{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,25]],"date-time":"2026-04-25T10:55:51Z","timestamp":1777114551231,"version":"3.51.4"},"reference-count":54,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2024,9,1]],"date-time":"2024-09-01T00:00:00Z","timestamp":1725148800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2024,9,1]],"date-time":"2024-09-01T00:00:00Z","timestamp":1725148800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2024,9,1]],"date-time":"2024-09-01T00:00:00Z","timestamp":1725148800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2024,9,1]],"date-time":"2024-09-01T00:00:00Z","timestamp":1725148800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2024,9,1]],"date-time":"2024-09-01T00:00:00Z","timestamp":1725148800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2024,9,1]],"date-time":"2024-09-01T00:00:00Z","timestamp":1725148800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,9,1]],"date-time":"2024-09-01T00:00:00Z","timestamp":1725148800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/100019217","name":"AlMaarefa University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100019217","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Journal of Neuroscience Methods"],"published-print":{"date-parts":[[2024,9]]},"DOI":"10.1016\/j.jneumeth.2024.110203","type":"journal-article","created":{"date-parts":[[2024,6,15]],"date-time":"2024-06-15T02:46:07Z","timestamp":1718419567000},"page":"110203","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":10,"special_numbering":"C","title":["Brain-computer interfaces inspired spiking neural network model for depression stage identification"],"prefix":"10.1016","volume":"409","author":[{"given":"M. Angelin","family":"Ponrani","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Monika","family":"Anand","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mahmood","family":"Alsaadi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ashit Kumar","family":"Dutta","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Roma","family":"Fayaz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sojomon","family":"Mathew","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mousmi Ajay","family":"Chaurasia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Sunila","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Manisha","family":"Bhende","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.jneumeth.2024.110203_bib1","doi-asserted-by":"crossref","unstructured":"Abstract of the joint meetings of the 23rd annual meeting of the Japan neuroscience society and the 10th annual meeting of the Japanese neural network society Yokohama, Japan, september 4\u20136, 2000 Plenary lecture,NeuroscienceResearch,Volume 38, Supplement 1, 2000, Pages S1-S189, ISSN 0168-0102, https:\/\/doi.org\/10.1016\/S0168-0102(00)82943-0.","DOI":"10.1016\/S0168-0102(00)82943-0"},{"key":"10.1016\/j.jneumeth.2024.110203_bib2","doi-asserted-by":"crossref","unstructured":"Abstracts from the 2016 Joint Meeting of the North American Neuromodulation Society and the Neural Interfaces Conference: \u201cWhere Science Meets Innovation\u201d,Neuromodulation: Technology at the Neural Interface,Volume 20, Issue 2, 2017, Pages e1-e108,ISSN 1094-7159, https:\/\/doi.org\/10.1111\/ner.12572.","DOI":"10.1111\/ner.12572"},{"key":"10.1016\/j.jneumeth.2024.110203_bib3","doi-asserted-by":"crossref","unstructured":"Abstracts from the 41st Neural Interfaces Conference June 23\u201325, 2014 Dallas, Texas, USA,Neuromodulation: Technology at the Neural Interface,Volume 17, Issue 5, 2014, Pages e40-e127,ISSN 1094-7159, https:\/\/doi.org\/10.1111\/ner.12232.","DOI":"10.1111\/ner.12232"},{"key":"10.1016\/j.jneumeth.2024.110203_bib4","article-title":"Unleashing the potential of gallium oxide: a paradigm shift in optoelectronic applications for image sensing and neuromorphic computing applications","volume":"Volume 38","author":"Al-Hardan","year":"2023","journal-title":"Mater. Today Phys."},{"key":"10.1016\/j.jneumeth.2024.110203_bib5","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.cogsys.2018.04.001","article-title":"From cybernetics to brain theory, and more: A memoir","volume":"Volume 50","author":"Arbib","year":"2018","journal-title":"Cogn. Syst. Res."