{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,9]],"date-time":"2025-04-09T02:21:42Z","timestamp":1744165302395,"version":"3.37.3"},"reference-count":91,"publisher":"IOP Publishing","issue":"1","license":[{"start":{"date-parts":[[2023,3,24]],"date-time":"2023-03-24T00:00:00Z","timestamp":1679616000000},"content-version":"vor","delay-in-days":23,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2023,3,24]],"date-time":"2023-03-24T00:00:00Z","timestamp":1679616000000},"content-version":"tdm","delay-in-days":23,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100003554","name":"Lundbeckfonden","doi-asserted-by":"crossref","award":["R370-2021-948"],"award-info":[{"award-number":["R370-2021-948"]}],"id":[{"id":"10.13039\/501100003554","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Neuromorph. Comput. Eng."],"published-print":{"date-parts":[[2023,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Neurorobotics has emerged from the alliance between neuroscience and robotics. It pursues the investigation of reproducing living organism-like behaviors in robots by means of the embodiment of computational models of the central nervous system. This perspective article discusses the current trend of implementing tools for the pressing challenge of early-diagnosis of neurodegenerative diseases and how neurorobotics approaches can help. Recently, advances in this field have allowed the testing of some neuroscientific hypotheses related to brain diseases, but the lack of biological plausibility of developed brain models and musculoskeletal systems has limited the understanding of the underlying brain mechanisms that lead to deficits in motor and cognitive tasks. Key aspects and methods to enhance the reproducibility of natural behaviors observed in healthy and impaired brains are proposed in this perspective. In the long term, the goal is to move beyond finding therapies and look into how researchers can use neurorobotics to reduce testing on humans as well as find root causes for disease.<\/jats:p>","DOI":"10.1088\/2634-4386\/acc2e1","type":"journal-article","created":{"date-parts":[[2023,3,9]],"date-time":"2023-03-09T22:28:14Z","timestamp":1678400894000},"page":"013001","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Perspective on investigation of neurodegenerative diseases with neurorobotics approaches"],"prefix":"10.1088","volume":"3","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1825-8440","authenticated-orcid":true,"given":"Silvia","family":"Tolu","sequence":"first","affiliation":[]},{"given":"Beck","family":"Strohmer","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1644-6480","authenticated-orcid":true,"given":"Omar","family":"Zahra","sequence":"additional","affiliation":[]}],"member":"266","published-online":{"date-parts":[[2023,3,24]]},"reference":[{"key":"nceacc2e1bib1","doi-asserted-by":"publisher","first-page":"830","DOI":"10.1126\/science.1090349","article-title":"Looking backward to move forward: early detection of neurodegenerative disorders","volume":"302","author":"DeKosky","year":"2003","journal-title":"Science"},{"key":"nceacc2e1bib2","doi-asserted-by":"publisher","first-page":"54","DOI":"10.3389\/fmolb.2015.00054","article-title":"Molecular diagnostics of neurodegenerative disorders","volume":"2","author":"Agrawal","year":"2015","journal-title":"Front. Mol. Biosci."},{"key":"nceacc2e1bib3","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1159\/000435917","article-title":"The big bluff of amyotrophic lateral sclerosis diagnosis: the role of neurodegenerative disease mimics","volume":"15","author":"Bicchi","year":"2015","journal-title":"Neurodegener. Dis."