Wang Ridey H, Dai Lulin, Okamura Jun-Ya, Fuchida Takayasu, Wang Gang
Dept. of Bioengineering, Graduate School of Science and Engineering, Kagoshima University, Kagoshima 890-0065, Japan.
IBRO Neurosci Rep. 2021 Feb 25;10:171-177. doi: 10.1016/j.ibneur.2021.02.008. eCollection 2021 Jun.
We have previously reported an increase in response tolerance of inferotemporal cells around trained views. However, an inferotemporal cell usually displays different response patterns in an initial response phase immediately after the stimulus onset and in a late phase from approximately 260 ms after stimulus onset. This study aimed to understand the difference between the two time periods and their involvement in the view-invariant object recognition. Responses to object images with and without prior experience of object discrimination across views, recorded by microelectrodes, were pooled together from our previous experiments. With a machine learning algorithm, we trained to build classifiers for object discrimination. In the early phase, the performance of classifiers created based on data of responses to the object images with prior training of object discrimination across views did not significantly differ from that based on data of responses to the object images without prior experience of object discrimination across views. However, the performance was significantly better in the late phase. Furthermore, compared to the preferred stimulus image in the early phase, we found 2/3 of cells changed their preference in the late phase. For object images with prior experience of training with object discrimination across views, a significant higher percentage of cells responded in the late phase to the same objects as in the early phase, but under different views. The results demonstrate the dynamics of selectivity changes and suggest the involvement of the late phase in the view-invariant object recognition rather than that of the early phase.
我们之前曾报道过,颞下叶细胞对经过训练的视图周围的反应耐受性有所增加。然而,颞下叶细胞通常在刺激开始后的初始反应阶段以及刺激开始后约260毫秒的后期表现出不同的反应模式。本研究旨在了解这两个时间段之间的差异以及它们在视图不变的物体识别中的作用。通过微电极记录的对有和没有跨视图物体辨别先验经验的物体图像的反应,是从我们之前的实验中汇总而来的。我们使用机器学习算法训练以构建用于物体辨别的分类器。在早期阶段,基于对经过跨视图物体辨别先验训练的物体图像的反应数据创建的分类器的性能,与基于对没有跨视图物体辨别先验经验的物体图像的反应数据创建的分类器的性能没有显著差异。然而,在后期阶段,性能明显更好。此外,与早期阶段的偏好刺激图像相比,我们发现三分之二的细胞在后期改变了它们的偏好。对于有跨视图物体辨别训练先验经验的物体图像,在后期对相同物体但在不同视图下做出反应的细胞百分比显著高于早期。结果证明了选择性变化的动态性,并表明后期阶段参与了视图不变的物体识别,而不是早期阶段。