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Survey of encoding and decoding of visual stimulus via FMRI: an image analysis perspective

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Abstract

A variety of exciting scientific achievements have been made in the last few decades in brain encoding and decoding via functional magnetic resonance imaging (fMRI). This trend continues to rise in recent years, as evidenced by the increasing number of published papers in this topic and several published survey papers addressing different aspects of research issues. Essentially, these survey articles were mainly from cognitive neuroscience and neuroimaging perspectives, although computational challenges were briefly discussed. To complement existing survey articles, this paper focuses on the survey of the variety of image analysis methodologies, such as neuroimage registration, fMRI signal analysis, ROI (regions of interest) selection, machine learning algorithms, reproducibility analysis, structural and functional connectivity, and natural image analysis, which were employed in previous brain encoding/decoding research works. This paper also provides discussions of potential limitations of those image analysis methodologies and possible future improvements. It is hoped that extensive discussions of image analysis issues could contribute to the advancements of the increasingly important brain encoding/decoding field.

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Acknowledgments

T. Liu was supported by the NIH Career Award (EB006878), NIH R01 HL087923-03S2, NIH R01 DA033393, NSF CAREER Award (IIS-1149260) and The University of Georgia start-up research funding. J. Han was supported by the National Science Foundation of China under Grant 61005018 and 91120005, NPU-FFR-JC20120237 and Program for New Century Excellent Talents in University under grant NCET-10-0079. L. Guo was supported by the National Science Foundation of China under grant 61273362. X. Hu was supported by the National Science Foundation of China under Grant 61103061, China Postdoctoral Science Foundation under Grant 20110490174 and 2012T50819. The author would like to thank the following collaborators for helpful discussions: Kaiming Li, Xiang Ji, Fan Deng, Dajiang Zhu, Tuo Zhang, Hanbo Chen, Xiang Li, Shu Zhang, Carlos, Faraco, L. Stephen Miller, Heng Huang, Xian-Sheng Hua, and Lie Lu.

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  1. School of Automation, Northwestern Polytechnical University, Xi’an, China

    Mo Chen, Junwei Han, Xintao Hu & Lei Guo

  2. Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA, USA

    Xi Jiang & Tianming Liu

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  1. Mo Chen
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Correspondence to Tianming Liu.

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Chen, M., Han, J., Hu, X. et al. Survey of encoding and decoding of visual stimulus via FMRI: an image analysis perspective. Brain Imaging and Behavior 8, 7–23 (2014). https://doi.org/10.1007/s11682-013-9238-z

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