{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T00:22:40Z","timestamp":1743121360583,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":25,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819770007"},{"type":"electronic","value":"9789819770014"}],"license":[{"start":{"date-parts":[[2024,9,22]],"date-time":"2024-09-22T00:00:00Z","timestamp":1726963200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,9,22]],"date-time":"2024-09-22T00:00:00Z","timestamp":1726963200000},"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":[[2025]]},"DOI":"10.1007\/978-981-97-7001-4_32","type":"book-chapter","created":{"date-parts":[[2024,9,21]],"date-time":"2024-09-21T18:01:43Z","timestamp":1726941703000},"page":"449-462","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Study on Image Reconstruction Based on Decoding fMRI Through Extracting Image Depth Features"],"prefix":"10.1007","author":[{"given":"Xin","family":"Deng","sequence":"first","affiliation":[]},{"given":"Feiyang","family":"Bao","sequence":"additional","affiliation":[]},{"given":"Bin","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Yijia","family":"Li","sequence":"additional","affiliation":[]},{"given":"Lianhua","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,9,22]]},"reference":[{"issue":"1","key":"32_CR1","doi-asserted-by":"publisher","first-page":"679","DOI":"10.1038\/nn1444","volume":"8","author":"Y Kamitani","year":"2005","unstructured":"Kamitani, Y.: Decoding the visual and subjective contents of the human brain. Nat. Neurosci. 8(1), 679\u2013685 (2005)","journal-title":"Nat. Neurosci."},{"issue":"5","key":"32_CR2","doi-asserted-by":"publisher","first-page":"686","DOI":"10.1038\/nn1445","volume":"8","author":"JD Haynes","year":"2010","unstructured":"Haynes, J.D.: Predicting the orientation of invisible stimuli from activity in human primary visual cortex. Nat. Neurosci. 8(5), 686\u2013691 (2010)","journal-title":"Nat. Neurosci."},{"issue":"5539","key":"32_CR3","doi-asserted-by":"publisher","first-page":"2425","DOI":"10.1126\/science.1063736","volume":"293","author":"JV Haxby","year":"2001","unstructured":"Haxby, J.V.: Distributed and overlapping representations of faces and objects in ventral temporal cortex. Science 293(5539), 2425\u20132430 (2001)","journal-title":"Science"},{"issue":"2","key":"32_CR4","doi-asserted-by":"publisher","first-page":"261","DOI":"10.1016\/S1053-8119(03)00049-1","volume":"19","author":"DD Cox","year":"2003","unstructured":"Cox, D.D.: Functional magnetic resonance imaging (fMRI) \u201cbrain reading\u201d: detecting and classifying distributed patterns of fMRI activity in human visual cortex. Neuroimage 19(2), 261\u2013270 (2003)","journal-title":"Neuroimage"},{"issue":"7185","key":"32_CR5","doi-asserted-by":"publisher","first-page":"352","DOI":"10.1038\/nature06713","volume":"452","author":"KN Kay","year":"2008","unstructured":"Kay, K.N.: Identifying natural images from human brain activity. Nature 452(7185), 352\u2013355 (2008)","journal-title":"Nature"},{"issue":"5","key":"32_CR6","doi-asserted-by":"publisher","first-page":"915","DOI":"10.1016\/j.neuron.2008.11.004","volume":"60","author":"Y Miyawaki","year":"2008","unstructured":"Miyawaki, Y.: Visual image reconstruction from human brain activity using a combination of multiscale local image decoders. Neuron 60(5), 915\u2013929 (2008)","journal-title":"Neuron"},{"issue":"6","key":"32_CR7","doi-asserted-by":"publisher","first-page":"1013","DOI":"10.1162\/08989290051137549","volume":"12","author":"KM O\u2019Craven","year":"2000","unstructured":"O\u2019Craven, K.M., Kanwisher, N.: Mental imagery of faces and places activates corresponding stimulus-specific brain regions. J. Cogn. Neurosci. 12(6), 1013\u20131023 (2000)","journal-title":"J. Cogn. Neurosci."},{"issue":"1","key":"32_CR8","doi-asserted-by":"publisher","first-page":"951","DOI":"10.1016\/j.neuroimage.2013.07.043","volume":"83","author":"S Schoenmakers","year":"2013","unstructured":"Schoenmakers, S.: Linear reconstruction of perceived images from human brain activity. Neuroimage 83(1), 951\u2013961 (2013)","journal-title":"Neuroimage"},{"issue":"1","key":"32_CR9","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1038\/s42003-019-0438-y","volume":"2","author":"R VanRullen","year":"2019","unstructured":"VanRullen, R.: Reconstructing faces from fMRI patterns using deep generative neural networks. Commun. Biol. 2(1), 193\u2013203 (2019)","journal-title":"Commun. Biol."},{"issue":"1","key":"32_CR10","doi-asserted-by":"publisher","first-page":"e1006633","DOI":"10.1371\/journal.pcbi.1006633","volume":"15","author":"G Shen","year":"2019","unstructured":"Shen, G.: Deep image reconstruction from human brain activity. Plos Comput. Biol. 15(1), e1006633 (2019)","journal-title":"Plos Comput. Biol."