Neuronal mechanisms of selective attention in early vision

摘要：早期视觉中选择性注意的神经机制 在过去的二十年里，选择性注意的机制得到了广泛的研究。作为 因此，现在对参与视觉活动的大脑区域网络有了更好的了解。 注意力和个体神经元对注意力转移的反应。当前的注意力模型也是其中之一 更接近于提供可能具有直接临床意义的注意回路的一般框架。 然而，当前模型的主要限制是缺乏细胞特异性。目前大多数模型都将 一个给定的皮层区域内的一个细胞，就好像它是从神经元的随机样本，只是在不同的 它们感受野的空间位置以及它们对线取向和运动方向的选择性。的 具有可能不同功能的不同细胞类型的存在被完全忽略。不同的神经元 层，神经元进行局部和远程连接，直到最近，抑制和兴奋 所有神经元都被模型平等对待。 这项提案的主要目标是提供细胞选择性的生物学数据，这是建立更多的 视觉注意力的现实和临床相关模型。我们的目标是表征不同的细胞类型， 参与V1区的注意力网络。我们的目标还在于识别具有不同 注意力功能：那些参与增强注意力焦点的视力的功能， 抑制周围区域的干扰。我们将使用最先进的技术来密集采样 单个神经元和神经元群体穿过V1区的皮层深度。我们的新技术 如果有必要，它可以让我们研究给定神经元群体的特性几天或几个月。我们的目标是 利用这项技术提供了不同皮层注意回路的详细特征， 区域V1的深度，并确定使注意力调制最强的任务参数。

ABSTRACT: Neuronal mechanisms of selective attention in early vision The mechanisms of selective attention have been intensively investigated over the past two decades. As a consequence, there is now a better understanding of the network of brain areas that are involved in visual attention and the responses of individual neurons to attentional shifts. Current models of attention are also one step closer to providing a general framework of attentional circuits that could have direct clinical significance. However, a major limitation of current models is the lack of cellular specificity. Most current models treat each cell within a given cortical area as if it was taken from a random sample of neurons that simply differ in the spatial location of their receptive fields and their selectivity for line orientation and direction of movement. The existence of different cell types with possible different functions is completely neglected. Neurons in different layers, neurons making local and long-range connections and, until very recently, inhibitory and excitatory neurons are all treated equally by models. The main goal of this proposal is to provide the biological data on cell selectivity that is needed to build more realistic and clinically relevant models of visual attention. We aim to characterize the different cell types that are involved in attentional networks in area V1. We also aim to identify populations of neurons with different functions in attention: those involved in enhancing vision at the focus of attention and those involved in suppressing distraction in surrounding areas. We will use state-of-the-art technology to densely sample individual neurons and populations of neurons through the cortical depths of area V1. Our novel technology allows us to study the properties of a given population of neurons for days or months, if necessary. We aim to take advantage of this technology to provide a detailed characterization of attention circuits at different cortical depths of area V1 and identify the task parameters that make attentional modulations strongest.