Shifting attention within or between feature dimensions. Neural temporal dynamics in human early visual cortex

在特征维度内或特征维度之间转移注意力。

• 批准号: 317885770
• 负责人: Professor Dr. Matthias M. Müller
• 金额: --
• 依托单位: Wilhelm-Wundt-Institut für Psychologie
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2016
• 资助国家: 德国
• 起止时间: 2015-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/317885770?language=en
• 关键词: Shifting; attention; within; between; feature

Shifting attention within or between feature dimensions is an elementary requirement for many visual processes, including visual search. Currently, the neural temporal dynamics of these shifts are unknown. While the Dimensional Weighting Account claims that shifts between feature dimensions last longer compared to within-dimensional shifts, the finding of a reversed top-down backward progression has led some researchers to hypothesize that shifts towards a feature that is processed upwards in the traditional visual hierarchy (i.e. color) occur earlier than shifts towards features that are processed further down (i.e. orientation). The feature similarity gain model has no clear predictions with regard to shifting times, but one may derive that there are no distinct latency differences. In a number of our studies, we showed that frequency-tagged stimuli eliciting the Steady state visual evoked potential (SSVEP) serve as a powerful tool to uncover temporal dynamics of top-down modulated attentional shifting in early visual cortex. To uncover the temporal dynamics we will present frequency-tagged stimuli that contain two feature dimensions, such as color and orientation. Cues will prompt participants to shift attention either within (i.e. color to color) or between feature dimensions (i.e. color to orientation). Time course analysis of SSVEP amplitudes provides a near-real-time measurement of shifting dynamics in early visual cortex as a function of time after a shifting cue. Knowing the anatomical activation patterns related to frequency-tagged stimuli is crucial for testing the controversial hypotheses regarding attention shifting. To test whether attending to a certain feature of a frequency-tagged stimulus will result in a selective activation of areas with high affinity to that feature, we will conduct (i) an attention task combined with retinotopic mapping in a 7 Tesla scanner, and (ii) combined fMRI-EEG recordings (at 3 Tesla). The first will provide information about area-specificity relative to the nature of the attended/ignored features at a fine anatomical scale, within the extend visual cortex. At present, it is unclear whether the increase in SSVEP amplitude with attention is based on a general facilitation effect, i.e. an increase of activation in all visual areas that are activated by the flickering stimuli, or if attending to a specific feature results in a feature-specific activation involving a subset of visual areas. Knowing these processes however is crucial for a clear interpretation of temporal shifting time differences between vs. across feature dimensions on the basis of SSVEP amplitudes. We are convinced that at the end of the proposed project, we can resolve the controversy mentioned above with regard to the mechanism mediating feature-based attention shifts. We will thus make a critical and novel contribution to our understanding of the neural mechanisms underlying feature-based visual selective attention.

在特征维度内或特征维度之间转移注意力是许多视觉过程的基本要求，包括视觉搜索。目前，这些变化的神经时间动力学是未知的。虽然维度加权账户声称，特征维度之间的转移比维度内的转移持续的时间更长，但自上而下的反向进展的发现使得一些研究人员假设，在传统的视觉层次中，向上处理的特征（如颜色）的转移比向下处理的特征（如方向）的转移发生得更早。特征相似度增益模型对移位时间没有明确的预测，但可以得出没有明显的延迟差异。在我们的许多研究中，我们发现频率标记刺激引发稳态视觉诱发电位（SSVEP）是揭示早期视觉皮层自上而下调节的注意力转移的时间动态的有力工具。为了揭示时间动态，我们将呈现包含两个特征维度的频率标记刺激，如颜色和方向。线索会促使参与者在特征维度内（即颜色到颜色）或特征维度之间（即颜色到方向）转移注意力。SSVEP振幅的时间过程分析提供了一种接近实时的早期视觉皮层移动动态的测量，作为移动提示后时间的函数。了解与频率标记刺激相关的解剖激活模式对于测试有关注意力转移的有争议的假设至关重要。为了测试关注频率标记刺激的某个特征是否会导致选择性激活与该特征高度相关的区域，我们将进行(i)在7特斯拉扫描仪中结合视网膜定位的注意力任务，以及（ii）结合fMRI-EEG记录（3特斯拉）。第一个将提供有关区域特异性的信息，相对于被关注/被忽视的特征的性质，在精细的解剖尺度上，在扩展的视觉皮层内。目前，尚不清楚SSVEP振幅随注意力的增加是基于一般的促进效应，即所有视觉区域被闪烁刺激激活的激活增加，还是关注特定特征导致涉及视觉区域子集的特征特异性激活。然而，了解这些过程对于清晰地解释基于SSVEP振幅的特征维度之间和跨特征维度的时间转移时间差至关重要。我们相信，在提议的项目结束时，我们可以解决上述关于调解基于特征的注意力转移的机制的争议。因此，我们将对基于特征的视觉选择性注意的神经机制的理解做出重要而新颖的贡献。