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是许多视觉过程的基本要求，包括视觉搜索。目前，这些移位的神经时间动力学尚不清楚。虽然维度加权解释声称，与维度内的移动相比，特征维度之间的移动持续时间更长，但自上而下反向倒序的发现导致一些研究人员假设，向传统视觉层次结构中向上处理的特征(即颜色)的移动比向进一步向下处理的特征(即定向)的移动发生得更早。特征相似性增益模型没有关于移位时间的明确预测，但可以推导出没有明显的延迟差异。在我们的多项研究中，我们发现频率标记刺激诱发的稳态视觉诱发电位(SSVEP)是揭示早期视皮层自上而下调制注意转移的时间动力学的有力工具。为了揭示时间动态，我们将提供包含两个特征维度的频率标记刺激，如颜色和方向。提示将提示参与者将注意力转移到特征维度内(即颜色到颜色)或特征维度之间(即颜色到方向)。SSVEP幅值的时程分析提供了在转换提示后作为时间函数的早期视觉皮质的转换动态的近实时测量。了解与频率标记刺激相关的解剖激活模式，对于检验有关注意力转移的有争议的假说至关重要。为了测试注意频率标记刺激的特定特征是否会导致对该特征具有高亲和力的区域的选择性激活，我们将在7特斯拉扫描仪中进行(I)结合视网膜定位的注意任务，以及(Ii)结合fMRI-EEG记录(在3特斯拉)。第一个将在扩展的视觉皮质内，在精细的解剖尺度上提供与关注/忽略特征的性质相关的区域特异性的信息。目前尚不清楚SSVEP波幅的增加是否基于一般的易化效应，即闪光刺激激活的所有视觉区域的激活增加，或者是否注意到特定的特征导致涉及到视觉区域的子集的特征特异性激活。然而，了解这些过程对于在SSVEP幅度的基础上清楚地解释特征维度之间的时移时间差是至关重要的。我们相信，在拟议的项目结束时，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，我们将在理解基于特征的视觉选择性注意的神经机制方面做出重要而新颖的贡献。

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.