Neurosciences Graduate Program, Stanford University, Stanford, California 94305,
Wu Tsai Neurosciences Institute, Stanford, California 94305.
J Neurosci. 2020 Apr 8;40(15):3008-3024. doi: 10.1523/JNEUROSCI.2106-19.2020. Epub 2020 Feb 24.
Human ventral temporal cortex (VTC) is critical for visual recognition. It is thought that this ability is supported by large-scale patterns of activity across VTC that contain information about visual categories. However, it is unknown how category representations in VTC are organized at the submillimeter scale and across cortical depths. To fill this gap in knowledge, we measured BOLD responses in medial and lateral VTC to images spanning 10 categories from five domains (written characters, bodies, faces, places, and objects) at an ultra-high spatial resolution of 0.8 mm using 7 Tesla fMRI in both male and female participants. Representations in lateral VTC were organized most strongly at the general level of domains (e.g., places), whereas medial VTC was also organized at the level of specific categories (e.g., corridors and houses within the domain of places). In both lateral and medial VTC, domain-level and category-level structure decreased with cortical depth, and downsampling our data to standard resolution (2.4 mm) did not reverse differences in representations between lateral and medial VTC. The functional diversity of representations across VTC partitions may allow downstream regions to read out information in a flexible manner according to task demands. These results bridge an important gap between electrophysiological recordings in single neurons at the micron scale in nonhuman primates and standard-resolution fMRI in humans by elucidating distributed responses at the submillimeter scale with ultra-high-resolution fMRI in humans. Visual recognition is a fundamental ability supported by human ventral temporal cortex (VTC). However, the nature of fine-scale, submillimeter distributed representations in VTC is unknown. Using ultra-high-resolution fMRI of human VTC, we found differential distributed visual representations across lateral and medial VTC. Domain representations (e.g., faces, bodies, places, characters) were most salient in lateral VTC, whereas category representations (e.g., corridors/houses within the domain of places) were equally salient in medial VTC. These results bridge an important gap between electrophysiological recordings in single neurons at a micron scale and fMRI measurements at a millimeter scale.
人类腹侧颞叶皮层(VTC)对视觉识别至关重要。人们认为,这种能力是由 VTC 中包含视觉类别的大规模活动模式支持的。然而,目前尚不清楚 VTC 中的类别表示在亚毫米尺度和皮层深度上是如何组织的。为了填补这一知识空白,我们使用 7 特斯拉 fMRI 在男性和女性参与者中以 0.8 毫米的超高空间分辨率测量了内侧和外侧 VTC 对跨越五个领域(书写字符、身体、面部、地点和物体)的 10 个类别的图像的 BOLD 反应。外侧 VTC 的表示形式最强地组织在域的一般水平(例如,地点),而内侧 VTC 也组织在特定类别的水平(例如,地点域中的走廊和房屋)。在内侧和外侧 VTC 中,域级和类别级结构随皮层深度而降低,并且将我们的数据下采样到标准分辨率(2.4 毫米)不会改变外侧和内侧 VTC 之间表示的差异。VTC 分区中表示的功能多样性可能允许下游区域根据任务需求以灵活的方式读取信息。这些结果在非人类灵长类动物的微米尺度上的单个神经元的电生理记录和人类的标准分辨率 fMRI 之间架起了一座重要的桥梁,通过阐明人类的超高分辨率 fMRI 亚毫米尺度上的分布式反应。视觉识别是人类腹侧颞叶皮层(VTC)支持的基本能力。然而,VTC 中细尺度、亚毫米分布式表示的性质尚不清楚。使用人类 VTC 的超高分辨率 fMRI,我们发现了外侧和内侧 VTC 之间的差异分布式视觉表示。域表示(例如,面孔、身体、地点、字符)在外侧 VTC 中最为突出,而类别表示(例如,地点域中的走廊/房屋)在内侧 VTC 中同样突出。这些结果在微米尺度上的单个神经元的电生理记录和毫米尺度上的 fMRI 测量之间架起了一座重要的桥梁。