of the inferior frontal gyrus—a meta-analysis of neuroimaging studies. Behavioural Brain Research, 225(1), 341–347. https://doi.org/https://doi.org/10.1016/j.bbr.2011.06.022
- Liu, Q., Ganzetti, M., Wenderoth, N., & Mantini, D. (2018). Detecting large-scale brain networks using EEG: Impact of electrode density, head modeling and source localization. Frontiers in Neuroinformatics, 12(4), 12, 4. https://doi.org/https://doi.org/10.3389/fninf.2018.00004
- 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/https://doi.org/10.1016/j.tics.2011.08.003
- Miraglia, F., Vecchio, F., Bramanti, P., & Rossini, P. M. (2015). Small-worldness characteristics and its gender relation in specific hemispheric networks. Neuroscience, 310, 1–11. https://doi.org/https://doi.org/10.1016/j.neuroscience.2015.09.028
- Mizuhara, H., & Yamaguchi, Y. (2007). Human cortical circuits for central executive function emerge by theta phase synchronization. Neuroimage, 36(1), 232–244. https://doi.org/https://doi.org/10.1016/j.neuroimage.2007.02.026
- Moss, H., Abdallah, S., Fletcher, P., Bright, P., Pilgrim, L., Acres, K., & Tyler, L. (2005). Selecting among competing alternatives: Selection and retrieval in the left inferior frontal gyrus. Cerebral Cortex, 15(11), 1723–1735. https://doi.org/https://doi.org/10.1093/cercor/bhi049
- Mulert, C., Jager, L., Schmitt, R., Bussfeld, P., Pogarell, O., Moller, H. J., Juckel, G., & Hegerl, U. (2004). Integration of fMRI and simultaneous EEG: Towards a comprehensive understanding of localization and time-course of brain activity in target detection. Neuroimage, 22(1), 83–94. https://doi.org/https://doi.org/10.1016/j.neuroimage.2003.10.051
- Mussel, P., Ulrich, N., Allen, J. J., Osinsky, R., & Hewig, J. (2016). Patterns of theta oscillation reflect the neural basis of individual differences in epistemic motivation. Scientific Reports, 6(1), 1–10. https://doi.org/https://doi.org/10.1038/srep29245
- Nekovarova, T., Fajnerova, I., Horacek, J., & Spaniel, F. (2014). Bridging disparate symptoms of schizophrenia: A triple network dysfunction theory. Frontiers in Behavioral Neuroscience, 8, 171. https://doi.org/https://doi.org/10.3389/fnbeh.2014.00171
- Neuner, I., Arrubla, J., Werner, C. J., Hitz, K., Boers, F., Kawohl, W., Shah, N. J., & Chialvo, D. R. (2014). The default mode network and EEG regional spectral power: A simultaneous fMRI-EEG study. PloS one, 9(2), e88214. https://doi.org/https://doi.org/10.1371/journal.pone.0088214
- Nichols, T. E., & Holmes, A. P. (2002). Nonparametric permutation tests for functional neuroimaging: A primer with examples. Human Brain Mapping, 15(1), 1–25. https://doi.org/https://doi.org/10.1002/hbm.1058
- Niendam, T. A., Laird, A. R., Ray, K. L., Dean, Y. M., Glahn, D. C., & Carter, C. S. (2012). Meta-analytic evidence for a superordinate cognitive control network subserving diverse executive functions. Cognitive, Affective & Behavioral Neuroscience, 12(2), 241–268. https://doi.org/https://doi.org/10.3758/s13415-011-0083-5
- Nostro, A. D., Müller, V. I., Varikuti, D. P., Pläschke, R. N., Hoffstaedter, F., Langner, R., Patil, K. R., & Eickhoff, S. B. (2018). Predicting personality from network-based resting-state functional connectivity. Brain Structure & Function, 223(6), 2699–2719. https://doi.org/https://doi.org/10.1007/s00429-018-1651-z
- Olbrich, S., Tränkner, A., Chittka, T., Hegerl, U., & Schönknecht, P. (2014). Functional connectivity in major depression: Increased phase synchronization between frontal cortical EEG-source estimates. Psychiatry Research: Neuroimaging, 222(1–2), 91–99. https://doi.org/https://doi.org/10.1016/j.pscychresns.2014.02.010
- Palva, S., & Palva, J. M. (2011). Functional roles of alpha-band phase synchronization in local and large-scale cortical networks. Frontiers in Psychology, 2, 204. https://doi.org/https://doi.org/10.3389/fpsyg.2011.00204
- Panno, A., Carrus, G., Maricchiolo, F., & Mannetti, L. (2015). Cognitive reappraisal and pro‐environmental behavior: The role of global climate change perception. European Journal of Social Psychology, 45(7), 858–867. https://doi.org/https://doi.org/10.1002/ejsp.2162
- 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. Series A, Mathematical, Physical, and Engineering Sciences, 369(1952), 3768–3784. https://doi.org/https://doi.org/10.1098/rsta.2011.0081
- Pierro, A., & Kruglanski, A. W. (2006). Shortened need for closure scale. Rome, Italy: Sapienza University of Rome.
