{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T00:17:22Z","timestamp":1776817042579,"version":"3.51.2"},"reference-count":72,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T00:00:00Z","timestamp":1758672000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>The widespread adoption of deep learning (DL) models in neuroscience research has introduced a fundamental epistemological paradox: while these models demonstrate remarkable performance in pattern recognition and prediction tasks, their inherent opacity contradicts neuroscience\u2019s foundational goal of understanding biological mechanisms. This review article examines the growing trend of using DL models to interpret neural dynamics and extract insights about brain function, arguing that the black box nature of these models fundamentally undermines their utility for mechanistic understanding. We explore the distinction between computational performance and scientific explanation, analyze the limitations of current interpretability techniques, and discuss the implications for neuroscience research methodology. We propose that the field must critically evaluate whether DL models can genuinely contribute to our understanding of neural processes or whether they merely provide sophisticated curve-fitting tools that obscure rather than illuminate the underlying biology.<\/jats:p>","DOI":"10.3390\/info16100823","type":"journal-article","created":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T09:43:12Z","timestamp":1758706992000},"page":"823","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["The Black Box Paradox: AI Models and the Epistemological Crisis in Motor Control Research"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-2223-3713","authenticated-orcid":false,"given":"Nuno","family":"Dias","sequence":"first","affiliation":[{"name":"Escola Superior de Sa\u00fade do Vale do Ave, Cooperativa de Ensino Superior Polit\u00e9cnico e Universit\u00e1rio, Rua Jos\u00e9 Ant\u00f3nio Vidal, 81, 4760-409 Vila Nova de Famalic\u00e3o, Portugal"},{"name":"HM\u2014Health and Human Movement Unit, Cooperativa de Ensino Superior Polit\u00e9cnico e Universit\u00e1rio, CRL, 4760-409 Vila Nova de Famalic\u00e3o, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6751-5269","authenticated-orcid":false,"given":"Liliana","family":"Pinho","sequence":"additional","affiliation":[{"name":"Escola Superior de Sa\u00fade do Vale do Ave, Cooperativa de Ensino Superior Polit\u00e9cnico e Universit\u00e1rio, Rua Jos\u00e9 Ant\u00f3nio Vidal, 81, 4760-409 Vila Nova de Famalic\u00e3o, Portugal"},{"name":"HM\u2014Health and Human Movement Unit, Cooperativa de Ensino Superior Polit\u00e9cnico e Universit\u00e1rio, CRL, 4760-409 Vila Nova de Famalic\u00e3o, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4815-4896","authenticated-orcid":false,"given":"Sandra","family":"Silva","sequence":"additional","affiliation":[{"name":"Escola Superior de Sa\u00fade do Vale do Ave, Cooperativa de Ensino Superior Polit\u00e9cnico e Universit\u00e1rio, Rua Jos\u00e9 Ant\u00f3nio Vidal, 81, 4760-409 Vila Nova de Famalic\u00e3o, Portugal"},{"name":"HM\u2014Health and Human Movement Unit, Cooperativa de Ensino Superior Polit\u00e9cnico e Universit\u00e1rio, CRL, 4760-409 Vila Nova de Famalic\u00e3o, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6325-6412","authenticated-orcid":false,"given":"Marta","family":"Freitas","sequence":"additional","affiliation":[{"name":"Escola Superior de Sa\u00fade do Vale do Ave, Cooperativa de Ensino Superior Polit\u00e9cnico e Universit\u00e1rio, Rua Jos\u00e9 Ant\u00f3nio Vidal, 81, 4760-409 Vila Nova de Famalic\u00e3o, Portugal"},{"name":"HM\u2014Health and Human Movement Unit, Cooperativa de Ensino Superior Polit\u00e9cnico e Universit\u00e1rio, CRL, 4760-409 Vila Nova de Famalic\u00e3o, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7924-6895","authenticated-orcid":false,"given":"V\u00e2nia","family":"Figueira","sequence":"additional","affiliation":[{"name":"Escola Superior de Sa\u00fade do Vale do Ave, Cooperativa de Ensino Superior Polit\u00e9cnico e Universit\u00e1rio, Rua Jos\u00e9 Ant\u00f3nio Vidal, 81, 4760-409 Vila Nova de Famalic\u00e3o, Portugal"},{"name":"HM\u2014Health and Human Movement Unit, Cooperativa de Ensino Superior Polit\u00e9cnico e Universit\u00e1rio, CRL, 4760-409 Vila Nova de Famalic\u00e3o, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0640-8181","authenticated-orcid":false,"given":"Francisco","family":"Pinho","sequence":"additional","affiliation":[{"name":"Escola Superior de Sa\u00fade do Vale do Ave, Cooperativa de Ensino Superior Polit\u00e9cnico e Universit\u00e1rio, Rua