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Quiza-Montealegre, J. J., Quintero-Zea, A., Trujillo, N., & López, J. D. (2024). Análisis de conectividad funcional del prejuicio entre antiguos actores del conflicto armado colombiano. International Journal of Psychological Research, 17(2), 36–46. https://doi.org/10.21500/20112084.7333
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To give up copyright, the authors allow that, International Journal of Psychological Research, distribute the work more broadly, check for the reuse by others and take care of the necessary procedures for the registration and administration of copyright; at the same time, our editorial board represents the interests of the author and allows authors to re-use his work in various forms. In response to the above, authors transfer copyright to the journal, International Journal of Psychological Research. This transfer does not imply other rights which are not those of authorship (for example those that concern about patents). Likewise, preserves the authors rights to use the work integral or partially in lectures, books and courses, as well as make copies for educational purposes. Finally, the authors may use freely the tables and figures in its future work, wherever make explicit reference to the previous publication in International Journal of Psychological Research. The assignment of copyright includes both virtual rights and forms of the article to allow the editorial to disseminate the work in the manner which it deems appropriate.
The editorial board reserves the right of amendments deemed necessary in the application of the rules of publication.
Resumen
A pesar de los esfuerzos institucionales, aún no se ha logrado la reconciliación entre antiguos actores del conflicto armado colombiano, debido en parte al prejuicio que todavía persiste. Presentamos un estudio de conectividad funcional basado en EEG, aplicado a sujetos de cuatro grupos de actores que completaron una Prueba de Asociación Implícita que mide el prejuicio hacia víctimas o combatientes. Analizamos siete medidas de conectividad funcional calculadas en seis bandas de frecuencia y dos condiciones experimentales diferentes. En la tarea conductual, hallamos que las víctimas tienen mayor prejuicio hacia ellas mismas, mientras los civiles tienen mayor prejuicio hacia los combatientes. También encontramos diferencias en algunas medidas de víctimas y exparamilitares con respecto a los civiles y exguerrilleros, en la banda theta, y de víctimas y exguerrilleros con respecto a los exparamilitares, en la banda beta2. Estos resultados nos ayudan a diseñar intervenciones sociocognitivas más eficaces para reducir los prejuicios.
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Referencias
Alto Comisionado para la Paz. (2016). Acuerdo final para la terminación del conflicto y la construcción de una paz estable y duradera. Jurisdicción Especial para la Paz. https://www.jep.gov.co/Marco Normativo/Normativa_v2/01 ACUERDOS/Texto-Nuevo-Acuerdo-Final.pdf?csf=1&e=0fpYA0
Amodio, D. M. (2014). The neuroscience of prejudice and stereotyping. Nature Reviews Neuroscience, 15(10), 670–682. https://doi.org/10.1038/nrn3800
Amodio, D. M., & Cikara, M. (2021). The Social Neuroscience of Prejudice. Annual Review of Psychology, 72, 439–469. https://doi.org/10.1146/annurev-psych-010419-050928
Baez, S., Santamaría-García, H., & Ibáñez, A. (2019). Disarming ex-combatants’ minds: Toward situated reintegration process in post-conflict Colombia. Frontiers in Psychology, 10(JAN), 73. https://doi.org/10.3389/fpsyg.2019.00073
Bar-Siman-Tov, Y. (2004). From conflict resolution to reconciliation. Oxford University Press.
