A Neuropsychological Framework for Assessing Marital Conflict: Development of a Brain Systems–Based Conceptual Model
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Objective: This study aimed to identify neuropsychological pattern factors involved in marital conflict and develop a brain systems–based framework for assessment.
Methods and Materials: This applied mixed-methods study used an exploratory sequential design. In the qualitative phase, thematic network analysis, based on Attride-Stirling’s approach, was conducted by reviewing scientific sources on neuropsychology, brain systems, and marital conflict. Initial codes were refined using Q-sort data from 30 men and women with moderate to severe marital conflict and expert evaluation by 9 psychiatrists. The extracted items were assessed for content validity using the content validity ratio and content validity index criteria.
Findings: The analysis identified five major neuropsychological domains associated with marital conflict: prefrontal cortex, anterior cingulate gyrus, basal ganglia, deep limbic system, and temporal cortex. Couples most frequently reported symptoms related to prefrontal dysfunction, including impulsivity, hasty decisions, poor planning, and weak empathy (25%), followed by deep limbic symptoms such as negativity, depression, rejection sensitivity, low sexual desire, and intense emotional reactions (22%). Anterior cingulate symptoms included inflexibility and fixation on past conflicts (20%), basal ganglia symptoms included chronic anxiety and conflict avoidance (18%), and temporal cortex symptoms included aggression, suspiciousness, and misinterpretation of the spouse’s words (15%). Expert review confirmed acceptable content validity, with mean CVR values ranging from 0.80 to 0.87 and mean CVI values from 0.87 to 0.91.
Conclusion: Marital conflict can be conceptualized as a multidimensional outcome of interactions among executive, emotional, anxiety-related, cognitive-flexibility, and socio-emotional brain systems. This framework may support culturally adapted assessment tools and neuroscience-informed couple therapy.
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Almuhtaseb, M. I., Alby, F., Zucchermaglio, C., & Fatigante, M. (2021). Social support for breast cancer patients in the occupied Palestinian territory. Plos one, 16(6), e0252608. https://doi.org/10.1371/journal.pone.0252608
Ashrafi, A., Latifi, Z., Haghayegh, A., & Sajjadian, P. S. (2025). A Comparison of the Effectiveness of Self-Compassion-Focused Therapy and Mentalization‐Based Therapy on Attachment Styles among Married Women Experiencing Marital Boredom. Women’s Health Bulletin, 12(4), 282-293.
Attride-Stirling, J. (2001). Thematic networks: an analytic tool for qualitative research. Qualitative research, 1(3), 385-405. https://doi.org/10.1177/146879410100100307
Bahramian, A., Kazemi, S., Javidi, H. A., & Majid, B. (2024). The Relationship between Conflict Resolution Styles, Irrational Beliefs and Communication Patterns with Marital Conflicts. Quarterly Journal of Psychological Methods and Models Spring, 15(55). 10.30495/jpmm.2023.28979.3501
Bakhshipour, A., Sadeghi, A., & Hosseini, F. (2024). Modeling marital conflicts based on alexithymia with the mediating role of anxiety sensitivity and sexual dissatisfaction in married female students at University of Guilan. Journal of Family Relations Studies, 4(12), 15-25. 10.22098/jfrs.2024.13542.1142
Bloch, L., Haase, C. M., & Levenson, R. W. (2014). Emotion regulation predicts marital satisfaction: More than a wives’ tale. Emotion, 14(1), 130. https://doi.org/10.1037/a0034272
Charbonneau-Lefebvre, V., Vaillancourt-Morel, M.-P., Bigras, N., Opuda, E., & Gewirtz-Meydan, A. (2025). Between struggle and strength: a rapid review of dual-trauma couples. Trauma, Violence, & Abuse, 15248380251335036. https://doi.org/10.1177/15248380251335036
