German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany; Bernstein Center for Computational Neuroscience (BCCN), Berlin, Germany.
Leibniz Institute for Neurobiology (LIN), Magdeburg, Germany.
Neuroimage. 2021 Apr 15;230:117820. doi: 10.1016/j.neuroimage.2021.117820. Epub 2021 Jan 29.
Subsequent memory paradigms allow to identify neural correlates of successful encoding by separating brain responses as a function of memory performance during later retrieval. In functional magnetic resonance imaging (fMRI), the paradigm typically elicits activations of medial temporal lobe, prefrontal and parietal cortical structures in young, healthy participants. This categorical approach is, however, limited by insufficient memory performance in older and particularly memory-impaired individuals. A parametric modulation of encoding-related activations with memory confidence could overcome this limitation. Here, we applied cross-validated Bayesian model selection (cvBMS) for first-level fMRI models to a visual subsequent memory paradigm in young (18-35 years) and older (51-80 years) adults. Nested cvBMS revealed that parametric models, especially with non-linear transformations of memory confidence ratings, outperformed categorical models in explaining the fMRI signal variance during encoding. We thereby provide a framework for improving the modeling of encoding-related activations and for applying subsequent memory paradigms to memory-impaired individuals.
后续记忆范式允许通过在后期检索过程中根据记忆表现来分离大脑反应，从而确定成功编码的神经相关性。在功能磁共振成像 (fMRI) 中，该范式通常会在年轻健康参与者中引发内侧颞叶、前额叶和顶叶皮质结构的激活。然而，这种分类方法受到老年个体，特别是记忆受损个体记忆表现不足的限制。通过对与记忆信心相关的编码激活进行参数调制，可以克服这一限制。在这里，我们在年轻（18-35 岁）和老年（51-80 岁）成年人中应用交叉验证贝叶斯模型选择（cvBMS）对视觉后续记忆范式进行了一级 fMRI 模型。嵌套 cvBMS 表明，参数模型，特别是使用记忆信心评分的非线性变换，在解释编码期间 fMRI 信号方差方面优于分类模型。因此，我们为改进与编码相关的激活模型以及将后续记忆范式应用于记忆受损个体提供了一个框架。
