Department of Psychology, Harvard University, Cambridge, USA.
Computer Science & Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, USA.
Sci Rep. 2022 Oct 27;12(1):18081. doi: 10.1038/s41598-022-21768-2.
We can easily perceive the spatial scale depicted in a picture, regardless of whether it is a small space (e.g., a close-up view of a chair) or a much larger space (e.g., an entire class room). How does the human visual system encode this continuous dimension? Here, we investigated the underlying neural coding of depicted spatial scale, by examining the voxel tuning and topographic organization of brain responses. We created naturalistic yet carefully-controlled stimuli by constructing virtual indoor environments, and rendered a series of snapshots to smoothly sample between a close-up view of the central object and far-scale view of the full environment (object-to-scene continuum). Human brain responses were measured to each position using functional magnetic resonance imaging. We did not find evidence for a smooth topographic mapping for the object-to-scene continuum on the cortex. Instead, we observed large swaths of cortex with opposing ramp-shaped profiles, with highest responses to one end of the object-to-scene continuum or the other, and a small region showing a weak tuning to intermediate scale views. However, when we considered the population code of the entire ventral occipito-temporal cortex, we found smooth and linear representation of the object-to-scene continuum. Our results together suggest that depicted spatial scale information is encoded parametrically in large-scale population codes across the entire ventral occipito-temporal cortex.
我们可以轻松感知图像中描绘的空间尺度,无论它是小空间(例如,椅子的特写)还是大得多的空间(例如,整个教室)。人类视觉系统如何对这个连续的维度进行编码?在这里,我们通过检查大脑反应的体素调谐和地形组织,研究了所描绘的空间尺度的潜在神经编码。我们通过构建虚拟室内环境来创建自然但经过精心控制的刺激,并渲染一系列快照,以便在中央物体的特写视图和整个环境的远距视图(物体到场景连续体)之间平滑采样。我们使用功能磁共振成像测量了每个位置的人类大脑反应。我们没有发现皮层上物体到场景连续体的平滑地形映射的证据。相反,我们观察到大片皮层具有相反的斜坡状轮廓,对物体到场景连续体的一端或另一端的反应最高,而一小部分区域对中间尺度的视图表现出较弱的调谐。然而,当我们考虑整个腹侧枕颞叶皮层的群体编码时,我们发现物体到场景连续体的表示是平滑和线性的。我们的结果共同表明,所描绘的空间尺度信息在整个腹侧枕颞叶皮层的大规模群体编码中以参数方式进行编码。