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Recent advancements in neurotechnology and neuroengineering have significantly enhanced brain\u2013computer interfaces, artificial intelligence, and organoid technologies, making them pivotal instruments for diagnosis, monitoring, disease modeling, treatment development, and rehabilitation of various diseases. Nonetheless, the majority of neural interface platforms focus on unidirectional control paradigms, neglecting the need for co-adaptive systems where both the human user and the interface continually learn and adapt. This selected review consolidates information from neuroscience, artificial intelligence, and organoid engineering to identify the conceptual underpinnings of co-adaptive and symbiotic human\u2013machine interaction. We emphasize significant shortcomings in the advancement of long-term AI-facilitated co-adaptation, which permits individualized diagnostics and progression tracking in Alzheimer\u2019s disease and Parkinson\u2019s disease. We concentrate on incorporating deep learning for adaptive decoding, reinforcement learning for bidirectional feedback, and hybrid organoid\u2013brain\u2013computer interface platforms to mimic disease dynamics and expedite therapy discoveries. This study outlines the trends and limitations of the topics at hand, proposing a research framework for next-generation AI-enhanced neural interfaces targeting neurodegenerative diseases and neurological disorders that are both technologically sophisticated and clinically viable, while adhering to ethical standards.<\/jats:p>","DOI":"10.3390\/app152111316","type":"journal-article","created":{"date-parts":[[2025,10,23]],"date-time":"2025-10-23T01:14:02Z","timestamp":1761182042000},"page":"11316","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Neuroengineering Frontiers: A Selective Review of Neural Interfaces, Brain\u2013Machine Interactions, and Artificial Intelligence in Neurodegenerative Diseases"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-7173-8231","authenticated-orcid":false,"given":"Mutiyat","family":"Usman","sequence":"first","affiliation":[{"name":"Department of Mathematics and Statistics, North Carolina A&T State University, Greensboro, NC 27411, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-8929-7632","authenticated-orcid":false,"given":"Simachew","family":"Ashebir","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Statistics, North Carolina A&T State University, Greensboro, NC 27411, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-8942-6571","authenticated-orcid":false,"given":"Chioma","family":"Okey-Mbata","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, Applied Science and Technology, North Carolina A&T State University, Greensboro, NC 27411, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yeoheung","family":"Yun","sequence":"additional","affiliation":[{"name":"Bioengineering Program, Department of Chemical, Biological, and Bioengineering, North Carolina A&T State University, Greensboro, NC 27411, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7436-1405","authenticated-orcid":false,"given":"Seongtae","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Statistics, North Carolina A&T State University, Greensboro, NC 27411, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,10,22]]},"reference":[{"key":"ref_1","unstructured":"Alzheimer\u2019s Association (2025, July 17). 2025 Alzheimer\u2019s Disease Facts and Figures. 6.5 Million Americans Age 65+ with AD, Projected to 13.8 Million by 2060. Available online: https:\/\/www.alz.org\/alzheimers-dementia\/facts-figures."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1001\/jamaneurol.2017.3299","article-title":"The Emerging Evidence of the Parkinson Pandemic","volume":"75","author":"Dorsey","year":"2018","journal-title":"JAMA Neurol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1038\/s41531-020-0117-1","article-title":"Current and projected future economic burden of Parkinson\u2019s disease in the US","volume":"6","author":"Yang","year":"2020","journal-title":"npj Park. Dis."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"767","DOI":"10.1016\/S1388-2457(02)00057-3","article-title":"Brain\u2013computer interfaces for communication and control","volume":"113","author":"Wolpaw","year":"2002","journal-title":"Clin. Neurophysiol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"665","DOI":"10.1016\/j.neuron.2014.08.038","article-title":"Combining decoder design and neural adaptation in brain-machine interfaces","volume":"84","author":"Shenoy","year":"2014","journal-title":"Neuron"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1016\/S0959-4388(00)00192-6","article-title":"Behavioral planning in the prefrontal cortex","volume":"11","author":"Tanji","year":"2001","journal-title":"Curr. Opin. Neurobiol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1016\/j.neuron.2011.05.040","article-title":"Differences between neural activity in prefrontal cortex and striatum during learning of novel abstract categories","volume":"71","author":"Antzoulatos","year":"2011","journal-title":"Neuron"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1826","DOI":"10.1126\/science.8091209","article-title":"The basal ganglia and adaptive motor control","volume":"265","author":"Graybiel","year":"1994","journal-title":"Science"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Goldman-Rakic, P. (2007). Motor control function of the prefrontal cortex. Ciba Foundation Symposium 132-Motor Areas of the Cerebral Cortex: Motor Areas of The Cerebral Cortex: Ciba Foundation Symposium 132, Wiley Online Library.","DOI":"10.1002\/9780470513545.ch12"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"953","DOI":"10.1038\/35082081","article-title":"Single neurons in prefrontal cortex encode abstract rules","volume":"411","author":"Wallis","year":"2001","journal-title":"Nature"},{"key":"ref_11","first-page":"1","article-title":"Machine learning techniques for the diagnosis of Alzheimer\u2019s disease: A review","volume":"16","author":"Tanveer","year":"2020","journal-title":"ACM Trans. Multimed. Comput. Commun. Appl. (TOMM)"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"102332","DOI":"10.1016\/j.artmed.2022.102332","article-title":"Deep learning for Alzheimer\u2019s disease diagnosis: A survey","volume":"130","author":"Haghighi","year":"2022","journal-title":"Artif. Intell. Med."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Liu, M., Cheng, D., Yan, W., and Initiative, A.D.N. (2018). Classification of Alzheimer\u2019s disease by combination of convolutional and recurrent neural networks using FDG-PET images. Front. Neuroinform., 12.","DOI":"10.3389\/fninf.2018.00035"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Zhang, S., Yang, J., Zhang, Y., Zhong, J., Hu, W., Li, C., and Jiang, J. (2023). The combination of a graph neural network technique and brain imaging to diagnose neurological disorders: A review and outlook. Brain Sci., 13.","DOI":"10.3390\/brainsci13101462"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"3141","DOI":"10.1109\/JBHI.2021.3053568","article-title":"Auto-metric graph neural network based on a meta-learning strategy for the diagnosis of Alzheimer\u2019s disease","volume":"25","author":"Song","year":"2021","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1979","DOI":"10.1007\/s12559-022-10072-w","article-title":"A deep learning approach for robust, multi-oriented, and curved text detection","volume":"16","author":"Ranjbarzadeh","year":"2024","journal-title":"Cogn. Comput."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"056013","DOI":"10.1088\/1741-2552\/aace8c","article-title":"EEGNet: A compact convolutional neural network for EEG-based brain\u2013computer interfaces","volume":"15","author":"Lawhern","year":"2018","journal-title":"J. Neural Eng."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"031001","DOI":"10.1088\/1741-2552\/ab0ab5","article-title":"Deep learning for electroencephalogram (EEG) classification tasks: A review","volume":"16","author":"Craik","year":"2019","journal-title":"J. Neural Eng."},{"key":"ref_19","first-page":"2211","article-title":"Transformer-based deep learning models for EEG signal analysis: A review","volume":"31","author":"Roy","year":"2023","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_20","unstructured":"Zhang, L., Wang, M., Chen, H., and Li, R. (2024). Hybrid AI-FEM Modeling for Multiphysics Simulation of Neuroelectronic Interfaces. Electronics, 14."