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Spatial scale and distribution of neurovascular signals underlying decoding of orientation and eye of origin from fMRI data

机译:FMRI数据取向和眼睛引起的潜在解码的空间尺度和分布

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摘要

Multivariate pattern analysis of functional magnetic resonance imaging (fMRI) data is widely used, yet the spatial scales and origin of neurovascular signals underlying such analyses remain unclear. We compared decoding performance for stimulus orientation and eye of origin from fMRI measurements in human visual cortex with predictions based on the columnar organization of each feature and estimated the spatial scales of patterns driving decoding. Both orientation and eye of origin could be decoded significantly above chance in early visual areas (V1-V3). Contrary to predictions based on a columnar origin of response biases, decoding performance for eye of origin in V2 and V3 was not significantly lower than that in V1, nor did decoding performance for orientation and eye of origin differ significantly. Instead, response biases for both features showed large-scale organization, evident as a radial bias for orientation, and a nasotemporal bias for eye preference. To determine whether these patterns could drive classification, we quantified the effect on classification performance of binning voxels according to visual field position. Consistent with large-scale biases driving classification, binning by polar angle yielded significantly better decoding performance for orientation than random binning in V1-V3. Similarly, binning by hemifield significantly improved decoding performance for eye of origin. Patterns of orientation and eye preference bias in V2 and V3 showed a substantial degree of spatial correlation with the corresponding patterns in V1, suggesting that response biases in these areas originate in V1. Together, these findings indicate that multivariate classification results need not reflect the underlying columnar organization of neuronal response selectivities in early visual areas.
机译:函数磁共振成像(FMRI)数据的多变量模式分析被广泛使用,但这种分析潜在的神经血管信号的空间尺度和起源仍然尚不清楚。我们比较了从人类视觉皮层中的FMRI测量的刺激性能和原籍的眼睛的解码性能与每个特征的柱状组织的预测,并估计了驾驶解码的模式的空间尺度。原产地的取向和眼睛都可以在早期视觉区域(V1-V3)中显着解码。与基于柱状响应偏差的柱状起源的预测相反,V2和V3中原产地的解码性能不会显着低于V1中的,而不是原产地的取向和眼睛的解码性能显着差异显着。相反,两个特征的响应偏差显示出大规模的组织,视为定向的径向偏差,以及用于眼睛偏好的鼻偏见。为了确定这些模式是否可以驱动分类,我们根据视野位置量化了对分箱体素分类性能的影响。与大规模偏置驾驶分类一致,通过极性角度的分叉产生比V1-V3中的随机衬合所显着更好地解码性能。类似地,通过升降箱搭桥显着改善了原点眼睛的解码性能。 V2和V3中的取向和眼睛偏好偏压的图案显示了与V1中的相应图案的基本程度的空间相关性,表明这些区域中的响应偏差源于V1。这些发现在一起表明,多变量分类结果不需要反映早期视觉区域的神经元反应选择性的潜在柱状组织。

著录项

  • 来源
    《Journal of Neurophysiology》 |2017年第2期|共18页
  • 作者单位

    Royal Holloway Univ London Dept Psychol Egham TW20 0EX Surrey England;

    Royal Holloway Univ London Dept Psychol Egham TW20 0EX Surrey England;

    Royal Holloway Univ London Dept Psychol Egham TW20 0EX Surrey England;

    Royal Holloway Univ London Dept Psychol Egham TW20 0EX Surrey England;

    Royal Holloway Univ London Dept Psychol Egham TW20 0EX Surrey England;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 人体生理学;
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