Barnes-Holmes, D., Staunton, C., Barnes-Holmes, Y., Whelan, R., Stewart, I., Commins, S., Walsh, D., Smeets, P. M., & Dymond, S. (2004). Interfacing relational frame theory with cognitive neuroscience: Semantic priming, the implicit association test, and event related potentials [Conectando la relational frame theory con la neurociencia cognitiva: Priming semántico, el test de asociación I. International Journal of Psychology and Psychological Therapy, 4(2), 215–240. https://www.scopus.com/inward/record.uri?eid=2-s2.0-26444477995&partnerID=40&md5=5558ef48d1d23c5d35e06c3b76038daa
Bastos, A. M., & Schoffelen, J. M. (2016). A tutorial review of functional connectivity analysis methods and their interpretational pitfalls. Frontiers in Systems Neuroscience, 9(JAN2016), 175. https://doi.org/10.3389/fnsys.2015.00175
Beste, C., Münchau, A., & Frings, C. (2023). Towards a systematization of brain oscillatory activity in actions. Communications Biology, 6(1), 137. https://doi.org/10.1038/s42003-023-04531-9
Bigdely-Shamlo, N., Mullen, T., Kothe, C., Su, K.-M., & Robbins, K. A. (2015). The PREP pipeline: standardized preprocessing for large-scale EEG analysis. Frontiers in Neuroinformatics, 9(JUNE), 1–19. https://doi.org/10.3389/fninf.2015.00016
Blomsma, N., de Rooy, B., Gerritse, F., van der Spek, R., Tewarie, P., Hillebrand, A., Otte, W. M., Stam, C. J., & van Dellen, E. (2022). Minimum spanning tree analysis of brain networks: A systematic review of network size effects, sensitivity for neuropsychiatric pathology, and disorder specificity. Network Neuroscience, 6(2), 301–319. https://doi.org/10.1162/netn_a_00245
Böttcher, A., Wilken, S., Adelhöfer, N., Raab, M., Hoffmann, S., & Beste, C. (2023). A dissociable functional relevance of theta- and beta-band activities during complex sensorimotor integration. Cerebral Cortex, 33(14), 9154–9164. https://doi.org/10.1093/cercor/bhad191
Cao, R., Hao, Y., Wang, X., Gao, Y., Shi, H., Huo, S., Wang, B., Guo, H., & Xiang, J. (2020). EEG Functional Connectivity Underlying Emotional Valance and Arousal Using Minimum Spanning Trees. Frontiers in Neuroscience, 14, 355. https://doi.org/10.3389/fnins.2020.00355
Cavanagh, J. F., & Frank, M. J. (2014). Frontal theta as a mechanism for cognitive control. Trends in Cognitive Sciences, 18(8), 414–421. https://doi.org/https://doi.org/10.1016/j.tics.2014.04.012
Comisión de la Verdad. (2022). Cifras de la Comisión de la Verdad presentadas junto con el Informe Final (Vol. 1). https://web.comisiondelaverdad.co/actualidad/noticias/principales-cifras-comision-de-la-verdad-informe-final
Congreso de la República de Colombia. (2005). Ley 975 de 2005, por la cual se dictan disposiciones para la reincorporación de miembros de grupos armados organizados al margen de la ley, que contribuyan de manera efectiva a la consecución de la paz nacional y se dictan otras disposiciones para acuerdo. Diario Oficial, 45980.
Etz, A., & Vandekerckhove, J. (2018). Introduction to Bayesian Inference for Psychology. Psychonomic Bulletin and Review, 25(1), 5–34.
Forbes, C. E., Cameron, K. A., Grafman, J., Barbey, A. K., Solomon, J., Ritter, W., & Ruchkin, D. (2012). Identifying temporal and causal contributions of neural processes underlying the Implicit Association Test (IAT). Frontiers in Human Neuroscience, 6(NOVEMBER 2012), 320. https://doi.org/10.3389/fnhum.2012.00320
Fornito, A., Zalesky, A., & Bullmore, E. (2016). Fundamentals of brain network analysis. Academic Press.
Friston, K. J. (1994). Functional and effective connectivity in neuroimaging: a synthesis. Human Brain Mapping, 2(1‐2), 56–78.
Friston, K. J. (2011). Functional and Effective Connectivity: A Review. Brain Connectivity, 1(1), 13–36. https://doi.org/10.1089/brain.2011.0008
Gedeon, C., Esseily, R., & Badea, C. (2021). Examining differences in minority versus majority preschoolers on social categorization and perceived intergroup distance. Journal of Community & Applied Social Psychology, 31(1), 94–106. https://doi.org/https://doi.org/10.1002/casp.2479
Gramfort, A. (2013). MEG and EEG data analysis with MNE-Python. Frontiers in Neuroscience, 7(7 DEC), 267.
