Duann Jeng-Ren, Jung Tzyy-Ping, Kuo Wen-Jui, Yeh Tzu-Chen, Makeig Scott, Hsieh Jen-Chuen, Sejnowski Terrence J
Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, California 92037, USA.
Neuroimage. 2002 Apr;15(4):823-35. doi: 10.1006/nimg.2001.1049.
Most current analysis methods for fMRI data assume a priori knowledge of the time course of the hemodynamic response (HR) to experimental stimuli or events in brain areas of interest. In addition, they typically assume homogeneity of both the HR and the non-HR "noise" signals, both across brain regions and across similar experimental events. When HRs vary unpredictably, from area to area or from trial to trial, an alternative approach is needed. Here, we use Infomax independent component analysis (ICA) to detect and visualize variations in single-trial HRs in event-related fMRI data. Six subjects participated in four fMRI sessions each in which ten bursts of 8-Hz flickering-checkerboard stimulation were presented for 0.5-s (short) or 3-s (long) durations at 30-s intervals. Five axial slices were acquired by a Bruker 3-T magnetic resonance imager at interscan intervals of 500 ms (TR). ICA decomposition of the resulting blood oxygenation level-dependent (BOLD) data from each session produced an independent component active in primary visual cortex (V1) and, in several sessions, another active in medial temporal cortex (MT/V5). Visualizing sets of BOLD response epochs with novel BOLD-image plots demonstrated that component HRs varied substantially and often systematically across trials as well as across sessions, subjects, and brain areas. Contrary to expectation, in four of the six subjects the V1 component HR contained two positive peaks in response to short-stimulus bursts, while components with nearly identical regions of activity in long-stimulus sessions from the same subjects were associated with single-peaked HRs. Thus, ICA combined with BOLD-image visualization can reveal dramatic and unforeseen HR variations not apparent to researchers analyzing their data with event-related response averaging and fixed HR templates.
当前大多数功能磁共振成像(fMRI)数据的分析方法都假定对感兴趣脑区中实验刺激或事件的血液动力学反应(HR)的时间进程具有先验知识。此外,它们通常假定HR和非HR“噪声”信号在脑区之间以及相似实验事件之间具有同质性。当HR在不同区域或不同试验中不可预测地变化时,就需要一种替代方法。在这里,我们使用信息最大化独立成分分析(ICA)来检测和可视化事件相关fMRI数据中单次试验HR的变化。六名受试者每人参加了四次fMRI实验,每次实验中以30秒的间隔呈现十次8赫兹闪烁棋盘格刺激,持续时间为0.5秒(短)或3秒(长)。由布鲁克3-T磁共振成像仪以500毫秒的扫描间隔(TR)采集五个轴向切片。对每个实验中得到的血氧水平依赖(BOLD)数据进行ICA分解,产生了一个在初级视觉皮层(V1)活跃的独立成分,并且在几次实验中,另一个在颞叶内侧皮层(MT/V5)活跃。用新颖的BOLD图像图可视化BOLD反应时期的集合表明,成分HR在不同试验以及不同实验、受试者和脑区之间有很大差异,且常常是系统性的。与预期相反,在六名受试者中的四名中,V1成分HR对短刺激爆发的反应包含两个正峰,而来自同一受试者的长刺激实验中具有几乎相同活动区域的成分与单峰HR相关。因此,ICA与BOLD图像可视化相结合可以揭示出戏剧性的、不可预见的HR变化,而这些变化对于使用事件相关反应平均和固定HR模板分析数据的研究人员来说并不明显。