},{"key":"nceacc2e1bib4","doi-asserted-by":"publisher","first-page":"284","DOI":"10.1007\/s11065-017-9357-1","article-title":"Population base rates and disease course of common psychiatric and neurodegenerative disorders","volume":"27","author":"Andren","year":"2017","journal-title":"Neuropsychol. Rev."},{"key":"nceacc2e1bib5","doi-asserted-by":"publisher","first-page":"440","DOI":"10.1038\/s41582-020-0377-8","article-title":"Applications of machine learning to diagnosis and treatment of neurodegenerative diseases","volume":"16","author":"Myszczynska","year":"2020","journal-title":"Nat. Rev. Neurol."},{"key":"nceacc2e1bib6","doi-asserted-by":"publisher","first-page":"86","DOI":"10.14802\/jmd.20062","article-title":"The case of a patient with pantothenate kinase-associated neurodegeneration presenting with a prolonged history of stuttering speech and a misdiagnosis of Parkinson\u2019s disease","volume":"14","author":"Natteru","year":"2021","journal-title":"J. Mov. Disorders"},{"key":"nceacc2e1bib7","doi-asserted-by":"publisher","DOI":"10.1101\/cshperspect.a033118","article-title":"Clinical neurology and epidemiology of the major neurodegenerative diseases","volume":"10","author":"Erkkinen","year":"2018","journal-title":"Cold Spring Harb. perspect. Biol."},{"key":"nceacc2e1bib8","doi-asserted-by":"publisher","first-page":"954","DOI":"10.1038\/s41591-021-01382-x","article-title":"Biomarkers for neurodegenerative diseases","volume":"27","author":"Hansson","year":"2021","journal-title":"Nat. Med."},{"key":"nceacc2e1bib9","doi-asserted-by":"publisher","first-page":"259","DOI":"10.3109\/1354750X.2014.904001","article-title":"The potential of microRNAs as biofluid markers of neurodegenerative diseases\u2013a systematic review","volume":"19","author":"Danborg","year":"2014","journal-title":"Biomarkers"},{"key":"nceacc2e1bib10","doi-asserted-by":"publisher","first-page":"561","DOI":"10.1038\/nrneurol.2009.135","article-title":"Biological fluid biomarkers in neurodegenerative Parkinsonism","volume":"5","author":"Eller","year":"2009","journal-title":"Nat. Rev. Neurol."},{"key":"nceacc2e1bib11","doi-asserted-by":"publisher","first-page":"1083","DOI":"10.3233\/JPD-213082","article-title":"Reaching and grasping movements in Parkinson\u2019s disease: a review","volume":"4","author":"Fasano","year":"2022","journal-title":"J. Parkinson\u2019s Dis."},{"first-page":"pp 1453","year":"2008","author":"Arbib","key":"nceacc2e1bib12"},{"key":"nceacc2e1bib13","doi-asserted-by":"publisher","first-page":"12","DOI":"10.3389\/fnbot.2018.00012","article-title":"Neurorobotics\u2014a thriving community and a promising pathway toward intelligent cognitive robots","volume":"12","author":"Ballardini","year":"2018","journal-title":"Front. Neurorobot."},{"key":"nceacc2e1bib14","doi-asserted-by":"publisher","DOI":"10.1142\/S0129065717500174","article-title":"A multiple-plasticity spiking neural network embedded in a closed-loop control system to model cerebellar pathologies","volume":"28","author":"Geminiani","year":"2018","journal-title":"Int. J. Neural Syst."},{"key":"nceacc2e1bib15","doi-asserted-by":"publisher","first-page":"26","DOI":"10.3389\/fnbot.2021.634045","article-title":"Neurorobotic models of neurological disorders: a mini review","volume":"15","author":"Pronin","year":"2021","journal-title":"Front. Neurorobot."},{"key":"nceacc2e1bib16","doi-asserted-by":"publisher","DOI":"10.1002\/04018860.s00498","article-title":"Mental disorders, computational models of. Encyclopedia of Cognitive Science","author":"O\u2019Donnell","year":"2006"},{"key":"nceacc2e1bib17","doi-asserted-by":"publisher","first-page":"122","DOI":"10.3389\/fnsys.2013.00122","article-title":"Computational models of basal-ganglia pathway functions: focus on functional neuroanatomy","volume":"7","author":"Schroll","year":"2013","journal-title":"Front. Syst. Neurosci."