Greenwald, A. G., McGhee, D. E., & Schwartz, J. L. K. (1998). Measuring individual differences in implicit cognition: the implicit association test. Journal of Personality and Social Psychology, 74(6), 1464.
Greenwald, A. G., Nosek, B. A., & Banaji, M. R. (2003). Understanding and using the implicit association test: I. An improved scoring algorithm. Journal of Personality and Social Psychology, 85(2), 197.
Healy, G. F., Boran, L., & Smeaton, A. F. (2015). Neural patterns of the implicit association test. Frontiers in Human Neuroscience, 9(NOV), 605. https://doi.org/10.3389/fnhum.2015.00605
Jas, M., Engemann, D. A., Bekhti, Y., Raimondo, F., & Gramfort, A. (2017). Autoreject: Automated artifact rejection for MEG and EEG data. NeuroImage, 159, 417–429. https://doi.org/10.1016/j.neuroimage.2017.06.030
Jeffreys, H. (1938). Significance tests when several degrees of freedom arise simultaneously. Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences, 165(921), 161–198.
Jost, J. T., Banaji, M. R., & Nosek, B. A. (2004). A decade of system justification theory: Accumulated evidence of conscious and unconscious bolstering of the status quo. Political Psychology, 25(6), 881–919.
Kato, K., Kadokura, H., Kuroki, T., & Ishikawa, A. (2018). Event-related synchronization/desynchronization in neural oscillatory changes caused by implicit biases of spatial frequency in electroencephalography. In I. G. S. Lhotska L. Sukupova L., Lackovic I. (Eds.), IFMBE Proceedings, vol 68/2 (Vol. 68, pp. 175–178). Springer Verlag. https://doi.org/10.1007/978-981-10-9038-7_32
Keysers, C., Gazzola, V., & Wagenmakers, E. J. (2020). Using Bayes factor hypothesis testing in neuroscience to establish evidence of absence. Nature Neuroscience, 23(7), 788–799. https://doi.org/10.1038/s41593-020-0660-4
Kruskal, J. B. (1956). On the shortest spanning subtree of a graph and the traveling salesman problem. Proceedings of the American Mathematical Society, 7(1), 48–50. https://doi.org/10.1090/s0002-9939-1956-0078686-7
March, D. S., & Graham, R. (2014). Exploring implicit ingroup and outgroup bias toward Hispanics. Group Processes & Intergroup Relations, 18(1), 89–103. https://doi.org/10.1177/1368430214542256
Martin, D. (2014). IAT: Cleaning and Visualizing Implicit Association Test (IAT) Data.
Newheiser, A.-K., Dunham, Y., Merrill, A., Hoosain, L., & Olson, K. R. (2014). Preference for high status predicts implicit outgroup bias among children from low-status groups. Developmental Psychology, 50(4), 1081.
Poli, D., Pastore, V. P., & Massobrio, P. (2015). Functional connectivity in in vitro neuronal assemblies. Frontiers in Neural Circuits, 0(OCT), 57. https://doi.org/10.3389/FNCIR.2015.00057
Prim, R. C. (1957). Shortest connection networks and some generalizations. The Bell System Technical Journal, 36(6), 1389–1401.
Rösler, I. K., & Amodio, D. M. (2022). Neural Basis of Prejudice and Prejudice Reduction. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 7(12), 1200–1208. https://doi.org/https://doi.org/10.1016/j.bpsc.2022.10.008
Rubinov, M., & Sporns, O. (2010). Complex network measures of brain connectivity: Uses and interpretations. NeuroImage, 52(3), 1059–1069. https://doi.org/10.1016/j.neuroimage.2009.10.003
Schindler, S., & Wolff, W. (2015). Cerebral correlates of automatic associations towards performance enhancing substances. Frontiers in Psychology, 6(DEC), 1923. https://doi.org/10.3389/fpsyg.2015.01923
Smit, D., Trevino, L., Mohamed, S. M. H., & Enriquez-Geppert, S. (2023). Theta power and functional connectivity as neurophysiological markers of executive functions in individuals with cognitive complaints in daily life. Biological Psychology, 178, 108503. https://doi.org/https://doi.org/10.1016/j.biopsycho.2023.108503
Stam, C. J., Tewarie, P., Van Dellen, E., van Straaten, E. C. W., Hillebrand, A., & Van Mieghem, P. (2014). The trees and the forest: Characterization of complex brain networks with minimum spanning trees. International Journal of Psychophysiology, 92(3), 129–138. https://doi.org/10.1016/j.ijpsycho.2014.04.001
Tajfel, H., Turner, J. C., Austin, W. G., & Worchel, S. (1979). An integrative theory of intergroup conflict. Organizational Identity: A Reader, 56(65), 9780203505984–16.
