Population spatial frequency tuning in human early visual cortex
Population spatial frequency tuning in human early visual cortex
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DOI：
10.1152/jn.00291.2019
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发表时间：
2020-02-01
影响因子：
2.5
通讯作者：
Ling, Sam
中科院分区：
文献类型：
--
作者：
Aghajari, Sara;Vinke, Louis N.;Ling, Sam
早期视觉皮层内的神经元对基本图像统计数据（包括空间频率）具有选择性。然而，这些神经元被认为充当带通滤波器，空间频率敏感度的窗口在整个视野和视觉区域中变化。尽管之前的一些功能性 (f)MRI 研究已经使用传统设计和分析方法检查了人类空间频率敏感性，但这些测量非常耗时，并且无法捕获空间频率调谐（带宽）的精度。在这项研究中，我们引入了一种模型驱动的功能磁共振成像分析方法，可以快速有效地估计单个体素的群体空间频率调谐（pSFT）。当受试者观看一系列扫过大范围空间频率内容的全场刺激时，就会获得早期视觉皮层内的血氧水平依赖性（BOLD）反应。每个刺激都是通过带通滤波白噪声产生的，其中心频率在最小 0.5 周期/度 (cpd) 和最大 12 cpd 之间周期性变化。为了估计每个体素的基本频率调谐，我们假设了一个对数高斯 pSFT，并通过将我们的模型输出与测量的 BOLD 时间序列进行比较来优化该函数的参数。与之前的研究一致，我们的结果表明，每个视觉区域内偏心率的增加伴随着 pSFT 峰值空间频率的下降。此外，我们发现 pSFT 带宽取决于偏心率并与 pSFT 峰值相关；峰值较低的群体在对数尺度上拥有更宽的带宽，而在线性尺度上，这种关系是相反的。新的和值得注意的空间频率选择性是早期视觉皮层神经元的标志特性，映射这些敏感性使我们能够深入了解视觉区域内信息的层次结构。由于技术障碍，我们缺乏对人类这种敏感性特性的全面了解。在这里，我们引入了一种新方法，即创造的群体空间频率调谐映射，它规避了传统神经成像方法的局限性，产生了更完整的空间频率敏感性的视觉皮层图。
Neurons within early visual cortex are selective for basic image statistics, including spatial frequency. However, these neurons are thought to act as band-pass filters, with the window of spatial frequency sensitivity varying across the visual field and across visual areas. Although a handful of previous functional (f)MRI studies have examined human spatial frequency sensitivity using conventional designs and analysis methods, these measurements are time consuming and fail to capture the precision of spatial frequency tuning (bandwidth). In this study, we introduce a model-driven approach to fMRI analyses that allows for fast and efficient estimation of population spatial frequency tuning (pSFT) for individual voxels. Blood oxygen level-dependent (BOLD) responses within early visual cortex were acquired while subjects viewed a series of full-field stimuli that swept through a large range of spatial frequency content. Each stimulus was generated by band-pass filtering white noise with a central frequency that changed periodically between a minimum of 0.5 cycles/degree (cpd) and a maximum of 12 cpd. To estimate the underlying frequency tuning of each voxel, we assumed a log-Gaussian pSFT and optimized the parameters of this function by comparing our model output against the measured BOLD time series. Consistent with previous studies, our results show that an increase in eccentricity within each visual area is accompanied by a drop in the peak spatial frequency of the pSFT. Moreover, we found that pSFT bandwidth depends on eccentricity and is correlated with the pSFT peak; populations with lower peaks possess broader bandwidths in logarithmic scale, whereas in linear scale this relationship is reversed.NEW & NOTEWORTHY Spatial frequency selectivity is a hallmark property of early visuocortical neurons, and mapping these sensitivities gives us crucial insight into the hierarchical organization of information within visual areas. Due to technical obstacles, we lack a comprehensive picture of the properties of this sensitivity in humans. Here, we introduce a new method, coined population spatial frequency tuning mapping, which circumvents the limitations of the conventional neuroimaging methods, yielding a fuller visuocortical map of spatial frequency sensitivity.