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与学习相关的效应和功能神经影像学。

Learning-related effects and functional neuroimaging.

作者信息

Petersson K M, Elfgren C, Ingvar M

机构信息

Department of Clinical Neuroscience, Karolinska Institute, Karolinska Hospital, Stockholm, Sweden.

出版信息

Hum Brain Mapp. 1999;7(4):234-43. doi: 10.1002/(sici)1097-0193(1999)7:4<234::aid-hbm2>3.0.co;2-o.

DOI:10.1002/(sici)1097-0193(1999)7:4<234::aid-hbm2>3.0.co;2-o
PMID:10408767
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6873329/
Abstract

A fundamental problem in the study of learning is that learning-related changes may be confounded by nonspecific time effects. There are several strategies for handling this problem. This problem may be of greater significance in functional magnetic resonance imaging (fMRI) compared to positron emission tomography (PET). Using the general linear model, we describe, compare, and discuss two approaches for separating learning-related from nonspecific time effects. The first approach makes assumptions on the general behavior of nonspecific effects and explicitly models these effects, i.e., nonspecific time effects are incorporated as a linear or nonlinear confounding covariate in the statistical model. The second strategy makes no a priori assumption concerning the form of nonspecific time effects, but implicitly controls for nonspecific effects using an interaction approach, i.e., learning effects are assessed with an interaction contrast. The two approaches depend on specific assumptions and have specific limitations. With certain experimental designs, both approaches may be used and the results compared, lending particular support to effects that are independent of the method used. A third and perhaps better approach that sometimes may be practically unfeasible is to use a completely temporally balanced experimental design. The choice of approach may be of particular importance when learning-related effects are studied with fMRI.

摘要

学习研究中的一个基本问题是,与学习相关的变化可能会被非特异性的时间效应混淆。有几种策略可以处理这个问题。与正电子发射断层扫描(PET)相比,这个问题在功能磁共振成像(fMRI)中可能具有更大的意义。使用一般线性模型,我们描述、比较并讨论了两种将与学习相关的效应与非特异性时间效应分离的方法。第一种方法对非特异性效应的一般行为做出假设,并明确地对这些效应进行建模,即非特异性时间效应作为线性或非线性的混杂协变量纳入统计模型。第二种策略对非特异性时间效应的形式不做先验假设,而是使用交互作用方法隐式地控制非特异性效应,即通过交互对比来评估学习效应。这两种方法依赖于特定的假设,并且有特定的局限性。在某些实验设计中,可以同时使用这两种方法并比较结果,这尤其支持了那些与所使用方法无关的效应。第三种可能更好但有时在实际中不可行的方法是使用完全时间平衡的实验设计。当使用fMRI研究与学习相关的效应时,方法的选择可能尤为重要。

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