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1203","DOI":"10.1109\/JPROC.2008.922581","article-title":"The design of integrated circuits to observe brain activity","volume":"96","author":"Harrison","year":"2008","journal-title":"Proc. IEEE"},{"key":"ref_22","first-page":"391","article-title":"SPAD-based imaging of neural activity: Emerging photonic front-ends for neurotechnology","volume":"17","author":"Park","year":"2023","journal-title":"Nat. Photonics"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"dev166074","DOI":"10.1242\/dev.166074","article-title":"Brain organoids: Advances, applications and challenges","volume":"146","author":"Qian","year":"2019","journal-title":"Development"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1038\/nature12517","article-title":"Cerebral organoids model human brain development and microcephaly","volume":"501","author":"Lancaster","year":"2013","journal-title":"Nature"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"4047","DOI":"10.1038\/s41467-024-48452-5","article-title":"Three-dimensional liquid metal-based neuro-interfaces for human hippocampal organoids","volume":"15","author":"Wu","year":"2024","journal-title":"Nat. Commun."},{"key":"ref_26","first-page":"582","article-title":"A high-performance speech neuroprosthesis","volume":"621","author":"Anumanchipalli","year":"2023","journal-title":"Nature"},{"key":"ref_27","unstructured":"Wired Magazine (2025, June 25). Paradromics Tested a Brain Implant. Now the FDA Is Involved. Available online: https:\/\/www.wired.com\/story\/paradromics-neuralink-rival-tested-brain-implant."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"9580","DOI":"10.1038\/s41467-024-53858-2","article-title":"Constructing organoid-brain\u2013computer interfaces for neurofunctional repair after brain injury","volume":"15","author":"Hu","year":"2024","journal-title":"Nat. Commun."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"510","DOI":"10.1016\/0013-4694(88)90149-6","article-title":"Talking off the top of your head: Toward a mental prosthesis utilizing event-related brain potentials","volume":"70","author":"Farwell","year":"1988","journal-title":"Electroencephalogr. Clin. Neurophysiol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1038\/18581","article-title":"A spelling device for the paralysed","volume":"398","author":"Birbaumer","year":"1999","journal-title":"Nature"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"538","DOI":"10.1016\/j.clinph.2005.06.027","article-title":"A P300-based brain\u2013computer interface: Initial tests by ALS patients","volume":"117","author":"Sellers","year":"2006","journal-title":"Clin. Neurophysiol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1909","DOI":"10.1016\/j.clinph.2008.03.034","article-title":"A P300-based brain\u2013computer interface for people with amyotrophic lateral sclerosis","volume":"119","author":"Nijboer","year":"2008","journal-title":"Clin. Neurophysiol."},{"key":"ref_33","first-page":"111","article-title":"Brain\u2013computer interfaces in the context of neurorehabilitation: Current and future directions","volume":"32","year":"2007","journal-title":"Appl. Psychophysiol. Biofeedback"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1016\/j.neulet.2009.06.045","article-title":"How many people are able to control a P300-based brain\u2013computer interface (BCI)?","volume":"462","author":"Guger","year":"2009","journal-title":"Neurosci. Lett."},{"key":"ref_35","first-page":"34","article-title":"Smart wearable electronics for biomedical monitoring and therapy","volume":"4","author":"Li","year":"2021","journal-title":"Nat. Electron."},{"key":"ref_36","first-page":"4581","article-title":"Stretchable bioelectronics for real-time physiological monitoring and therapy","volume":"120","author":"Kim","year":"2020","journal-title":"Chem. Rev."},{"key":"ref_37","first-page":"2300787","article-title":"Wireless smart implants for continuous and real-time in vivo monitoring of tissue temperature and SAR in biomedical applications","volume":"10","author":"Yang","year":"2023","journal-title":"Adv. Sci."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1016\/j.conb.2019.03.008","article-title":"Towards neural co-processors for the brain: Combining decoding and encoding in brain\u2013computer interfaces","volume":"55","author":"Rao","year":"2019","journal-title":"Curr. Opin. Neurobiol."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Nguyen, C.H., Karavas, G.K., and Artemiadis, P. (2019). Adaptive multi-degree of freedom Brain Computer Interface using online feedback: Towards novel methods and metrics of mutual adaptation between humans and machines for BCI. PLoS ONE, 14.","DOI":"10.1371\/journal.pone.0212620"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"De Santis, D. (2021). A framework for optimizing co-adaptation in body-machine interfaces. Front. Neurorobot., 15.","DOI":"10.3389\/fnbot.2021.662181"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"179","DOI":"10.54254\/2753-8818\/2024.17988","article-title":"Brain-computer interfaces in cognitive rehabilitation for Alzheimer\u2019s disease","volume":"64","author":"Yang","year":"2024","journal-title":"Theor. Nat. Sci."},{"key":"ref_42","unstructured":"Squire, L., Berg, D., Bloom, F.E., Du Lac, S., Ghosh, A., and Spitzer, N.C. (2012). Fundamental Neuroscience, Academic Press."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"292","DOI":"10.15302\/J-ENG-2015078","article-title":"Systems neuroengineering: Understanding and interacting with the brain","volume":"1","author":"Edelman","year":"2015","journal-title":"Engineering"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"536","DOI":"10.1016\/j.tins.2006.07.004","article-title":"Brain\u2013machine interfaces: Past, present and future","volume":"29","author":"Lebedev","year":"2006","journal-title":"TRENDS Neurosci."},{"key":"ref_45","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_46","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1016\/j.neubiorev.2017.01.002","article-title":"Using deep learning to investigate the neuroimaging correlates of psychiatric and neurological disorders: Methods and applications","volume":"74","author":"Vieira","year":"2017","journal-title":"Neurosci. Biobehav. Rev."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"051001","DOI":"10.1088\/1741-2552\/ab260c","article-title":"Deep learning-based electroencephalography analysis: A systematic review","volume":"16","author":"Roy","year":"2019","journal-title":"J. Neural Eng."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"470","DOI":"10.1016\/j.bbi.2023.11.005","article-title":"Machine learning and artificial intelligence in neuroscience: A primer for researchers","volume":"115","author":"Badrulhisham","year":"2024","journal-title":"Brain Behav. Immun."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"470","DOI":"10.1126\/science.aan8866","article-title":"Big data and the industrialization of neuroscience: A safe roadmap for understanding the brain?","volume":"358","year":"2017","journal-title":"Science"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1597","DOI":"10.1038\/s41467-023-37180-x","article-title":"Catalyzing next-generation artificial intelligence through neuroai","volume":"14","author":"Zador","year":"2023","journal-title":"Nat. Commun."},{"key":"ref_51","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_52","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1016\/j.neuroimage.2018.08.042","article-title":"Reproducible evaluation of classification methods in Alzheimer\u2019s disease: Framework and application to MRI and PET data","volume":"183","author":"Burgos","year":"2018","journal-title":"NeuroImage"},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Solana-Lavalle, G., and Rosas-Romero, R. (2021). Classification of PPMI MRI scans with voxel-based morphometry and machine learning to assist in the diagnosis of Parkinson\u2019s disease. Comput. Methods Programs Biomed., 198.","DOI":"10.1016\/j.cmpb.2020.105793"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"794","DOI":"10.1109\/JBHI.2016.2547901","article-title":"High-accuracy classification of Parkinson\u2019s disease through shape analysis and surface fitting in 123I-Ioflupane SPECT imaging","volume":"21","author":"Prashanth","year":"2016","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1016\/j.jneumeth.2013.11.016","article-title":"Machine learning on brain MRI data for differential diagnosis of Parkinson\u2019s disease and Progressive Supranuclear Palsy","volume":"222","author":"Salvatore","year":"2014","journal-title":"J. Neurosci. Methods"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1001","DOI":"10.1002\/hbm.24428","article-title":"Effective feature learning and fusion of multimodality data using stage-wise deep neural network for dementia diagnosis","volume":"40","author":"Zhou","year":"2019","journal-title":"Hum. Brain Mapp."