Reconstructing Perceived Images From Human Brain Activities With Bayesian Deep Multiview Learning

doi:10.1109/TNNLS.2018.2882456

	Reconstructing Perceived Images From Human Brain Activities With Bayesian Deep Multiview Learning
	Du, Changde 1,2; Du, Changying 3,4; Huang, Lijie 1,2; He, Huiguang1,2,5
刊名	IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
	2019-08-01
卷号	30 期号:8 页码:2310-2323
关键词	Deep neural network (DNN) image reconstruction multiview learning neural decoding variational Bayesian inference
ISSN号	2162-237X
DOI	10.1109/TNNLS.2018.2882456
通讯作者	He, Huiguang(huiguang.he@ia.ac.cn)
英文摘要	Neural decoding, which aims to predict external visual stimuli information from evoked brain activities, plays an important role in understanding human visual system. Many existing methods are based on linear models, and most of them only focus on either the brain activity pattern classification or visual stimuli identification. Accurate reconstruction of the perceived images from the measured human brain activities still remains challenging. In this paper, we propose a novel deep generative multiview model for the accurate visual image reconstruction from the human brain activities measured by functional magnetic resonance imaging (fMRI). Specifically, we model the statistical relationships between the two views (i.e., the visual stimuli and the evoked fMRI) by using two view-specific generators with a shared latent space. On the one hand, we adopt a deep neural network architecture for visual image generation, which mimics the stages of human visual processing. On the other hand, we design a sparse Bayesian linear model for fMRI activity generation, which can effectively capture voxel correlations, suppress data noise, and avoid overfitting. Furthermore, we devise an efficient mean-field variational inference method to train the proposed model. The proposed method can accurately reconstruct visual images via Bayesian inference. In particular, we exploit a posterior regularization technique in the Bayesian inference to regularize the model posterior. The quantitative and qualitative evaluations conducted on multiple fMRI data sets demonstrate the proposed method can reconstruct visual images more accurately than the state of the art.
资助项目	National Natural Science Foundation of China[91520202] ; National Natural Science Foundation of China[61602449] ; CAS Scientific Equipment Development Project[YJKYYQ20170050] ; Beijing Municipal Science and Technology Commission[Z181100008918010] ; Youth Innovation Promotion Association CAS ; Strategic Priority Research Program of CAS
WOS关键词	NEURAL-NETWORKS ; NATURAL IMAGES ; FMRI ; REPRESENTATIONS ; CATEGORIES ; PATTERNS ; OBJECTS ; MODELS ; FACES
WOS研究方向	Computer Science ; Engineering
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000476787300006
资助机构	National Natural Science Foundation of China ; CAS Scientific Equipment Development Project ; Beijing Municipal Science and Technology Commission ; Youth Innovation Promotion Association CAS ; Strategic Priority Research Program of CAS
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/27781]
专题	中国科学院自动化研究所
通讯作者	He, Huiguang
作者单位	1.Chinese Acad Sci, Inst Automat, Res Ctr Brain Inspired Intelligence, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Inst Software, Lab Parallel Software & Computat Sci, Beijing 100190, Peoples R China 4.360 Search Lab, Beijing 100015, Peoples R China 5.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Du, Changde,Du, Changying,Huang, Lijie,et al. Reconstructing Perceived Images From Human Brain Activities With Bayesian Deep Multiview Learning[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2019,30(8):2310-2323.
APA	Du, Changde,Du, Changying,Huang, Lijie,&He, Huiguang.(2019).Reconstructing Perceived Images From Human Brain Activities With Bayesian Deep Multiview Learning.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,30(8),2310-2323.
MLA	Du, Changde,et al."Reconstructing Perceived Images From Human Brain Activities With Bayesian Deep Multiview Learning".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 30.8(2019):2310-2323.