{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T03:37:43Z","timestamp":1743133063387,"version":"3.40.3"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031720680"},{"type":"electronic","value":"9783031720697"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-72069-7_37","type":"book-chapter","created":{"date-parts":[[2024,10,3]],"date-time":"2024-10-03T19:02:59Z","timestamp":1727982179000},"page":"389-399","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["SimBrainNet: Evaluating Brain Network Similarity for\u00a0Attention Disorders"],"prefix":"10.1007","author":[{"given":"Debashis","family":"Das Chakladar","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Foteini","family":"Simistira Liwicki","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rajkumar","family":"Saini","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,10,4]]},"reference":[{"issue":"1","key":"37_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/sdata.2017.181","volume":"4","author":"LM Alexander","year":"2017","unstructured":"Alexander, L.M., Escalera, J., Ai, L., Andreotti, C., Febre, K., Mangone, A., Vega-Potler, N., Langer, N., Alexander, A., Kovacs, M., et\u00a0al.: An open resource for transdiagnostic research in pediatric mental health and learning disorders. Scientific data 4(1), 1\u201326 (2017)","journal-title":"Scientific data"},{"issue":"1","key":"37_CR2","doi-asserted-by":"publisher","first-page":"236","DOI":"10.1038\/s41398-023-02536-w","volume":"13","author":"M Cao","year":"2023","unstructured":"Cao, M., Martin, E., Li, X.: Machine learning in attention-deficit\/hyperactivity disorder: new approaches toward understanding the neural mechanisms. Translational Psychiatry 13(1), \u00a0236 (2023)","journal-title":"Translational Psychiatry"},{"key":"37_CR3","doi-asserted-by":"crossref","unstructured":"Chakladar, D.D., Pal, N.R.: Brain connectivity analysis for EEG-based face perception task. IEEE Transactions on Cognitive and Developmental Systems (2024)","DOI":"10.1109\/TCDS.2024.3370635"},{"issue":"4","key":"37_CR4","doi-asserted-by":"publisher","first-page":"1507","DOI":"10.1109\/TCDS.2021.3116079","volume":"14","author":"DD Chakladar","year":"2021","unstructured":"Chakladar, D.D., Roy, P.P., Iwamura, M.: EEG-based cognitive state classification and analysis of brain dynamics using deep ensemble model and graphical brain network. IEEE Transactions on Cognitive and Developmental Systems 14(4), 1507\u20131519 (2021)","journal-title":"IEEE Transactions on Cognitive and Developmental Systems"},{"issue":"8","key":"37_CR5","doi-asserted-by":"publisher","first-page":"1256","DOI":"10.1016\/j.clinph.2019.05.001","volume":"130","author":"AR Clarke","year":"2019","unstructured":"Clarke, A.R., Barry, R.J., Johnstone, S.J., McCarthy, R., Selikowitz, M.: EEG development in attention deficit hyperactivity disorder: From child to adult. Clinical Neurophysiology 130(8), 1256\u20131262 (2019)","journal-title":"Clinical Neurophysiology"},{"key":"37_CR6","doi-asserted-by":"crossref","unstructured":"Criaud, M., Wulff, M., Alegria, A., Barker, G., Giampietro, V., Rubia, K.: Increased left inferior fronto-striatal activation during error monitoring after fMRI neurofeedback of right inferior frontal cortex in adolescents with attention deficit hyperactivity disorder. NeuroImage: Clinical 27, 102311 (2020)","DOI":"10.1016\/j.nicl.2020.102311"},{"key":"37_CR7","doi-asserted-by":"crossref","unstructured":"Dong, Q., Qiang, N., Lv, J., Li, X., Liu, T., Li, Q.: Spatiotemporal attention autoencoder (STAAE) for ADHD classification. In: Medical Image Computing and Computer Assisted Intervention\u2013MICCAI 2020: 23rd International Conference, Lima, Peru, October 4\u20138, 2020, Proceedings, Part VII 23. pp. 508\u2013517. Springer (2020)","DOI":"10.1007\/978-3-030-59728-3_50"},{"key":"37_CR8","doi-asserted-by":"publisher","first-page":"251","DOI":"10.3389\/fnins.2020.00251","volume":"14","author":"L Dubreuil-Vall","year":"2020","unstructured":"Dubreuil-Vall, L., Ruffini, G., Camprodon, J.A.: Deep learning convolutional neural networks discriminate adult ADHD from healthy individuals on the basis of event-related spectral