},{"key":"10.1016\/j.jneumeth.2024.110203_bib6","series-title":"Artificial Neural Network for Drug Design, Delivery and Disposition","first-page":"29","article-title":"Chapter 3 - Computational Basis of Neural Elements,Editor(s): Munish Puri, Yashwant Pathak, Vijay Kumar Sutariya, Srinivas Tipparaju, Wilfrido Moreno","author":"Arslan","year":"2016"},{"key":"10.1016\/j.jneumeth.2024.110203_bib7","article-title":"Chandra Sekhara Rao Annavarapu, AnnushreeBablani,Machine learning algorithms for social media analysis: a survey","volume":"Volume 40","author":"Balaji","year":"2021","journal-title":"Comput. Sci. Rev."},{"key":"10.1016\/j.jneumeth.2024.110203_bib8","doi-asserted-by":"crossref","unstructured":"Dipali Bansal, Rashima Mahajan, Chapter 2 - EEG-Based Brain-Computer Interfacing (BCI),Editor(s): Dipali Bansal, Rashima Mahajan,EEG-Based Brain-Computer Interfaces, Academic Press, 2019, Pages 21-71,ISBN 9780128146873, https:\/\/doi.org\/10.1016\/B978-0-12-814687-3.00002-8.","DOI":"10.1016\/B978-0-12-814687-3.00002-8"},{"key":"10.1016\/j.jneumeth.2024.110203_bib9","doi-asserted-by":"crossref","first-page":"806","DOI":"10.1016\/j.neubiorev.2021.08.014","article-title":"Bridging the gap between emotion and joint action","volume":"Volume 131","author":"Bie\u0144kiewicz","year":"2021","journal-title":"Neurosci. Biobehav. Rev."},{"issue":"Issue 5","key":"10.1016\/j.jneumeth.2024.110203_bib10","article-title":"Network structure mediates functional reorganization induced by optogenetic stimulation of non-human primate sensorimotor cortex","volume":"Volume 25","author":"Bloch","year":"2022","journal-title":"iScience"},{"issue":"1","key":"10.1016\/j.jneumeth.2024.110203_bib11","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10143-016-0709-8","article-title":"Current and future strategies for treatment of glioma","volume":"40","author":"Bush","year":"2017","journal-title":"Neurosurg. Rev."},{"key":"10.1016\/j.jneumeth.2024.110203_bib12","doi-asserted-by":"crossref","first-page":"1065","DOI":"10.3390\/jcm12031065","article-title":"Short-term and long-term outcomes of fetal ventriculomegaly beyond gestational 37 weeks: a retrospective cohort study","volume":"12","author":"Chen","year":"2023","journal-title":"J. Clin. Med"},{"issue":"8","key":"10.1016\/j.jneumeth.2024.110203_bib13","doi-asserted-by":"crossref","first-page":"2702","DOI":"10.1007\/s12555-021-0430-4","article-title":"PDBNet: parallel dual branch network for real-time semantic segmentation","volume":"20","author":"Dai","year":"2022","journal-title":"Int. J. Control, Autom. Syst."},{"key":"10.1016\/j.jneumeth.2024.110203_bib14","first-page":"107","article-title":"Incorporatingbehavioral and sensory context into spectro-temporal models of auditory encoding","volume":"Volume 360","author":"David","year":"2018","journal-title":"HearingResearch"},{"issue":"Issues 4\u20136","key":"10.1016\/j.jneumeth.2024.110203_bib15","doi-asserted-by":"crossref","first-page":"540","DOI":"10.1016\/j.jphysparis.2005.09.008","article-title":"Exploring spike transfer through the thalamus using hybrid artificial-biological neuronal networks","volume":"Volume 98","author":"Debay","year":"2004","journal-title":"J. Physiol. -Paris"},{"issue":"24","key":"10.1016\/j.jneumeth.2024.110203_bib16","doi-asserted-by":"crossref","first-page":"7354","DOI":"10.3390\/s20247354","article-title":"Interpretability of spatiotemporal dynamics of the brain processes followed by mindfulness intervention in a brain-inspired spiking neural network architecture","volume":"20","author":"Doborjeh","year":"2020","journal-title":"Sensors"},{"key":"10.1016\/j.jneumeth.2024.110203_bib17","series-title":"Chapter 7 - Sex differences in invasive and noninvasiveneurotechnologies,Editor(s): Davide Cirillo, Silvina Catuara-Solarz, Emre Guney,Sex and Gender Bias in Technology and Artificial Intelligence","first-page":"133","author":"Dubreuil-Vall","year":"2022"},{"issue":"Issue 3","key":"10.1016\/j.jneumeth.2024.110203_bib18","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1016\/j.plrev.2014.04.005","article-title":"Toward a computational framework for cognitive biology: unifying approaches from cognitive neuroscience and comparative cognition","volume":"Volume 11","author":"Fitch","year":"2014","journal-title":"Phys. Life Rev."