Jos\u00e9 Ant\u00f3nio Vidal, 81, 4760-409 Vila Nova de Famalic\u00e3o, Portugal"},{"name":"HM\u2014Health and Human Movement Unit, Cooperativa de Ensino Superior Polit\u00e9cnico e Universit\u00e1rio, CRL, 4760-409 Vila Nova de Famalic\u00e3o, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2025,9,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1089\/omi.2019.0038","article-title":"Integrating Artificial and Human Intelligence: A Partnership for Responsible Innovation in Biomedical Engineering and Medicine","volume":"24","author":"Dzobo","year":"2020","journal-title":"Omics J. Integr. Biol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"603","DOI":"10.1016\/j.neunet.2021.09.018","article-title":"Natural and Artificial Intelligence: A Brief Introduction to the Interplay Between AI and Neuroscience Research","volume":"144","author":"Macpherson","year":"2021","journal-title":"Neural Netw."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Onciul, R., Tataru, C.-I., Dumitru, A.V., Crivoi, C., Serban, M., Covache-Busuioc, R.-A., Radoi, M.P., and Toader, C. (2025). Artificial Intelligence and Neuroscience: Transformative Synergies in Brain Research and Clinical Applications. J. Clin. Med., 14.","DOI":"10.3390\/jcm14020550"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Tekin, U., and Dener, M. (2025). A Bibliometric Analysis of Studies on Artificial Intelligence in Neuroscience. Front. Neurol., 16.","DOI":"10.3389\/fneur.2025.1474484"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"101805","DOI":"10.1016\/j.inffus.2023.101805","article-title":"Explainable Artificial Intelligence (XAI): What We Know and What Is Left to Attain Trustworthy Artificial Intelligence","volume":"99","author":"Ali","year":"2023","journal-title":"Inf. Fusion"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1007\/s12559-023-10179-8","article-title":"Interpreting Black-Box Models: A Review on Explainable Artificial Intelligence","volume":"16","author":"Hassija","year":"2024","journal-title":"Cogn. Comput."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"501","DOI":"10.1146\/annurev-conmatphys-031119-050745","article-title":"Statistical Mechanics of Deep Learning","volume":"11","author":"Bahri","year":"2020","journal-title":"Annu. Rev. Condens. Matter Phys."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1146\/annurev-statistics-032921-013738","article-title":"A Brief Tour of Deep Learning from a Statistical Perspective","volume":"10","author":"Nalisnick","year":"2023","journal-title":"Annu. Rev. Stat. Appl."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1146\/annurev-neuro-092619-094115","article-title":"Computation Through Neural Population Dynamics","volume":"43","author":"Vyas","year":"2020","journal-title":"Annu. Rev. Neurosci."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Simon, G.J., and Aliferis, C. (2024). Lessons Learned from Historical Failures, Limitations and Successes of AI\/ML in Healthcare and the Health Sciences. Enduring Problems, and the Role of Best Practices. Artificial Intelligence and Machine Learning in Health Care and Medical Sciences: Best Practices and Pitfalls, Springer International Publishing.","DOI":"10.1007\/978-3-031-39355-6_12"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"240","DOI":"10.1016\/j.tins.2022.12.008","article-title":"Using Artificial Neural Networks to Ask \u2018Why\u2019 Questions of Minds and Brains","volume":"46","author":"Kanwisher","year":"2023","journal-title":"Trends Neurosci."},{"key":"ref_12","unstructured":"Ji, J., Qiu, T., Chen, B., Zhang, B., Lou, H., Wang, K., Duan, Y., He, Z., Vierling, L., and Hong, D. (2025). AI Alignment: A Comprehensive Survey. arXiv."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Ribeiro, M.T., Singh, S., and Guestrin, C. (2016). \u201cWhy Should I Trust You?\u201d: Explaining the Predictions of Any Classifier. Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ACM.","DOI":"10.1145\/2939672.2939778"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"259","DOI":"10.17705\/2msqe.00037","article-title":"Challenges of Explaining the Behavior of Black-Box AI Systems","volume":"19","author":"Asatiani","year":"2020","journal-title":"MIS Q. Exec."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1142\/S1793351X16500045","article-title":"Deep Learning","volume":"10","author":"Hao","year":"2016","journal-title":"Int. J. Semant. Comput."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep Learning","volume":"521","author":"LeCun","year":"2015","journal-title":"Nature"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"685","DOI":"10.1007\/s12525-021-00475-2","article-title":"Machine Learning and Deep Learning","volume":"31","author":"Janiesch","year":"2021","journal-title":"Electron. Mark."