- Raichle, M. E. (2011). The restless brain. Brain Connectivity, 1(1), 3–12. https://doi.org/https://doi.org/10.1089/brain.2011.0019
- Raichle, M. E. (2015). The brain’s default mode network. Annual Review of Neuroscience, 38(1), 433–447. https://doi.org/https://doi.org/10.1146/annurev-neuro-071013-014030
- Reineberg, A. E., Andrews-Hanna, J. R., Depue, B. E., Friedman, N. P., & Banich, M. T. (2015). Resting-state networks predict individual differences in common and specific aspects of executive function. Neuroimage, 104, 69–78. https://doi.org/https://doi.org/10.1016/j.neuroimage.2014.09.045
- Roets, A., Kruglanski, A. W., Kossowska, M., Pierro, A., & Hong, Y.-Y. (2015). The motivated gatekeeper of our minds: New directions in need for closure theory and research. In Advances in experimental social psychology (Vol. 52, pp. 221–283). Elsevier. https://doi.org/https://doi.org/10.1016/bs.aesp.2015.01.001
- Roets, A., & Van Hiel, A. (2008). Why some hate to dilly-dally and others do not: The arousal-invoking capacity of decision-making for low-and high-scoring need for closure individuals. Social Cognition, 26(3), 333–346. https://doi.org/https://doi.org/10.1521/soco.2008.26.3.333
- Sadaghiani, S., Dombert, P. L., Løvstad, M., Funderud, I., Meling, T. R., Endestad, T., Knight, R. T., Solbakk, A.-K., & D’Esposito, M. (2019). Lesions to the fronto-parietal network impact alpha-band phase synchrony and cognitive control. Cerebral Cortex, 29(10), 4143–4153. https://doi.org/https://doi.org/10.1093/cercor/bhy296
- Sadaghiani, S., Scheeringa, R., Lehongre, K., Morillon, B., Giraud, A.-L., d’Esposito, M., & Kleinschmidt, A. (2012). Alpha-band phase synchrony is related to activity in the fronto-parietal adaptive control network. Journal of Neuroscience, 32(41), 14305–14310. https://doi.org/https://doi.org/10.1523/JNEUROSCI.1358-12.2012
- Sauseng, P., Klimesch, W., Schabus, M., & Doppelmayr, M. (2005). Fronto-parietal EEG coherence in theta and upper alpha reflect central executive functions of working memory. International Journal of Psychophysiology, 57(2), 97–103. https://doi.org/https://doi.org/10.1016/j.ijpsycho.2005.03.018
- Schumpe, B. M., Brizi, A., Giacomantonio, M., Panno, A., Kopetz, C., Kosta, M., & Mannetti, L. (2017). Need for cognitive closure decreases risk taking and motivates discounting of delayed rewards. Personality and Individual Differences, 107, 66–71. https://doi.org/https://doi.org/10.1016/j.paid.2016.11.039
- Seeley, W. W., Menon, V., Schatzberg, A. F., Keller, J., Glover, G. H., Kenna, H., Reiss, A. L., & Greicius, M. D. (2007). Dissociable intrinsic connectivity networks for salience processing and executive control. Journal of Neuroscience, 27(9), 2349–2356. https://doi.org/https://doi.org/10.1523/JNEUROSCI.5587-06.2007
- Shen, X., Finn, E. S., Scheinost, D., Rosenberg, M. D., Chun, M. M., Papademetris, X., & Constable, R. T. (2017). Using connectome-based predictive modeling to predict individual behavior from brain connectivity. Nature Protocols, 12(3), 506–518. https://doi.org/https://doi.org/10.1038/nprot.2016.178
- Smith, S. M., Vidaurre, D., Beckmann, C. F., Glasser, M. F., Jenkinson, M., Miller, K. L., Nichols, T. E., Robinson, E. C., Salimi-Khorshidi, G., Woolrich, M. W., Barch, D. M., Uğurbil, K., & Van Essen, D. C. (2013). Functional connectomics from resting-state fMRI. Trends in Cognitive Sciences, 17(12), 666–682. https://doi.org/https://doi.org/10.1016/j.tics.2013.09.016
