Hautzel H, Mottaghy F M, Schmidt D, Müller H-W, Krause B J
Klinik für Nuklearmedizin, Forschungszentrum Jülich, 52426 Jülich, Deutschland.
Nuklearmedizin. 2003 Oct;42(5):197-209.
In cognitive neuroscience regional cerebral blood flow (rCBF) imaging with positron-emission-tomography (PET) is a powerful tool to characterize different aspects of cognitive processes by using different data analysis approaches. By use of an n-back verbal working memory task (varied from 0- to 3-back) we present cognitive subtraction analysis as basic strategy as well as parametric and covariance analyses and discuss the results.
Correlation analyses were performed using the individual performance rate as an external covariate, computing inter-regional correlations, and as network analysis applying structural equation modelling to evaluate the effective connectivity between the involved brain regions.
Subtraction analyses revealed a fronto-parietal neuronal network also including the anterior cingulate cortex and the cerebellum. With higher memory load the parametric analysis evidenced linear rCBF increases in prefrontal, pre-motor and inferior parietal areas including the precuneus as well as in the anterior cingulate cortex. The rCBF correlation with the individual performance as external covariate depicted negative correlations in bilateral prefrontal and inferior parietal regions, in the precuneus and the anterior cingulate cortex. The network analysis demonstrated mainly occipito-frontally directed interactions which were predominantly left-hemispheric. Additionally, strong linkages were found between extrastriate and parietal regions as well as within the parietal cortex.
The data analysis approaches presented here contribute to an extended and more elaborated understanding of cognitive processes and their different sub-aspects.
在认知神经科学中,正电子发射断层扫描(PET)的局部脑血流(rCBF)成像是一种强大的工具,可通过使用不同的数据分析方法来表征认知过程的不同方面。通过使用n-back言语工作记忆任务(从0-back到3-back变化),我们展示了认知减法分析作为基本策略以及参数分析和协方差分析,并讨论了结果。
使用个体表现率作为外部协变量进行相关分析,计算区域间相关性,并作为网络分析应用结构方程模型来评估所涉及脑区之间的有效连接性。
减法分析揭示了一个额顶神经元网络,还包括前扣带回皮质和小脑。随着记忆负荷增加,参数分析证明前额叶、运动前区和顶叶下部区域(包括楔前叶)以及前扣带回皮质的rCBF呈线性增加。rCBF与作为外部协变量的个体表现的相关性在双侧前额叶和顶叶下部区域、楔前叶和前扣带回皮质中呈现负相关。网络分析显示主要是枕额方向的相互作用,主要是左半球的。此外,在纹外区和顶叶区域之间以及顶叶皮质内发现了强连接。
本文提出的数据分析方法有助于对认知过程及其不同子方面进行更广泛和更详细的理解。