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"101645","DOI":"10.1016\/j.nicl.2018.101645","article-title":"Automated classification of Alzheimer\u2019s disease and mild cognitive impairment using a single MRI and deep neural networks","volume":"21","author":"Basaia","year":"2019","journal-title":"Neuroimage Clin."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"456","DOI":"10.1148\/radiol.2018180958","article-title":"A deep learning model to predict a diagnosis of Alzheimer disease by using 18F-FDG PET of the brain","volume":"290","author":"Ding","year":"2019","journal-title":"Radiology"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1186\/s13550-021-00795-6","article-title":"A three-stage, deep learning, ensemble approach for prognosis in patients with Parkinson\u2019s disease","volume":"11","author":"Leung","year":"2021","journal-title":"EJNMMI Res."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"15467","DOI":"10.1007\/s11042-019-7469-8","article-title":"Deep learning based diagnosis of Parkinson\u2019s disease using convolutional neural network","volume":"79","author":"Sivaranjini","year":"2020","journal-title":"Multimed. Tools Appl."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"100219","DOI":"10.1016\/j.tbench.2025.100219","article-title":"Comparative study of deep learning models for Parkinson\u2019s Disease detection","volume":"5","author":"Aliero","year":"2025","journal-title":"Benchcouncil Trans. Benchmarks, Stand. Eval."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"1813","DOI":"10.1007\/s12065-020-00470-0","article-title":"Detection of Parkinson\u2019s disease from handwriting using deep learning: A comparative study","volume":"16","author":"Taleb","year":"2023","journal-title":"Evol. Intell."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Mohammed, B.A., Senan, E.M., Rassem, T.H., Makbol, N.M., Alanazi, A.A., Al-Mekhlafi, Z.G., Almurayziq, T.S., and Ghaleb, F.A. (2021). Multi-method analysis of medical records and MRI images for early diagnosis of dementia and Alzheimer\u2019s disease based on deep learning and hybrid methods. Electronics, 10.","DOI":"10.3390\/electronics10222860"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"60761","DOI":"10.1007\/s11042-023-17867-5","article-title":"BiLSTM-ANN: Early diagnosis of Alzheimer\u2019s disease using hybrid deep learning algorithms","volume":"83","author":"Matlani","year":"2024","journal-title":"Multimed. Tools Appl."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"5117","DOI":"10.1007\/s10072-024-07649-8","article-title":"AI for the prediction of early stages of Alzheimer\u2019s disease from neuroimaging biomarkers: A narrative review of a growing field","volume":"45","author":"Rudroff","year":"2024","journal-title":"Neurol. Sci."},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Yang, J., Wang, F., Li, Z., Yang, Z., Dong, X., and Han, Q. (2023). Constructing high-order functional networks based on hypergraph for diagnosis of autism spectrum disorders. Front. Neurosci., 17.","DOI":"10.3389\/fnins.2023.1257982"},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"574","DOI":"10.1016\/j.neuroimage.2010.10.081","article-title":"Predictive markers for AD in a multi-modality framework: An analysis of MCI progression in the ADNI population","volume":"55","author":"Hinrichs","year":"2011","journal-title":"NeuroImage"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"481","DOI":"10.1016\/j.nicl.2013.10.006","article-title":"Diffusion tensor imaging of nigral degeneration in Parkinson\u2019s disease: A region-of-interest and voxel-based study at 3 T and systematic review with meta-analysis","volume":"3","author":"Schwarz","year":"2013","journal-title":"NeuroImage Clin."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1038\/s41531-022-00404-w","article-title":"Longitudinal clinical and biomarker characteristics of non-manifesting LRRK2 G2019S carriers in the PPMI cohort","volume":"8","author":"Simuni","year":"2022","journal-title":"npj Park. Dis."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"20","DOI":"10.24018\/ejece.2023.7.2.488","article-title":"Classification of Parkinson\u2019s disease using speech signal with machine learning and deep learning approaches","volume":"7","author":"Rahman","year":"2023","journal-title":"Eur. J. Electr. Eng. Comput. Sci."},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Hu, Q., Whitney, H.M., and Giger, M.L. (2020). A deep learning methodology for improved breast cancer diagnosis using multiparametric MRI. Sci. Rep., 10.","DOI":"10.1038\/s41598-020-67441-4"},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"103175","DOI":"10.1016\/j.inffus.2025.103175","article-title":"Artificial intelligence-enabled detection and assessment of Parkinson\u2019s disease using multimodal data: A survey","volume":"121","author":"Zhao","year":"2025","journal-title":"Inf. Fusion"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1038\/s41586-021-04362-w","article-title":"Brain-inspired computing needs a master plan","volume":"604","author":"Mehonic","year":"2022","journal-title":"Nature"},{"key":"ref_74","first-page":"525","article-title":"AI-enabled organoids: Construction, analysis, and application","volume":"31","author":"Bai","year":"2024","journal-title":"Bioact. Mater."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"5798","DOI":"10.1038\/s41467-023-41553-7","article-title":"A GPU-based computational framework that bridges neuron simulation and artificial intelligence","volume":"14","author":"Zhang","year":"2023","journal-title":"Nat. Commun."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1038\/nature22047","article-title":"Cell diversity and network dynamics in photosensitive human brain organoids","volume":"545","author":"Quadrato","year":"2017","journal-title":"Nature"},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"558","DOI":"10.1016\/j.stem.2019.08.002","article-title":"Complex oscillatory waves emerging from cortical organoids model early human brain network development","volume":"25","author":"Trujillo","year":"2019","journal-title":"Cell Stem Cell"},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1038\/s41576-018-0051-9","article-title":"Progress and potential in organoid research","volume":"19","author":"Rossi","year":"2018","journal-title":"Nat. Rev. Genet."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"4403","DOI":"10.1038\/s41467-022-32115-4","article-title":"Functional neuronal circuitry and oscillatory dynamics in human brain organoids","volume":"13","author":"Sharf","year":"2022","journal-title":"Nat. Commun."},{"key":"ref_80","doi-asserted-by":"crossref","unstructured":"Smirnova, L., Caffo, B.S., Gracias, D.H., Huang, Q., Morales Pantoja, I.E., Tang, B., Zack, D.J., Berlinicke, C.A., Boyd, J.L., and Harris, T.D. (2023). Organoid intelligence (OI): The new frontier in biocomputing and intelligence-in-a-dish. Front. Sci., 1.","DOI":"10.3389\/fsci.2023.1017235"},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1038\/nature22330","article-title":"Assembly of functionally integrated human forebrain spheroids","volume":"545","author":"Birey","year":"2017","journal-title":"Nature"},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"611","DOI":"10.1037\/hea0001201","article-title":"Brain system integration and message consistent health behavior change","volume":"41","author":"Jovanova","year":"2022","journal-title":"Health Psychol."},{"key":"ref_83","first-page":"1721","article-title":"Brain-region-specific organoids using mini-bioreactors for modeling human neural development","volume":"11","author":"Qian","year":"2016","journal-title":"Nature Protocols"},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"573","DOI":"10.1038\/nrn.2017.107","article-title":"The use of brain organoids to investigate neural development and disease","volume":"18","author":"Kriegstein","year":"2017","journal-title":"Nat. Rev. Neurosci."},{"key":"ref_85","first-page":"50","article-title":"Human cerebral organoids as a model for prion disease","volume":"9","author":"Groveman","year":"2021","journal-title":"Acta Neuropathol. Commun."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"5688","DOI":"10.1038\/s41467-022-33364-z","article-title":"Modeling human telencephalic development and autism-associated SHANK3 deficiency using organoids generated from single neural rosettes","volume":"13","author":"Wang","year":"2022","journal-title":"Nat. Commun."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1038\/s41586-022-05277-w","article-title":"Maturation and circuit integration of transplanted human cortical organoids","volume":"610","author":"Revah","year":"2022","journal-title":"Nature"},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"7945","DOI":"10.1038\/s41467-022-35536-3","article-title":"Multimodal monitoring of human cortical organoids implanted in mice reveal functional connection with visual cortex","volume":"13","author":"Wilson","year":"2022","journal-title":"Nat. Commun."