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首页> 美国卫生研究院文献>The Journal of Neuroscience >Bottom-Up and Top-Down Factors Differentially Influence Stimulus Representations Across Large-Scale Attentional Networks
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Bottom-Up and Top-Down Factors Differentially Influence Stimulus Representations Across Large-Scale Attentional Networks

机译：自下而上和自上而下的因素差异影响跨大型注意网络的刺激表示。

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Visual attention is thought to be supported by three large-scale frontoparietal networks: the frontoparietal control network (FPCN), the dorsal attention network (DAN), and the ventral attention network (VAN). The traditional view is that these networks support visual attention by biasing and evaluating sensory representations in visual cortical regions. However, recent evidence suggests that frontoparietal regions actively represent perceptual stimuli. Here, we assessed how perceptual stimuli are represented across large-scale frontoparietal and visual networks. Specifically, we tested whether representations of stimulus features across these networks are differentially sensitive to bottom-up and top-down factors. In a pair of pattern-based fMRI studies, male and female human subjects made perceptual decisions about face images that varied along two independent dimensions: gender and affect. Across studies, we interrupted bottom-up visual input using backward masks. Within studies, we manipulated which stimulus features were goal relevant (i.e., whether gender or affect was relevant) and task switching (i.e., whether the goal on the current trial matched the goal on the prior trial). We found that stimulus features could be reliably decoded from all four networks and, importantly, that subregions within each attentional network maintained coherent representations. Critically, the different attentional manipulations (interruption, goal relevance, and task switching) differentially influenced feature representations across networks. Whereas visual interruption had a relatively greater influence on representations in visual regions, goal relevance and task switching had a relatively greater influence on representations in frontoparietal networks. Therefore, large-scale brain networks can be dissociated according to how attention influences the feature representations that they maintain.>SIGNIFICANCE STATEMENT Visual attention is supported by multiple frontoparietal attentional networks. However, it remains unclear how stimulus features are represented within these networks and how they are influenced by attention. Here, we assessed feature representations in four large-scale networks using a perceptual decision-making paradigm in which we manipulated top-down and bottom-up factors. We found that top-down manipulations such as goal relevance and task switching modulated feature representations in attentional networks, whereas bottom-up manipulations such as interruption of visual processing had a relatively stronger influence on feature representations in visual regions. Together, these findings indicate that attentional networks actively represent stimulus features and that representations within different large-scale networks are influenced by different forms of attention.
机译：视觉注意力被认为由三个大规模的额叶额顶网络支持：额叶额顶控制网络（FPCN），背侧注意力网络（DAN）和腹侧注意力网络（VAN）。传统观点认为，这些网络通过偏见和评估视觉皮层区域中的感觉表示来支持视觉注意力。但是，最近的证据表明，前额额叶区域积极地代表了知觉刺激。在这里，我们评估了如何在大规模的额叶和视觉网络上表现知觉刺激。具体来说，我们测试了这些网络中刺激特征的表示是否对自下而上和自上而下的因素具有不同的敏感性。在一对基于模式的功能磁共振成像研究中，男性和女性受试者对面部图像做出了感知决定，该决定沿两个独立的维度变化：性别和情感。在所有研究中，我们使用后向遮罩打断了自下而上的视觉输入。在研究中，我们操纵了哪些刺激特征与目标相关（即性别或情感是否相关）和任务切换（即当前试验的目标是否与先前试验的目标相匹配）。我们发现刺激特征可以从所有四个网络中可靠地解码，而且重要的是，每个注意力网络中的子区域都保持一致的表示形式。至关重要的是，不同的注意力操纵（中断，目标相关性和任务切换）对跨网络的特征表示有不同的影响。视觉中断对视觉区域中表示的影响相对较大，而目标相关性和任务切换对额顶网络中的表示具有相对较大的影响。因此，可以根据注意力如何影响它们所维护的特征表示来分离大规模的大脑网络。>显着性陈述视觉注意得到多个额叶注意网络的支持。然而，目前尚不清楚这些网络中如何表现刺激特征以及注意力如何影响它们。在这里，我们使用感知决策模型对四个自上而下和自下而上的因素进行评估，评估了四个大型网络中的特征表示。我们发现自上而下的操作（如目标相关性和任务切换）在注意力网络中调制了特征表示，而自下而上的操作（如中断视觉处理）对视觉区域中的特征表示具有相对较强的影响。总之，这些发现表明注意网络积极地代表了刺激特征，并且不同规模的注意会影响不同规模的网络中的表示。

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