Teige-Mocigemba, S., Klauer, K. C., & Sherman, J. W. (2016). A practical guide to Implicit Association Task and related tasks. In B. Gawronski & B. K. Payne (Eds.), Handbook of implicit social cognition: Measurement, theory, and applications (pp. 117-139). Guilford Press
Tewarie, P., van Dellen, E., Hillebrand, A., & Stam, C. J. (2015). The minimum spanning tree: An unbiased method for brain network analysis. NeuroImage, 104, 177–188. https://doi.org/10.1016/J.NEUROIMAGE.2014.10.015
Trujillo, S., Trujillo, N., Lopez, J. D., Gomez, D., Valencia, S., Rendon, J., Pineda, D. A., & Parra, M. A. (2017). Social cognitive training improves emotional processing and reduces aggressive attitudes in ex-combatants. Frontiers in Psychology, 8, 510.
Ugarriza, J. E., Villegas, C. A., Trujillo, N., & López, J. D. (2019). Restaurar tejidos sociales en comunidades durante el postconflicto a través de un enfoque de intervención biopsicosocial comprehensivo: estrategias hacia a la construcción de paz en Colombia [Research Project]. Universidad del Rosario. https://pure.urosario.edu.co/es/projects/restoring-social-fabrics-in-communities-during-the-post-conflict-
Valencia, S., Trujillo, N., Trujillo, S., Acosta, A., Rodríguez, M., Ugarriza, J. E., López, J. D., García, A. M., & Parra, M. A. (2020). Neurocognitive reorganization of emotional processing following a socio-cognitive intervention in Colombian ex-combatants. Social Neuroscience. https://doi.org/10.1080/17470919.2020.1735511
van Dellen, E., Sommer, I. E., Bohlken, M. M., Tewarie, P., Draaisma, L., Zalesky, A., Di Biase, M., Brown, J. A., Douw, L., Otte, W. M., Mandl, R. C. W., & Stam, C. J. (2018). Minimum spanning tree analysis of the human connectome. Human Brain Mapping, 39(6), 2455–2471. https://doi.org/10.1002/HBM.24014
van Doorn, J., van den Bergh, D., Böhm, U., Dablander, F., Derks, K., Draws, T., Etz, A., Evans, N. J., Gronau, Q. F., Haaf, J. M., Hinne, M., Kucharský, Š., Ly, A., Marsman, M., Matzke, D., Gupta, A. R. K. N., Sarafoglou, A., Stefan, A., Voelkel, J. G., & Wagenmakers, E. J. (2021). The JASP guidelines for conducting and reporting a Bayesian analysis. Psychonomic Bulletin and Review, 28(3), 813–826. https://doi.org/10.3758/s13423-020-01798-5
Vinck, M., Oostenveld, R., Van Wingerden, M., Battaglia, F., & Pennartz, C. M. A. (2011). An improved index of phase-synchronization for electrophysiological data in the presence of volume-conduction, noise and sample-size bias. NeuroImage, 55(4), 1548–1565. https://doi.org/10.1016/j.neuroimage.2011.01.055
Wagenmakers, E.-J., Marsman, M., Jamil, T., Ly, A., Verhagen, J., Love, J., Selker, R., Gronau, Q. F., Šmíra, M., Epskamp, S., Matzke, D., Rouder, J. N., & Morey, R. D. (2018). Bayesian inference for psychology. Part I: Theoretical advantages and practical ramifications. Psychonomic Bulletin & Review, 25(1), 35–57. https://doi.org/10.3758/s13423-017-1343-3
Westfall, P. H., Johnson, W. O., & Utts, J. M. (1997). A Bayesian perspective on the Bonferroni adjustment. Biometrika, 84(2), 419–427. https://doi.org/10.1093/biomet/84.2.419
Wetzels, R., Grasman, R. P. P. P., & Wagenmakers, E.-J. (2012). A Default Bayesian Hypothesis Test for ANOVA Designs. The American Statistician, 66(2), 104–111. https://doi.org/10.1080/00031305.2012.695956
