Center for Cognition and Sociality, Institute for Basic Science, Daejeon 34126, Korea.
Department of Biological Science, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea.
J Neurosci. 2022 Feb 9;42(6):1141-1153. doi: 10.1523/JNEUROSCI.0628-21.2021. Epub 2021 Dec 13.
It is clear that humans can extract statistical information from streams of visual input, yet how our brain processes sequential images into the abstract representation of the mean feature value remains poorly explored. Using multivariate pattern analyses of electroencephalography recorded while human observers viewed 10 sequentially presented Gabors of different orientations to estimate their mean orientation at the end, we investigated sequential averaging mechanism by tracking the quality of individual and mean orientation as a function of sequential position. Critically, we varied the sequential variance of Gabor orientations to understand the neural basis of perceptual mean errors occurring during a sequential averaging task. We found that the mean-orientation representation emerged at specific delays from each sequential stimulus onset and became increasingly accurate as additional Gabors were viewed. Especially in frontocentral electrodes, the neural representation of mean orientation improved more rapidly and to a greater degree in less volatile environments, whereas individual orientation information was encoded precisely regardless of environmental volatility. The computational analysis of behavioral data also showed that perceptual mean errors arise from the cumulative construction of the mean orientation rather than the low-level encoding of individual stimulus orientation. Thus, our findings provide neural mechanisms to differentially accumulate increasingly abstract features from a concrete piece of information across the cortical hierarchy depending on environmental volatility. The visual system extracts behaviorally relevant summary statistical representation by exploiting statistical regularity of the visual stream over time. However, how the neural representation of the abstract mean feature value develops in a temporally changing environment remains poorly identified. Here, we directly recover the mean orientation information of sequentially delivered Gabor stimuli with different orientations as a function of their positions in time. The mean orientation representation, which is regularly updated, becomes increasingly accurate with increasing sequential position especially in the frontocentral region. Further, perceptual mean errors arise from the cumulative process rather than the low-level stimulus encoding. Overall, our study reveals a role of higher cortical areas in integrating stimulus-specific information into increasingly abstract task-oriented information.
很明显，人类可以从视觉输入流中提取统计信息，但我们的大脑如何将连续的图像转化为均值特征值的抽象表示形式，仍未得到充分探索。我们使用记录人类观察者观看 10 个不同方向的顺序呈现的 Gabor 图案时的脑电图的多元模式分析，来估计他们在最后看到的平均方向，以此来研究顺序平均机制，通过跟踪个别和平均方向的质量作为顺序位置的函数。关键的是，我们改变了 Gabor 方向的顺序方差，以了解在顺序平均任务中出现的感知平均误差的神经基础。我们发现，平均方向的表示在每个顺序刺激开始后特定的延迟出现，并随着更多的 Gabor 被观看而变得越来越准确。特别是在前额中央电极，平均方向的神经表示在环境变化较小的情况下，以更快和更大的程度改善，而个体方向信息无论环境变化如何都被精确编码。对行为数据的计算分析也表明，感知平均误差是由平均方向的累积构建引起的，而不是由个体刺激方向的低级编码引起的。因此，我们的发现提供了神经机制，根据环境的变化，在皮质层次结构中从具体信息中逐渐积累越来越抽象的特征。视觉系统通过随时间利用视觉流的统计规律来提取行为相关的摘要统计表示。然而，在时间变化的环境中，抽象的均值特征值的神经表示是如何发展的，仍然没有得到很好的确定。在这里，我们直接根据它们在时间中的位置，作为时间函数，恢复顺序呈现的具有不同方向的 Gabor 刺激的平均方向信息。平均方向的表示是定期更新的，随着顺序位置的增加而变得越来越准确，特别是在前额中央区域。此外，感知平均误差是由累积过程而不是低级刺激编码引起的。总的来说，我们的研究揭示了更高的皮质区域在将刺激特定信息整合到越来越抽象的任务导向信息中的作用。
