大数据和开放科学时代的功能神经影像学:现代概述

IF 4.4 2区 数学 Q1 STATISTICS & PROBABILITY Wiley Interdisciplinary Reviews-Computational Statistics Pub Date : 2023-04-19 DOI:10.1002/wics.1609
N. Lazar
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引用次数: 0

摘要

过去30年 近年来,功能性神经影像学数据的统计分析取得了很大的进展,并激发了许多新的研究方向。与此同时,再现性和可复制性的问题一直困扰着该领域,部分原因是样本量小,数据预处理阶段的选择过多,以及报告总体缺乏透明度。后两者尤其对想要参与这一领域的统计学家构成了障碍。神经影像学界的一些人最近为解决这些问题所做的努力代表了一个转折点。这篇文章强调了当前的形势,并介绍了“开放神经成像”中的一些相关资源
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Functional neuroimaging in the era of Big Data and Open Science: A modern overview
In the past 30 years, the statistical analysis of functional neuroimaging data has made much progress, and spurred many new research directions. At the same time, problems with reproducibility and replicability have plagued the field, owing in part to small sample sizes, a plethora of choices at the data preprocessing stage, and overall lack of transparency in reporting. The latter two in particular pose barriers to statisticians who want to become involved in the area. Recent efforts by some in the neuroimaging community to address these problems represent a turning point. This article highlights the current landscape and provides an introduction to some of the relevant resources in “open neuroimaging.”
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来源期刊
CiteScore
6.20
自引率
0.00%
发文量
31
期刊最新文献
Neuroimaging statistical approaches for determining neural correlates of Alzheimer's disease via positron emission tomography imaging. A spectrum of explainable and interpretable machine learning approaches for genomic studies Functional neuroimaging in the era of Big Data and Open Science: A modern overview Information criteria for model selection Data Integration in Causal Inference.
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