Yao, D. (2001). A method to standardize a reference of scalp EEG recordings to a point at infinity. Physiological Measurement, 22(4), 693–711. https://doi.org/10.1088/0967-3334/22/4/305
Zakharov, I., Tabueva, A., Adamovich, T., Kovas, Y., & Malykh, S. (2020). Alpha Band Resting-State EEG Connectivity Is Associated With Non-verbal Intelligence. Frontiers in Human Neuroscience, 14, 10. https://doi.org/10.3389/FNHUM.2020.00010/BIBTEX
Amodio, D. M. (2014). The neuroscience of prejudice and stereotyping. Nature Reviews Neuroscience, 15(10), 670–682. https://doi.org/10.1038/nrn3800
Amodio, D. M., & Cikara, M. (2021). The Social Neuroscience of Prejudice. Annual Review of Psychology, 72, 439–469. https://doi.org/10.1146/annurev-psych-010419-050928
Baez, S., Santamaría-García, H., & Ibáñez, A. (2019). Disarming ex-combatants’ minds: Toward situated reintegration process in post-conflict Colombia. Frontiers in Psychology, 10(JAN), 73. https://doi.org/10.3389/fpsyg.2019.00073
Bar-Siman-Tov, Y. (2004). From conflict resolution to reconciliation. Oxford University Press.
Barnes-Holmes, D., Staunton, C., Barnes-Holmes, Y., Whelan, R., Stewart, I., Commins, S., Walsh, D., Smeets, P. M., & Dymond, S. (2004). Interfacing relational frame theory with cognitive neuroscience: Semantic priming, the implicit association test, and event related potentials [Conectando la relational frame theory con la neurociencia cognitiva: Priming semántico, el test de asociación I. International Journal of Psychology and Psychological Therapy, 4(2), 215–240. https://www.scopus.com/inward/record.uri?eid=2-s2.0-26444477995&partnerID=40&md5=5558ef48d1d23c5d35e06c3b76038daa
Bastos, A. M., & Schoffelen, J. M. (2016). A tutorial review of functional connectivity analysis methods and their interpretational pitfalls. Frontiers in Systems Neuroscience, 9(JAN2016), 175. https://doi.org/10.3389/fnsys.2015.00175
Beste, C., Münchau, A., & Frings, C. (2023). Towards a systematization of brain oscillatory activity in actions. Communications Biology, 6(1), 137. https://doi.org/10.1038/s42003-023-04531-9
Bigdely-Shamlo, N., Mullen, T., Kothe, C., Su, K.-M., & Robbins, K. A. (2015). The PREP pipeline: standardized preprocessing for large-scale EEG analysis. Frontiers in Neuroinformatics, 9(JUNE), 1–19. https://doi.org/10.3389/fninf.2015.00016
Blomsma, N., de Rooy, B., Gerritse, F., van der Spek, R., Tewarie, P., Hillebrand, A., Otte, W. M., Stam, C. J., & van Dellen, E. (2022). Minimum spanning tree analysis of brain networks: A systematic review of network size effects, sensitivity for neuropsychiatric pathology, and disorder specificity. Network Neuroscience, 6(2), 301–319. https://doi.org/10.1162/netn_a_00245
Böttcher, A., Wilken, S., Adelhöfer, N., Raab, M., Hoffmann, S., & Beste, C. (2023). A dissociable functional relevance of theta- and beta-band activities during complex sensorimotor integration. Cerebral Cortex, 33(14), 9154–9164. https://doi.org/10.1093/cercor/bhad191
Cao, R., Hao, Y., Wang, X., Gao, Y., Shi, H., Huo, S., Wang, B., Guo, H., & Xiang, J. (2020). EEG Functional Connectivity Underlying Emotional Valance and Arousal Using Minimum Spanning Trees. Frontiers in Neuroscience, 14, 355. https://doi.org/10.3389/fnins.2020.00355