},{"key":"ref_18","unstructured":"Lundberg, S., and Lee, S.-I. (2017). A Unified Approach to Interpreting Model Predictions. arXiv."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1007\/s11747-019-00710-5","article-title":"Explainable AI: From Black Box to Glass Box","volume":"48","author":"Rai","year":"2020","journal-title":"J. Acad. Mark. Sci."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"102301","DOI":"10.1016\/j.inffus.2024.102301","article-title":"Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions","volume":"106","author":"Longo","year":"2024","journal-title":"Inf. Fusion"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Miller, T. (2018). Explanation in Artificial Intelligence: Insights from the Social Sciences. arXiv.","DOI":"10.1016\/j.artint.2018.07.007"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.conb.2019.01.007","article-title":"Analyzing Biological and Artificial Neural Networks: Challenges with Opportunities for Synergy?","volume":"55","author":"Barrett","year":"2019","journal-title":"Curr. Opin. Neurobiol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"124710","DOI":"10.1016\/j.eswa.2024.124710","article-title":"Survey on Explainable AI: Techniques, Challenges and Open Issues","volume":"255","author":"Abusitta","year":"2024","journal-title":"Expert Syst. Appl."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1016\/j.inffus.2019.12.012","article-title":"Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges Toward Responsible AI","volume":"58","author":"Bennetot","year":"2020","journal-title":"Inf. Fusion"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1016\/j.shpsc.2005.03.001","article-title":"Mechanisms in Biology. Introduction","volume":"36","author":"Craver","year":"2005","journal-title":"Stud. Hist. Philos. Sci. Part C Stud. Hist. Philos. Biol. Biomed. Sci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1016\/j.shpsc.2005.03.010","article-title":"Explanation: A Mechanist Alternative","volume":"36","author":"Bechtel","year":"2005","journal-title":"Stud. Hist. Philos. Sci. Part C Stud. Hist. Philos. Biol. Biomed. Sci."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"3517","DOI":"10.1128\/IAI.00623-09","article-title":"Mechanistic Science","volume":"77","author":"Casadevall","year":"2009","journal-title":"Infect. Immun."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1109\/MSP.2022.3142719","article-title":"Robust Explainability: A Tutorial on Gradient-Based Attribution Methods for Deep Neural Networks","volume":"39","author":"Nielsen","year":"2022","journal-title":"IEEE Signal Process. Mag."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"3279","DOI":"10.1109\/TKDE.2021.3126456","article-title":"A General Survey on Attention Mechanisms in Deep Learning","volume":"35","author":"Brauwers","year":"2023","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"El Houda Dehimi, N., and Tolba, Z. (2024, January 24\u201325). Attention Mechanisms in Deep Learning: Towards Explainable Artificial Intelligence. Proceedings of the 2024 6th International Conference on Pattern Analysis and Intelligent Systems (PAIS), El Oued, Algeria.","DOI":"10.1109\/PAIS62114.2024.10541203"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Montavon, G., Binder, A., Lapuschkin, S., Samek, W., and M\u00fcller, K.R. (2019). Layer-Wise Relevance Propagation: An Overview. Lecture Notes in Computer Science, Springer International Publishing.","DOI":"10.1007\/978-3-030-28954-6_10"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.neuroscience.2020.04.023","article-title":"Perceptual and Motor Effects of Muscle Co-Activation in a Force Production Task","volume":"437","author":"Cuadra","year":"2020","journal-title":"Neuroscience"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Latash, M.L., and Singh, T. (2024). Neurophysiological Basis of Motor Control, Human Kinetics. [3rd ed.].","DOI":"10.5040\/9781718243828"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Tanaka, H., Miyakoshi, M., and Makeig, S. (2018). Dynamics of Directional Tuning and Reference Frames in Humans: A High-Density EEG Study. Sci. Rep., 8.","DOI":"10.1038\/s41598-018-26609-9"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1038\/nature11129","article-title":"Neural Population Dynamics During Reaching","volume":"487","author":"Churchland","year":"2012","journal-title":"Nature"},{"key":"ref_36","unstructured":"Latash, M.L., Zatsiorsky, V.M., and Latash, M.L. (2016). Biomechanics and Motor Control: Defining Central Concepts, Elsevier\/AP."