Population coding for figure-ground texture segregation in macaque V1 and V4

IF 6.7 2区 医学 Q1 NEUROSCIENCES
Xing-Nan Zhao , Xing-Si Dong , Dan-Qing Jiang , Si Wu , Shi-Ming Tang , Cong Yu
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Abstract

Object recognition often involves the brain segregating objects from their surroundings. Neurophysiological studies of figure-ground texture segregation have yielded inconsistent results, particularly on whether V1 neurons can perform figure-ground texture segregation or just detect texture borders. To address this issue from a population perspective, we utilized two-photon calcium imaging to simultaneously record the responses of large samples of V1 and V4 neurons to figure-ground texture stimuli in awake, fixating macaques. The average response changes indicate that V1 neurons mainly detect texture borders, while V4 neurons are involved in figure-ground segregation. However, population analysis (SVM decoding of PCA-transformed neuronal responses) reveal that V1 neurons not only detect figure-ground borders, but also contribute to figure-ground texture segregation, although requiring substantially more principal components than V4 neurons to reach a 75 % decoding accuracy. Individually, V1/V4 neurons showing larger (negative/positive) figure-ground response differences contribute more to figure-ground segregation. But for V1 neurons, the contribution becomes significant only when many principal components are considered. We conclude that V1 neurons participate in figure-ground segregation primarily by defining the figure borders, and the poorly structured figure-ground information V1 neurons carry could be further utilized by V4 neurons to accomplish figure-ground segregation.

猕猴 V1 和 V4 中图形-地面纹理分离的群体编码。
物体:识别通常需要大脑将物体从周围环境中分离出来。关于图-地纹理分离的神经生理学研究结果并不一致,尤其是关于 V1 神经元是能进行图-地纹理分离还是只能检测纹理边界的研究。为了从群体角度解决这个问题,我们利用双光子钙成像技术,同时记录了清醒、固定不动的猕猴体内大量 V1 和 V4 神经元样本对图-地纹理刺激的反应。平均响应变化表明,V1 神经元主要检测纹理边界,而 V4 神经元则参与图-地分离。然而,群体分析(对PCA转换后的神经元响应进行SVM解码)显示,V1神经元不仅能检测图-地边界,还能参与图-地纹理分离,尽管要达到75%的解码准确率,V1神经元需要比V4神经元多得多的主成分。单独来看,V1/V4 神经元的图形-地面响应差异较大(负/正),对图形-地面分离的贡献更大。但对于 V1 神经元来说,只有在考虑多个主成分时,其贡献才会变得显著。我们的结论是,V1 神经元主要通过定义图形边界来参与图形-地面分离,它们所携带的结构不良的图形-地面信息可被 V4 神经元进一步利用来完成图形-地面分离。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Progress in Neurobiology
Progress in Neurobiology 医学-神经科学
CiteScore
12.80
自引率
1.50%
发文量
107
审稿时长
33 days
期刊介绍: Progress in Neurobiology is an international journal that publishes groundbreaking original research, comprehensive review articles and opinion pieces written by leading researchers. The journal welcomes contributions from the broad field of neuroscience that apply neurophysiological, biochemical, pharmacological, molecular biological, anatomical, computational and behavioral analyses to problems of molecular, cellular, developmental, systems, and clinical neuroscience.
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