},{"key":"nceacc2e1bib18","doi-asserted-by":"publisher","first-page":"1181","DOI":"10.1136\/jnnp-2017-315922","article-title":"Insights into Parkinson\u2019s disease from computational models of the basal ganglia","volume":"89","author":"Humphries","year":"2018","journal-title":"J. Neurol. Neurosurg. Psychiatry"},{"key":"nceacc2e1bib19","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2022.118973","article-title":"Brain simulation as a cloud service: The Virtual Brain on EBRAINS","volume":"251","author":"Schirner","year":"2022","journal-title":"NeuroImage"},{"key":"nceacc2e1bib20","doi-asserted-by":"publisher","first-page":"2533","DOI":"10.1007\/s11948-020-00248-8","article-title":"Ethical and social aspects of neurorobotics","volume":"26","author":"Aicardi","year":"2020","journal-title":"Sci. Eng. Ethics"},{"key":"nceacc2e1bib21","doi-asserted-by":"publisher","DOI":"10.1142\/S0129065721500283","article-title":"A neurorobotic embodiment for exploring the dynamical interactions of a spiking cerebellar model and a robot arm during vision-based manipulation tasks","volume":"32","author":"Zahra","year":"2021","journal-title":"Int. J. Neural Syst."},{"key":"nceacc2e1bib22","doi-asserted-by":"publisher","first-page":"1459","DOI":"10.1016\/j.drudis.2021.02.007","article-title":"Driving success in personalized medicine through AI-enabled computational modeling","volume":"26","author":"Chakravarty","year":"2021","journal-title":"Drug Discov. Today"},{"key":"nceacc2e1bib23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13073-019-0701-3","article-title":"Digital twins to personalize medicine","volume":"12","author":"Bj\u00f6rnsson","year":"2020","journal-title":"Genome Med."},{"key":"nceacc2e1bib24","doi-asserted-by":"publisher","first-page":"166","DOI":"10.3390\/jpm12020166","article-title":"Computational models for clinical applications in personalized medicine\u2014guidelines and recommendations for data integration and model validation","volume":"12","author":"Collin","year":"2022","journal-title":"J. Pers. Med."},{"key":"nceacc2e1bib25","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41576-021-00435-8","article-title":"Human organs-on-chips for disease modelling, drug development and personalized medicine","volume":"23","author":"Willson","year":"2022","journal-title":"Nat. Rev. Genet."},{"key":"nceacc2e1bib26","doi-asserted-by":"publisher","first-page":"180","DOI":"10.1016\/j.neuroimage.2017.10.028","article-title":"Mapping human brain lesions and their functional consequences","volume":"165","author":"Karnath","year":"2018","journal-title":"NeuroImage"},{"key":"nceacc2e1bib27","doi-asserted-by":"publisher","first-page":"653","DOI":"10.1016\/j.tics.2019.05.009","article-title":"Lesion studies in contemporary neuroscience","volume":"23","author":"Vaidya","year":"2019","journal-title":"Trends Cogn. Sci."},{"key":"nceacc2e1bib28","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1006234","article-title":"Subgraphs of functional brain networks identify dynamical constraints of cognitive control","volume":"14","author":"Khambhati","year":"2018","journal-title":"PLoS Computational Biol."},{"key":"nceacc2e1bib29","doi-asserted-by":"publisher","first-page":"365","DOI":"10.1038\/nn.4478","article-title":"Building better biomarkers: brain models in translational neuroimaging","volume":"20","author":"Woo","year":"2017","journal-title":"Nat. Neurosci."},{"key":"nceacc2e1bib30","doi-asserted-by":"publisher","first-page":"56","DOI":"10.3389\/fncom.2018.00056","article-title":"Modern machine learning as a benchmark for fitting neural responses","volume":"12","author":"Benjamin","year":"2018","journal-title":"Front. Comput. Neurosci."