{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,23]],"date-time":"2026-03-23T21:56:01Z","timestamp":1774302961424,"version":"3.50.1"},"reference-count":32,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T00:00:00Z","timestamp":1763164800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>The digital transformation in the treatment of mental health and emotional disharmony requires artificial intelligence architectures that overcome the limitations of purely neural approaches, such as temporal inconsistency, opacity, and lack of theoretical foundations. Assuming the existence and use of generalist LLMs currently used in clinical settings and considering the appropriate limitations indicated by experts, this article aims to offer clinicians an alternative Neuro-symbolic-Psychological multi-agent architecture (NSPA-AI), which integrates archetypal symbolic reasoning with neurobiological modelling, based on our established framework of artificial neurotransmitters for the modelling and analysis of affective-emotional stimuli to enable interpretable AI-assisted psychological intervention. The system implements a hub-and-spoke topology that coordinates five specialized agents (symbolic, psychological, neurofunctional, decision fusion, learning) that process heterogeneous information via SPADE protocols. Seven archetypal constructs from Jungian psychology and narrative identity theory provide stable symbolic frameworks for longitudinal therapeutic consistency. An empirical study of 156 university students demonstrated significant improvements in depression (Cohen\u2019s d = 1.03), stress (d = 0.89), and narrative identity integration (d = 0.75), which were maintained at a 12-week follow-up and superior to GPT-4 controls (d = 0.34). Neurofunctional correlations\u2014downregulation of cortisol (r = 0.71 with stress reduction), increase in serotonin (r = \u22120.68 with depression improvement)\u2014validated the neurobiological basis of the entropy-energy framework. Qualitative analysis revealed the following four mechanisms of improvement: symbolic emotional support (93%), increased self-awareness through neurotransmitter visualization (84%), non-judgmental AI interaction (98%), and archetypal narrative organization (87%). The results establish that neuro-symbolic architectures are viable alternatives to large language models for digital mental health, providing the interpretability and clinical validity essential for adoption in the healthcare sector.<\/jats:p>","DOI":"10.3390\/a18110721","type":"journal-article","created":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T11:17:27Z","timestamp":1763551047000},"page":"721","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Neuro-Symbolic Multi-Agent Architecture for Digital Transformation of Psychological Support Systems via Artificial Neurotransmitters and Archetypal Reasoning"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3119-4608","authenticated-orcid":false,"given":"Gerardo","family":"Iovane","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-9008-7757","authenticated-orcid":false,"given":"Iana","family":"Fominska","sequence":"additional","affiliation":[{"name":"Department of Education, Cultural Heritage and Tourism Sciences, University of Macerata, 62100 Macerata, Italy"}]},{"given":"Raffaella","family":"Di Pasquale","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2025,11,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Iovane, G., and Di Pasquale, R. (2025). A Complexity Theory-Based Novel AI Algorithm for Exploring Emotions and Affections by Utilizing Artificial Neurotransmitters. Electronics, 14.","DOI":"10.3390\/electronics14061093"},{"key":"ref_2","unstructured":"Jung, C.G. (1991). The Archetypes and the Collective Unconscious, Routledge. [2nd ed.]."},{"key":"ref_3","unstructured":"McAdams, D.P. (1997). The Stories We Live By: Personal Myths and the Making of the Self, Guilford Press."},{"key":"ref_4","unstructured":"Young, J.E., Klosko, J.S., and Weishaar, M.E. (2003). Schema Therapy: A Practitioner\u2019s Guide, Guilford Press."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Norcross, J.C., and Goldfried, M.R. (2019). Handbook of Psychotherapy Integration, Oxford University Press. [3rd ed.].","DOI":"10.1093\/med-psych\/9780190690465.001.0001"},{"key":"ref_6","unstructured":"Garcez, A.S.d., Lamb, L.C., and Gabbay, D.M. (2009). Neural-Symbolic Cognitive Reasoning, Springer."},{"key":"ref_7","unstructured":"Marcus, G. (2020). The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence. arXiv."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Schuller, B., and Batliner, A. (2013). Computational Paralinguistics: Emotion, Affect and Personality in Speech and Language Processing, John Wiley & Sons.","DOI":"10.1002\/9781118706664"},{"key":"ref_9","unstructured":"Scholem, G. (1965). On the Kabbalah and Its Symbolism. Princeton University Press."