},{"issue":"12","key":"32_CR11","doi-asserted-by":"publisher","first-page":"4136","DOI":"10.1093\/cercor\/bhx268","volume":"28","author":"H Wen","year":"2018","unstructured":"Wen, H.: Neural encoding and decoding with deep learning for dynamic natural vision. Cereb. Cortex 28(12), 4136\u20134160 (2018)","journal-title":"Cereb. Cortex"},{"unstructured":"Dosovitskiy, A.: An image is worth 16 \u00d7 16 words: transformers for image recognition at scale. arxiv preprint arxiv:2010.11929 (2020)","key":"32_CR12"},{"issue":"1","key":"32_CR13","doi-asserted-by":"publisher","first-page":"15037","DOI":"10.1038\/ncomms15037","volume":"8","author":"T Horikawa","year":"2017","unstructured":"Horikawa, T.: Generic decoding of seen and imagined objects using hierarchical visual features. Nat. Commun. 8(1), 15037 (2017)","journal-title":"Nat. Commun."},{"unstructured":"Simonyan, K.: Very deep convolutional networks for large-scale image recognition. In: Proceedings of the 3rd International Conference on Learning Representations, pp. 1\u201310. DBIP, San Diego (2014)","key":"32_CR14"},{"doi-asserted-by":"crossref","unstructured":"Deng, J.: ImageNet: a large-scale hierarchical image database. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 248\u2212255. IEEE, New York (2009)","key":"32_CR15","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"32_CR16","volume-title":"Pattern Recognition and Machine Learning","author":"CM Bishop","year":"2006","unstructured":"Bishop, C.M., Nasrabadi, N.M.: Pattern Recognition and Machine Learning, 2nd edn. Springer, New York (2006)","edition":"2"},{"unstructured":"Le, Q.V., Ngiam, J.: On optimization methods for deep learning. In: Proceedings of the 28th International Conference on International Conference on Machine Learning, pp. 265\u2013272. JMLR Workshop and Conference Proceedings, Bellevue (2011)","key":"32_CR17"},{"issue":"1","key":"32_CR18","doi-asserted-by":"publisher","first-page":"503","DOI":"10.1007\/BF01589116","volume":"45","author":"DC Liu","year":"1989","unstructured":"Liu, D.C.: On the limited memory BFGS method for large scale optimization. Math. Program. 45(1), 503\u2013528 (1989)","journal-title":"Math. Program."},{"doi-asserted-by":"crossref","unstructured":"Gatys, L.A.: Image style transfer using convolutional neural networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2414\u22122423. IEEE Computer Society, Las Vegas(2016)","key":"32_CR19","DOI":"10.1109\/CVPR.2016.265"},{"unstructured":"Radford, A., Metz, L., Chintala, S.: Unsupervised representation learning with deep convolutional generative adversarial networks. Comput. Sci. (2015)","key":"32_CR20"},{"unstructured":"Nguyen, A., Dosovitskiy, A., Yosinski, J., Brox, T., Clune, J.: Synthesizing the preferred inputs for neurons in neural networks via deep generator networks. Neurips 3(1) (2016)","key":"32_CR21"},{"unstructured":"Dosovitskiy, A.: Generating images with perceptual similarity metrics based on deep networks. In: Proceedings of the 30th International Conference on Neural Information Processing Systems, pp. 658\u2013666. NIPS, Barcelona (2016)","key":"32_CR22"},{"unstructured":"Dataset Homepage. https:\/\/openneuro.org\/datasets\/ds001506. Accessed 20 June 2023","key":"32_CR23"},{"unstructured":"SPM Homepage. http:\/\/www.fil.ion.ucl.ac.uk\/spm. Accessed 10 July 2023","key":"32_CR24"},{"issue":"10","key":"32_CR25","doi-asserted-by":"publisher","first-page":"1186","DOI":"10.1109\/10.951522","volume":"48","author":"JC Rajapakse","year":"2001","unstructured":"Rajapakse, J.C.: Bayesian approach to segmentation of statistical parametric maps. IEEE Trans. Biomed. Eng. 48(10), 1186\u20131194 (2001)","journal-title":"IEEE Trans. Biomed. Eng."}],"container-title":["Communications in Computer and Information Science","Neural Computing for Advanced Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-7001-4_32","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,21]],"date-time":"2024-09-21T18:03:37Z","timestamp":1726941817000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-7001-4_32"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,22]]},"ISBN":["9789819770007","9789819770014"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-7001-4_32","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2024,9,22]]},"assertion":[{"value":"22 September 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"NCAA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Neural Computing for Advanced Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Guilin","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","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":"5 July 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 July 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ncaa2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/aaci.org.hk\/ncaa2024\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}