},{"key":"nceacc2e1bib31","doi-asserted-by":"publisher","DOI":"10.3389\/fnagi.2021.633752","article-title":"Machine learning for the diagnosis of Parkinson\u2019s disease: a review of literature","volume":"13","author":"Mei","year":"2021","journal-title":"Front. Aging Neurosci."},{"key":"nceacc2e1bib32","doi-asserted-by":"publisher","first-page":"1042","DOI":"10.1016\/j.neuron.2019.03.004","article-title":"Circuit mechanisms of Parkinson\u2019s disease","volume":"101","author":"McGregor","year":"2019","journal-title":"Neuron"},{"key":"nceacc2e1bib33","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1016\/S0959-4388(02)00314-8","article-title":"Computational perspectives on dopamine function in prefrontal cortex","volume":"12","author":"Cohen","year":"2002","journal-title":"Curr. Opin. Neurobiol."},{"key":"nceacc2e1bib34","doi-asserted-by":"publisher","first-page":"550","DOI":"10.3389\/fnins.2019.00550","article-title":"Different dopaminergic dysfunctions underlying Parkinsonian akinesia and tremor","volume":"13","author":"Caligiore","year":"2019","journal-title":"Front. Neurosci."},{"key":"nceacc2e1bib35","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0189109","article-title":"The role of cortical oscillations in a spiking neural network model of the basal ganglia","volume":"12","author":"Fountas","year":"2017","journal-title":"PLoS One"},{"key":"nceacc2e1bib36","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1162\/0898929052880093","article-title":"Dynamic dopamine modulation in the basal ganglia: a neurocomputational account of cognitive deficits in medicated and nonmedicated Parkinsonism","volume":"17","author":"Frank","year":"2005","journal-title":"J. Cogn. Neurosci."},{"key":"nceacc2e1bib37","doi-asserted-by":"publisher","DOI":"10.1142\/S0129065720500574","article-title":"A basal ganglia computational model to explain the paradoxical sensorial improvement in the presence of Huntington\u2019s disease","volume":"30","author":"Gonz\u00e1lez-Redondo","year":"2020","journal-title":"Int. J. Neural Syst."},{"key":"nceacc2e1bib38","doi-asserted-by":"publisher","first-page":"ENEURO.0156-16.2016","DOI":"10.1523\/ENEURO.0156-16.2016","article-title":"Untangling basal ganglia network dynamics and function: role of dopamine depletion and inhibition investigated in a spiking network model","volume":"3","author":"Lindahl","year":"2016","journal-title":"Eneuro"},{"key":"nceacc2e1bib39","doi-asserted-by":"publisher","first-page":"3","DOI":"10.3389\/fncir.2018.00003","article-title":"Basal ganglia neuromodulation over multiple temporal and structural scales\u2014simulations of direct pathway MSNs investigate the fast onset of dopaminergic effects and predict the role of Kv4 2","volume":"12","author":"Lindroos","year":"2018","journal-title":"Front. Neural Circuits"},{"key":"nceacc2e1bib40","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1016\/j.ddmod.2017.02.005","article-title":"Capturing intracellular Ca2+ dynamics in computational models of neurodegenerative diseases","volume":"19","author":"Anwar","year":"2016","journal-title":"Drug Discov. Today"},{"key":"nceacc2e1bib41","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1172\/jci.insight.130441","article-title":"Computational modeling reveals multiple abnormalities of myocardial noradrenergic function in Lewy body diseases","volume":"4","author":"Goldstein","year":"2019","journal-title":"JCI Insight"},{"key":"nceacc2e1bib42","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2560\/8\/6\/066005","article-title":"From Parkinsonian thalamic activity to suppression by deep brain stimulation: new insights from computational modeling","volume":"8","author":"Meijer","year":"2011","journal-title":"J. Neural Eng."