},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/j.stem.2023.01.004","article-title":"Structural and functional integration of human forebrain organoids with the injured adult rat visual system","volume":"30","author":"Jgamadze","year":"2023","journal-title":"Cell Stem Cell"},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1038\/s41536-023-00301-7","article-title":"Cerebral organoids transplantation repairs infarcted cortex and restores impaired function after stroke","volume":"8","author":"Cao","year":"2023","journal-title":"NPJ Regen. Med."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1016\/j.stemcr.2017.05.035","article-title":"Electrical guidance of human stem cells in the rat brain","volume":"9","author":"Feng","year":"2017","journal-title":"Stem Cell Rep."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1038\/s41928-020-0390-3","article-title":"Electronic neural interfaces","volume":"3","author":"Zhang","year":"2020","journal-title":"Nat. Electron."},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"100694","DOI":"10.1016\/j.inat.2020.100694","article-title":"Brain computer interface advancement in neurosciences: Applications and issues","volume":"20","author":"Mudgal","year":"2020","journal-title":"Interdiscip. Neurosurg."},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1038\/s41591-024-03341-8","article-title":"A high-performance brain\u2013computer interface for finger decoding and quadcopter game control in an individual with paralysis","volume":"31","author":"Willsey","year":"2025","journal-title":"Nat. Med."},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"e16194","DOI":"10.2196\/16194","article-title":"An Integrated Brain-Machine Interface Platform with Thousands of Channels","volume":"21","author":"Musk","year":"2019","journal-title":"J. Med. Internet Res."},{"key":"ref_96","doi-asserted-by":"crossref","first-page":"1194","DOI":"10.1038\/s41587-021-01071-7","article-title":"Patent landscape of brain-machine interface technology","volume":"39","author":"Greenberg","year":"2021","journal-title":"Nat. Biotechnol."},{"key":"ref_97","doi-asserted-by":"crossref","first-page":"6853","DOI":"10.1021\/acs.nanolett.9b02019","article-title":"A flexible, robust, and gel-free electroencephalogram electrode for noninvasive brain-computer interfaces","volume":"19","author":"Lin","year":"2019","journal-title":"Nano Lett."},{"key":"ref_98","doi-asserted-by":"crossref","first-page":"011001","DOI":"10.1088\/1741-2552\/aaf12e","article-title":"A comprehensive review of EEG-based brain-computer interface paradigms","volume":"16","author":"Abiri","year":"2019","journal-title":"J. Neural Eng."},{"key":"ref_99","doi-asserted-by":"crossref","unstructured":"Wolpaw, J.R. (2007, January 15\u201317). Brain-computer interfaces (BCIs) for communication and control. Proceedings of the 9th International ACM SIGACCESS Conference on Computers and Accessibility, Tempe, AZ, USA.","DOI":"10.1145\/1296843.1296845"},{"key":"ref_100","doi-asserted-by":"crossref","first-page":"1533","DOI":"10.1053\/apmr.2001.26621","article-title":"Brain-computer communication: Self-regulation of slow cortical potentials for verbal communication","volume":"82","author":"Neumann","year":"2001","journal-title":"Arch. Phys. Med. Rehabil."},{"key":"ref_101","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1038\/s44222-023-00110-z","article-title":"Genetically targeted chemical assembly","volume":"2","author":"Zhang","year":"2024","journal-title":"Nat. Rev. Bioeng."},{"key":"ref_102","doi-asserted-by":"crossref","unstructured":"Kim, S.H., and Chang, M.Y. (2023). Application of human brain organoids: Opportunities and challenges in modeling human brain development and Neurodevelopmental Diseases. Int. J. Mol. Sci., 24.","DOI":"10.3390\/ijms241512528"},{"key":"ref_103","first-page":"361","article-title":"Comprehensive biocompatibility analysis of neural interfaces","volume":"13","author":"Kisban","year":"2011","journal-title":"Biomed. Microdevices"},{"key":"ref_104","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1126\/science.1260318","article-title":"Electronic dura mater for long-term multimodal neural interfaces","volume":"347","author":"Minev","year":"2015","journal-title":"Science"},{"key":"ref_105","first-page":"429","article-title":"Bioelectronics for neuroprosthetics","volume":"2","author":"Chung","year":"2019","journal-title":"Nat. Electron."},{"key":"ref_106","doi-asserted-by":"crossref","first-page":"1599","DOI":"10.1038\/nn.2973","article-title":"Flexible, foldable, actively multiplexed, high-density electrode array for mapping brain activity in vivo","volume":"14","author":"Viventi","year":"2011","journal-title":"Nat. Neurosci."},{"key":"ref_107","doi-asserted-by":"crossref","first-page":"e1601966","DOI":"10.1126\/sciadv.1601966","article-title":"Ultraflexible nanoelectronic probes form reliable, glial scar-free neural integration","volume":"3","author":"Luan","year":"2017","journal-title":"Sci. Adv."},{"key":"ref_108","doi-asserted-by":"crossref","first-page":"590","DOI":"10.1016\/j.devcel.2016.08.014","article-title":"Organoids: Modeling development and the stem cell niche in a dish","volume":"38","author":"Kretzschmar","year":"2016","journal-title":"Dev. Cell"},{"key":"ref_109","doi-asserted-by":"crossref","first-page":"3952","DOI":"10.1016\/j.neuron.2022.09.001","article-title":"In vitro neurons learn and exhibit sentience when embodied in a simulated game-world","volume":"110","author":"Kagan","year":"2022","journal-title":"Neuron"},{"key":"ref_110","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1097\/WCO.0b013e32833aa567","article-title":"Graph theoretical modeling of brain connectivity","volume":"23","author":"He","year":"2010","journal-title":"Curr. Opin. Neurol."},{"key":"ref_111","doi-asserted-by":"crossref","first-page":"2693","DOI":"10.1039\/D2LC01109C","article-title":"Vascularized human brain organoid on-chip","volume":"23","author":"Tan","year":"2023","journal-title":"Lab Chip"},{"key":"ref_112","doi-asserted-by":"crossref","first-page":"1615","DOI":"10.1039\/D1LC00535A","article-title":"Engineering neurovascular organoids with 3D printed microfluidic chips","volume":"22","author":"Salmon","year":"2022","journal-title":"Lab Chip"},{"key":"ref_113","doi-asserted-by":"crossref","unstructured":"Papamichail, L., Koch, L.S., Veerman, D., Broersen, K., and van der Meer, A.D. (2025). Organoids-on-a-chip: Microfluidic technology enables culture of organoids with enhanced tissue function and potential for disease modeling. Front. Bioeng. Biotechnol., 13.","DOI":"10.3389\/fbioe.2025.1515340"},{"key":"ref_114","doi-asserted-by":"crossref","first-page":"118529","DOI":"10.1016\/j.atherosclerosis.2024.118529","article-title":"Engineering next generation vascularized organoids","volume":"398","author":"Werschler","year":"2024","journal-title":"Atherosclerosis"},{"key":"ref_115","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1038\/s41467-022-35619-1","article-title":"Large-scale perfused tissues via synthetic 3D soft microfluidics","volume":"14","author":"Grebenyuk","year":"2023","journal-title":"Nat. Commun."},{"key":"ref_116","doi-asserted-by":"crossref","unstructured":"Aguirre, M., Escobar, M., Forero Am\u00e9zquita, S., Cubillos, D., Rinc\u00f3n, C., Vanegas, P., Tarazona, M.P., Atuesta Escobar, S., Blanco, J.C., and Celis, L.G. (2023). Application of the Yamanaka transcription factors Oct4, Sox2, Klf4, and c-Myc from the laboratory to the clinic. Genes, 14.","DOI":"10.3390\/genes14091697"},{"key":"ref_117","doi-asserted-by":"crossref","first-page":"663","DOI":"10.1016\/j.cell.2006.07.024","article-title":"Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors","volume":"126","author":"Takahashi","year":"2006","journal-title":"Cell"},{"key":"ref_118","doi-asserted-by":"crossref","unstructured":"Yan, Y., Bejoy, J., Marzano, M., and Li, Y. (2019). The use of pluripotent stem cell-derived organoids to study extracellular matrix development during neural degeneration. Cells, 8.","DOI":"10.3390\/cells8030242"},{"key":"ref_119","doi-asserted-by":"crossref","first-page":"981","DOI":"10.1038\/s41556-022-00929-5","article-title":"Enhanced cortical neural stem cell identity through short SMAD and WNT inhibition in human cerebral organoids facilitates emergence of outer radial glial cells","volume":"24","author":"Rosebrock","year":"2022","journal-title":"Nat. Cell Biol."