Cavanagh, J. F., & Frank, M. J. (2014). Frontal theta as a mechanism for cognitive control. Trends in Cognitive Sciences, 18(8), 414–421. https://doi.org/https://doi.org/10.1016/j.tics.2014.04.012
Comisión de la Verdad. (2022). Cifras de la Comisión de la Verdad presentadas junto con el Informe Final (Vol. 1). https://web.comisiondelaverdad.co/actualidad/noticias/principales-cifras-comision-de-la-verdad-informe-final
Congreso de la República de Colombia. (2005). Ley 975 de 2005, por la cual se dictan disposiciones para la reincorporación de miembros de grupos armados organizados al margen de la ley, que contribuyan de manera efectiva a la consecución de la paz nacional y se dictan otras disposiciones para acuerdo. Diario Oficial, 45980.
Etz, A., & Vandekerckhove, J. (2018). Introduction to Bayesian Inference for Psychology. Psychonomic Bulletin and Review, 25(1), 5–34.
Forbes, C. E., Cameron, K. A., Grafman, J., Barbey, A. K., Solomon, J., Ritter, W., & Ruchkin, D. (2012). Identifying temporal and causal contributions of neural processes underlying the Implicit Association Test (IAT). Frontiers in Human Neuroscience, 6(NOVEMBER 2012), 320. https://doi.org/10.3389/fnhum.2012.00320
Fornito, A., Zalesky, A., & Bullmore, E. (2016). Fundamentals of brain network analysis. Academic Press.
Friston, K. J. (1994). Functional and effective connectivity in neuroimaging: a synthesis. Human Brain Mapping, 2(1‐2), 56–78.
Friston, K. J. (2011). Functional and Effective Connectivity: A Review. Brain Connectivity, 1(1), 13–36. https://doi.org/10.1089/brain.2011.0008
Gedeon, C., Esseily, R., & Badea, C. (2021). Examining differences in minority versus majority preschoolers on social categorization and perceived intergroup distance. Journal of Community & Applied Social Psychology, 31(1), 94–106. https://doi.org/https://doi.org/10.1002/casp.2479
Gramfort, A. (2013). MEG and EEG data analysis with MNE-Python. Frontiers in Neuroscience, 7(7 DEC), 267.
Greenwald, A. G., McGhee, D. E., & Schwartz, J. L. K. (1998). Measuring individual differences in implicit cognition: the implicit association test. Journal of Personality and Social Psychology, 74(6), 1464.
Greenwald, A. G., Nosek, B. A., & Banaji, M. R. (2003). Understanding and using the implicit association test: I. An improved scoring algorithm. Journal of Personality and Social Psychology, 85(2), 197.
Healy, G. F., Boran, L., & Smeaton, A. F. (2015). Neural patterns of the implicit association test. Frontiers in Human Neuroscience, 9(NOV), 605. https://doi.org/10.3389/fnhum.2015.00605
Jas, M., Engemann, D. A., Bekhti, Y., Raimondo, F., & Gramfort, A. (2017). Autoreject: Automated artifact rejection for MEG and EEG data. NeuroImage, 159, 417–429. https://doi.org/10.1016/j.neuroimage.2017.06.030
Jeffreys, H. (1938). Significance tests when several degrees of freedom arise simultaneously. Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences, 165(921), 161–198.
Jost, J. T., Banaji, M. R., & Nosek, B. A. (2004). A decade of system justification theory: Accumulated evidence of conscious and unconscious bolstering of the status quo. Political Psychology, 25(6), 881–919.