},{"key":"nceacc2e1bib43","doi-asserted-by":"publisher","first-page":"11","DOI":"10.3389\/fncir.2019.00011","article-title":"A computational model of loss of dopaminergic cells in Parkinson\u2019s disease due to glutamate-induced excitotoxicity","volume":"13","author":"Muddapu","year":"2019","journal-title":"Front. Neural Circuits"},{"key":"nceacc2e1bib44","first-page":"pp 3638","article-title":"Evaluation of frequency-dependent effects of deep brain stimulation in a cortex-basal ganglia-thalamus network model of Parkinson\u2019s disease","author":"Romano","year":"2020"},{"key":"nceacc2e1bib45","doi-asserted-by":"publisher","first-page":"77","DOI":"10.3389\/fncom.2018.00077","article-title":"A computational model of deep-brain stimulation for acquired dystonia in children","volume":"12","author":"Sanger","year":"2018","journal-title":"Front. Comput. Neurosci."},{"key":"nceacc2e1bib46","doi-asserted-by":"publisher","first-page":"1154","DOI":"10.1016\/j.mehy.2006.06.039","article-title":"A computational model for the Huntington disease","volume":"68","author":"Sarbaz","year":"2007","journal-title":"Med. Hypotheses"},{"key":"nceacc2e1bib47","doi-asserted-by":"publisher","first-page":"26","DOI":"10.3389\/neuro.10.026.2009","article-title":"Capturing dopaminergic modulation and bimodal membrane behaviour of striatal medium spiny neurons in accurate, reduced models","volume":"3","author":"Humphries","year":"2009","journal-title":"Front. Comput. Neurosci."},{"key":"nceacc2e1bib48","doi-asserted-by":"publisher","first-page":"338","DOI":"10.1038\/s41583-018-0002-7","article-title":"The basal ganglia and the cerebellum: nodes in an integrated network","volume":"19","author":"Bostan","year":"2018","journal-title":"Nat. Rev. Neurosci."},{"key":"nceacc2e1bib49","doi-asserted-by":"publisher","first-page":"818","DOI":"10.1093\/cercor\/12.8.818","article-title":"Machine psychology: autonomous behavior, perceptual categorization and conditioning in a brain-based device","volume":"12","author":"Krichmar","year":"2002","journal-title":"Cereb. Cortex"},{"key":"nceacc2e1bib50","doi-asserted-by":"publisher","first-page":"1103","DOI":"10.1126\/science.1148677","article-title":"Learning in and from brain-based devices","volume":"318","author":"Edelman","year":"2007","journal-title":"Science"},{"key":"nceacc2e1bib51","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1016\/j.neunet.2005.06.049","article-title":"A robot model of the basal ganglia: behavior and intrinsic processing","volume":"19","author":"Prescott","year":"2006","journal-title":"Neural Netw."},{"key":"nceacc2e1bib52","doi-asserted-by":"publisher","DOI":"10.1098\/rspb.2016.2134","article-title":"A spiking neural model of adaptive arm control","volume":"283","author":"DeWolf","year":"2016","journal-title":"Proc. R. Soc. B"},{"key":"nceacc2e1bib53","first-page":"pp 4423","article-title":"A fully spiking neural control system based on cerebellar predictive learning for sensor-guided robots","author":"Zahra","year":"2021"},{"key":"nceacc2e1bib54","doi-asserted-by":"publisher","first-page":"13","DOI":"10.3389\/fnbot.2015.00013","article-title":"Cortical spiking network interfaced with virtual musculoskeletal arm and robotic arm","volume":"9","author":"Dura-Bernal","year":"2015","journal-title":"Front. Neurorobot."},{"key":"nceacc2e1bib55","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1038\/s44172-022-00004-9","article-title":"Humanoid robots to mechanically stress human cells grown in soft bioreactors","volume":"1","author":"Mouthuy","year":"2022","journal-title":"Nat. Commun. Eng."},{"key":"nceacc2e1bib56","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1007\/s10339-016-0761-x","article-title":"Lateral specialization in unilateral spatial neglect: a cognitive robotics model","volume":"17","author":"Conti","year":"2016","journal-title":"Cogn. Process."