连接组学调和了看似不可调和的神经影像学发现。
Connectomics reconciles seemingly irreconcilable neuroimaging findings.
机构信息
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Chinese Institute for Brain Research, Beijing, China.
出版信息
Trends Cogn Sci. 2023 Jun;27(6):512-513. doi: 10.1016/j.tics.2023.04.005. Epub 2023 Apr 24.
Neuroimaging studies have reported heterogeneity of regional anatomical localization for the same disease, impeding reproducible conclusions regarding brain alterations. In recent work, Cash and colleagues help to reconcile inconsistent findings in functional neuroimaging studies in depression by identifying reliable and clinically valuable distributed brain networks from a connectomic perspective.
神经影像学研究报告称，同一疾病的区域解剖定位存在异质性，这阻碍了关于大脑变化的可重复结论的得出。在最近的工作中，Cash 及其同事从连接组学的角度出发，确定了可靠且具有临床价值的分布式大脑网络，有助于调和抑郁症功能神经影像学研究中的不一致发现。
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