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Decoding Attention Position Based on Shifted Receptive Field in Visual Cortex

机译:基于视觉皮层位移感受野的注意力集中位置解码

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Visual attention is an important issue in the field of neuroscience and computer vision. According to recent research of visual cognitive computation, receptive fields are thought to be shifted with the influence of spatial attention. In the traditional method, researchers decoded various positions of attention based on constant population receptive field (pRF) parameters. Comparing with previous attention decoding researches, recent discovery may help improve the decoding accuracy. In this research, to get a better accuracy, a new decoding method is proposed with introducing the shift of pRF parameters. Firstly, we adopted two-dimensional Gaussian receptive field model to characterize the population receptive field(pRF) of each voxel in seven visual areas [V1-V4, inferior occipital gyrus (IOG), posterior fusiform gyrus (pFus), and mid-fusiform gyrus (mFus)]. Then, we introduced a parameter to measure the shift of pRF. With the shifted pRF parameters, the attention position could be decoded by maximum likelihood estimation. With published fMRI dataset, a better decoding accuracy could be obtained in most regions, especially in higher regions. The result also indicated that with the modulation of spatial attention, pRF parameters of voxels in high regions were shifted much more than those in early regions.
机译:视觉注意力是神经科学和计算机视觉领域的重要问题。根据最近的视觉认知计算研究,认为感受力场在空间注意的影响下发生了变化。在传统方法中,研究人员根据恒定的人口接受场(pRF)参数对注意力的各个位置进行解码。与以前的注意力解码研究相比,最近的发现可能有助于提高解码精度。在这项研究中,为了获得更好的精度,提出了一种新的解码方法,其中引入了pRF参数的偏移。首先,我们采用二维高斯接受场模型来表征七个视觉区域[V1-V4,枕下回(IOG),后梭状回(pFus)和中梭状)的每个体素的人口接受场(pRF)。 gyrus(mFus)]。然后,我们引入了一个参数来测量pRF的偏移。使用移位的pRF参数,可以通过最大似然估计来解码关注位置。使用已发布的fMRI数据集,可以在大多数区域,尤其是较高区域中获得更好的解码精度。结果还表明,随着空间注意力的调节,高区域中体素的pRF参数比早期区域中的变化更大。

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