{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T07:33:44Z","timestamp":1769758424680,"version":"3.49.0"},"publisher-location":"Cham","reference-count":22,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030205201","type":"print"},{"value":"9783030205218","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-20521-8_38","type":"book-chapter","created":{"date-parts":[[2019,6,4]],"date-time":"2019-06-04T19:02:40Z","timestamp":1559674960000},"page":"457-466","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Echo State Networks with Artificial Astrocytes and Hebbian Connections"],"prefix":"10.1007","author":[{"given":"Peter","family":"Gergel\u2019","sequence":"first","affiliation":[]},{"given":"Igor","family":"Farka\u0161","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,5,16]]},"reference":[{"key":"38_CR1","doi-asserted-by":"crossref","unstructured":"Alvarellos-Gonz\u00e1lez, A., Pazos, A., Porto-Pazos, A.B.: Computational models of neuron-astrocyte interactions lead to improved efficacy in the performance of neural networks. Comput. Math. Methods Med. 2012, 10 pages (2012)","DOI":"10.1155\/2012\/476324"},{"issue":"11","key":"38_CR2","doi-asserted-by":"publisher","first-page":"4091","DOI":"10.1523\/JNEUROSCI.20-11-04091.2000","volume":"20","author":"Veronica Alvarez-Maubecin","year":"2000","unstructured":"Alvarez-Maubecin, V., Garc\u00eda-Hern\u00e1ndez, F., Williams, J.T., Van Bockstaele, E.J.: Functional coupling between neurons and GLIA. J. Neurosci. 20(11), 4091\u20134098 (2000)","journal-title":"The Journal of Neuroscience"},{"issue":"5","key":"38_CR3","doi-asserted-by":"publisher","first-page":"532","DOI":"10.1002\/cne.21974","volume":"513","author":"FA Azevedo","year":"2009","unstructured":"Azevedo, F.A., et al.: Equal numbers of neuronal and nonneuronal cells make the human brain an isometrically scaled-up primate brain. J. Comp. Neurol. 513(5), 532\u2013541 (2009)","journal-title":"J. Comp. Neurol."},{"key":"38_CR4","unstructured":"Chen, Y., et al.: The UCR time series classification archive (2015). \n                      www.cs.ucr.edu\/~eamonn\/time_series_data\/"},{"key":"38_CR5","doi-asserted-by":"publisher","first-page":"159","DOI":"10.3389\/fncel.2013.00159","volume":"7","author":"G Dall\u00e9rac","year":"2013","unstructured":"Dall\u00e9rac, G., Chever, O., Rouach, N.: How do astrocytes shape synaptic transmission? insights from electrophysiology. Front. Cell. Neurosci. 7, 159 (2013)","journal-title":"Front. Cell. Neurosci."},{"issue":"3","key":"38_CR6","doi-asserted-by":"publisher","first-page":"208","DOI":"10.1152\/physiol.00161.2005","volume":"21","author":"T Fellin","year":"2006","unstructured":"Fellin, T., Pascual, O., Haydon, P.G.: Astrocytes coordinate synaptic networks: balanced excitation and inhibition. Physiology 21(3), 208\u2013215 (2006)","journal-title":"Physiology"},{"key":"38_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1007\/978-3-030-01424-7_8","volume-title":"Artificial Neural Networks and Machine Learning \u2013 ICANN 2018","author":"P Gergel\u2019","year":"2018","unstructured":"Gergel\u2019, P., Farkas\u0302, I.: Investigating the role of astrocyte units in a feedforward neural network. In: Kurkov\u00e1, V., Manolopoulos, Y., Hammer, B., Iliadis, L., Maglogiannis, I. (eds.) ICANN 2018. LNCS, vol. 11141, pp. 73\u201383. Springer, Cham (2018). \n                      https:\/\/doi.org\/10.1007\/978-3-030-01424-7_8"},{"issue":"19","key":"38_CR8","doi-asserted-by":"publisher","first-page":"R712","DOI":"10.1016\/S0960-9822(00)00708-9","volume":"10","author":"PG Haydon","year":"2000","unstructured":"Haydon, P.G.: Neuroglial networks: neurons and glia talk to each other. Curr. Biol. 10(19), R712\u2013R714 (2000)","journal-title":"Curr. Biol."},{"key":"38_CR9","volume-title":"The Organization of Behavior: A Neuropsychological Theory","author":"DO Hebb","year":"1949","unstructured":"Hebb, D.O.: The Organization of Behavior: A Neuropsychological Theory. Wiley, New York (1949)"},{"key":"38_CR10","doi-asserted-by":"crossref","unstructured":"Ikuta, C., Uwate, Y., Nishio, Y.: Chaos glial network connected to multi-layer perceptron for solving two-spiral problem. In: Proceedings of 2010 IEEE International Symposium on Circuits and Systems, pp. 1360\u20131363 (2010)","DOI":"10.1109\/ISCAS.2010.5537060"},{"key":"38_CR11","doi-asserted-by":"crossref","unstructured":"Ikuta, C., Uwate, Y., Nishio, Y.: Multi-layer perceptron with impulse glial network. In: IEEE Workshop on Nonlinear Circuit Networks, pp. 9\u201311 (2010)","DOI":"10.1109\/IJCNN.2011.6033549"},{"key":"38_CR12","doi-asserted-by":"crossref","unstructured":"Ikuta, C., Uwate, Y., Nishio, Y.: Performance and features of multi-layer perceptron with impulse glial network. In: International Joint Conference on Neural Networks, pp. 2536\u20132541 (2011)","DOI":"10.1109\/IJCNN.2011.6033549"},{"key":"38_CR13","doi-asserted-by":"crossref","unstructured":"Ikuta, C., Uwate, Y., Nishio, Y.: Multi-layer perceptron with positive and negative pulse glial chain for solving two-spirals problem. In: International Joint Conference on Neural Networks, pp. 1\u20136 (2012)","DOI":"10.1109\/IJCNN.2012.6252725"},{"issue":"34","key":"38_CR14","first-page":"13","volume":"148","author":"H Jaeger","year":"2001","unstructured":"Jaeger, H.: The \u201cecho state\" approach to analysing and training recurrent neural networks-with an erratum note. Bonn, Ger.: Ger. Nat. Res. Cent. Inf. Technol. GMD Tech. Rep. 148(34), 13 (2001)","journal-title":"Bonn, Ger.: Ger. Nat. Res. Cent. Inf. Technol. GMD Tech. Rep."