},{"key":"ref_120","doi-asserted-by":"crossref","first-page":"766","DOI":"10.1016\/j.stem.2020.02.002","article-title":"Sliced human cortical organoids for modeling distinct cortical layer formation","volume":"26","author":"Qian","year":"2020","journal-title":"Cell Stem Cell"},{"key":"ref_121","doi-asserted-by":"crossref","unstructured":"Rathore, G.S., Ankj\u00e6r, M., Rifes, P., H\u00e4nninen, E., Calleja, F.S., Rusimbi, C., Kajtez, J., Nygaard, A.H., Piilgaard, L.S., and Dubonyte, U. (2025). Mapping early patterning events in human neural development using an in-vitro microfluidic stem cell model. bioRxiv.","DOI":"10.1101\/2025.05.23.655442"},{"key":"ref_122","doi-asserted-by":"crossref","first-page":"e45842","DOI":"10.15252\/embr.201845842","article-title":"New roles for Wnt and BMP signaling in neural anteroposterior patterning","volume":"20","author":"Polevoy","year":"2019","journal-title":"EMBO Rep."},{"key":"ref_123","doi-asserted-by":"crossref","unstructured":"Avnet, S., Mizushima, E., Severino, B., Lipreri, M.V., Scognamiglio, A., Corvino, A., Baldini, N., and Cortini, M. (2025). Antagonizing the S1P-S1P3 Axis as a Promising Anti-Angiogenic Strategy. Metabolites, 15.","DOI":"10.3390\/metabo15030178"},{"key":"ref_124","doi-asserted-by":"crossref","unstructured":"Shi, Y., Sun, L., Wang, M., Liu, J., Zhong, S., Li, R., Li, P., Guo, L., Fang, A., and Chen, R. (2020). Vascularized human cortical organoids (vOrganoids) model cortical development in vivo. PLoS Biol., 18.","DOI":"10.1371\/journal.pbio.3000705"},{"key":"ref_125","doi-asserted-by":"crossref","first-page":"85","DOI":"10.15283\/ijsc21157","article-title":"Generation of cortical brain organoid with vascularization by assembling with vascular spheroid","volume":"15","author":"Kook","year":"2022","journal-title":"Int. J. Stem Cells"},{"key":"ref_126","doi-asserted-by":"crossref","unstructured":"Ahn, Y., An, J.H., Yang, H.J., Lee, D.G., Kim, J., Koh, H., Park, Y.H., Song, B.S., Sim, B.W., and Lee, H.J. (2021). Human blood vessel organoids penetrate human cerebral organoids and form a vessel-like system. Cells, 10.","DOI":"10.3390\/cells10082036"},{"key":"ref_127","doi-asserted-by":"crossref","first-page":"653","DOI":"10.1172\/JCI200522655","article-title":"Neurotrophins promote revascularization by local recruitment of TrkB+ endothelial cells and systemic mobilization of hematopoietic progenitors","volume":"115","author":"Kermani","year":"2005","journal-title":"J. Clin. Investig."},{"key":"ref_128","first-page":"461","article-title":"Upregulation of the BDNF\/TrKB pathway promotes epithelial-mesenchymal transition, as well as the migration and invasion of cervical cancer","volume":"52","author":"Yuan","year":"2017","journal-title":"Int. J. Oncol."},{"key":"ref_129","doi-asserted-by":"crossref","first-page":"e76707","DOI":"10.7554\/eLife.76707","article-title":"Generation of vascularized brain organoids to study neurovascular interactions","volume":"11","author":"Sun","year":"2022","journal-title":"eLife"},{"key":"ref_130","doi-asserted-by":"crossref","first-page":"588","DOI":"10.1097\/WNR.0000000000001014","article-title":"Generation of human vascularized brain organoids","volume":"29","author":"Pham","year":"2018","journal-title":"Neuroreport"},{"key":"ref_131","doi-asserted-by":"crossref","first-page":"100041","DOI":"10.1016\/j.xpro.2020.100041","article-title":"Generation of vascularized neural organoids by co-culturing with mesodermal progenitor cells","volume":"1","author":"Rockel","year":"2020","journal-title":"STAR Protoc."},{"key":"ref_132","doi-asserted-by":"crossref","first-page":"114031","DOI":"10.1016\/j.celrep.2024.114031","article-title":"Generation of human cerebral organoids with a structured outer subventricular zone","volume":"43","author":"Walsh","year":"2024","journal-title":"Cell Rep."},{"key":"ref_133","doi-asserted-by":"crossref","first-page":"14892","DOI":"10.1074\/jbc.M110.181156","article-title":"Transcriptional repression in the Notch pathway: Thermodynamic characterization of CSL-MINT (Msx2-interacting nuclear target protein) complexes","volume":"286","author":"VanderWielen","year":"2011","journal-title":"J. Biol. Chem."},{"key":"ref_134","doi-asserted-by":"crossref","first-page":"419","DOI":"10.1089\/ten.tea.2019.0202","article-title":"Wnt-Notch signaling interactions during neural and astroglial patterning of human stem cells","volume":"26","author":"Bejoy","year":"2020","journal-title":"Tissue Eng. Part A"},{"key":"ref_135","doi-asserted-by":"crossref","first-page":"1356","DOI":"10.1016\/j.cell.2018.03.051","article-title":"Human-specific NOTCH2NL genes affect notch signaling and cortical neurogenesis","volume":"173","author":"Fiddes","year":"2018","journal-title":"Cell"},{"key":"ref_136","doi-asserted-by":"crossref","first-page":"1516","DOI":"10.1016\/j.stemcr.2023.05.018","article-title":"Familial Alzheimer\u2019s disease-associated PSEN1 mutations affect neurodevelopment through increased Notch signaling","volume":"18","author":"Hurley","year":"2023","journal-title":"Stem Cell Rep."},{"key":"ref_137","unstructured":"Subramaniam, N. (2025, July 19). The Process of Sprouting Angiogenesis in a Healthy Blood Vessel. Available online: https:\/\/app.biorender.com\/biorender-templates\/details\/t-5f2aaabc52f1f600aaadc271-the-process-of-sprouting-angiogenesis-in-a-healthy-blood-vessel."},{"key":"ref_138","doi-asserted-by":"crossref","first-page":"188","DOI":"10.1038\/s41586-021-03993-3","article-title":"The mouse cortico-basal ganglia-thalamic network","volume":"598","author":"Foster","year":"2021","journal-title":"Nature"},{"key":"ref_139","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1152\/physrev.00048.2021","article-title":"Cortical-subcortical interactions in goal-directed behavior","volume":"103","author":"Cruz","year":"2023","journal-title":"Physiol. Rev."},{"key":"ref_140","doi-asserted-by":"crossref","first-page":"1124","DOI":"10.1016\/j.cub.2004.06.053","article-title":"Differential corticostriatal plasticity during fast and slow motor skill learning in mice","volume":"14","author":"Costa","year":"2004","journal-title":"Curr. Biol."},{"key":"ref_141","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1016\/j.neuron.2014.05.005","article-title":"Increases in functional connectivity between prefrontal cortex and striatum during category learning","volume":"83","author":"Antzoulatos","year":"2014","journal-title":"Neuron"},{"key":"ref_142","doi-asserted-by":"crossref","first-page":"557","DOI":"10.1016\/j.tins.2012.06.008","article-title":"Striatal microcircuitry and movement disorders","volume":"35","author":"Gittis","year":"2012","journal-title":"Trends Neurosci."},{"key":"ref_143","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1146\/annurev-physiol-021115-105355","article-title":"Cortico\u2013basal ganglia circuit function in psychiatric disease","volume":"78","author":"Gunaydin","year":"2016","journal-title":"Annu. Rev. Physiol."},{"key":"ref_144","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1111\/j.1749-6632.2003.tb07477.x","article-title":"Pathophysiology of Parkinson\u2019s disease: The MPTP primate model of the human disorder","volume":"991","author":"Wichmann","year":"2003","journal-title":"Ann. N. Y. Acad. Sci."},{"key":"ref_145","doi-asserted-by":"crossref","first-page":"9629","DOI":"10.1073\/pnas.1606792113","article-title":"Human striatal recordings reveal abnormal discharge of projection neurons in Parkinson\u2019s disease","volume":"113","author":"Singh","year":"2016","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_146","doi-asserted-by":"crossref","first-page":"107422","DOI":"10.1016\/j.pharmthera.2019.107422","article-title":"Impaired chloride homeostasis in epilepsy: Molecular basis, impact on treatment, and current treatment approaches","volume":"205","author":"Auer","year":"2020","journal-title":"Pharmacol. Ther."},{"key":"ref_147","doi-asserted-by":"crossref","first-page":"4407","DOI":"10.1038\/s41380-023-02018-x","article-title":"Probing neural circuit mechanisms in Alzheimer\u2019s disease using novel technologies","volume":"28","author":"Grieco","year":"2023","journal-title":"Mol. Psychiatry"},{"key":"ref_148","doi-asserted-by":"crossref","first-page":"3587","DOI":"10.1093\/brain\/awad150","article-title":"Advances in understanding the function of alpha-synuclein: Implications for Parkinson\u2019s disease","volume":"146","author":"Calabresi","year":"2023","journal-title":"Brain"},{"key":"ref_149","doi-asserted-by":"crossref","first-page":"831","DOI":"10.1007\/s00401-020-02227-6","article-title":"Neuronal activity modulates alpha-synuclein aggregation and spreading in organotypic brain slice cultures and in vivo","volume":"140","author":"Wu","year":"2020","journal-title":"Acta Neuropathol."