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Sternad, D. (2009). Origin and Advances of the Equilibrium-Point Hypothesis. Progress in Motor Control: A Multidisciplinary Perspective, Springer.","DOI":"10.1007\/978-0-387-77064-2"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"978","DOI":"10.1016\/j.neuron.2017.05.025","article-title":"Neural Manifolds for the Control of Movement","volume":"94","author":"Gallego","year":"2017","journal-title":"Neuron"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Merton, P.A. (1953). Speculations on the Servo-Control of Movement. Ciba Foundation Symposium\u2014The Spinal Cord, John Wiley & Sons, Ltd.","DOI":"10.1002\/9780470718827.ch18"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1775","DOI":"10.1016\/j.neuroimage.2004.05.003","article-title":"Feedforward and Feedback Processes in Motor Control","volume":"22","author":"Seidler","year":"2004","journal-title":"NeuroImage"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1038\/s41539-025-00304-7","article-title":"The Control of Movement Gradually Transitions from Feedback Control to Feedforward Adaptation Throughout Childhood","volume":"10","author":"Malone","year":"2025","journal-title":"npj Sci. Learn."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Favela, L.H.H. (2024). The Ecological Brain, Routledge.","DOI":"10.4324\/9781003009955"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Blau, J.J.C., and Wagman, J.B. (2022). Introduction to Ecological Psychology: A Lawful Approach to Perceiving, Acting, and Cognizing, Routledge. [1st ed.].","DOI":"10.4324\/9781003145691"},{"key":"ref_44","unstructured":"Gibson, J.J. (1979). The Ecological Approach to Visual Perception, Psychology Press."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1152\/jn.1990.64.1.164","article-title":"Neural Representations of the Target (Goal) of Visually Guided Arm Movements in Three Motor Areas of the Monkey","volume":"64","author":"Alexander","year":"1990","journal-title":"J. Neurophysiol."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1152\/jn.1990.64.1.133","article-title":"Preparation for Movement: Neural Representations of Intended Direction in Three Motor Areas of the Monkey","volume":"64","author":"Alexander","year":"1990","journal-title":"J. Neurophysiol."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1527","DOI":"10.1523\/JNEUROSCI.02-11-01527.1982","article-title":"On the Relations Between the Direction of Two-Dimensional Arm Movements and Cell Discharge in Primate Motor Cortex","volume":"2","author":"Georgopoulos","year":"1982","journal-title":"J. Neurosci."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Michaels, J.A., Dann, B., and Scherberger, H. (2016). Neural Population Dynamics During Reaching Are Better Explained by a Dynamical System than Representational Tuning. PLoS Comput. Biol., 12.","DOI":"10.1371\/journal.pcbi.1005175"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1038\/s41586-021-03506-2","article-title":"High-Performance Brain-to-Text Communication via Handwriting","volume":"593","author":"Willett","year":"2021","journal-title":"Nature"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"356","DOI":"10.1038\/nn.4244","article-title":"Using Goal-Driven Deep Learning Models to Understand Sensory Cortex","volume":"19","author":"Yamins","year":"2016","journal-title":"Nat. Neurosci."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1146\/annurev-vision-082114-035447","article-title":"Deep Neural Networks: A New Framework for Modeling Biological Vision and Brain Information Processing","volume":"1","author":"Kriegeskorte","year":"2015","journal-title":"Annu. Rev. Vis. Sci."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1025","DOI":"10.1038\/nn.4042","article-title":"A Neural Network That Finds a Naturalistic Solution for the Production of Muscle Activity","volume":"18","author":"Sussillo","year":"2015","journal-title":"Nat. Neurosci."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"805","DOI":"10.1038\/s41592-018-0109-9","article-title":"Inferring Single-Trial Neural Population Dynamics Using Sequential Auto-Encoders","volume":"15","author":"Pandarinath","year":"2018","journal-title":"Nat. Methods"},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Marblestone, A.H., Wayne, G., and Kording, K.P. (2016). Toward an Integration of Deep Learning and Neuroscience. Front. Comput. Neurosci., 10.","DOI":"10.3389\/fncom.2016.00094"},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Woodward, J. (2004). Making Things Happen: A Theory of Causal Explanation, Oxford University Press.","DOI":"10.1093\/0195155270.001.0001"},{"key":"ref_56","unstructured":"Lundy-Ekman, L. (2013). Neuroscience: Fundamentals for Rehabilitation, Elsevier Inc.. [4th ed.]