},{"key":"nceacc2e1bib57","doi-asserted-by":"publisher","first-page":"26","DOI":"10.9758\/cpn.2022.20.1.26","article-title":"Computational neuroscience approach to psychiatry: a review on theory-driven approaches","volume":"20","author":"Khaleghi","year":"2022","journal-title":"Clin. Psychopharmacol. Neurosci."},{"key":"nceacc2e1bib58","doi-asserted-by":"publisher","first-page":"117","DOI":"10.3758\/s13415-017-0556-2","article-title":"Pure correlates of exploration and exploitation in the human brain","volume":"18","author":"Blanchard","year":"2018","journal-title":"Cogn. Affect. Behav. Neurosci."},{"key":"nceacc2e1bib59","doi-asserted-by":"publisher","first-page":"477","DOI":"10.1162\/NECO_a_00073","article-title":"Modeling basal ganglia for understanding Parkinsonian reaching movements","volume":"23","author":"Magdoom","year":"2011","journal-title":"Neural Comput."},{"key":"nceacc2e1bib60","doi-asserted-by":"publisher","first-page":"88","DOI":"10.3389\/fnbot.2021.640449","article-title":"Neuro4pd: an initial neurorobotics model of Parkinson\u2019s disease","author":"Pimentel","year":"2021","journal-title":"Front. Neurorobot."},{"key":"nceacc2e1bib61","first-page":"pp 319","article-title":"Behavior selection mechanism of two typical brain movement disorders: comparative study using robot","volume":"vol 1","author":"Yiping","year":"2010"},{"key":"nceacc2e1bib62","doi-asserted-by":"publisher","first-page":"207","DOI":"10.1007\/s10827-016-0593-9","article-title":"A biophysical model of the cortex-basal ganglia-thalamus network in the 6-OHDA lesioned rat model of Parkinson\u2019s disease","volume":"40","author":"Kumaravelu","year":"2016","journal-title":"J. Comput. Neurosci."},{"year":"2006","author":"Bishop","key":"nceacc2e1bib63"},{"key":"nceacc2e1bib64","doi-asserted-by":"publisher","first-page":"2021","DOI":"10.3390\/ijms22042021","article-title":"Machine learning and novel biomarkers for the diagnosis of Alzheimer\u2019s disease","volume":"22","author":"Galano","year":"2021","journal-title":"Int. J. Mol. Sci."},{"key":"nceacc2e1bib65","doi-asserted-by":"publisher","first-page":"444","DOI":"10.3109\/21678421.2014.893361","article-title":"RandomForest4life: a random forest for predicting ALS disease progression","volume":"15","author":"Hothorn","year":"2014","journal-title":"Amyotroph. Lateral Scler. Frontotemporal Degener."},{"key":"nceacc2e1bib66","doi-asserted-by":"publisher","first-page":"368","DOI":"10.1136\/jnnp.2007.131045","article-title":"Parkinson\u2019s disease: clinical features and diagnosis","volume":"79","author":"Jankovic","year":"2008","journal-title":"J. Neurol. Neurosurg. Psychiatry"},{"key":"nceacc2e1bib67","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1016\/j.ijpsycho.2007.11.002","article-title":"Quantitative EEG in early Alzheimer\u2019s disease patients\u2014power spectrum and complexity features","volume":"68","author":"Czigler","year":"2008","journal-title":"Int. J. Psychophysiol."},{"key":"nceacc2e1bib68","doi-asserted-by":"publisher","first-page":"398","DOI":"10.3389\/fneur.2019.00398","article-title":"Grand total EEG score can differentiate Parkinson\u2019s disease from Parkinson-related disorders","volume":"10","author":"Barcelon","year":"2019","journal-title":"Front. Neurol."},{"key":"nceacc2e1bib69","first-page":"1648","article-title":"A survey of machine learning based approaches for Parkinson disease prediction","volume":"6","author":"Bind","year":"2015","journal-title":"Int. J. Comput. Sci. Inf. Technol"},{"key":"nceacc2e1bib70","doi-asserted-by":"publisher","first-page":"1590","DOI":"10.1038\/s41467-022-28423-4","article-title":"Integrating deep learning and unbiased automated high-content screening to identify complex disease signatures in human fibroblasts","volume":"13","author":"Schiff","year":"2022","journal-title":"Nat. Commun."