{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T07:55:44Z","timestamp":1776930944514,"version":"3.51.2"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783031150364","type":"print"},{"value":"9783031150371","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-15037-1_13","type":"book-chapter","created":{"date-parts":[[2022,8,19]],"date-time":"2022-08-19T15:03:06Z","timestamp":1660921386000},"page":"152-163","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Classifying EEG Signals of\u00a0Mind-Wandering Across Different Styles of\u00a0Meditation"],"prefix":"10.1007","author":[{"given":"Shivam","family":"Chaudhary","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pankaj","family":"Pandey","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Krishna Prasad","family":"Miyapuram","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Derek","family":"Lomas","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,8,20]]},"reference":[{"key":"13_CR1","unstructured":"Meditation: In depth. https:\/\/www.nccih.nih.gov\/health\/meditation-in-depth"},{"issue":"2","key":"13_CR2","doi-asserted-by":"publisher","first-page":"124","DOI":"10.1007\/s12671-012-0157-7","volume":"5","author":"YQ Deng","year":"2014","unstructured":"Deng, Y.Q., Li, S., Tang, Y.Y.: The relationship between wandering mind, depression and mindfulness. Mindfulness 5(2), 124\u2013128 (2014)","journal-title":"Mindfulness"},{"issue":"5","key":"13_CR3","doi-asserted-by":"publisher","first-page":"e0251490","DOI":"10.1371\/journal.pone.0251490","volume":"16","author":"HW Dong","year":"2021","unstructured":"Dong, H.W., Mills, C., Knight, R.T., Kam, J.W.: Detection of mind wandering using EEG: within and across individuals. PLoS ONE 16(5), e0251490 (2021)","journal-title":"PLoS ONE"},{"key":"13_CR4","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1007\/978-3-319-20816-9_20","volume-title":"Foundations of Augmented Cognition","author":"L Galway","year":"2015","unstructured":"Galway, L., Brennan, C., McCullagh, P., Lightbody, G.: BCI and eye gaze: collaboration at the interface. In: Schmorrow, D.D., Fidopiastis, C.M. (eds.) AC 2015. LNCS (LNAI), vol. 9183, pp. 199\u2013210. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-20816-9_20"},{"issue":"267","key":"13_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3389\/fnins.2013.00267","volume":"7","author":"A Gramfort","year":"2013","unstructured":"Gramfort, A., et al.: MEG and EEG data analysis with MNE-Python. Front. Neurosci. 7(267), 1\u201313 (2013). https:\/\/doi.org\/10.3389\/fnins.2013.00267","journal-title":"Front. Neurosci."},{"key":"13_CR6","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization (2017)"},{"key":"13_CR7","doi-asserted-by":"publisher","first-page":"101329","DOI":"10.1016\/j.ctcp.2021.101329","volume":"43","author":"P Kora","year":"2021","unstructured":"Kora, P., Meenakshi, K., Swaraja, K., Rajani, A., Raju, M.S.: EEG based interpretation of human brain activity during yoga and meditation using machine learning: a systematic review. Complement. Ther. Clin. Pract. 43, 101329 (2021)","journal-title":"Complement. Ther. Clin. Pract."},{"issue":"4","key":"13_CR8","doi-asserted-by":"publisher","first-page":"848","DOI":"10.1007\/s12671-014-0329-8","volume":"6","author":"T Lomas","year":"2015","unstructured":"Lomas, T., Cartwright, T., Edginton, T., Ridge, D.: A qualitative analysis of experiential challenges associated with meditation practice. Mindfulness 6(4), 848\u2013860 (2015)","journal-title":"Mindfulness"},{"key":"13_CR9","unstructured":"Van der Maaten, L., Hinton, G.: Visualizing data using t-SNE. J. Mach. Learn. Res. 9(11) (2008)"},{"issue":"6","key":"13_CR10","doi-asserted-by":"publisher","first-page":"2063","DOI":"10.1109\/TNNLS.2018.2790388","volume":"29","author":"M Mahmud","year":"2018","unstructured":"Mahmud, M., Kaiser, M.S., Hussain, A., Vassanelli, S.: Applications of deep learning and reinforcement learning to biological data. IEEE Trans. Neural Netw. Learn. Syst. 29(6), 2063\u20132079 (2018). https:\/\/doi.org\/10.1109\/TNNLS.2018.2790388","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"1","key":"13_CR11","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1037\/a0031569","volume":"67","author":"BW Mooneyham","year":"2013","unstructured":"Mooneyham, B.W., Schooler, J.W.: The costs and benefits of mind-wandering: a review. Can. J. Exp. Psychol.\/Revue canadienne de psychologie exp\u00e9rimentale 67(1), 11 (2013)","journal-title":"Can. J. Exp. Psychol.\/Revue canadienne de psychologie exp\u00e9rimentale"},{"key":"13_CR12","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1007\/978-3-030-86993-9_9","volume-title":"Brain Informatics","author":"P Pandey","year":"2021","unstructured":"Pandey, P., Gupta, P., Miyapuram, K.P.: Brain connectivity based classification of meditation expertise. In: Mahmud, M., Kaiser, M.S., Vassanelli, S., Dai, Q., Zhong, N. (eds.) BI 2021. LNCS (LNAI), vol. 12960, pp. 89\u201398. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-86993-9_9"},{"key":"13_CR13","doi-asserted-by":"crossref","unstructured":"Pandey, P., Miyapuram, K.P.: Classifying oscillatory signatures of expert vs nonexpert meditators. In: 2020 International Joint Conference on Neural Networks (IJCNN), pp. 1\u20137. IEEE (2020)","DOI":"10.1109\/IJCNN48605.2020.9207340"},{"key":"13_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"394","DOI":"10.1007\/978-3-030-80432-9_30","volume-title":"Medical Image Understanding and Analysis","author":"P Pandey","year":"2021","unstructured":"Pandey, P., Miyapuram, K.P.: BRAIN2DEPTH: lightweight CNN model for classification of cognitive states from EEG recordings. In: Papie\u017c, B.W., Yaqub, M., Jiao, J., Namburete, A.I.L., Noble, J.A. (eds.) MIUA 2021. LNCS, vol. 12722, pp. 394\u2013407. