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类别学习可诱导跨视野的模式识别位置不变性。

Category learning induces position invariance of pattern recognition across the visual field.

作者信息

Jüttner Martin, Rentschler Ingo

机构信息

Psychology - School of Life and Health Sciences, Aston University, Aston Triangle, Birmingham B4 7ET, UK.

出版信息

Proc Biol Sci. 2008 Feb 22;275(1633):403-10. doi: 10.1098/rspb.2007.1492.

Abstract

Human object recognition is considered to be largely invariant to translation across the visual field. However, the origin of this invariance to positional changes has remained elusive, since numerous studies found that the ability to discriminate between visual patterns develops in a largely location-specific manner, with only a limited transfer to novel visual field positions. In order to reconcile these contradicting observations, we traced the acquisition of categories of unfamiliar grey-level patterns within an interleaved learning and testing paradigm that involved either the same or different retinal locations. Our results show that position invariance is an emergent property of category learning. Pattern categories acquired over several hours at a fixed location in either the peripheral or central visual field gradually become accessible at new locations without any position-specific feedback. Furthermore, categories of novel patterns presented in the left hemifield are distinctly faster learnt and better generalized to other locations than those learnt in the right hemifield. Our results suggest that during learning initially position-specific representations of categories based on spatial pattern structure become encoded in a relational, position-invariant format. Such representational shifts may provide a generic mechanism to achieve perceptual invariance in object recognition.

摘要

人类物体识别在很大程度上被认为对视野中的平移具有不变性。然而,这种对位置变化的不变性的起源仍然难以捉摸,因为大量研究发现,区分视觉模式的能力在很大程度上是以特定位置的方式发展的,对新的视野位置的转移非常有限。为了调和这些相互矛盾的观察结果,我们在一个交错学习和测试范式中追踪了对不熟悉灰度模式类别的习得,该范式涉及相同或不同的视网膜位置。我们的结果表明,位置不变性是类别学习的一种涌现属性。在周边或中央视野的固定位置经过数小时习得的模式类别,在没有任何特定位置反馈的情况下,逐渐在新位置变得可获取。此外,与在右半视野习得的模式类别相比,在左半视野呈现的新图案类别学习速度明显更快,并且能更好地推广到其他位置。我们的结果表明,在学习过程中,最初基于空间模式结构的类别特定位置表征会以一种关系性的、位置不变的格式进行编码。这种表征转变可能提供一种通用机制,以实现物体识别中的感知不变性。

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