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Survey of Encoding and Decoding of Visual Stimulus via FMRI: An Image Analysis Perspective

机译：基于FMRI的视觉刺激编码和解码研究：图像分析

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摘要

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.
机译：在过去的几十年中，通过功能磁共振成像（fMRI）在大脑编码和解码方面取得了各种令人兴奋的科学成就。近年来，这种趋势继续上升，这一主题的已发表论文数量不断增加，并且针对研究问题的不同方面发表了几篇调查论文。从本质上讲，尽管简要讨论了计算挑战，但这些调查文章主要来自认知神经科学和神经影像学的观点。为了补充现有的调查文章，本文着重于对各种图像分析方法的调查，例如神经图像配准，fMRI信号分析，ROI（感兴趣区域）选择，机器学习算法，再现性分析，结构和功能连通性以及自然图像分析，以前的大脑编码/解码研究工作都采用了这种方法。本文还讨论了那些图像分析方法的潜在局限性以及未来可能的改进。希望对图像分析问题进行广泛的讨论可以为日益重要的大脑编码/解码领域的发展做出贡献。

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