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.

在特征维度内或之间转移注意力是许多视觉过程（包括视觉搜索）的基本要求。当前，这些转移的神经时间动态尚不清楚。与维度内的变化相比，尺寸的加权帐户声称的特征维度之间的变化持续更长的时间，但发现反向自上而下的向后进程的发现使一些研究人员假设该功能向向上处理的功能转向传统的视觉层次结构（即颜色）的转变更早地朝着更早的变化而朝着更早的特征进行了更早的特征。特征相似性增益模型在变化时间方面没有明确的预测，但是人们可能会发现没有明显的延迟差异。在我们的许多研究中，我们表明频率标记的刺激引起了稳态视觉引起的电势（SSVEP），是发现早期视觉皮层中自上而下的调制注意力转移的时间动力学的强大工具。为了揭示时间动力学，我们将提出频率标记的刺激，其中包含两个特征维度，例如颜色和方向。提示将促使参与者转移注意力（即颜色为颜色）或特征维度（即颜色到方向）之间的注意力。 SSVEP振幅的时间课程分析提供了对早期视觉皮层转移动态的近实时测量，这是转移提示后时间的函数。了解与频率标记的刺激有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。为了测试频率标记的刺激的某些特征是否会导致对该功能具有高亲和力的区域的选择性激活，我们将执行（i）注意任务与7 tesla扫描仪中的视网膜映射结合，以及（ii）（ii）FMRi-Eegegs Recordings（在3 Tesla中）。第一个将提供有关区域特异性相对于在扩展视觉皮层内以精细的解剖量表的性质的性质提供的有关区域特异性的信息。目前，目前尚不清楚随着注意力的SSVEP振幅的增加是基于一般促进效应，即，在所有视觉区域的激活增加而在所有视觉区域中的激活增加，或者是否参与特定特征会导致涉及视觉区域子集的特定功能特异性激活。 但是，了解这些过程对于明确解释了根据SSVEP振幅对特征维度之间的时间变化时间差异的明确解释。我们坚信，在拟议项目的结尾，我们可以解决上述有关基于特征注意力转移的机制的争议。因此，我们将对我们对基于特征的视觉选择性关注的神经机制的理解做出批判性和新颖的贡献。