NeuroDataRR: Replication of cortical microstructure correlations with face and object recognition

人脸识别是一项重要的技能，大多数人在生命早期就开始获得，而其他人类活动依赖于只有我们中的一些人在成年后才能学习的专业知识（例如，识别汽车或匹配指纹）。之前的研究只对男性进行了小样本研究，结果发现，根据大脑中对面孔有优先反应的部分皮层的厚度，可以预测在这类任务中的行为表现。重要的是，大脑结构预测人脸和非人脸识别能力的方式是不同的，大脑皮层较厚的人比大脑皮层较薄的人更擅长识别车辆，而大脑皮层较薄的人在人脸识别任务中表现更好。此外，对于人脸，只有较深的、发育较早的皮层层的厚度才能预测其表现。这项研究将测试这些结果是否能在更大的男性和女性样本中复制。它将研究面孔选择皮层与大脑中对社会互动敏感的其他部分之间的联系如何有助于解释早期面孔经历如何影响大脑皮层深层的厚度。更好地了解大脑结构与视觉能力的关系，可以将预测扩展到广泛的职业，如法医、医学成像和国土安全。这项工作还可以改变我们研究神经系统疾病（如自闭症谱系障碍）的皮层发育方式。该项目将通过该团队对范德比尔特大学科学与数学学院的贡献，提高纳什维尔公立学校中代表性不足的初高中学生的参与度，并提高他们的科学素养。本研究旨在促进我们对视觉区域皮层微观结构与个体视觉能力差异之间关系的理解。利用7特斯拉的超高分辨率成像和最先进的视觉能力心理测量，该项目将复制和扩展与面部和物体视觉识别有关的发现，并将其扩展到梭状回面部区（FFA）皮层的层流结构。该项目还将测试一个人的社会网络大小与杏仁核（AMG）大小之间关系的复制，并测试AMG大小是否介导面部识别与FFA深层厚度之间的相关性。这项工作将把先前对男性的研究结果推广到女性样本中，将行为测试扩展到新的对象类别，并将FFA的层流效应与其他视觉区域的层流效应进行比较。研究视觉能力的神经标记可以增加我们对大脑-行为关系的理解，而不仅仅是一般智力或健康相关行为等已经成功的领域。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Face recognition is an important skill that most people begin to acquire early in life, while other human activities depend on expertise that only some of us learn as adults (e.g., recognizing cars or matching fingerprints). Prior work with a small sample of only men found that it is possible to predict behavioral performance in such tasks based on the thickness of the cortex in a part of the brain that responds preferentially to faces. Importantly, the manner in which face and non-face recognition abilities were predicted by brain structure was different, with individuals with thicker cortex being better at recognizing vehicles than those with thinner cortex, while individuals with thinner cortex performing better in face recognition tasks. In addition, for faces, only the thickness of the deeper, early developing, layers of the cortex predicted performance. This research will test whether these results replicate in a larger sample of men and women. It will investigate how connections between face-selective cortex and other parts of the brain sensitive to social interactions could help explain how early experience with faces influences the thickness of deep cortical layers. A better understanding of how the structure of the brain relates to visual abilities could extend predictions to a wide range of occupations such as forensics, medical imaging, and homeland security. The work could also transform how we study cortical development in neurological disorders such as Autism Spectrum Disorders. The project will improve participation of underrepresented middle and high school students from Nashville public schools and increase scientific literacy, via the team's contributions to the School for Science and Math at Vanderbilt.This research seeks to advance our understanding of how the cortical microstructure of visual areas relates to individual differences in visual abilities. Using ultra-high resolution imaging at 7 Tesla and state-of-the-art psychometric measurement of visual abilities, the project will replicate and extend findings relating visual recognition of faces and objects to the laminar structure of cortex in the fusiform face area (FFA). The project will also test for replication of the relation between one's social network size and the size of the amygdala (AMG), and test whether AMG size mediates the correlation between face recognition and the thickness of FFA's deep layers. The work will generalize prior findings with men to a sample of women, expand behavioral testing to new object categories, and compare laminar effects in FFA to those in other visual areas. Studying the neuromarkers of visual abilities can increase our understanding of brain-behavior relationships beyond already successful domains like general intelligence or health-related behaviors.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.