Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland; Department of Decoded Neurofeedback, Advanced Telecommunications Research (ATR) Computational Neuroscience Laboratories, 2-2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0288, Japan.
Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland.
Trends Neurosci. 2020 Sep;43(9):667-680. doi: 10.1016/j.tins.2020.06.005. Epub 2020 Jul 15.
Human behavior comprises many aspects that stand out by their dynamic nature. To quantify its neural underpinnings, time-resolved fMRI methods have blossomed over the past decade. In this review we conceptually organize a broad repertoire of dynamic analytical pipelines and extract general observations on their application to the study of behavior and brain disorders. We aim to provide an extensive overview instead of examining only selected methodological families or specific behavioral domains. We consider behavioral aspects with distinct long-term stability (e.g., physiological state versus personality), and also address selected brain disorders with complementary genetics and symptomatology. This synthesis exposes the somewhat limited consistency of dynamic findings in the literature, as well as the unbalanced application of the multitude of available approaches which would, owing to their technical specificities, have potential to reveal distinct aspects of dynamics. We call for further comparative and collaborative efforts in the future.
人类行为包含许多方面，其动态性质尤为突出。为了量化其神经基础，过去十年中，时间分辨 fMRI 方法蓬勃发展。在这篇综述中，我们从概念上组织了广泛的动态分析管道，并对其在行为和大脑障碍研究中的应用得出了一些普遍的观察结果。我们的目标是提供广泛的概述，而不是只检查特定的方法家族或特定的行为领域。我们考虑了具有不同长期稳定性的行为方面（例如，生理状态与个性），还针对具有互补遗传学和症状学的选定大脑障碍进行了探讨。这种综合研究揭示了文献中动态研究结果的一致性有限，以及多种可用方法的应用不平衡，这些方法由于其技术特性，有可能揭示动态的不同方面。我们呼吁未来进行更多的比较和合作研究。