Kato, K., Kadokura, H., Kuroki, T., & Ishikawa, A. (2018). Event-related synchronization/desynchronization in neural oscillatory changes caused by implicit biases of spatial frequency in electroencephalography. In I. G. S. Lhotska L. Sukupova L., Lackovic I. (Eds.), IFMBE Proceedings, vol 68/2 (Vol. 68, pp. 175–178). Springer Verlag. https://doi.org/10.1007/978-981-10-9038-7_32
Keysers, C., Gazzola, V., & Wagenmakers, E. J. (2020). Using Bayes factor hypothesis testing in neuroscience to establish evidence of absence. Nature Neuroscience, 23(7), 788–799. https://doi.org/10.1038/s41593-020-0660-4
Kruskal, J. B. (1956). On the shortest spanning subtree of a graph and the traveling salesman problem. Proceedings of the American Mathematical Society, 7(1), 48–50. https://doi.org/10.1090/s0002-9939-1956-0078686-7
March, D. S., & Graham, R. (2014). Exploring implicit ingroup and outgroup bias toward Hispanics. Group Processes & Intergroup Relations, 18(1), 89–103. https://doi.org/10.1177/1368430214542256
Martin, D. (2014). IAT: Cleaning and Visualizing Implicit Association Test (IAT) Data.
Newheiser, A.-K., Dunham, Y., Merrill, A., Hoosain, L., & Olson, K. R. (2014). Preference for high status predicts implicit outgroup bias among children from low-status groups. Developmental Psychology, 50(4), 1081.
Poli, D., Pastore, V. P., & Massobrio, P. (2015). Functional connectivity in in vitro neuronal assemblies. Frontiers in Neural Circuits, 0(OCT), 57. https://doi.org/10.3389/FNCIR.2015.00057
Prim, R. C. (1957). Shortest connection networks and some generalizations. The Bell System Technical Journal, 36(6), 1389–1401.
Rösler, I. K., & Amodio, D. M. (2022). Neural Basis of Prejudice and Prejudice Reduction. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 7(12), 1200–1208. https://doi.org/https://doi.org/10.1016/j.bpsc.2022.10.008
Rubinov, M., & Sporns, O. (2010). Complex network measures of brain connectivity: Uses and interpretations. NeuroImage, 52(3), 1059–1069. https://doi.org/10.1016/j.neuroimage.2009.10.003
Schindler, S., & Wolff, W. (2015). Cerebral correlates of automatic associations towards performance enhancing substances. Frontiers in Psychology, 6(DEC), 1923. https://doi.org/10.3389/fpsyg.2015.01923
Smit, D., Trevino, L., Mohamed, S. M. H., & Enriquez-Geppert, S. (2023). Theta power and functional connectivity as neurophysiological markers of executive functions in individuals with cognitive complaints in daily life. Biological Psychology, 178, 108503. https://doi.org/https://doi.org/10.1016/j.biopsycho.2023.108503
Stam, C. J., Tewarie, P., Van Dellen, E., van Straaten, E. C. W., Hillebrand, A., & Van Mieghem, P. (2014). The trees and the forest: Characterization of complex brain networks with minimum spanning trees. International Journal of Psychophysiology, 92(3), 129–138. https://doi.org/10.1016/j.ijpsycho.2014.04.001
Tajfel, H., Turner, J. C., Austin, W. G., & Worchel, S. (1979). An integrative theory of intergroup conflict. Organizational Identity: A Reader, 56(65), 9780203505984–16.
Teige-Mocigemba, S., Klauer, K. C., & Sherman, J. W. (2016). A practical guide to Implicit Association Task and related tasks. In B. Gawronski & B. K. Payne (Eds.), Handbook of implicit social cognition: Measurement, theory, and applications (pp. 117-139). Guilford Press
Tewarie, P., van Dellen, E., Hillebrand, A., & Stam, C. J. (2015). The minimum spanning tree: An unbiased method for brain network analysis. NeuroImage, 104, 177–188. https://doi.org/10.1016/J.NEUROIMAGE.2014.10.015
Trujillo, S., Trujillo, N., Lopez, J. D., Gomez, D., Valencia, S., Rendon, J., Pineda, D. A., & Parra, M. A. (2017). Social cognitive training improves emotional processing and reduces aggressive attitudes in ex-combatants. Frontiers in Psychology, 8, 510.