EEG. Frontiers in neuroscience 14, \u00a0251 (2020)","journal-title":"Frontiers in neuroscience"},{"key":"37_CR9","doi-asserted-by":"crossref","unstructured":"Gao, Y., Ren, L., Li, R., Zhang, Y.: Electroencephalogram\u2013electromyography coupling analysis in stroke based on symbolic transfer entropy. Frontiers in neurology 8, \u00a0716 (2018)","DOI":"10.3389\/fneur.2017.00716"},{"key":"37_CR10","doi-asserted-by":"publisher","first-page":"85","DOI":"10.3389\/fncom.2019.00085","volume":"13","author":"DJ Harmah","year":"2020","unstructured":"Harmah, D.J., Li, C., Li, F., Liao, Y., Wang, J., Ayedh, W.M., Bore, J.C., Yao, D., Dong, W., Xu, P.: Measuring the non-linear directed information flow in schizophrenia by multivariate transfer entropy. Frontiers in computational neuroscience 13, \u00a085 (2020)","journal-title":"Frontiers in computational neuroscience"},{"key":"37_CR11","doi-asserted-by":"crossref","unstructured":"Hong, J., Park, B.y., Cho, H.h., Park, H.: Age-related connectivity differences between attention deficit and hyperactivity disorder patients and typically developing subjects: a resting-state functional MRI study. Neural regeneration research 12(10), \u00a01640 (2017)","DOI":"10.4103\/1673-5374.217339"},{"issue":"5","key":"37_CR12","doi-asserted-by":"publisher","first-page":"2340","DOI":"10.1109\/TIP.2018.2799706","volume":"27","author":"B Jie","year":"2018","unstructured":"Jie, B., Liu, M., Zhang, D., Shen, D.: Sub-network kernels for measuring similarity of brain connectivity networks in disease diagnosis. IEEE Transactions on Image Processing 27(5), 2340\u20132353 (2018)","journal-title":"IEEE Transactions on Image Processing"},{"issue":"6","key":"37_CR13","doi-asserted-by":"publisher","first-page":"904","DOI":"10.1002\/hbm.21058","volume":"31","author":"K Konrad","year":"2010","unstructured":"Konrad, K., Eickhoff, S.B.: Is the ADHD brain wired differently? a review on structural and functional connectivity in attention deficit hyperactivity disorder. Human brain mapping 31(6), 904\u2013916 (2010)","journal-title":"Human brain mapping"},{"issue":"1","key":"37_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/sdata.2017.40","volume":"4","author":"N Langer","year":"2017","unstructured":"Langer, N., Ho, E.J., Alexander, L.M., Xu, H.Y., Jozanovic, R.K., Henin, S., Petroni, A., Cohen, S., Marcelle, E.T., Parra, L.C., et\u00a0al.: A resource for assessing information processing in the developing brain using EEG and eye tracking. Scientific data 4(1), 1\u201320 (2017)","journal-title":"Scientific data"},{"issue":"1","key":"37_CR15","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1177\/1550059416643824","volume":"48","author":"S Markovska-Simoska","year":"2017","unstructured":"Markovska-Simoska, S., Pop-Jordanova, N.: Quantitative in children and adults with attention deficit hyperactivity disorder: comparison of absolute and relative power spectra and theta\/beta ratio. Clinical EEG and neuroscience 48(1), 20\u201332 (2017)","journal-title":"Clinical EEG and neuroscience"},{"issue":"9","key":"37_CR16","doi-asserted-by":"publisher","first-page":"2238","DOI":"10.1109\/TPAMI.2017.2750160","volume":"40","author":"A Mheich","year":"2017","unstructured":"Mheich, A., Hassan, M., Khalil, M., Gripon, V., Dufor, O., Wendling, F.: Siminet: a novel method for quantifying brain network similarity. IEEE Transactions on Pattern Analysis and Machine Intelligence 40(9), 2238\u20132249 (2017)","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"3","key":"37_CR17","doi-asserted-by":"publisher","first-page":"507","DOI":"10.1162\/netn_a_00133","volume":"4","author":"A Mheich","year":"2020","unstructured":"Mheich, A., Wendling, F., Hassan, M.: Brain network similarity: methods and applications. Network Neuroscience 4(3), 507\u2013527 (2020)","journal-title":"Network Neuroscience"},{"issue":"10","key":"37_CR18","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0109462","volume":"9","author":"A Montalto","year":"2014","unstructured":"Montalto, A., Faes, L., Marinazzo, D.: Mute: a matlab toolbox to compare established and novel estimators of the multivariate transfer entropy. PloS one 9(10), e109462 (2014)","journal-title":"PloS one"},{"key":"37_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2011\/156869","volume":"2011","author":"R Oostenveld","year":"2011","unstructured":"Oostenveld, R., Fries, P., Maris, E., Schoffelen, J.M.: Fieldtrip: open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data. Computational intelligence and neuroscience 2011, \u00a01\u20139 (2011)","journal-title":"Computational intelligence and neuroscience"},{"key":"37_CR20","doi-asserted-by":"crossref","unstructured":"Osmanl\u0131o\u011flu, Y., Tun\u00e7, B., Alappatt, J.A., Parker, D., Kim, J., Shokoufandeh, A., Verma, R.: A graph representation and similarity measure for brain networks with nodal features. In: Graphs in Biomedical Image Analysis and Integrating Medical Imaging and Non-Imaging Modalities: Second International Workshop, GRAIL 2018 and First International Workshop, Beyond MIC 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings 2. pp. 14\u201323. Springer (2018)","DOI":"10.1007\/978-3-030-00689-1_2"},{"key":"37_CR21","doi-asserted-by":"publisher","first-page":"100","DOI":"10.3389\/fnhum.2018.00100","volume":"12","author":"K Rubia","year":"2018","unstructured":"Rubia, K.: Cognitive neuroscience of attention deficit hyperactivity disorder (ADHD) and its clinical translation. Frontiers in human neuroscience 12, \u00a0100 (2018)","journal-title":"Frontiers in human neuroscience"},{"issue":"2","key":"37_CR22","doi-asserted-by":"publisher","first-page":"461","DOI":"10.1103\/PhysRevLett.85.461","volume":"85","author":"T Schreiber","year":"2000","unstructured":"Schreiber, T.: Measuring information transfer. Physical review letters 85(2), \u00a0461 (2000)","journal-title":"Physical review letters"},{"key":"37_CR23","doi-asserted-by":"publisher","DOI":"10.1016\/j.neubiorev.2022.104752","volume":"139","author":"J Slater","year":"2022","unstructured":"Slater, J., Joober, R., Koborsy, B.L., Mitchell, S., Sahlas, E., Palmer, C.: Can electroencephalography (EEG) identify ADHD subtypes? a systematic review. Neuroscience & Biobehavioral Reviews 139, 104752 (2022)","journal-title":"Neuroscience & Biobehavioral Reviews"},{"key":"37_CR24","doi-asserted-by":"crossref","unstructured":"Vicente, R., Wibral, M., Lindner, M., Pipa, G.: Transfer entropy\u2014a model-free measure of effective connectivity for the neurosciences. Journal of computational neuroscience 30, 45\u201367 (2011)","DOI":"10.1007\/s10827-010-0262-3"},{"issue":"7","key":"37_CR25","doi-asserted-by":"publisher","first-page":"577","DOI":"10.1016\/j.braindev.2019.03.006","volume":"41","author":"A Yasumura","year":"2019","unstructured":"Yasumura, A., Omori, M., Fukuda, A., Takahashi, J., Yasumura, Y., Nakagawa, E., Koike, T., Yamashita, Y., Miyajima, T., Koeda, T., et\u00a0al.: Age-related differences in frontal lobe function in children with ADHD. Brain and Development 41(7), 577\u2013586 (2019)","journal-title":"Brain and Development"}],"container-title":["Lecture Notes in Computer Science","Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2024"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-72069-7_37","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,3]],"date-time":"2024-10-03T19:06:59Z","timestamp":1727982419000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-72069-7_37"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031720680","9783031720697"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-72069-7_37","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"4 October 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests in the paper as required by the publisher.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"MICCAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Medical Image Computing and Computer-Assisted Intervention","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Marrakesh","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Morocco","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 October 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"miccai2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/conferences.miccai.org\/2024\/en\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}