},{"key":"38_CR15","doi-asserted-by":"crossref","unstructured":"Matthews, B.W.: Comparison of the predicted and observed secondary structure of t4 phage lysozyme. Biochimica et Biophysica Acta (BBA)-Protein Struct. 405(2), 442\u2013451 (1975)","DOI":"10.1016\/0005-2795(75)90109-9"},{"issue":"04","key":"38_CR16","doi-asserted-by":"publisher","first-page":"1550012","DOI":"10.1142\/S0129065715500124","volume":"25","author":"P Mesejo","year":"2015","unstructured":"Mesejo, P., Ib\u00e1nez, O., Fern\u00e1ndez-Blanco, E., Cedr\u00f3n, F., Pazos, A., Porto-Pazos, A.B.: Artificial neuron-glia networks learning approach based on cooperative coevolution. Int. J. Neural Syst. 25(04), 1550012 (2015)","journal-title":"Int. J. Neural Syst."},{"issue":"3","key":"38_CR17","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1007\/BF00275687","volume":"15","author":"E Oja","year":"1982","unstructured":"Oja, E.: Simplified neuron model as a principal component analyzer. J. Math. Biol. 15(3), 267\u2013273 (1982)","journal-title":"J. Math. Biol."},{"key":"38_CR18","doi-asserted-by":"publisher","first-page":"76","DOI":"10.1016\/j.brainresbull.2017.01.027","volume":"136","author":"F Oschmann","year":"2018","unstructured":"Oschmann, F., Berry, H., Obermayer, K., Lenk, K.: From in silico astrocyte cell models to neuron-astrocyte network models: a review. Brain Res. Bull. 136, 76\u201384 (2018)","journal-title":"Brain Res. Bull."},{"issue":"4","key":"38_CR19","doi-asserted-by":"publisher","first-page":"439","DOI":"10.1016\/S0301-0082(96)00068-8","volume":"51","author":"JT Porter","year":"1997","unstructured":"Porter, J.T., McCarthy, K.D.: Astrocytic neurotransmitter receptors in situ and in vivo. Prog. Neurobiol. 51(4), 439\u2013455 (1997)","journal-title":"Prog. Neurobiol."},{"issue":"4","key":"38_CR20","doi-asserted-by":"publisher","first-page":"e19109","DOI":"10.1371\/journal.pone.0019109","volume":"6","author":"AB Porto-Pazos","year":"2011","unstructured":"Porto-Pazos, A.B., et al.: Artificial astrocytes improve neural network performance. PloS ONE 6(4), e19109 (2011)","journal-title":"PloS ONE"},{"key":"38_CR21","doi-asserted-by":"publisher","first-page":"58","DOI":"10.3389\/fncom.2012.00058","volume":"6","author":"V Volman","year":"2012","unstructured":"Volman, V., Bazhenov, M., Sejnowski, T.J.: Computational models of neuron-astrocyte interaction in epilepsy. Front. Comput. Neurosci. 6, 58 (2012)","journal-title":"Front. Comput. Neurosci."},{"key":"38_CR22","doi-asserted-by":"crossref","unstructured":"Wade, J., Kelso, S., Crunelli, V., McDaid, L.J., Harkin, J.: Biophysically based computational models of astrocyte-neuron coupling and their functional significance. Frontiers E-books (2014)","DOI":"10.3389\/978-2-88919-178-9"}],"container-title":["Lecture Notes in Computer Science","Advances in Computational Intelligence"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-20521-8_38","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,6,4]],"date-time":"2019-06-04T19:06:59Z","timestamp":1559675219000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-20521-8_38"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030205201","9783030205218"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-20521-8_38","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"16 May 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IWANN","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Work-Conference on Artificial Neural Networks","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Gran Canaria","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 June 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 June 2019","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":"iwann2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/iwann.uma.es\/","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"}},{"value":"easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"210","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"150","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"71% - 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"}},{"value":"2,9","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"2,5","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}}]}}