Linking patterns of infant eye movements to a neural network model of the ventral stream using representational similarity analysis.

Linking patterns of infant eye movements to a neural network model of the ventral stream using representational similarity analysis.
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DOI:
10.1111/desc.13155
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发表时间:
2022-01
影响因子:
3.7
通讯作者:
Oakes LM
Oakes LM
中科院分区:
心理学1区
文献类型:
--
作者:
Kiat JE;Luck SJ;Beckner AG;Hayes TR;Pomaranski KI;Henderson JM;Oakes LM

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人们对婴儿期视觉皮质高级区域的发育知之甚少,更不知道视觉引导行为的发展与大脑皮层不同处理层次的不同水平之间的关系。作为填补这些空白的第一步,我们使用代表性相似性分析(RSA)来评估凝视模式和捕捉腹侧视觉处理流关键特性的神经网络模型之间的联系。我们记录了4到12个月大的婴儿(N=54)在观看场景照片时的眼球运动。对于每个婴儿,我们计算了每对照片的凝视模式的相似性。我们还使用卷积神经网络模型分析了图像,在该模型中,连续的层大致对应于腹侧流区域的顺序。对于网络的每一层,我们计算了每对照片的激活模式的相似性,然后将其与婴儿凝视数据进行比较。我们发现,在年龄较小的婴儿中,与较低水平的视觉皮质区域相对应的网络层比在较大的婴儿中更好地解释了凝视模式,而在较大的婴儿中,与较高水平的视觉皮质区域相对应的网络层对凝视模式的解释比在较小的婴儿中更好。因此,在4到12个月之间,凝视会越来越多地被更抽象、更高层次的表征所控制。这些结果也证明了使用RSA将婴儿凝视行为与神经网络模型联系起来的可行性。
Little is known about the development of higher-level areas of visual cortex during infancy, and even less is known about how the development of visually guided behavior is related to the different levels of the cortical processing hierarchy. As a first step toward filling these gaps, we used representational similarity analysis (RSA) to assess links between gaze patterns and a neural network model that captures key properties of the ventral visual processing stream. We recorded the eye movements of 4- to 12-month-old infants (N = 54) as they viewed photographs of scenes. For each infant, we calculated the similarity of the gaze patterns for each pair of photographs. We also analyzed the images using a convolutional neural network model in which the successive layers correspond approximately to the sequence of areas along the ventral stream. For each layer of the network, we calculated the similarity of the activation patterns for each pair of photographs, which was then compared with the infant gaze data. We found that the network layers corresponding to lower-level areas of visual cortex accounted for gaze patterns better in younger infants than in older infants, whereas the network layers corresponding to higher-level areas of visual cortex accounted for gaze patterns better in older infants than in younger infants. Thus, between 4 and 12 months, gaze becomes increasingly controlled by more abstract, higher-level representations. These results also demonstrate the feasibility of using RSA to link infant gaze behavior to neural network models.
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