Thickness of Deep Layers in the Fusiform Face Area Predicts Face Recognition
Thickness of Deep Layers in the Fusiform Face Area Predicts Face Recognition
复制标题
DOI：
10.1162/jocn_a_01551
复制
发表时间：
2020-07-01
影响因子：
3.2
通讯作者：
Gauthier, Isabel
中科院分区：
文献类型：
--
作者：
McGugin, Rankin W.;Newton, Allen T.;Gauthier, Isabel
面部识别能力强的人，面部选择性大脑区域的皮质相对较薄，而车辆识别能力强的人，同一区域的皮质相对较厚。我们认为，这些相反的相关性反映了影响皮质厚度（CT）的不同机制，因为能力是在发育的不同阶段获得的。我们通过皮层深度探索了关于这些效应的特异性的新预测：面部识别选择性地与面部选择性区域中最深层状细分的厚度呈负相关。利用 7T 的超高分辨率 MRI，我们估计了 14 名成年男性右侧梭形面部区域 (FFA) 中三个层状细分（我们称之为“MR 层”）的厚度。人脸识别与深层 MR 层的厚度呈负相关，而车辆识别与所有层的厚度呈正相关。回归模型比较为模型提供了压倒性的支持，该模型指定人脸识别和 CT 之间的关联程度在 MR 层（深层与浅层/中层）之间有所不同，而车辆识别和 CT 之间的关联程度在各层之间是不变的。右侧FFA的总CT占人脸识别方差的69%，仅深层厚度就占该方差的84%。我们的研究结果证明了 FFA 中 MR 层流估计的功能有效性。研究同一皮质区域多种能力的个体差异的结构基础可以揭示在研究平均变异或发育时不明显的不同机制的影响。
People with superior face recognition have relatively thin cortex in face-selective brain areas, whereas those with superior vehicle recognition have relatively thick cortex in the same areas. We suggest that these opposite correlations reflect distinct mechanisms influencing cortical thickness (CT) as abilities are acquired at different points in development. We explore a new prediction regarding the specificity of these effects through the depth of the cortex: that face recognition selectively and negatively correlates with thickness of the deepest laminar subdivision in face-selective areas. With ultrahigh resolution MRI at 7T, we estimated the thickness of three laminar subdivisions, which we term "MR layers," in the right fusiform face area (FFA) in 14 adult male humans. Face recognition was negatively associated with the thickness of deep MR layers, whereas vehicle recognition was positively related to the thickness of all layers. Regression model comparisons provided overwhelming support for a model specifying that the magnitude of the association between face recognition and CT differs across MR layers (deep vs. superficial/middle) whereas the magnitude of the association between vehicle recognition and CT is invariant across layers. The total CT of right FFA accounted for 69% of the variance in face recognition, and thickness of the deep layer alone accounted for 84% of this variance. Our findings demonstrate the functional validity of MR laminar estimates in FFA. Studying the structural basis of individual differences for multiple abilities in the same cortical area can reveal effects of distinct mechanisms that are not apparent when studying average variation or development.