Turk-Browne Nicholas B, Norman-Haignere Samuel V, McCarthy Gregory
Department of Psychology, Princeton University Princeton, NJ, USA.
Front Hum Neurosci. 2010 Sep 24;4:176. doi: 10.3389/fnhum.2010.00176. eCollection 2010.
Faces activate specific brain regions in fMRI, including the fusiform gyrus (FG) and the posterior superior temporal sulcus (pSTS). The fact that the FG and pSTS are frequently co-activated suggests that they may interact synergistically in a distributed face processing network. Alternatively, the functions implemented by these regions may be encapsulated from each other. It has proven difficult to evaluate these two accounts during visual processing of face stimuli. However, if the FG and pSTS interact during face processing, the substrate for such interactions may be apparent in a correlation of the BOLD timeseries from these two regions during periods of rest when no faces are present. To examine face-specific resting correlations, we developed a new partial functional connectivity approach in which we removed variance from the FG that was shared with other category-selective and control regions. The remaining face-specific FG resting variance was then used to predict resting signals throughout the brain. In two experiments, we observed face-specific resting functional connectivity between FG and pSTS, and importantly, these correlations overlapped precisely with the face-specific pSTS region obtained from independent localizer runs. Additional region-of-interest and pattern analyses confirmed that the FG-pSTS resting correlations were face-specific. These findings support a model in which face processing is distributed among a finite number of connected, but nevertheless face-specialized regions. The discovery of category-specific interactions in the absence of visual input suggests that resting networks may provide a latent foundation for task processing.
在功能磁共振成像(fMRI)中,面孔会激活特定的脑区,包括梭状回(FG)和颞上沟后部(pSTS)。FG和pSTS经常共同激活,这一事实表明它们可能在分布式面孔处理网络中协同作用。或者,这些区域所执行的功能可能相互独立。在对面孔刺激进行视觉处理时,很难评估这两种情况。然而,如果FG和pSTS在面孔处理过程中相互作用,那么在没有面孔呈现的静息期,这两个区域的血氧水平依赖(BOLD)时间序列的相关性中,这种相互作用的基础可能会显现出来。为了研究面孔特异性静息相关性,我们开发了一种新的部分功能连接方法,在该方法中,我们去除了FG中与其他类别选择性和控制区域共享的方差。然后,将剩余的面孔特异性FG静息方差用于预测全脑的静息信号。在两个实验中,我们观察到FG和pSTS之间存在面孔特异性静息功能连接,重要的是,这些相关性与从独立定位运行中获得的面孔特异性pSTS区域精确重叠。额外的感兴趣区域和模式分析证实,FG - pSTS静息相关性是面孔特异性的。这些发现支持了一种模型,即面孔处理分布在有限数量的相互连接但专门用于面孔处理的区域中。在没有视觉输入的情况下发现类别特异性相互作用表明,静息网络可能为任务处理提供潜在基础。