},{"key":"ref_150","doi-asserted-by":"crossref","first-page":"e20190811","DOI":"10.1542\/peds.2019-0811","article-title":"Prevalence and trends of developmental disabilities among children in the United States: 2009\u20132017","volume":"144","author":"Zablotsky","year":"2019","journal-title":"Pediatrics"},{"key":"ref_151","doi-asserted-by":"crossref","first-page":"1402","DOI":"10.1016\/j.brs.2019.07.005","article-title":"Theoretical principles of deep brain stimulation induced synaptic suppression","volume":"12","author":"Farokhniaee","year":"2019","journal-title":"Brain Stimul."},{"key":"ref_152","doi-asserted-by":"crossref","first-page":"949","DOI":"10.1176\/appi.ajp.2019.18121427","article-title":"Long-term outcomes of subcallosal cingulate deep brain stimulation for treatment-resistant depression","volume":"176","author":"Crowell","year":"2019","journal-title":"Am. J. Psychiatry"},{"key":"ref_153","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1080\/13554794.2024.2346987","article-title":"The effects of deep transcranial magnetic stimulation on Alzheimer\u2019s disease: A case report examining cognitive functioning, memory, and QEEG","volume":"29","author":"Shanok","year":"2023","journal-title":"Neurocase"},{"key":"ref_154","doi-asserted-by":"crossref","first-page":"3726","DOI":"10.1038\/s41467-025-59113-6","article-title":"Deep brain stimulation alleviates Parkinsonian motor deficits through desynchronizing GABA release in mice","volume":"16","author":"Xu","year":"2025","journal-title":"Nat. Commun."},{"key":"ref_155","doi-asserted-by":"crossref","first-page":"3587","DOI":"10.1038\/s41467-025-58825-z","article-title":"Shared pathway-specific network mechanisms of dopamine and deep brain stimulation for the treatment of Parkinson\u2019s disease","volume":"16","author":"Binns","year":"2025","journal-title":"Nat. Commun."},{"key":"ref_156","doi-asserted-by":"crossref","first-page":"696","DOI":"10.1016\/j.conb.2003.11.001","article-title":"Deep brain stimulation for Parkinson\u2019s disease","volume":"13","author":"Benabid","year":"2003","journal-title":"Curr. Opin. Neurobiol."},{"key":"ref_157","doi-asserted-by":"crossref","unstructured":"Alosaimi, F., Temel, Y., Hescham, S., Witzig, V.S., Almasabi, F., Tan, S.K.H., and Jahanshahi, A. (2022). High-frequency stimulation of the subthalamic nucleus induces a sustained inhibition of serotonergic system via loss of cell phenotype. Sci. Rep., 12.","DOI":"10.1038\/s41598-022-18294-6"},{"key":"ref_158","doi-asserted-by":"crossref","first-page":"651","DOI":"10.1016\/j.neuron.2005.02.014","article-title":"Deep brain stimulation for treatment-resistant depression","volume":"45","author":"Mayberg","year":"2005","journal-title":"Neuron"},{"key":"ref_159","doi-asserted-by":"crossref","unstructured":"Portillo-Lara, R., Tahirbegi, B., Chapman, C.A.R., Goding, J.A., and Green, R.A. (2021). Mind the gap: State-of-the-art technologies and applications for EEG-based brain\u2013computer interfaces. APL Bioeng., 5.","DOI":"10.1063\/5.0047237"},{"key":"ref_160","doi-asserted-by":"crossref","first-page":"635","DOI":"10.1038\/nn.2782","article-title":"Single-neuron dynamics in human focal epilepsy","volume":"14","author":"Truccolo","year":"2011","journal-title":"Nat. Neurosci."},{"key":"ref_161","first-page":"e3993","article-title":"Recording human electrocorticographic (ECoG) signals for neuroscientific research and real-time functional cortical mapping","volume":"64","author":"Hill","year":"2012","journal-title":"J. Vis. Exp."},{"key":"ref_162","doi-asserted-by":"crossref","first-page":"474","DOI":"10.1038\/s41593-018-0108-2","article-title":"Promises and limitations of human intracranial EEG","volume":"21","author":"Parvizi","year":"2018","journal-title":"Nat. Neurosci."},{"key":"ref_163","doi-asserted-by":"crossref","first-page":"1034","DOI":"10.1109\/TBME.2004.827072","article-title":"BCI2000: A general-purpose brain-computer interface (BCI) system","volume":"51","author":"Schalk","year":"2004","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_164","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.jneumeth.2003.10.009","article-title":"EEGLAB: An open source toolbox for analysis of single-trial EEG dynamics including independent component analysis","volume":"134","author":"Delorme","year":"2004","journal-title":"J. Neurosci. Methods"},{"key":"ref_165","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1146\/annurev-bioeng-062117-120853","article-title":"Electrophysiological source imaging: A noninvasive window to brain dynamics","volume":"20","author":"He","year":"2018","journal-title":"Annu. Rev. Biomed. Eng."},{"key":"ref_166","doi-asserted-by":"crossref","first-page":"117815","DOI":"10.1016\/j.neuroimage.2021.117815","article-title":"Measuring functional connectivity with wearable MEG","volume":"230","author":"Boto","year":"2021","journal-title":"NeuroImage"},{"key":"ref_167","doi-asserted-by":"crossref","unstructured":"Jiang, R., Tong, S., Wu, J., Hu, H., Zhang, R., Wang, H., Zhao, Y., Zhu, W., Li, S., and Zhang, X. (2025). A novel EEG artifact removal algorithm based on an advanced attention mechanism. Sci. Rep., 15.","DOI":"10.1038\/s41598-025-98653-1"},{"key":"ref_168","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1016\/j.neunet.2022.06.008","article-title":"Transfer learning for motor imagery based brain-computer interfaces: A tutorial","volume":"153","author":"Wu","year":"2022","journal-title":"Neural Netw."},{"key":"ref_169","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1038\/nature04970","article-title":"Neuronal ensemble control of prosthetic devices by a human with tetraplegia","volume":"442","author":"Hochberg","year":"2006","journal-title":"Nature"},{"key":"ref_170","doi-asserted-by":"crossref","first-page":"1112","DOI":"10.1016\/S1474-4422(19)30321-7","article-title":"An exoskeleton controlled by an epidural wireless brain\u2013machine interface in a tetraplegic patient: A proof-of-concept demonstration","volume":"18","author":"Benabid","year":"2019","journal-title":"Lancet Neurol."},{"key":"ref_171","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1038\/nn.4504","article-title":"Magnetoencephalography for brain electrophysiology and imaging","volume":"20","author":"Baillet","year":"2017","journal-title":"Nat. Neurosci."},{"key":"ref_172","doi-asserted-by":"crossref","first-page":"657","DOI":"10.1038\/nature26147","article-title":"Moving magnetoencephalography towards real-world applications with a wearable system","volume":"555","author":"Boto","year":"2018","journal-title":"Nature"},{"key":"ref_173","doi-asserted-by":"crossref","first-page":"2731","DOI":"10.1038\/s41467-025-58095-9","article-title":"A wearable repetitive transcranial magnetic stimulation device","volume":"16","author":"Qi","year":"2025","journal-title":"Nat. Commun."},{"key":"ref_174","doi-asserted-by":"crossref","unstructured":"Li, J., Chen, G., Li, G., Xiao, L., Jia, R., and Zhang, K. (2025). Flexible brain electronic sensors advance wearable brain-computer interface. npj Biomed. Innov., 2.","DOI":"10.1038\/s44385-025-00029-7"},{"key":"ref_175","doi-asserted-by":"crossref","first-page":"20443","DOI":"10.1073\/pnas.1214850109","article-title":"Palette of fluorinated voltage-sensitive hemicyanine dyes","volume":"109","author":"Yan","year":"2012","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_176","doi-asserted-by":"crossref","first-page":"862","DOI":"10.1016\/j.neuron.2012.02.011","article-title":"Imaging calcium in neurons","volume":"73","author":"Grienberger","year":"2012","journal-title":"Neuron"},{"key":"ref_177","doi-asserted-by":"crossref","unstructured":"He, C.X., Arroyo, E.D., Cantu, D.A., Goel, A., and Portera-Cailliau, C. (2018). A versatile method for viral transfection of calcium indicators in the neonatal mouse brain. Front. Neural Circuits, 12.","DOI":"10.3389\/fncir.2018.00056"},{"key":"ref_178","doi-asserted-by":"crossref","unstructured":"Park, J.H., Eom, Y.S., and Kim, T.H. (2023). Recent advances in aptamer-based sensors for sensitive detection of neurotransmitters. Biosensors, 13.","DOI":"10.3390\/bios13040413"},{"key":"ref_179","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1021\/acschemneuro.7b00262","article-title":"A detailed model of electroenzymatic glutamate biosensors to aid in sensor optimization and in applications in vivo","volume":"9","author":"Clay","year":"2018","journal-title":"ACS Chem. Neurosci."},{"key":"ref_180","doi-asserted-by":"crossref","first-page":"15541","DOI":"10.1021\/acs.analchem.2c04050","article-title":"Development of dual-nanopore biosensors for detection of intracellular dopamine and dopamine efflux from single PC12 cell","volume":"94","author":"Zhao","year":"2022","journal-title":"Anal. Chem."