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-80432-9_30"},{"key":"13_CR15","doi-asserted-by":"publisher","unstructured":"Pandey, P., Miyapuram, K.P.: Nonlinear EEG analysis of mindfulness training using interpretable machine learning. In: 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 3051\u20133057 (2021). https:\/\/doi.org\/10.1109\/BIBM52615.2021.9669457","DOI":"10.1109\/BIBM52615.2021.9669457"},{"key":"13_CR16","doi-asserted-by":"publisher","unstructured":"Gupta, P., Pandey, P., Miyapuram, K.P.: Reliable EEG neuromarker to discriminate meditative states across practitioners (2022). https:\/\/doi.org\/10.13140\/RG.2.2.23937.94568","DOI":"10.13140\/RG.2.2.23937.94568"},{"key":"13_CR17","doi-asserted-by":"crossref","unstructured":"Ribeiro, M.T., Singh, S., Guestrin, C.: \u201cWhy should i trust you?\u201d Explaining the predictions of any classifier. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1135\u20131144 (2016)","DOI":"10.1145\/2939672.2939778"},{"issue":"5500","key":"13_CR18","doi-asserted-by":"publisher","first-page":"2323","DOI":"10.1126\/science.290.5500.2323","volume":"290","author":"ST Roweis","year":"2000","unstructured":"Roweis, S.T., Saul, L.K.: Nonlinear dimensionality reduction by locally linear embedding. Science 290(5500), 2323\u20132326 (2000)","journal-title":"Science"},{"key":"13_CR19","first-page":"1","volume":"25","author":"H Sharma","year":"2021","unstructured":"Sharma, H., Raj, R., Juneja, M.: An empirical comparison of machine learning algorithms for the classification of brain signals to assess the impact of combined yoga and sudarshan kriya. Comput. Methods Biomech. Biomed. Eng. 25, 1\u20138 (2021)","journal-title":"Comput. Methods Biomech. Biomed. Eng."},{"key":"13_CR20","doi-asserted-by":"publisher","unstructured":"Vallat, R., Walker, M.P.: An open-source, high-performance tool for automated sleep staging. eLife 10, e70092 (2021). https:\/\/doi.org\/10.7554\/elife.70092","DOI":"10.7554\/elife.70092"},{"key":"13_CR21","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1016\/j.neuroscience.2020.01.033","volume":"431","author":"RM Vivot","year":"2020","unstructured":"Vivot, R.M., Pallavicini, C., Zamberlan, F., Vigo, D., Tagliazucchi, E.: Meditation increases the entropy of brain oscillatory activity. Neuroscience 431, 40\u201351 (2020)","journal-title":"Neuroscience"},{"issue":"5","key":"13_CR22","doi-asserted-by":"publisher","first-page":"457","DOI":"10.1192\/bjp.135.5.457","volume":"135","author":"M West","year":"1979","unstructured":"West, M.: Meditation. Br. J. Psychiatry 135(5), 457\u2013467 (1979). https:\/\/doi.org\/10.1192\/bjp.135.5.457","journal-title":"Br. J. Psychiatry"},{"issue":"4","key":"13_CR23","doi-asserted-by":"publisher","first-page":"e0231946","DOI":"10.1371\/journal.pone.0231946","volume":"15","author":"A Yamaoka","year":"2020","unstructured":"Yamaoka, A., Yukawa, S.: Mind wandering in creative problem-solving: relationships with divergent thinking and mental health. PLoS ONE 15(4), e0231946 (2020)","journal-title":"PLoS ONE"},{"key":"13_CR24","doi-asserted-by":"publisher","unstructured":"Young, J.H., Arterberry, M.E., Martin, J.P.: Contrasting electroencephalography-derived entropy and neural oscillations with highly skilled meditators. Front. Hum. Neurosci. 15, 628417 (2021). https:\/\/doi.org\/10.3389\/fnhum.2021.628417. https:\/\/www.frontiersin.org\/article\/10.3389\/fnhum.2021.628417","DOI":"10.3389\/fnhum.2021.628417"},{"key":"13_CR25","doi-asserted-by":"publisher","unstructured":"Zhang, Y., Zhang, Z., Luo, L., Tong, H., Chen, F., Hou, S.T.: 40 HZ light flicker alters human brain electroencephalography microstates and complexity implicated in brain diseases. Front. Neurosci. 15 (2021). https:\/\/doi.org\/10.3389\/fnins.2021.777183. https:\/\/www.frontiersin.org\/article\/10.3389\/fnins.2021.777183","DOI":"10.3389\/fnins.2021.777183"}],"container-title":["Lecture Notes in Computer Science","Brain Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-15037-1_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,19]],"date-time":"2022-08-19T23:11:14Z","timestamp":1660950674000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-15037-1_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031150364","9783031150371"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-15037-1_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"20 August 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"BI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Brain Informatics","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Padua","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 July 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 July 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"brain2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/wi-consortium.org\/conferences\/bi2022\/index.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Cyber Chair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"65","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"29","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"45% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}