- Sridharan, D., Levitin, D. J., & Menon, V. (2008). A critical role for the right fronto-insular cortex in switching between central-executive and default-mode networks. Proceedings of the National Academy of Sciences, 105(34), 12569–12574. https://doi.org/https://doi.org/10.1073/pnas.0800005105
- Srinivasan, R., Winter, W. R., Ding, J., & Nunez, P. L. (2007). EEG and MEG coherence: Measures of functional connectivity at distinct spatial scales of neocortical dynamics. The Journal of Neuroscience Methods, 166(1), 41–52. https://doi.org/https://doi.org/10.1016/j.jneumeth.2007.06.026
- Thatcher, R. W., North, D. M., & Biver, C. J. (2014). LORETA EEG phase reset of the default mode network. Frontiers in Human Neuroscience, 8, 529. https://doi.org/https://doi.org/10.3389/fnhum.2014.00529
- Thompson-Schill, S. L., Jonides, J., Marshuetz, C., Smith, E. E., D’Esposito, M., Kan, I. P., Knight, R. T., & Swick, D. (2002). Effects of frontal lobe damage on interference effects in working memory. Cognitive, Affective & Behavioral Neuroscience, 2(2), 109–120. https://doi.org/https://doi.org/10.3758/CABN.2.2.109
- Viola, V., Tosoni, A., Kruglanski, A. W., Galati, G., Mannetti, L., & Chialvo, D. R. (2014). Routes of motivation: Stable psychological dispositions are associated with dynamic changes in cortico-cortical functional connectivity. PloS one, 9(6), e98010. https://doi.org/https://doi.org/10.1371/journal.pone.0098010
- Wei, T., Liang, X., He, Y., Zang, Y., Han, Z., Caramazza, A., & Bi, Y. (2012). Predicting conceptual processing capacity from spontaneous neuronal activity of the left middle temporal gyrus. Journal of Neuroscience, 32(2), 481–489. https://doi.org/https://doi.org/10.1523/JNEUROSCI.1953-11.2012
- Wei, Z., Ruz, M., Zhao, Z., & Zheng, Y. (2015). Epistemic motivation affects the processing of negative emotional stimuli in interpersonal decisions. Frontiers in Psychology, 6, 1057. https://doi.org/https://doi.org/10.3389/fpsyg.2015.01057
- Whitton, A. E., Deccy, S., Ironside, M. L., Kumar, P., Beltzer, M., & Pizzagalli, D. A. (2018). Electroencephalography source functional connectivity reveals abnormal high-frequency communication among large-scale functional networks in depression. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 3(1), 50–58. https://doi.org/https://doi.org/10.1016/j.bpsc.2017.07.001
- Williams, M. N., Grajales, C. A. G., & Kurkiewicz, D. (2013). Assumptions of multiple regression: Correcting two misconceptions. Practical Assessment, Research, and Evaluation, 18(1), 11. https://doi.org/https://doi.org/10.7275/55hn-wk47
- Winkler, A. M., Webster, M. A., Brooks, J. C., Tracey, I., Smith, S. M., & Nichols, T. E. (2016). Non-parametric combination and related permutation tests for neuroimaging. Human Brain Mapping, 37(4), 1486–1511. https://doi.org/https://doi.org/10.1002/hbm.23115
- Zanto, T. P., & Gazzaley, A. (2013). Fronto-parietal network: Flexible hub of cognitive control. Trends in Cognitive Sciences, 17(12), 602–603. https://doi.org/https://doi.org/10.1016/j.tics.2013.10.001
- Zinn, M. L., Zinn, M. A., & Jason, L. A. (2016). Intrinsic functional hypoconnectivity in core neurocognitive networks suggests central nervous system pathology in patients with myalgic encephalomyelitis: A pilot study. Applied Psychophysiology and Biofeedback, 41(3), 283–300. https://doi.org/https://doi.org/10.1007/s10484-016-9331-3