精神分裂症(面向对象编程)
双相情感障碍
脑老化
单变量
心理学
体素
神经影像学
多元统计
神经科学
精神科
医学
认知
机器学习
计算机科学
放射科
作者
Igor Nenadić,Maren Dietzek,Kerstin Langbein,Heinrich Sauer,Christian Gaser
标识
DOI:10.1016/j.pscychresns.2017.05.006
摘要
BrainAGE (brain age gap estimation) is a novel morphometric parameter providing a univariate score derived from multivariate voxel-wise analyses. It uses a machine learning approach and can be used to analyse deviation from physiological developmental or aging-related trajectories. Using structural MRI data and BrainAGE quantification of acceleration or deceleration of in individual aging, we analysed data from 45 schizophrenia patients, 22 bipolar I disorder patients (mostly with previous psychotic symptoms / episodes), and 70 healthy controls. We found significantly higher BrainAGE scores in schizophrenia, but not bipolar disorder patients. Our findings indicate significantly accelerated brain structural aging in schizophrenia. This suggests, that despite the conceptualisation of schizophrenia as a neurodevelopmental disorder, there might be an additional progressive pathogenic component.
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