},{"key":"nceacc2e1bib71","doi-asserted-by":"publisher","first-page":"eaa7885","DOI":"10.1126\/sciadv.aap7885","article-title":"Deep reinforcement learning for de novo drug design","volume":"4","author":"Popova","year":"2018","journal-title":"Sci. Adv."},{"key":"nceacc2e1bib72","first-page":"20903","volume":"vol 34","author":"Saboo","year":"2021","edition":"ed"},{"key":"nceacc2e1bib73","doi-asserted-by":"publisher","first-page":"1591","DOI":"10.1002\/mds.26424","article-title":"MDS clinical diagnostic criteria for Parkinson\u2019s disease","volume":"30","author":"Postuma","year":"2015","journal-title":"Mov. Disorders"},{"key":"nceacc2e1bib74","first-page":"pp 1","article-title":"Predicting neurodegenerative diseases using a novel blood biomarkers-based model by machine learning","author":"Chiu","year":"2019"},{"key":"nceacc2e1bib75","doi-asserted-by":"publisher","first-page":"2475","DOI":"10.1007\/s00415-020-10037-9","article-title":"Biomarkers in the diagnosis and prognosis of Alzheimer\u2019s disease","volume":"267","author":"Davda","year":"2020","journal-title":"J. Neurol."},{"key":"nceacc2e1bib76","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1186\/s13195-020-00612-7","article-title":"Imaging biomarkers in neurodegeneration: current and future practices","volume":"12","author":"Young","year":"2020","journal-title":"Alz. Res. Ther."},{"key":"nceacc2e1bib77","doi-asserted-by":"publisher","first-page":"114","DOI":"10.3390\/jpm10030114","article-title":"Biomarkers for Alzheimer\u2019s disease early diagnosis","volume":"10","author":"Aus\u00f3","year":"2020","journal-title":"J. Pers. Med."},{"key":"nceacc2e1bib78","doi-asserted-by":"publisher","first-page":"22","DOI":"10.3389\/fninf.2015.00022","article-title":"A unified framework for spiking and gap-junction interactions in distributed neuronal network simulations","volume":"9","author":"Hahne","year":"2015","journal-title":"Front. NeuroInf."},{"key":"nceacc2e1bib79","doi-asserted-by":"publisher","DOI":"10.1523\/ENEURO.0458-21.2022","article-title":"Biophysical modeling of dopaminergic denervation landscapes in the striatum reveals new therapeutic strategy","volume":"9","author":"Heltberg","year":"2022","journal-title":"Eneuro"},{"key":"nceacc2e1bib80","first-page":"pp 1","article-title":"An astrocyte-modulated neuromorphic central pattern generator for hexapod robot locomotion on intel\u2019s loihi","author":"Polykretis","year":"2020"},{"key":"nceacc2e1bib81","first-page":"pp 3953","article-title":"Spike-thrift: towards energy-efficient deep spiking neural networks by limiting spiking activity via attention-guided compression","author":"Kundu","year":"2021"},{"key":"nceacc2e1bib82","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2020.102170","article-title":"Energy efficient ECG classification with spiking neural network","volume":"63","author":"Yan","year":"2021","journal-title":"Biomed. Signal Process. Control"},{"key":"nceacc2e1bib83","first-page":"pp 388","article-title":"Deep spiking neural network: energy efficiency through time based coding","author":"Han","year":"2020"},{"key":"nceacc2e1bib84","first-page":"pp 254","article-title":"Efficient neuromorphic signal processing with loihi 2","author":"Orchard","year":"2021"},{"key":"nceacc2e1bib85","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1097\/WCO.0000000000000795","article-title":"Data science in neurodegenerative disease: Its capabilities, limitations and perspectives","volume":"33","author":"Khatami","year":"2020","journal-title":"Curr. Opin. Neurol."