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Picard, R.W. (1997). Affective Computing, MIT Press.","DOI":"10.7551\/mitpress\/1140.001.0001"},{"key":"ref_11","unstructured":"Hayes, S.C., Strosahl, K.D., and Wilson, K.G. (2012). Acceptance and Commitment Therapy: The Process and Practice of Mindful Change, The Guilford Press. [2nd ed.]."},{"key":"ref_12","unstructured":"Damasio, A. (1999). The Feeling of What Happens: Body and Emotion in the Making of Consciousness, Harcourt College Publishers."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1146\/annurev-neuro-071013-014030","article-title":"The Brain\u2019s Default Mode Network","volume":"38","author":"Raichle","year":"2015","journal-title":"Annu. Rev. Neurosci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1196\/annals.1440.011","article-title":"The Brain\u2019s Default Network: Anatomy, Function, and Relevance to Disease","volume":"1124","author":"Buckner","year":"2008","journal-title":"Ann. N. Y. Acad. Sci."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"483","DOI":"10.1016\/j.tics.2011.08.003","article-title":"Large-Scale Brain Networks and Psychopathology: A Unifying Triple Network Model","volume":"15","author":"Menon","year":"2011","journal-title":"Trends Cogn. Sci."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.tics.2010.11.004","article-title":"Emotional Processing in Anterior Cingulate and Medial Prefrontal Cortex","volume":"15","author":"Etkin","year":"2011","journal-title":"Trends Cogn. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Northoff, G. (2018). The Spontaneous Brain: From the Mind-Body to the World-Brain Problem, MIT Press.","DOI":"10.7551\/mitpress\/9780262038072.001.0001"},{"key":"ref_18","first-page":"1","article-title":"A Review and Meta-Analysis of Multimodal Affect Detection Systems","volume":"47","author":"Kory","year":"2015","journal-title":"ACM Comput. Surv."},{"key":"ref_19","unstructured":"Seligman, M.E.P. (2011). Flourish: A Visionary New Understanding of Happiness and Well-Being, Free Press."},{"key":"ref_20","unstructured":"Campbell, J. (1949). The Hero with a Thousand Faces, Pantheon Books."},{"key":"ref_21","unstructured":"Trask, W.R. (1957). The Sacred and The Profane: The Nature of Religion, Harcourt, Brace & World."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"631","DOI":"10.1177\/00218863241283919","article-title":"Artificial Intelligence (AI) Coaching: Redefining People Development and Organizational Performance","volume":"60","author":"Terblanche","year":"2024","journal-title":"J. Appl. Behav. Sci."},{"key":"ref_23","first-page":"856","article-title":"Artificial Intelligence for Mental Health Care: Clinical Applications, Barriers, Facilitators, and Artificial Wisdom","volume":"6","author":"Lee","year":"2021","journal-title":"Biol. Psychiatry Cogn. Neurosci. Neuroimaging"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Fitzpatrick, K.K., Darcy, A., and Vierhile, M. (2017). Delivering Cognitive Behaviour Therapy to Young Adults with Symptoms of Depression and Anxiety Using a Fully Automated Conversational Agent (Woebot): A Randomized Controlled Trial. JMIR Ment. Health, 4.","DOI":"10.2196\/mental.7785"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Bond, R.R., Mulvenna, M.D., Potts, C., O\u2019Neill, S., Ennis, E., and Torous, J. (2023). Digital Transformation of Mental Health Services. NPJ Ment. Health Res., 2.","DOI":"10.1038\/s44184-023-00033-y"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1631\/FITEE.1700826","article-title":"From Eliza to XiaoIce: Challenges and Opportunities with Social Chatbots","volume":"19","author":"Shum","year":"2018","journal-title":"Front. Inf. Technol. Electron. Eng."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"115109","DOI":"10.1109\/ACCESS.2020.3003726","article-title":"Decision and Reasoning in Incompleteness or Uncertainty Conditions","volume":"8","author":"Iovane","year":"2020","journal-title":"IEEE Access"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Iovane, G., Landi, R.E., Rapuano, A., and Amatore, R. (2022). Assessing the Relevance of Opinions in Uncertainty and Info-Incompleteness Conditions. Appl. Sci., 12.","DOI":"10.3390\/app12010194"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Iovane, G., and Chinnici, M. (2024). Decision Support System Driven by Thermo-Complexity: Scenario Analysis and Data Visualization. Appl. Sci., 14.","DOI":"10.3390\/app14062387"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1177\/0305735610362821","article-title":"A Comparison of the Discrete and Dimensional Models of Emotion in Music","volume":"39","author":"Eerola","year":"2011","journal-title":"Psychol. Music"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1191\/1478088706qp063oa","article-title":"Using Thematic Analysis in Psychology","volume":"3","author":"Braun","year":"2006","journal-title":"Qual. Res. Psychol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1111\/j.1467-9280.2007.01916.x","article-title":"Putting Feelings Into Words: Affect Labelling Disrupts Amygdala Activity in Response to Affective Stimuli","volume":"18","author":"Lieberman","year":"2007","journal-title":"Psychol. 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