},{"issue":"Issue 11","key":"10.1016\/j.jneumeth.2024.110203_bib19","volume":"Volume 4","year":"2023","journal-title":"Cell Rep. Phys. Sci."},{"key":"10.1016\/j.jneumeth.2024.110203_bib20","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1016\/j.neucom.2020.02.114","article-title":"Simulation, visualization and analysis tools for pattern recognition assessment with spiking neuronal networks","volume":"Volume 400","author":"Galindo","year":"2020","journal-title":"Neurocomputing"},{"issue":"9","key":"10.1016\/j.jneumeth.2024.110203_bib21","doi-asserted-by":"crossref","first-page":"2927","DOI":"10.1007\/s12555-022-0452-6","article-title":"Dynamic event-triggered exponential synchronization for neural networks with random controller gain perturbations","volume":"21","author":"Ge","year":"2023","journal-title":"Int. J. Control, Autom. Syst."},{"key":"10.1016\/j.jneumeth.2024.110203_bib22","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.cogsys.2020.10.008","article-title":"A bioinspired model of short-term satiety of hunger influenced by food properties in virtual creatures","volume":"Volume 66","author":"G\u00f3mez-Mart\u00ednez","year":"2021","journal-title":"Cogn. Syst. Res."},{"key":"10.1016\/j.jneumeth.2024.110203_bib23","first-page":"66","article-title":"On identification of driving-induced stress using electroencephalogram signals: a framework based on wearable safety-critical scheme and machine learning","volume":"Volume 53","author":"Halim","year":"2020","journal-title":"InformationFusion"},{"issue":"Issue 2","key":"10.1016\/j.jneumeth.2024.110203_bib24","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1016\/j.neuron.2017.06.011","article-title":"Neuroscience-inspired artificial intelligence","volume":"Volume 95","author":"Hassabis","year":"2017","journal-title":"Neuron"},{"key":"10.1016\/j.jneumeth.2024.110203_bib25","doi-asserted-by":"crossref","DOI":"10.1155\/2022\/3454167","article-title":"Vision transformer and deep sequence learning for human activity recognition in surveillance videos","volume":"2022","author":"Hussain","year":"2022","journal-title":"Comput. Intell. Neurosci."},{"key":"10.1016\/j.jneumeth.2024.110203_bib26","doi-asserted-by":"crossref","first-page":"632","DOI":"10.1016\/j.aej.2023.11.017","article-title":"Shots segmentation-based optimized dual-stream framework for robust human activity recognition in surveillance video","volume":"91","author":"Hussain","year":"2024","journal-title":"Alex. Eng. J."},{"key":"10.1016\/j.jneumeth.2024.110203_bib27","doi-asserted-by":"crossref","first-page":"1347856","DOI":"10.3389\/fonc.2024.1347856","article-title":"A novel fusion framework of deep bottleneck residual convolutional neural network for breast cancer classification from mammogram images","volume":"14","author":"Jabeen","year":"2024","journal-title":"Front. Oncol."},{"key":"10.1016\/j.jneumeth.2024.110203_bib28","article-title":"Emerging synaptic devices: from two-terminal memristors to multiterminal neuromorphic transistors","volume":"Volume 8","author":"Jiang","year":"2019","journal-title":"Mater. Today Nano"},{"key":"10.1016\/j.jneumeth.2024.110203_bib29","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.inffus.2020.11.008","article-title":"A review of hidden markov models and recurrent neural networks for event detection and localization in biomedical signals","volume":"Volume 69","author":"Khalifa","year":"2021","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.jneumeth.2024.110203_bib30","doi-asserted-by":"crossref","DOI":"10.1155\/2022\/7897669","article-title":"A novel and effective brain tumor classification model using deep feature fusion and famous machine learning classifiers","volume":"2022","author":"Kibriya","year":"2022","journal-title":"Comput. Intell. Neurosci."