Suppr超能文献

将视网膜特征整合到空间坐标中。

Integrating retinotopic features in spatiotopic coordinates.

机构信息

Schepens Eye Research Institute, Massachusetts Eye and Ear Infirmary, Department of Ophthalmology, Harvard Medical School, Boston, Massachusetts 02114

Schepens Eye Research Institute, Massachusetts Eye and Ear Infirmary, Department of Ophthalmology, Harvard Medical School, Boston, Massachusetts 02114.

出版信息

J Neurosci. 2014 May 21;34(21):7351-60. doi: 10.1523/JNEUROSCI.5252-13.2014.

Abstract

The receptive fields of early visual neurons are anchored in retinotopic coordinates (Hubel and Wiesel, 1962). Eye movements shift these receptive fields and therefore require that different populations of neurons encode an object's constituent features across saccades. Whether feature groupings are preserved across successive fixations or processing starts anew with each fixation has been hotly debated (Melcher and Morrone, 2003; Melcher, 2005, 2010; Knapen et al., 2009; Cavanagh et al., 2010a,b; Morris et al., 2010). Here we show that feature integration initially occurs within retinotopic coordinates, but is then conserved within a spatiotopic coordinate frame independent of where the features fall on the retinas. With human observers, we first found that the relative timing of visual features plays a critical role in determining the spatial area over which features are grouped. We exploited this temporal dependence of feature integration to show that features co-occurring within 45 ms remain grouped across eye movements. Our results thus challenge purely feedforward models of feature integration (Pelli, 2008; Freeman and Simoncelli, 2011) that begin de novo after every eye movement, and implicate the involvement of brain areas beyond early visual cortex. The strong temporal dependence we quantify and its link with trans-saccadic object perception instead suggest that feature integration depends, at least in part, on feedback from higher brain areas (Mumford, 1992; Rao and Ballard, 1999; Di Lollo et al., 2000; Moore and Armstrong, 2003; Stanford et al., 2010).

摘要

早期视觉神经元的感受野是固着在视网膜坐标上的(Hubel 和 Wiesel,1962)。眼球运动改变了这些感受野,因此需要不同的神经元群体在眼跳过程中对物体的组成特征进行编码。特征分组是否在连续的注视中得到保留,或者在每次注视时重新开始,这一直是一个激烈争论的问题(Melcher 和 Morrone,2003;Melcher,2005,2010;Knapen 等人,2009;Cavanagh 等人,2010a,b;Morris 等人,2010)。在这里,我们表明特征整合最初发生在视网膜坐标内,但随后在与视网膜上特征位置无关的空间坐标框架内得到保留。通过对人类观察者的研究,我们首先发现视觉特征的相对时间在决定特征分组的空间区域中起着关键作用。我们利用特征整合的这种时间依赖性,表明在 45 毫秒内共同出现的特征在眼球运动中仍保持分组。我们的结果因此挑战了纯粹的特征整合前馈模型(Pelli,2008;Freeman 和 Simoncelli,2011),这些模型在每次眼球运动后都从头开始,并且暗示了大脑区域除了早期视觉皮层之外的参与。我们量化的强烈的时间依赖性及其与跨眼跳物体感知的联系,反而表明特征整合至少部分依赖于来自大脑更高区域的反馈(Mumford,1992;Rao 和 Ballard,1999;Di Lollo 等人,2000;Moore 和 Armstrong,2003;斯坦福等人,2010)。

相似文献

1
Integrating retinotopic features in spatiotopic coordinates.将视网膜特征整合到空间坐标中。
J Neurosci. 2014 May 21;34(21):7351-60. doi: 10.1523/JNEUROSCI.5252-13.2014.
9
Nonretinotopic visual processing in the brain.大脑中的非视网膜拓扑视觉处理
Vis Neurosci. 2015 Jan;32:E017. doi: 10.1017/S095252381500019X.

引用本文的文献

3
8
Visual Remapping.视觉重映射。
Annu Rev Vis Sci. 2021 Sep 15;7:257-277. doi: 10.1146/annurev-vision-032321-100012. Epub 2021 Jul 9.

本文引用的文献

2
Crowding during restricted and free viewing.受限观看和自由观看时的拥挤情况。
Vision Res. 2013 May 24;84:50-9. doi: 10.1016/j.visres.2013.03.010. Epub 2013 Apr 4.
3
Visual crowding at a distance during predictive remapping.在预测重映射过程中远距离的视觉拥挤。
Curr Biol. 2013 May 6;23(9):793-8. doi: 10.1016/j.cub.2013.03.050. Epub 2013 Apr 4.
4
Eye movement targets are released from visual crowding.眼动目标从视觉拥挤中释放出来。
J Neurosci. 2013 Feb 13;33(7):2927-33. doi: 10.1523/JNEUROSCI.4172-12.2013.
6
Peri-saccadic natural vision.眼跳间期的自然视觉。
J Neurosci. 2013 Jan 16;33(3):1211-7. doi: 10.1523/JNEUROSCI.4344-12.2013.
7
Allocation of attention across saccades.眼球跳动时的注意力分配。
J Neurophysiol. 2013 Mar;109(5):1425-34. doi: 10.1152/jn.00656.2012. Epub 2012 Dec 5.
9
Metamers of the ventral stream.腹侧流的同型物。
Nat Neurosci. 2011 Aug 14;14(9):1195-201. doi: 10.1038/nn.2889.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验