{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T06:16:41Z","timestamp":1773123401980,"version":"3.50.1"},"reference-count":25,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2013,8,7]],"date-time":"2013-08-07T00:00:00Z","timestamp":1375833600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2014,1]]},"DOI":"10.1007\/s00521-013-1465-0","type":"journal-article","created":{"date-parts":[[2013,8,6]],"date-time":"2013-08-06T07:07:32Z","timestamp":1375772852000},"page":"91-97","source":"Crossref","is-referenced-by-count":22,"title":["A new dynamic Bayesian network approach for determining effective connectivity from fMRI data"],"prefix":"10.1007","volume":"24","author":[{"given":"Xia","family":"Wu","sequence":"first","affiliation":[]},{"given":"Xuyun","family":"Wen","sequence":"additional","affiliation":[]},{"given":"Juan","family":"Li","sequence":"additional","affiliation":[]},{"given":"Li","family":"Yao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2013,8,7]]},"reference":[{"issue":"1\u20132","key":"1465_CR1","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1002\/hbm.460020107","volume":"2","author":"KJ Friston","year":"1994","unstructured":"Friston KJ (1994) Functional and effective connectivity in neuroimaging: a synthesis. Hum Brain Mapp 2(1\u20132):56\u201378","journal-title":"Hum Brain Mapp"},{"issue":"1\u20132","key":"1465_CR2","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1002\/hbm.460020104","volume":"2","author":"AR McIntosh","year":"1994","unstructured":"McIntosh AR, Gonzalez-Lima F (1994) Structural equation modeling and its application to network analysis in functional brain imaging. Hum Brain Mapp 2(1\u20132):2\u201322","journal-title":"Hum Brain Mapp"},{"issue":"4","key":"1465_CR3","doi-asserted-by":"crossref","first-page":"1273","DOI":"10.1016\/S1053-8119(03)00202-7","volume":"19","author":"KJ Friston","year":"2003","unstructured":"Friston KJ, Harrison L, Penny W (2003) Dynamic causal modelling. NeuroImage 19(4):1273\u20131302","journal-title":"NeuroImage"},{"issue":"4","key":"1465_CR4","doi-asserted-by":"crossref","first-page":"1601","DOI":"10.1016\/j.neuroimage.2006.01.031","volume":"31","author":"X Zheng","year":"2006","unstructured":"Zheng X, Rajapakse JC (2006) Learning functional structure from fMR images. NeuroImage 31(4):1601\u20131613","journal-title":"NeuroImage"},{"issue":"9","key":"1465_CR5","doi-asserted-by":"crossref","first-page":"700","DOI":"10.1038\/nrn2201","volume":"8","author":"MD Fox","year":"2007","unstructured":"Fox MD, Raichle ME (2007) Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat Rev Neurosci 8(9):700\u2013711","journal-title":"Nat Rev Neurosci"},{"key":"1465_CR6","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1214\/aos\/1176344136","volume":"6","author":"G Schwarz","year":"1978","unstructured":"Schwarz G (1978) Estimate the dimension of a model. Ann Stat 6:461\u2013464","journal-title":"Ann Stat"},{"key":"1465_CR7","unstructured":"Olmsted SM (1983) On representing and solving decision problems, in EES department. Stanford University, Stanford, CA"},{"issue":"5","key":"1465_CR8","doi-asserted-by":"crossref","first-page":"527","DOI":"10.1287\/mnsc.35.5.527","volume":"35","author":"RD Shachter","year":"1989","unstructured":"Shachter RD, Kenley CR (1989) Gaussian influence diagrams. Manage Sci 35(5):527\u2013550","journal-title":"Manage Sci"},{"key":"1465_CR9","author":"D Karahoca","year":"2012","unstructured":"Karahoca D, Karahoca A, Yavuz \u00d6 (2012) An early warning system approach for the identification of currency crises with data mining techniques. Neural Comput Appl. doi: 10.1007\/s00521-012-1206-9","journal-title":"Neural Comput Appl"},{"key":"1465_CR10","doi-asserted-by":"crossref","first-page":"1017","DOI":"10.1007\/s00521-011-0674-7","volume":"21","author":"B Sohrabi","year":"2011","unstructured":"Sohrabi B, Mahmoudian P, Raeesi I (2011) A framework for improving e-commerce websites usability using a hybrid genetic algorithm and neural network system. Neural Comput Appl 21:1017\u20131029. doi: 10.1007\/s00521-011-0674-7","journal-title":"Neural Comput Appl"},{"key":"1465_CR11","author":"M Farid","year":"2012","unstructured":"Farid M, HosseinAbadi MM, Yazdani-Chamzini A et al (2012) Developing a new model based on neuro-fuzzy system for predicting roof fall in coal mines. Neural Comput Appl. doi: 10.1007\/s00521-012-1271-0","journal-title":"Neural Comput Appl"},{"key":"1465_CR12","doi-asserted-by":"crossref","unstructured":"Li R, Chen K, Zhang N (2009) Effective connectivity analysis of default mode