},{"key":"10.1016\/j.jneumeth.2024.110203_bib31","doi-asserted-by":"crossref","DOI":"10.1016\/j.neuroimage.2021.118017","article-title":"Combining brain perturbation and neuroimaging in non-human primates","volume":"Volume 235","author":"Klink","year":"2021","journal-title":"NeuroImage"},{"key":"10.1016\/j.jneumeth.2024.110203_bib32","doi-asserted-by":"crossref","first-page":"720","DOI":"10.3390\/biomedicines9070720","article-title":"Towards clinical application of artificial intelligence in ultrasound imaging","volume":"9","author":"Komatsu","year":"2021","journal-title":"Biomedicines"},{"key":"10.1016\/j.jneumeth.2024.110203_bib33","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2023.105283","article-title":"Automated classification of common maternal fetal ultrasound planes using multi-layer perceptron with deep feature integration","volume":"86","author":"Krishna","year":"2023","journal-title":"Biomed. Signal Process Control"},{"key":"10.1016\/j.jneumeth.2024.110203_bib34","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1016\/j.neunet.2019.08.029","article-title":"Deep learning and deep knowledge representation in spiking neural networks for brain-computer interfaces","volume":"121","author":"Kumarasinghe","year":"2020","journal-title":"Neural Netw."},{"issue":"Issue 3","key":"10.1016\/j.jneumeth.2024.110203_bib35","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1016\/j.pneurobio.2012.06.008","article-title":"High-frequency neural activity and human cognition: past, present and possible future of intracranial EEG research","volume":"Volume 98","author":"Lachaux","year":"2012","journal-title":"Prog. Neurobiol."},{"key":"10.1016\/j.jneumeth.2024.110203_bib36","doi-asserted-by":"crossref","DOI":"10.1016\/j.rcim.2023.102610","article-title":"Cognitive neuroscience and robotics: advancements and future research directions","volume":"Volume 85","author":"Liu","year":"2024","journal-title":"Robot. Comput. -Integr. Manuf."},{"key":"10.1016\/j.jneumeth.2024.110203_bib37","article-title":"Novel 2D MXene-based materials in memristors: fundamentals, resistive switching properties and applications","volume":"Volume 44","author":"Lv","year":"2024","journal-title":"Surf. Interfaces"},{"issue":"Issue 2","key":"10.1016\/j.jneumeth.2024.110203_bib38","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1016\/j.neuroimage.2011.12.039","article-title":"Towards the utilization of EEG as a brain imaging tool","volume":"Volume 61","author":"Michel","year":"2012","journal-title":"NeuroImage"},{"key":"10.1016\/j.jneumeth.2024.110203_bib39","series-title":"Cancer Epidemiology: Modifiable Factors","first-page":"323","article-title":"Epidemiology of brain tumors","author":"Ohgaki","year":"2009"},{"issue":"2","key":"10.1016\/j.jneumeth.2024.110203_bib40","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1007\/s12555-022-1127-z","article-title":"Neuro-adaptive event-triggered optimal control for power battery systems with state constraints","volume":"22","author":"Pei","year":"2024","journal-title":"Int. J. Control, Autom. Syst."},{"key":"10.1016\/j.jneumeth.2024.110203_bib41","doi-asserted-by":"crossref","unstructured":"Alfredo Pereira, Chapter Seven - Classical-quantum interfaces in living neural tissue supporting conscious functions,Editor(s): Roman R. Pozna\u0144ski, Erkki J. Br\u00e4ndas,Advances in Quantum Chemistry,AcademicPress,Volume 82, 2020,Pages 213-252,ISSN 0065-3276,ISBN 9780128226391, https:\/\/doi.org\/10.1016\/bs.aiq.2020.08.002.","DOI":"10.1016\/bs.aiq.2020.08.002"},{"key":"10.1016\/j.jneumeth.2024.110203_bib42","doi-asserted-by":"crossref","unstructured":"Sayantan Pradhan, Vamsi K. Yadavalli, Chapter 26 - Silk proteins for bioelectronic devices in healthcare, Editor(s): Subhas C. Kundu, Rui L. Reis, In Woodhead Publishing Series in Biomaterials,Silk-Based Biomaterials for Tissue Engineering, Regenerative and Precision Medicine (SECOND EDITION),Woodhead Publishing, 2024, Pages 735-769,ISBN 9780323960175, https:\/\/doi.org\/10.1016\/B978-0-323-96017-5.00025-X.","DOI":"10.1016\/B978-0-323-96017-5.00025-X"},{"key":"10.1016\/j.jneumeth.2024.110203_bib43","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1016\/j.neucom.2016.06.014","article-title":"Neural networks: an overview of early research, current frameworks and new challenges","volume":"Volume 214","author":"Prieto","year":"2016","journal-title":"Neurocomputing"},{"key":"10.1016\/j.jneumeth.2024.110203_bib44","article-title":"Detection of fetal brain abnormalities using data augmentation and convolutional neural network in internet of things","volume":"28","author":"Priya","year":"2023","journal-title":"Meas: Sens"},{"issue":"Issue 8","key":"10.1016\/j.jneumeth.2024.110203_bib45","first-page":"1850","article-title":"Enhancing memristor fundamentals through instrumental characterization and understanding reliability issues","volume":"Volume 4","author":"Qin","year":"2023","journal-title":"MaterialsAdvances"},{"key":"10.1016\/j.jneumeth.2024.110203_bib46","doi-asserted-by":"crossref","DOI":"10.3389\/fmed.2023.1330218","article-title":"Automated deep bottleneck residual 82-layered architecture with Bayesian optimization for the classification of brain and common maternal fetal ultrasound planes","volume":"10","author":"Rauf","year":"2023","journal-title":"Front. Med."