Godfrey, D. A., Bennett, V. E., Snead, A. L., & Babcock, J. (2021). Neuropsychological and psychophysiological correlates of intimate partner violence. In Handbook of Interpersonal Violence and Abuse Across the Lifespan: A project of the National Partnership to End Interpersonal Violence Across the Lifespan (NPEIV) (pp. 2511-2535). Springer. https://doi.org/10.1007/978-3-319-89999-2_136
Huang, X., & Menon, S. (2025). Deep Neural Network Analysis of Emotional Synchrony and Its Role in Marital Satisfaction. Research and Practice in Couple Therapy, 3(4), 1-11. 10.1073/pnas.2202515119
Kiani, M., Andreu-Perez, J., Hagras, H., Rigato, S., & Filippetti, M. L. (2022). Towards understanding human functional brain development with explainable artificial intelligence: Challenges and perspectives. IEEE Computational Intelligence Magazine, 17(1), 16-33. https://doi.org/10.1109/MCI.2021.3129956
Knox, L., Karantzas, G., & Ferguson, E. (2024). The role of attachment, insecurity, and stress in partner maltreatment: A meta-analysis. Trauma, Violence, & Abuse, 25(1), 721-737. https://doi.org/10.1177/15248380231161012
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, D., & Vazsonyi, A. T. (2024). Longitudinal links between parental emotional distress and adolescent delinquency: The role of marital conflict and parent–child conflict. Journal of youth and adolescence, 53(1), 200-216. https://doi.org/10.1007/s10964-023-01921-4
Mikulincer, M., & Shaver, P. R. (2010). Attachment in adulthood: Structure, dynamics, and change. Guilford Publications. https://www.academia.edu/34596672/Attachment_in_Adulthood_Structure_Dynamics_and_Change_Mario_Mikulincer_PhD_Phillip_R_Sha_pdf
Nasiri, P., Mousavi, S. F., & Mollazadeh, J. (2022). Mediating role of cognitive emotion regulation strategies in the relationship between brain-behavioral system activity and marital satisfaction. Iranian Journal of Psychiatry and Clinical Psychology, 27(4), 474-491. https://doi.org/10.32598/ijpcp.27.4.3506.1
Niam, M. P., & Jadidian, A. A. (2024). Comparison of Couples Therapy with Schema Therapy Approach and Gottman Method in Improving Marital Conflicts in Women on the Verge of Divorce.
Nikrahan, G. R. (2023). Theory of brain complexity and marital behaviors: The application of complexity science and neuroscience to explain the complexities of marital behaviors. Frontiers in human neuroscience, 17, 1050164. https://doi.org/10.3389/fnhum.2023.1050164
Razazan, S. (2025). The Role of Psychological Flexibility, Resilience, Self-efficacy, and Hope in Predicting Marital Satisfaction of Married Women. International Journal of Body, Mind & Culture (2345-5802), 12(1). https://doi.org/10.61838/ijbmc.v12i1.741
Schneider-Hassloff, H., Straube, B., Nuscheler, B., Wemken, G., & Kircher, T. (2015). Adult attachment style modulates neural responses in a mentalizing task. Neuroscience, 303, 462-473. https://doi.org/10.1016/j.neuroscience.2015.06.062
Teicher, M. H., Samson, J. A., Anderson, C. M., & Ohashi, K. (2016). The effects of childhood maltreatment on brain structure, function and connectivity. Nature reviews neuroscience, 17(10), 652-666. https://doi.org/10.1038/nrn.2016.111
Tomoda, A., Nishitani, S., Takiguchi, S., Fujisawa, T. X., Sugiyama, T., & Teicher, M. H. (2025). The neurobiological effects of childhood maltreatment on brain structure, function, and attachment. European archives of psychiatry and clinical neuroscience, 275(7), 1939-1958. https://doi.org/10.1007/s00406-024-01779-y
Vrtička, P., Bondolfi, G., Sander, D., & Vuilleumier, P. (2012). The neural substrates of social emotion perception and regulation are modulated by adult attachment style. Social neuroscience, 7(5), 473-493. https://doi.org/10.1080/17470919.2011.647410
Zhang, X., Ran, G., Xu, W., Ma, Y., & Chen, X. (2018). Adult attachment affects neural response to preference-inferring in ambiguous scenarios: evidence from an fMRI study. Frontiers in psychology, 9, 139. https://doi.org/10.3389/fpsyg.2018.00139
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