[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit ::
Main Menu
Home::
Journal Information::
Articles Archive::
Guide for Authors::
For Reviewers::
Ethical Statements::
Registration::
Site Facilities::
Contact us::
::
Indexed by
    
..
Search in website

Advanced Search
..
Receive site information
Enter your Email in the following box to receive the site news and information.
..
Copyright Policies

 

AWT IMAGE

 

..
Open Access Policy

This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge.

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported License which allows users to read, copy, distribute and make derivative works for non-commercial purposes from the material, as long as the author of the original work is cited properly.

..
:: Volume 13, Issue 1 (Winter 2024) ::
Shefaye Khatam 2024, 13(1): 63-73 Back to browse issues page
From Cognitive Systems to Alzheimer's Disease: The Role of Computational Modeling
Elias Mazrooei * , Seyyed Ali Zendehbad , Shahryar Salmani Bajestani
Department of Biomedical Engineering, Khavaran Institute of Higher Education, Mashhad, Iran , elias_mazrooei@yahoo.com
Abstract:   (418 Views)
Introduction: Computational modeling plays a pivotal role in bridging the gap between cognitive neuroscience and clinical neurology, particularly in the context of neurodegenerative diseases like Alzheimer's disease (AD). This study explores the application of computational models to understand cognitive systems and the pathological processes leading to cognitive decline in AD. Materials and Methods: We proposed a set of computational approaches, including neural networks and dynamical systems modeling, to simulate neural activity, synaptic plasticity, and interactions between genetic and environmental factors. Data integration from neuroimaging, genomics, and behavioral studies was crucial in enhancing the accuracy and predictive capabilities of these models. Results: The computational models provided significant insights into the mechanisms of cognition, memory formation, and their deterioration in AD. Our models identified potential biomarkers and informed strategies for therapeutic intervention, demonstrating the importance of a multi-disciplinary approach to understanding and treating cognitive decline. Conclusion: Computational modeling is essential for promoting our understanding of AD and other cognitive disorders. Future research should focus on refining these models and fostering greater interdisciplinary collaboration to develop more accurate and comprehensive simulations.
 