},{"key":"nceacc2e1bib86","doi-asserted-by":"publisher","DOI":"10.1117\/1.JEI.31.1.010901","article-title":"Review of spike-based neuromorphic computing for brain-inspired vision: biology, algorithms and hardware","volume":"31","author":"Hendy","year":"2022","journal-title":"J. Electron. Imaging"},{"key":"nceacc2e1bib87","doi-asserted-by":"publisher","first-page":"2","DOI":"10.3389\/fnbot.2017.00002","article-title":"Connecting artificial brains to robots in a comprehensive simulation framework: the neurorobotics platform","volume":"11","author":"Falotico","year":"2017","journal-title":"Front. Neurorobot."},{"key":"nceacc2e1bib88","doi-asserted-by":"publisher","first-page":"642","DOI":"10.1016\/j.neunet.2008.03.014","article-title":"Central pattern generators for locomotion control in animals and robots: a review","volume":"21","author":"Ijspeert","year":"2008","journal-title":"Neural Netw."},{"key":"nceacc2e1bib89","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41598-017-13766-6","article-title":"In vivo neuromechanics: decoding causal motor neuron behavior with resulting musculoskeletal function","volume":"7","author":"Sartori","year":"2017","journal-title":"Sci. Rep."},{"key":"nceacc2e1bib90","doi-asserted-by":"publisher","DOI":"10.1007\/s40430-022-03692-8","article-title":"A review on the application of autonomous and intelligent robotic devices in medical rehabilitation","volume":"44","author":"Garcia-Gonzalez","year":"2022","journal-title":"J. Braz. Soc. Mech. Sci. Eng."},{"key":"nceacc2e1bib91","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s40846-016-0115-2","article-title":"The three laws of neurorobotics: a review on what neurorehabilitation robots should do for patients and clinicians","volume":"36","author":"Iosa","year":"2016","journal-title":"J. Med. Biol. Eng."}],"container-title":["Neuromorphic Computing and Engineering"],"original-title":[],"link":[{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/2634-4386\/acc2e1","content-type":"text\/html","content-version":"am","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/2634-4386\/acc2e1\/pdf","content-type":"application\/pdf","content-version":"am","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/2634-4386\/acc2e1","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/2634-4386\/acc2e1\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/2634-4386\/acc2e1\/pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/2634-4386\/acc2e1\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/2634-4386\/acc2e1\/pdf","content-type":"application\/pdf","content-version":"am","intended-application":"similarity-checking"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/2634-4386\/acc2e1\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,3,24]],"date-time":"2023-03-24T10:23:25Z","timestamp":1679653405000},"score":1,"resource":{"primary":{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/2634-4386\/acc2e1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,1]]},"references-count":91,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2023,3,24]]},"published-print":{"date-parts":[[2023,3,1]]}},"URL":"https:\/\/doi.org\/10.1088\/2634-4386\/acc2e1","relation":{},"ISSN":["2634-4386"],"issn-type":[{"type":"electronic","value":"2634-4386"}],"subject":[],"published":{"date-parts":[[2023,3,1]]},"assertion":[{"value":"Perspective on investigation of neurodegenerative diseases with neurorobotics approaches","name":"article_title","label":"Article Title"},{"value":"Neuromorphic Computing and Engineering","name":"journal_title","label":"Journal Title"},{"value":"paper","name":"article_type","label":"Article Type"},{"value":"\u00a9 2023 The Author(s). Published by IOP Publishing Ltd","name":"copyright_information","label":"Copyright Information"},{"value":"2022-05-31","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2023-03-09","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2023-03-24","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}