},{"key":"ref_181","doi-asserted-by":"crossref","first-page":"eadp7460","DOI":"10.1126\/sciadv.adp7460","article-title":"Nanoplasmonic aptasensor for sensitive, selective, and real-time detection of dopamine from unprocessed whole blood","volume":"10","author":"Biswas","year":"2024","journal-title":"Sci. Adv."},{"key":"ref_182","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1016\/j.neuroimage.2013.09.054","article-title":"Test-retest reliability of structural brain networks from diffusion MRI","volume":"86","author":"Buchanan","year":"2014","journal-title":"Neuroimage"},{"key":"ref_183","doi-asserted-by":"crossref","first-page":"681","DOI":"10.1016\/j.neuron.2010.05.008","article-title":"Transcranial pulsed ultrasound stimulates intact brain circuits","volume":"66","author":"Tufail","year":"2010","journal-title":"Neuron"},{"key":"ref_184","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.conb.2020.12.008","article-title":"Distinct functions of ventral CA1 and dorsal CA2 in social memory","volume":"68","author":"Watarai","year":"2021","journal-title":"Curr. Opin. Neurobiol."},{"key":"ref_185","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1016\/j.neuroscience.2021.03.005","article-title":"Functional ultrasound imaging: A new imaging modality for neuroscience","volume":"474","author":"Deffieux","year":"2021","journal-title":"Neuroscience"},{"key":"ref_186","first-page":"192","article-title":"Three-dimensional-engineered bioprinted in vitro human neural stem cell self-assembling culture model constructs of Alzheimer\u2019s disease","volume":"11","author":"Zhang","year":"2022","journal-title":"Bioact. Mater."},{"key":"ref_187","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1186\/s13024-017-0188-6","article-title":"Microglia limit the expansion of \u03b2-amyloid plaques in a mouse model of Alzheimer\u2019s disease","volume":"12","author":"Zhao","year":"2017","journal-title":"Mol. Neurodegener."},{"key":"ref_188","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.conb.2021.10.003","article-title":"Harnessing cerebral organoids for Alzheimer\u2019s disease research","volume":"72","author":"Bubnys","year":"2022","journal-title":"Curr. Opin. Neurobiol."},{"key":"ref_189","doi-asserted-by":"crossref","first-page":"113310","DOI":"10.1016\/j.celrep.2023.113310","article-title":"Cerebral organoids derived from patients with Alzheimer\u2019s disease with PSEN1\/2 mutations have defective tissue patterning and altered development","volume":"42","author":"Vanova","year":"2023","journal-title":"Cell Rep."},{"key":"ref_190","doi-asserted-by":"crossref","unstructured":"Smits, L.M., and Schwamborn, J.C. (2020). Midbrain organoids: A new tool to investigate Parkinson\u2019s Disease. Front. Cell Dev. Biol., 8.","DOI":"10.3389\/fcell.2020.00359"},{"key":"ref_191","doi-asserted-by":"crossref","first-page":"e555","DOI":"10.1002\/cpz1.555","article-title":"Generation of human ventral midbrain organoids derived from pluripotent stem cells","volume":"2","author":"Sozzi","year":"2022","journal-title":"Curr. Protoc."},{"key":"ref_192","doi-asserted-by":"crossref","first-page":"518","DOI":"10.1016\/j.stemcr.2019.01.020","article-title":"Modeling G2019S-LRRK2 sporadic Parkinson\u2019s Disease in 3D midbrain organoids","volume":"12","author":"Kim","year":"2019","journal-title":"Stem Cell Rep."},{"key":"ref_193","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1038\/s41531-019-0078-4","article-title":"Modeling Parkinson\u2019s disease in midbrain-like organoids","volume":"5","author":"Smits","year":"2019","journal-title":"npj Park. Dis."},{"key":"ref_194","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1016\/B978-0-444-59575-1.00011-9","article-title":"Derivation of dopaminergic neurons from pluripotent stem cells","volume":"200","author":"Studer","year":"2012","journal-title":"Prog. Brain Res."},{"key":"ref_195","doi-asserted-by":"crossref","unstructured":"Harischandra, D.S., Rokad, D., Ghaisas, S., Verma, S., Robertson, A., Jin, H.g., Anantharam, V., Kanthasamy, A., and Kanthasamy, A.G. (2020). Enhanced differentiation of human dopaminergic neuronal cell model for preclinical translational research in Parkinson\u2019s disease. Biochim. Biophys. Acta (BBA) Mol. Basis Dis., 1866.","DOI":"10.1016\/j.bbadis.2019.165533"},{"key":"ref_196","doi-asserted-by":"crossref","first-page":"103251","DOI":"10.1016\/j.xpro.2024.103251","article-title":"Protocol for transplantation of cells derived from human midbrain organoids into a Parkinson\u2019s disease mouse model to restore motor function","volume":"5","author":"Fu","year":"2024","journal-title":"STAR Protoc."},{"key":"ref_197","doi-asserted-by":"crossref","first-page":"e24234","DOI":"10.1016\/j.heliyon.2024.e24234","article-title":"A cell therapy approach based on iPSC-derived midbrain organoids for the restoration of motor function in a Parkinson\u2019s disease mouse model","volume":"10","author":"Fu","year":"2024","journal-title":"Heliyon"},{"key":"ref_198","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1038\/nmeth.3415","article-title":"Functional cortical neurons and astrocytes from human pluripotent stem cells in 3D culture","volume":"12","author":"Sloan","year":"2015","journal-title":"Nat. Methods"},{"key":"ref_199","doi-asserted-by":"crossref","first-page":"6275","DOI":"10.1038\/s41467-022-34005-1","article-title":"Single cell transcriptomic profiling of a neuron-astrocyte assembloid tauopathy model","volume":"13","author":"Rickner","year":"2022","journal-title":"Nat. Commun."},{"key":"ref_200","doi-asserted-by":"crossref","unstructured":"Ye, B. (2023). Approaches to vascularizing human brain organoids. PLoS Biol., 21.","DOI":"10.1371\/journal.pbio.3002141"},{"key":"ref_201","doi-asserted-by":"crossref","first-page":"4558","DOI":"10.1038\/s41380-025-03041-w","article-title":"Alzheimer\u2019s disease patient brain extracts induce multiple pathologies in novel vascularized neuroimmune organoids for disease modeling and drug discovery","volume":"30","author":"Ji","year":"2025","journal-title":"Mol. Psychiatry"},{"key":"ref_202","doi-asserted-by":"crossref","first-page":"743","DOI":"10.1038\/nmeth.4304","article-title":"Fused cerebral organoids model interactions between brain regions","volume":"14","author":"Bagley","year":"2017","journal-title":"Nat. Methods"},{"key":"ref_203","doi-asserted-by":"crossref","unstructured":"Zourray, C., Kurian, M.A., Barral, S., and Lignani, G. (2022). Electrophysiological Properties of Human Cortical Organoids: Current State of the Art and Future Directions. Front. Mol. Neurosci., 15.","DOI":"10.3389\/fnmol.2022.839366"},{"key":"ref_204","doi-asserted-by":"crossref","first-page":"2034","DOI":"10.1038\/s41592-023-02080-x","article-title":"In vitro modeling of the human dopaminergic system using spatially arranged ventral midbrain\u2013striatum\u2013cortex assembloids","volume":"20","author":"Reumann","year":"2023","journal-title":"Nat. Methods"},{"key":"ref_205","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1080\/21507740.2023.2188310","article-title":"Human cerebral organoids: Implications of ontological considerations","volume":"14","author":"Khuram","year":"2023","journal-title":"AJOB Neurosci."},{"key":"ref_206","first-page":"1216","article-title":"APOE4 exacerbates pathology in iPSC-derived cerebral organoids","volume":"11","author":"Zhou","year":"2020","journal-title":"Nat. Commun."},{"key":"ref_207","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1038\/s41531-023-00616-8","article-title":"Impaired neuron differentiation in GBA-associated Parkinson\u2019s disease is linked to cell cycle defects in organoids","volume":"9","author":"Rosety","year":"2023","journal-title":"npj Park. Dis."},{"key":"ref_208","doi-asserted-by":"crossref","first-page":"2673","DOI":"10.7150\/thno.80271","article-title":"Human iPSC-derived midbrain organoids functionally integrate into striatum circuits and restore motor function in a mouse model of Parkinson\u2019s disease","volume":"13","author":"Zheng","year":"2023","journal-title":"Theranostics"},{"key":"ref_209","doi-asserted-by":"crossref","first-page":"eabq5031","DOI":"10.1126\/sciadv.abq5031","article-title":"Shell microelectrode arrays (MEAs) for brain organoids","volume":"8","author":"Huang","year":"2022","journal-title":"Sci. Adv."},{"key":"ref_210","doi-asserted-by":"crossref","first-page":"8896","DOI":"10.1038\/ncomms9896","article-title":"Generation of functional hippocampal neurons from self-organizing human embryonic stem cell-derived dorsomedial telencephalic tissue","volume":"6","author":"Sakaguchi","year":"2015","journal-title":"Nat. Commun."