network based on the Bayesian network learning approach. Proc SPIE 7262","DOI":"10.1117\/12.810893"},{"issue":"3","key":"1465_CR13","doi-asserted-by":"crossref","first-page":"749","DOI":"10.1016\/j.neuroimage.2007.06.003","volume":"37","author":"JC Rajapakse","year":"2007","unstructured":"Rajapakse JC, Zhou J (2007) Learning effective brain connectivity with dynamic Bayesian networks. NeuroImage 37(3):749\u2013760","journal-title":"NeuroImage"},{"issue":"1","key":"1465_CR14","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1002\/hbm.20490","volume":"30","author":"J Burge","year":"2009","unstructured":"Burge J, Lane T, Link H (2009) Discrete dynamic Bayesian network analysis of fMRI data. Hum Brain Mapp 30(1):122\u2013137","journal-title":"Hum Brain Mapp"},{"key":"1465_CR15","doi-asserted-by":"crossref","unstructured":"Zeng Z and Ji Q (2010) Knowledge based activity recognition with dynamic bayesian network. Computer Vision\u2013ECCV","DOI":"10.1007\/978-3-642-15567-3_39"},{"issue":"3","key":"1465_CR16","doi-asserted-by":"crossref","first-page":"794","DOI":"10.1016\/j.neuroimage.2005.10.019","volume":"30","author":"S Bhattacharya","year":"2006","unstructured":"Bhattacharya S, Ringo Ho MH, Purkayastha S (2006) A Bayesian approach to modeling dynamic effective connectivity with fMRI data. NeuroImage 30(3):794\u2013812","journal-title":"NeuroImage"},{"key":"1465_CR17","doi-asserted-by":"crossref","first-page":"527","DOI":"10.1287\/mnsc.35.5.527","volume":"35","author":"RD Shachter","year":"1989","unstructured":"Shachter RD, Kenley CR (1989) Ganssin influence diagrams. Manage Sci 35:527\u2013550","journal-title":"Manage Sci"},{"key":"1465_CR18","doi-asserted-by":"crossref","unstructured":"Geiger D, Heckerman D (1994) Learning Gaussian networks. Technical report MSR-TR-94-10","DOI":"10.1016\/B978-1-55860-332-5.50035-3"},{"key":"1465_CR19","unstructured":"Heckerman D (1995) A tutorial on learning with Bayesian networks. Technical Report MSR-TR-95-06"},{"key":"1465_CR20","unstructured":"Husmeier D (2003) Inferring dynamic Bayesian networks with MCMC. Available from: http:\/\/www.bioss.ac.uk\/~dirk\/software\/DBmcmc\/"},{"issue":"13","key":"1465_CR21","doi-asserted-by":"crossref","first-page":"4637","DOI":"10.1073\/pnas.0308627101","volume":"101","author":"MD Greicius","year":"2004","unstructured":"Greicius MD (2004) Default-mode network activity distinguishes Alzheimer\u2019s disease from healthy aging: evidence from functional MRI. Proc Natl Acad Sci 101(13):4637\u20134642","journal-title":"Proc Natl Acad Sci"},{"issue":"1","key":"1465_CR22","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1002\/hbm.21065","volume":"32","author":"Q Jiao","year":"2011","unstructured":"Jiao Q, Lu G, Zhang Z et al (2011) Granger causal influence predicts BOLD activity levels in the default mode network. Hum Brain Mapp 32(1):154\u2013161","journal-title":"Hum Brain Mapp"},{"key":"1465_CR23","doi-asserted-by":"crossref","first-page":"1456","DOI":"10.1016\/j.neurobiolaging.2007.03.029","volume":"29","author":"A Forsberg","year":"2008","unstructured":"Forsberg A, Engler H, Almkvist O et al (2008) PET imaging of amyloid deposition in patients with mild cognitive impairment. Neurobiol Aging 29:1456\u20131465","journal-title":"Neurobiol Aging"},{"key":"1465_CR24","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1002\/cne.10883","volume":"466","author":"Y Kobayashi","year":"2003","unstructured":"Kobayashi Y, Amaral DG (2003) Macaque monkey retrosplenial cortex: II. Cortical afferents. J Comp Neurol 466:48\u201379","journal-title":"J Comp Neurol"},{"key":"1465_CR25","doi-asserted-by":"crossref","first-page":"810","DOI":"10.1002\/cne.21346","volume":"502","author":"Y Kobayashi","year":"2007","unstructured":"Kobayashi Y, Amaral DG (2007) Macaque monkey retrosplenial cortex: III. Cortical efferents. J Comp Neurol 502:810\u2013833","journal-title":"J Comp Neurol"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-013-1465-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-013-1465-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-013-1465-0","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,7,20]],"date-time":"2019-07-20T12:19:37Z","timestamp":1563625177000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-013-1465-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,8,7]]},"references-count":25,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2014,1]]}},"alternative-id":["1465"],"URL":"https:\/\/doi.org\/10.1007\/s00521-013-1465-0","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,8,7]]}}}