Linking Neural Population Activity and Visual Perception

项目摘要 当前提案的首要目标是揭示构成图形背景的神经机制。 分离，自然场景解读的重要组成部分，注重初级视觉的作用 大脑皮质(V1)及其与高级视觉皮质区域的动态相互作用。具体地说，我们将测量V1 响应广泛的背景，包括人造和自然纹理，有没有 遮挡目标，并开发计算编码模型，使人们能够预测V1种群 在多个生物相关的空间尺度上对任意图形和背景作出反应(目标1)。在AIM 2 我们将通过测量和干扰V1人群来研究V1在图形-背景辨别中的作用 当动物检测到遮挡同一纹理家族背景的伪装目标时的反应。 这些实验将用于区分不同的候选解码模型，这些模型描述了 单次试验V1群体反应会导致任务中的行为。一个重要的目标是测试V1 在分割计算中起着积极的作用。另一种选择是V1提供前馈输入 到下游发生的分段计算，并且只接收自上而下的图形-地面信号 在分割完成之后。总体而言，拟议的实验将导致更深层次的 理解V1在基础中级视觉计算中的作用，将作为重要的 迈向对复杂自然场景的表示的定量理解 V1区神经元。

Project Summary The overarching goal of the current proposal is to uncover the neural mechanisms that underlie figure-ground segregation, an important component of natural scene interpretation, focusing on the role of the primary visual cortex (V1) and its dynamic interactions with higher visual cortical areas. Specifically, we will measure how V1 responds to a wide range of backgrounds, including artificial and naturalistic textures, with and without occluding targets, and develop computational encoding models that would allow one to predict V1 population responses at multiple biologically-relevant spatial scales to arbitrary figures and backgrounds (Aim 1). In Aim 2 we will study the role of V1 in figure-ground discrimination by measuring and perturbing V1 population responses while animals detect a camouflaged target that occludes a background of the same texture family. These experiments will be used to distinguish between different candidate decoding models that describe how single-trial V1 population responses lead to behavior in the task. An important goal would be to test whether V1 plays an active role in the segmentation computation. The alternative is that V1 provides the feedforward input to a segmentation computation that occurs downstream, and receives top-down figure-ground signals only after the segmentation had been completed. Overall, the proposed experiments will lead to a deeper understanding of the role of V1 in fundamental mid-level visual computations and will serve as an important step toward a quantitative understanding of the representation of complex natural scenes by populations of neurons in V1.