},{"key":"ref_211","doi-asserted-by":"crossref","first-page":"256","DOI":"10.1016\/j.stemcr.2020.06.001","article-title":"Human iPSC-derived hippocampal spheroids: An innovative tool for stratifying Alzheimer Disease patient-specific cellular phenotypes and developing therapies","volume":"15","author":"Pomeshchik","year":"2020","journal-title":"Stem Cell Rep."},{"key":"ref_212","doi-asserted-by":"crossref","unstructured":"Nishimura, H., and Li, Y. (2024). Human pluripotent stem cell-derived models of the hippocampus. Int. J. Biochem. Cell Biol., 177.","DOI":"10.1016\/j.biocel.2024.106695"},{"key":"ref_213","doi-asserted-by":"crossref","first-page":"025005","DOI":"10.1088\/1741-2560\/8\/2\/025005","article-title":"Towards passive brain\u2013computer interfaces: Applying brain\u2013computer interface technology to human\u2013machine systems in general","volume":"8","author":"Zander","year":"2011","journal-title":"J. Neural Eng."},{"key":"ref_214","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1007\/s13347-023-00636-5","article-title":"Neuroadaptive technology and the self: A postphenomenological perspective","volume":"36","author":"Fairclough","year":"2023","journal-title":"Philos. Technol."},{"key":"ref_215","doi-asserted-by":"crossref","first-page":"14898","DOI":"10.1073\/pnas.1605155114","article-title":"Neuroadaptive technology enables implicit cursor control based on medial prefrontal cortex activity","volume":"113","author":"Zander","year":"2016","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_216","doi-asserted-by":"crossref","unstructured":"Dehais, F., Ladouce, S., Darmet, L., Nong, T.V., Ferraro, G., Tresols, J.T., Velut, S., and Labedan, P. (2023). Dual passive reactive brain-computer interface: A novel approach to human-machine symbiosis. Front. Neuroergon., 3.","DOI":"10.3389\/fnrgo.2022.824780"},{"key":"ref_217","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1186\/s13287-023-03291-x","article-title":"Human cerebral organoids: The ethical stance of scientists","volume":"14","author":"Lavazza","year":"2023","journal-title":"Stem Cell Res. Ther."},{"key":"ref_218","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/j.semcdb.2022.03.020","article-title":"Brain organoids, consciousness, ethics and moral status","volume":"144","author":"Jeziorski","year":"2023","journal-title":"Semin. Cell Dev. Biol."},{"key":"ref_219","unstructured":"(2024). Ethics need to keep up with human brain organoid research. Nat. Rev. Bioeng., 2."},{"key":"ref_220","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1186\/s13287-022-02950-9","article-title":"Organoids: A systematic review of ethical issues","volume":"13","author":"Massey","year":"2022","journal-title":"Stem Cell Res. Ther."},{"key":"ref_221","doi-asserted-by":"crossref","first-page":"1201","DOI":"10.1016\/j.cell.2019.03.018","article-title":"Metabolic and innate immune cues merge into a specific inflammatory response via the UPR","volume":"177","author":"Mogilenko","year":"2019","journal-title":"Cell"},{"key":"ref_222","doi-asserted-by":"crossref","first-page":"440","DOI":"10.1016\/j.cell.2017.08.014","article-title":"Deconstruction of corticospinal circuits for goal-directed motor skills","volume":"171","author":"Wang","year":"2017","journal-title":"Cell"},{"key":"ref_223","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1038\/521274a","article-title":"Blame it on the antibodies","volume":"521","author":"Baker","year":"2015","journal-title":"Nature"},{"key":"ref_224","doi-asserted-by":"crossref","first-page":"a031666","DOI":"10.1101\/cshperspect.a031666","article-title":"Regulation of energy metabolism by bone-derived hormones","volume":"8","author":"Mera","year":"2018","journal-title":"Cold Spring Harb. Perspect. Med."},{"key":"ref_225","doi-asserted-by":"crossref","unstructured":"Peng, W., Datta, P., Wu, Y., Dey, M., Ayan, B., Dababneh, A., and Ozbolat, I.T. (2018). Challenges in bio-fabrication of organoid cultures. Cell Biology and Translational Medicine, Volume 3, Springer.","DOI":"10.1007\/5584_2018_216"},{"key":"ref_226","doi-asserted-by":"crossref","first-page":"1495","DOI":"10.1038\/s12276-021-00641-8","article-title":"Organoids in image-based phenotypic chemical screens","volume":"53","author":"Lukonin","year":"2021","journal-title":"Exp. Mol. Med."},{"key":"ref_227","doi-asserted-by":"crossref","first-page":"606","DOI":"10.1136\/medethics-2017-104555","article-title":"Cerebral organoids: Ethical issues and consciousness assessment","volume":"44","author":"Lavazza","year":"2018","journal-title":"J. Med. Ethics"},{"key":"ref_228","doi-asserted-by":"crossref","first-page":"388","DOI":"10.1177\/1073858420943192","article-title":"Brain organoids: Tiny mirrors of human neurodevelopment and neurological disorders","volume":"27","author":"Yadav","year":"2021","journal-title":"Neuroscientist"},{"key":"ref_229","doi-asserted-by":"crossref","first-page":"218","DOI":"10.1038\/nature17969","article-title":"Cold, clumpy accretion onto an active supermassive black hole","volume":"534","author":"Tremblay","year":"2016","journal-title":"Nature"},{"key":"ref_230","unstructured":"National Institutes of Health (2025, October 10). NIH Establishes Nation\u2019s First Dedicated Organoid Development Center to Reduce Reliance on Animal Modeling, Available online: https:\/\/www.nih.gov\/news-events\/news-releases\/nih-establishes-nations-first-dedicated-organoid-development-center-reduce-reliance-animal-modeling."},{"key":"ref_231","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1038\/s41378-023-00519-x","article-title":"Transparent neural interfaces: Challenges and solutions of microengineered multimodal implants designed to measure intact neuronal populations using high-resolution electrophysiology and microscopy simultaneously","volume":"9","author":"Fekete","year":"2023","journal-title":"Microsyst. Nanoeng."},{"key":"ref_232","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1038\/s41378-022-00444-5","article-title":"Recent developments in multifunctional neural probes for simultaneous neural recording and modulation","volume":"9","author":"Li","year":"2023","journal-title":"Microsyst. Nanoeng."},{"key":"ref_233","first-page":"517","article-title":"A wearable platform for closed-loop stimulation and recording of single-neuron and local field potential activity in freely moving humans","volume":"26","author":"Topalovic","year":"2023","journal-title":"Nat. Neurosci."},{"key":"ref_234","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1038\/s41593-021-00980-9","article-title":"Large-scale neural recordings call for new insights to link brain and behavior","volume":"25","author":"Urai","year":"2022","journal-title":"Nat. Neurosci."},{"key":"ref_235","doi-asserted-by":"crossref","first-page":"1440","DOI":"10.1038\/nn.3839","article-title":"Putting big data to good use in neuroscience","volume":"17","author":"Sejnowski","year":"2014","journal-title":"Nat. Neurosci."},{"key":"ref_236","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1038\/551159a","article-title":"Four ethical priorities for neurotechnologies and AI","volume":"551","author":"Yuste","year":"2017","journal-title":"Nature"},{"key":"ref_237","doi-asserted-by":"crossref","unstructured":"Kataoka, M., Niikawa, T., Nagaishi, N., Lee, T.L., Erler, A., Savulescu, J., and Sawai, T. (2025). Beyond consciousness: Ethical, legal, and social issues in human brain organoid research and application. Eur. J. Cell Biol., 104.","DOI":"10.1016\/j.ejcb.2024.151470"},{"key":"ref_238","doi-asserted-by":"crossref","first-page":"869","DOI":"10.1016\/j.procs.2022.08.105","article-title":"Explainable AI and Interpretable Machine Learning: A Case Study in Perspective","volume":"204","author":"Vishwarupe","year":"2022","journal-title":"Procedia Comput. Sci."},{"key":"ref_239","first-page":"491","article-title":"Ultrasound modulates ion channel currents","volume":"11","author":"Tyler","year":"2011","journal-title":"Nat. Neurosci."},{"key":"ref_240","doi-asserted-by":"crossref","first-page":"2401667","DOI":"10.1002\/advs.202401667","article-title":"AI-enhanced multiphysics modeling for targeted ultrasound neurostimulation","volume":"11","author":"Deng","year":"2024","journal-title":"Adv. Sci."}],"container-title":["Applied Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2076-3417\/15\/21\/11316\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T04:36:59Z","timestamp":1761280619000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2076-3417\/15\/21\/11316"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,22]]},"references-count":240,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2025,11]]}},"alternative-id":["app152111316"],"URL":"https:\/\/doi.org\/10.3390\/app152111316","relation":{},"ISSN":["2076-3417"],"issn-type":[{"value":"2076-3417","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,22]]}}}