Ugarriza, J. E., Villegas, C. A., Trujillo, N., & López, J. D. (2019). Restaurar tejidos sociales en comunidades durante el postconflicto a través de un enfoque de intervención biopsicosocial comprehensivo: estrategias hacia a la construcción de paz en Colombia [Research Project]. Universidad del Rosario. https://pure.urosario.edu.co/es/projects/restoring-social-fabrics-in-communities-during-the-post-conflict-
Valencia, S., Trujillo, N., Trujillo, S., Acosta, A., Rodríguez, M., Ugarriza, J. E., López, J. D., García, A. M., & Parra, M. A. (2020). Neurocognitive reorganization of emotional processing following a socio-cognitive intervention in Colombian ex-combatants. Social Neuroscience. https://doi.org/10.1080/17470919.2020.1735511
van Dellen, E., Sommer, I. E., Bohlken, M. M., Tewarie, P., Draaisma, L., Zalesky, A., Di Biase, M., Brown, J. A., Douw, L., Otte, W. M., Mandl, R. C. W., & Stam, C. J. (2018). Minimum spanning tree analysis of the human connectome. Human Brain Mapping, 39(6), 2455–2471. https://doi.org/10.1002/HBM.24014
van Doorn, J., van den Bergh, D., Böhm, U., Dablander, F., Derks, K., Draws, T., Etz, A., Evans, N. J., Gronau, Q. F., Haaf, J. M., Hinne, M., Kucharský, Š., Ly, A., Marsman, M., Matzke, D., Gupta, A. R. K. N., Sarafoglou, A., Stefan, A., Voelkel, J. G., & Wagenmakers, E. J. (2021). The JASP guidelines for conducting and reporting a Bayesian analysis. Psychonomic Bulletin and Review, 28(3), 813–826. https://doi.org/10.3758/s13423-020-01798-5
Vinck, M., Oostenveld, R., Van Wingerden, M., Battaglia, F., & Pennartz, C. M. A. (2011). An improved index of phase-synchronization for electrophysiological data in the presence of volume-conduction, noise and sample-size bias. NeuroImage, 55(4), 1548–1565. https://doi.org/10.1016/j.neuroimage.2011.01.055
Wagenmakers, E.-J., Marsman, M., Jamil, T., Ly, A., Verhagen, J., Love, J., Selker, R., Gronau, Q. F., Šmíra, M., Epskamp, S., Matzke, D., Rouder, J. N., & Morey, R. D. (2018). Bayesian inference for psychology. Part I: Theoretical advantages and practical ramifications. Psychonomic Bulletin & Review, 25(1), 35–57. https://doi.org/10.3758/s13423-017-1343-3
Westfall, P. H., Johnson, W. O., & Utts, J. M. (1997). A Bayesian perspective on the Bonferroni adjustment. Biometrika, 84(2), 419–427. https://doi.org/10.1093/biomet/84.2.419
Wetzels, R., Grasman, R. P. P. P., & Wagenmakers, E.-J. (2012). A Default Bayesian Hypothesis Test for ANOVA Designs. The American Statistician, 66(2), 104–111. https://doi.org/10.1080/00031305.2012.695956
Yao, D. (2001). A method to standardize a reference of scalp EEG recordings to a point at infinity. Physiological Measurement, 22(4), 693–711. https://doi.org/10.1088/0967-3334/22/4/305
Zakharov, I., Tabueva, A., Adamovich, T., Kovas, Y., & Malykh, S. (2020). Alpha Band Resting-State EEG Connectivity Is Associated With Non-verbal Intelligence. Frontiers in Human Neuroscience, 14, 10. https://doi.org/10.3389/FNHUM.2020.00010/BIBTEX
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