."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1038\/nature21056","article-title":"Dermatologist-Level Classification of Skin Cancer with Deep Neural Networks","volume":"542","author":"Esteva","year":"2017","journal-title":"Nature"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"1263","DOI":"10.1161\/STROKEAHA.118.024293","article-title":"Machine Learning\u2013Based Model for Prediction of Outcomes in Acute Stroke","volume":"50","author":"Heo","year":"2019","journal-title":"Stroke"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"532","DOI":"10.1038\/nrn1427","article-title":"Optimal Feedback Control and the Neural Basis of Volitional Motor Control","volume":"5","author":"Scott","year":"2004","journal-title":"Nat. Rev. Neurosci."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1226","DOI":"10.1038\/nn963","article-title":"Optimal Feedback Control as a Theory of Motor Coordination","volume":"5","author":"Todorov","year":"2002","journal-title":"Nat. Neurosci."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"718","DOI":"10.1016\/S0959-4388(99)00028-8","article-title":"Internal Models for Motor Control and Trajectory Planning","volume":"9","author":"Kawato","year":"1999","journal-title":"Curr. Opin. Neurobiol."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1007\/s11229-005-5000-4","article-title":"A Contextual Approach to Scientific Understanding","volume":"144","author":"Dieks","year":"2005","journal-title":"Synthese"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.neunet.2018.12.002","article-title":"Deep Learning in Spiking Neural Networks","volume":"111","author":"Tavanaei","year":"2019","journal-title":"Neural Netw."},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Konishi, M., Igarashi, K.M., and Miura, K. (2023). Biologically Plausible Local Synaptic Learning Rules Robustly Implement Deep Supervised Learning. Front. Neurosci., 17.","DOI":"10.3389\/fnins.2023.1160899"},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Simon, G.J., and Aliferis, C. (2024). Overfitting, Underfitting and General Model Overconfidence and Under-Performance Pitfalls and Best Practices in Machine Learning and AI. Artificial Intelligence and Machine Learning in Health Care and Medical Sciences: Best Practices and Pitfalls, Springer International Publishing.","DOI":"10.1007\/978-3-031-39355-6_10"},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Shao, F., and Shen, Z. (2023). How Can Artificial Neural Networks Approximate the Brain?. Front. Psychol., 13.","DOI":"10.3389\/fpsyg.2022.970214"},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"967","DOI":"10.1016\/j.neuron.2019.08.034","article-title":"Engineering a Less Artificial Intelligence","volume":"103","author":"Sinz","year":"2019","journal-title":"Neuron"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"691","DOI":"10.1007\/s43681-024-00419-4","article-title":"Anthropomorphism in AI: Hype and Fallacy","volume":"4","author":"Placani","year":"2024","journal-title":"AI Ethics"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"707","DOI":"10.1007\/s43681-024-00454-1","article-title":"Anthropomorphism and AI Hype","volume":"4","author":"Barrow","year":"2024","journal-title":"AI Ethics"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1186\/2008-2231-22-53","article-title":"The Urge to Publish More and Its Consequences","volume":"22","author":"Abdollahi","year":"2014","journal-title":"DARU J. Pharm. Sci."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1007\/s12664-020-01129-5","article-title":"Publication Ethics: Role and Responsibility of Authors","volume":"40","author":"Singhal","year":"2021","journal-title":"Indian J. Gastroenterol."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"1418","DOI":"10.1093\/nsr\/nwaa129","article-title":"Computational Neuroscience: A Frontier of the 21st Century","volume":"7","author":"Wang","year":"2020","journal-title":"Natl. Sci. Rev."}],"container-title":["Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2078-2489\/16\/10\/823\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T18:48:41Z","timestamp":1760035721000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2078-2489\/16\/10\/823"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,24]]},"references-count":72,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2025,10]]}},"alternative-id":["info16100823"],"URL":"https:\/\/doi.org\/10.3390\/info16100823","relation":{},"ISSN":["2078-2489"],"issn-type":[{"value":"2078-2489","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,24]]}}}