Keywords: Models, Biological, Brain Mapping, Cognitive Science, Dementia, Image Processing, Computer, Assisted
Full-Text [PDF 1290 kb]   (122 Downloads)    
Type of Study: Research --- Open Access, CC-BY-NC | Subject: Cognitive Neuroscience
References
1. Mazrooei e, Dastury Mr, Zendehbad SA. Comparative Analysis of Diagnostic Techniques in Alzheimer's Disease: The Role of AI, Biomarkers, and Brain Mapping Methods. The Neuroscience Journal of Shefaye Khatam. 2024; 12(3): 91-102. [DOI:10.61186/shefa.12.3.91]
2. Korczyn AD, Grinberg LT. Is Alzheimer disease a disease? Nature Reviews Neurology. 2024; 20(4): 245-51. [DOI:10.1038/s41582-024-00940-4]
3. Knopman DS, Amieva H, Petersen RC, Chételat G, Holtzman DM, Hyman BT, et al. Alzheimer disease. Nature reviews Disease primers. 2021; 7(1): 33. [DOI:10.1038/s41572-021-00269-y]
4. Hassan M, Abbas Q, Seo S-Y, Shahzadi S, Ashwal HA, Zaki N, et al. Computational modeling and biomarker studies of pharmacological treatment of Alzheimer's disease. Molecular medicine reports. 2018; 18(1): 639-55. [DOI:10.3892/mmr.2018.9044]
5. mazrooei rad e, pazhoumand h, salmani bajestani s. Separation of Healthy Individuals and Patients with Alzheimer's Disease Using the Effective Communication of Brain Signals. The Neuroscience Journal of Shefaye Khatam. 2022; 11(1): 1-12. [DOI:10.52547/shefa.11.1.1]
6. Saraceno C, Musardo S, Marcello E, Pelucchi S, Di Luca M. Modeling Alzheimer's disease: from past to future. Frontiers in pharmacology. 2013; 4: 77. [DOI:10.3389/fphar.2013.00077]
7. khazaei h, Mazrooei Rad E. Alzheimer's Disease Diagnosis Using Brain Signals and Artificial Neural Networks. The Neuroscience Journal of Shefaye Khatam. 2023; 11(3): 68-80. [DOI:10.61186/shefa.11.3.68]
8. Kumar S, Oh I, Schindler S, Lai AM, Payne PR, Gupta A. Machine learning for modeling the progression of Alzheimer disease dementia using clinical data: a systematic literature review. JAMIA open. 2021; 4(3): ooab052. [DOI:10.1093/jamiaopen/ooab052]
9. Stella E, Tsiampa AM, Stella A. Computational Models and Advanced Digital Techniques in Alzheimer's Disease. Handbook of Computational Neurodegeneration: Springer; 2023. p. 1-12. [DOI:10.1007/978-3-319-75479-6_47-1]
10. Rollo J, Crawford J, Hardy J. A dynamical systems approach for multiscale synthesis of Alzheimer's pathogenesis. Neuron. 2023; 111(14): 2126-39. [DOI:10.1016/j.neuron.2023.04.018]
11. Jang I, Li B, Riphagen JM, Dickerson BC, Salat DH, Initiative AsDN. Multiscale structural mapping of Alzheimer's disease neurodegeneration. Neuroimage: Clinical. 2022; 33: 102948. [DOI:10.1016/j.nicl.2022.102948]
12. Pinheiro R, Colón D, Fonseca-Pinto R. An Improved Alzheimer-Like Disease Computational Model via Delayed Hopfield Network with Lurie Control System for Healing. Authorea Preprints. 2023. [DOI:10.36227/techrxiv.24146775]
13. Mazrooei Rad E, Mazinani SM, akbari H. Diagnosis of Alzheimer's disease with convolutional neural network from magnetic resonance imaging. Advances in Cognitive Sciences. 2024; 25(4): 140-54.
14. Suhas S, Venugopal C, editors. MRI image preprocessing and noise removal technique using linear and nonlinear filters. 2017 International Conference on Electrical, Electronics, Communication, Computer, and Optimization Techniques (ICEECCOT); 2017: IEEE. [DOI:10.1109/ICEECCOT.2017.8284595]
15. Scarselli F, Gori M, Tsoi AC, Hagenbuchner M, Monfardini G. The graph neural network model. IEEE transactions on neural networks. 2008; 20(1): 61-80. [DOI:10.1109/TNN.2008.2005605]
16. Shao Y, Li H, Gu X, Yin H, Li Y, Miao X, et al. Distributed graph neural network training: A survey. ACM Computing Surveys. 2024; 56(8): 1-39. [DOI:10.1145/3648358]
17. Xiao H, Li L, Liu Q, Zhu X, Zhang Q. Transformers in medical image segmentation: A review. Biomedical Signal Processing and Control. 2023; 84: 104791. [DOI:10.1016/j.bspc.2023.104791]
18. Zhang P, Yan Y, Zhang X, Li C, Wang S, Huang F, Kim S, editors. TransGNN: Harnessing the Collaborative Power of Transformers and Graph Neural Networks for Recommender Systems. Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval; 2024. [DOI:10.1145/3626772.3657721]
19. Sun Y, Zhu D, Wang Y, Tian Z. GTC: GNN-Transformer Co-contrastive Learning for Self-supervised Heterogeneous Graph Representation. arXiv preprint arXiv: 240315520. 2024. [DOI:10.1016/j.neunet.2024.106645]
20. Wu Z, Jain P, Wright M, Mirhoseini A, Gonzalez JE, Stoica I. Representing long-range context for graph neural networks with global attention. Advances in Neural Information Processing Systems. 2021; 34: 13266-79.
21. mazrooei e, azarnoosh m, ghoshuni m, khalilzadeh m. Comparison of the Function of the Elman Neural Network and the Deep Neural Network for the Diagnosis of Mild Alzheimer's Disease. The Neuroscience Journal of Shefaye Khatam. 2021; 10(1): 1-11. [DOI:10.52547/shefa.10.1.1]
22. Zendehbad A, Kobravi HR, Khalilzadeh MM, Sharifi Razavi A, Sasannejad P. A New Visual Biofeedback Protocol Based on Analyzing the Muscle Synergy Patterns to Recover the Upper Limbs Movement in Ischemic Stroke Patients: A Pilot Study. The Neuroscience Journal of Shefaye Khatam. 2023; 11(3): 11-24. [DOI:10.61186/shefa.11.3.11]
23. Nagarajan I, Lakshmi Priya G. A comprehensive review on early detection of Alzheimer's disease using various deep learning techniques. Frontiers in Computer Science. 2025; 6: 1404494. [DOI:10.3389/fcomp.2024.1404494]
24. Viswan V, Shaffi N, Mahmud M, Subramanian K, Hajamohideen F. Explainable artificial intelligence in Alzheimer's disease classification: A systematic review. Cognitive Computation. 2024; 16(1): 1-44. [DOI:10.1007/s12559-023-10192-x]
25. Kale MB, Wankhede NL, Pawar RS, Ballal S, Kumawat R, Goswami M, et al. AI-driven innovations in Alzheimer's disease: Integrating early diagnosis, personalized treatment, and prognostic modelling. Ageing Research Reviews. 2024: 102497. [DOI:10.1016/j.arr.2024.102497]
26. Memudu AE, Olukade BA, Alex GS. Neurodegenerative Diseases: Alzheimer's Disease. Integrating Neuroimaging, Computational Neuroscience, and Artificial Intelligence. 128-47. [DOI:10.1201/9781032711102-8]
27. Tanveer M, Goel T, Sharma R, Malik A, Beheshti I, Del Ser J, et al. Ensemble deep learning for Alzheimer's disease characterization and estimation. Nature Mental Health. 2024: 1-13. [DOI:10.1038/s44220-024-00237-x]
28. Hafeez R, Waheed S, Naqvi SA, Maqbool F, Sarwar A, Saleem S, et al. Deep Learning in Early Alzheimers diseases Detection: A Comprehensive Survey of Classification, Segmentation, and Feature Extraction Methods. arXiv preprint arXiv: 250115293. 2025.
29. Carvalho CM, Seixas FL, Conci A, Muchaluat-Saade DC, Laks J, Boechat Y. A dynamic decision model for diagnosis of dementia, Alzheimer's disease and Mild Cognitive Impairment. Computers in Biology and Medicine. 2020; 126: 104010. [DOI:10.1016/j.compbiomed.2020.104010]



XML   Persian Abstract   Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

mazrooei E, Zendehbad S A, Salmani Bajestani S. From Cognitive Systems to Alzheimer's Disease: The Role of Computational Modeling. Shefaye Khatam 2024; 13 (1) :63-73
URL: http://shefayekhatam.ir/article-1-2543-en.html


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 13, Issue 1 (Winter 2024) Back to browse issues page
مجله علوم اعصاب شفای خاتم The Neuroscience Journal of Shefaye Khatam
Persian site map - English site map - Created in 0.08 seconds with 47 queries by YEKTAWEB 4710