Volume 7 • Issue 1 • PP: 01–07 • 2026
Future Directions of Artificial Intelligence in Neurological and Psychological Sciences: A Review of Innovations, Challenges, and Prospective Developments
View PDF Abstract
AI rapidly impacts the neurological and psychological sciences, both positive and negative, as more AI techniques are developed. This review will examine how reformative AI can improve mental health care and neuropsychological evaluations. Cognitive tools, including machine learning systems and therapeutic bots, are changing the approach to treatment and, in particular, the diagnosis of diseases. For example, early intervention in a mental health condition can be conducted when AI presents the results from a large data set where the disease may be concealed. Nevertheless, using AI also causes ethical concerns such as privacy, data pre-processing bias, and, obviously, the concern of validation. Since AI is a rapidly expanding field, it has essential consequences meant to be enacted to govern its safety and efficiency in usage in the clinical area. The future area of research should be aimed at minimizing the divergence between technical potentiality and clinical application of the developed AI so that the decision support is complementary to the existing stock of human expertise. The following review will discuss the current trends, issues, and prospects of neurological and psychological AI applications, focusing on the concept that interdisciplinary cooperation can fully unlock the potential of these developments while recognizing the potential issues. In this way, we must work together for a new era of mental health care that is evidence-based but also ethically sound.
Keywords
References
[1] A. van Oosterzee, “Ai and mental health: evaluating supervised machine learning models trained on diagnostic classifications,” AI & Society, vol. 40, no. 6, pp. 5077–5086, 2025.
[2] D. Dillion, N. Tandon, Y. Gu, and K. Gray, “Can ai language models replace human participants?” Trends in Cognitive Sciences, vol. 27, no. 7, pp. 597–600, 2023.
[3] Y. E. Bigman, D. Wilson, M. N. Arnestad, A. Waytz, and K. Gray, “Algorithmic discrimination causes less moral outrage than human discrimination,” Journal of Experimental Psychology: General, vol. 152, no. 1, p. 4, 2023.
[4] A. Thakkar, A. Gupta, and A. De Sousa, “Artificial intelligence in positive mental health: a narrative review,” Frontiers in Digital Health, vol. 6, p. 1280235, 2024.
[5] J. Abbasi and Y. Hswen, “One day, ai could mean better mental health for all,” JAMA, 2024.
[6] M. Brammer, “The role of neuroimaging in diagnosis and personalized medicine-current position and likely future directions,” Dialogues in Clinical Neuroscience, vol. 11, no. 4, pp. 389–396, 2009.
[7] G. Li, L. Deng, H. Tang, G. Pan, Y. Tian, K. Roy, and W. Maass, “Brain-inspired computing: A systematic survey and future trends,” Proceedings of the IEEE, vol. 112, no. 6, pp. 544–584, 2024.
[8] I. D. Dinov, “Neuroinformatics applications of data science and artificial intelligence,” Neuroinformatics, vol. 22, no. 4, pp. 403–405, 2024.
[9] D. G. Tate, M. L. Boninger, and A. B. Jackson, “Future directions for spinal cord injury research: Recent developments and model systems contributions,” Archives of Physical Medicine and Rehabilitation, vol. 92, no. 3, pp. 509–515, 2011.
[10] Q. Li, C. Wu, Y. He, S. Liu, and S. Zhang, “Evaluation of clinical diagnosis effect of intracranial aneurysms combined with artificial intelligence assistant diagnosis system,” Indian Journal of Pharmaceutical Education & Research, vol. 58, no. 3, 2024.
[11] H. Hassani, E. S. Silva, S. Unger, M. TajMazinani, and S. Mac Feely, “Artificial intelligence (ai) or intelligence augmentation (ia): What is the future?” AI, vol. 1, no. 2, pp. 143–155, 2020.
[12] Y.-c. Wu and J.-w. Feng, “Development and application of artificial neural network,” Wireless Personal Communications, vol. 102, no. 2, pp. 1645–1656, 2018.
[13] O. Shvetsova, M. Feroz, S. Salkutsan, and A. Efimov, “Artificial intelligence application for healthcare industry: Cases of developed and emerging markets,” in International Conference on Expert Clouds and Applications. Springer, 2022, pp. 419–432.
[14] T. Zandi, “Changes in memory processes of dementia patients,” New Directions in Understanding Dementia and Alzheimer’s Disease, pp. 89–100, 1990.
[15] S. Grand, “Moving ai out of its infancy: changing our preconceptions,” IEEE Intelligent Systems, vol. 19, no. 6, pp. 74–77, 2004.
[16] V. Baur, J. Hanggi, N. Langer, and L. Jancke, “Restingstate functional and structural connectivity within an insula–amygdala route specifically index state and trait anxiety,” Biological Psychiatry, vol. 73, no. 1, pp. 85– 92, 2013, structural and Functional Activity with Stress and Anxiety.
[17] E. Dudek, M. Williams, C. L. N. Kew, A. Day-Gorman, A. DeMello, A. Gonzalez, A. Holland, L. L. Novelo, X. Liu, B. Wright, and S. Juengst, “Exploring self-reported recent greatest problems among individuals with and without chronic traumatic brain injury via open-text survey responses,” Archives of Physical Medicine and Rehabilitation, vol. 105, no. 4, p. e117, 2024.
[18] T. Peterka, D. Bard, J. C. Bennett, E. W. Bethel, R. A. Oldfield, L. Pouchard, C. Sweeney, and M. Wolf, “Priority research directions for in situ data management: Enabling scientific discovery from diverse data sources,” The International Journal of High Performance Computing Applications, vol. 34, no. 4, pp. 409–427, 2020.
[19] F. Zheng, L. Wang, Z. Zeng, and S. Wu, “International technologies on prevention and treatment of neurological and psychiatric diseases: bibliometric analysis of patents,” JMIR Mental Health, vol. 9, no. 2, p. e25238, 2022.
[20] S. Morein-Zamir and B. J. Sahakian, “Neuroethics and public engagement training needed for neuroscientists,” Trends in Cognitive Sciences, vol. 14, no. 2, pp. 49–51, 2010.
Cite This Article
Choose your preferred format