},{"key":"10.1016\/j.jneumeth.2024.110203_bib47","doi-asserted-by":"crossref","first-page":"4725","DOI":"10.1109\/TNSRE.2023.3336467","article-title":"Depression identification using eeg signals via a hybrid of lstm and spiking neural networks","volume":"31","author":"Sam","year":"2023","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"10.1016\/j.jneumeth.2024.110203_bib48","series-title":"Neural Networks: Foundations to Applications,Single Neuron Computation","first-page":"525","article-title":"Chapter 20 - Critical Coherence and Characteristic Times in Brain Stem Neuronal Discharge Patterns","author":"Selz","year":"1992"},{"issue":"Issue 11","key":"10.1016\/j.jneumeth.2024.110203_bib49","first-page":"2140","article-title":"The associative brain at work: evidence from paired associative stimulation studies in humans","volume":"Volume 128","author":"Suppa","year":"2017","journal-title":"ClinicalNeurophysiology"},{"issue":"1","key":"10.1016\/j.jneumeth.2024.110203_bib50","doi-asserted-by":"crossref","first-page":"5895","DOI":"10.1038\/s41598-024-56657-3","article-title":"BrainNet: a fusion assisted novel optimal framework of residual blocks and stacked autoencoders for multimodal brain tumor classification","volume":"14","author":"Ullah","year":"2024","journal-title":"Sci. Rep."},{"key":"10.1016\/j.jneumeth.2024.110203_bib51","doi-asserted-by":"crossref","DOI":"10.3389\/fonc.2024.1335740","article-title":"Brain tumor classification from MRI scans: a framework of hybrid deep learning model with Bayesian optimization and quantum theory-based marine predator algorithm","volume":"14","author":"Ullah","year":"2024","journal-title":"Front. Oncol."},{"issue":"Issues 1\u20133","key":"10.1016\/j.jneumeth.2024.110203_bib52","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.jphysparis.2006.09.007","article-title":"Language models based on Hebbian cell assemblies","volume":"Volume 100","author":"Wennekers","year":"2006","journal-title":"J. Physiol. -Paris"},{"issue":"Issue 1","key":"10.1016\/j.jneumeth.2024.110203_bib53","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.cell.2020.02.054","article-title":"Emerging Modalities and Implantable Technologies for Neuromodulation","volume":"Volume 181","author":"Won","year":"2020","journal-title":"Cell"},{"key":"10.1016\/j.jneumeth.2024.110203_bib54","article-title":"Synapticbehaviors in flexible Au\/WOx\/Pt\/mica memristor for neuromorphic computing system","volume":"Volume 23","author":"Zhang","year":"2022","journal-title":"Mater. Today Phys."}],"container-title":["Journal of Neuroscience Methods"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0165027024001481?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0165027024001481?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2024,9,21]],"date-time":"2024-09-21T03:25:36Z","timestamp":1726889136000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0165027024001481"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9]]},"references-count":54,"alternative-id":["S0165027024001481"],"URL":"https:\/\/doi.org\/10.1016\/j.jneumeth.2024.110203","relation":{},"ISSN":["0165-0270"],"issn-type":[{"value":"0165-0270","type":"print"}],"subject":[],"published":{"date-parts":[[2024,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Brain-computer interfaces inspired spiking neural network model for depression stage identification","name":"articletitle","label":"Article Title"},{"value":"Journal of Neuroscience Methods","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.jneumeth.2024.110203","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2024 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"110203"}}