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学习连接视觉轮廓。

Learning to link visual contours.

作者信息

Li Wu, Piëch Valentin, Gilbert Charles D

机构信息

The Rockefeller University, New York, NY 10065, USA.

出版信息

Neuron. 2008 Feb 7;57(3):442-51. doi: 10.1016/j.neuron.2007.12.011.

Abstract

In complex visual scenes, linking related contour elements is important for object recognition. This process, thought to be stimulus driven and hard wired, has substrates in primary visual cortex (V1). Here, however, we find contour integration in V1 to depend strongly on perceptual learning and top-down influences that are specific to contour detection. In naive monkeys, the information about contours embedded in complex backgrounds is absent in V1 neuronal responses and is independent of the locus of spatial attention. Training animals to find embedded contours induces strong contour-related responses specific to the trained retinotopic region. These responses are most robust when animals perform the contour detection task but disappear under anesthesia. Our findings suggest that top-down influences dynamically adapt neural circuits according to specific perceptual tasks. This may serve as a general neuronal mechanism of perceptual learning and reflect top-down mediated changes in cortical states.

摘要

在复杂视觉场景中,将相关轮廓元素联系起来对物体识别很重要。这一过程被认为是由刺激驱动且固定不变的,其基础位于初级视觉皮层(V1)。然而,我们在此发现,V1中的轮廓整合强烈依赖于感知学习以及特定于轮廓检测的自上而下的影响。在未受过训练的猴子中,复杂背景中嵌入的轮廓信息在V1神经元反应中并不存在,且与空间注意力的位置无关。训练动物寻找嵌入的轮廓会诱导出特定于训练的视网膜区域的强烈的轮廓相关反应。当动物执行轮廓检测任务时,这些反应最为强烈,但在麻醉状态下会消失。我们的研究结果表明,自上而下的影响会根据特定的感知任务动态地调整神经回路。这可能是感知学习的一种普遍神经元机制,并反映了自上而下介导的皮层状态变化。

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