Representation of Visual Features in Mental Images of Complex Scenes.

复杂场景心理图像中视觉特征的表示。

• 批准号: 9033118
• 负责人: THOMAS P NASELARIS
• 金额: $ 37.38万
• 依托单位: MEDICAL UNIVERSITY OF SOUTH CAROLINA
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-04-01 至 2019-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9033118
• 关键词: Algorithms; Attention; Awareness; Brain; Brain imaging; Categories; Complex; Data; Development; Diagnosis; Environment; Exhibits; Feedback; Foundations; Frequencies; Functional Magnetic Resonance Imaging; Goals; Health; Image; Imagery; Knowledge; Link; Location; Maps; Measures; Mental Health; Modeling; Outcome; Perception; Play; Process; Psyche structure; Public Health; Research; Retina; Retinal; Role; Signal Transduction; Source; Spatial Distribution; System; Testing; Vision; Visual; Visual Cortex; Work; base; cognitive process; design; extrastriate visual cortex; innovation; mental imagery; neuromechanism; novel strategies; physical process; predictive modeling; receptive field; relating to nervous system; retinotopic

DESCRIPTION (provided by applicant): Mental imagery is a salient part of mental awareness but very little is understood about how visual percepts are generated without retinal input, or how visual features that are known to be an important part of visual representation drive neural activity during mental imagery. Our long-term goal is to provide clinicians with the ability to objectively interpret mental images by accessing underlying neural activity. The objective of the current work is to develop a basic understanding of the similarities and differences between the representation of visual features in veridical and mental images. Our central hypothesis is that the mechanisms for representing visual features during perception are fundamentally conserved during mental imagery and that receptive fields that link activity to veridical images should predict activity evoked by mental imagery. Nonetheless, mental images are clearly distinguishable from veridical images and we consider three potential sources of difference: (1) The potential for exaggerated effects of attention on mental imagery; (2) The predominate influence of feedback connections from high-level visual areas with large receptive fields (relative to the retina) during mental imagery; (3) Differences between the neural processes of generating mental images and the physical processes that generate retinal images. Two Specific Aims are proposed that will be pursued using an innovative new approach for analyzing functional MRI signals that is based upon voxel-wise modeling of receptive fields. Under this approach, a separate predictive model is constructed for each and every voxel in the acquired volumes. The model links activity measured in a voxel directly to specific visual features, including spatial frequency, orientation, object category, and object location. The models can then be used to decode perceived or recalled scenes from measured brain activity. We expect that our contribution will be an advance in our understanding of the specific factors that determine the degree of consistency between activity during imagery and perception, as well as a significant advance in our ability to quantitatively model the high-level visual areas where activity is most consistent. This contribution will be significant because it will take us several necessary steps toward the development of imagery receptive fields-predictive receptive field models that explain how the visual features in a scene drive activity when the scene is recalled in the form of a mental image. A receptive field model for mental imagery would place within reach a decoding algorithm for objectively interpreting and even pictorially reconstructing mental images.

描述（由申请人提供）：心理图像是心理意识的重要组成部分，但是关于没有视网膜输入的视觉感知是如何产生视觉感知的，或者是如何在视觉表现中驱动心理图像中神经活动的重要组成部分的知识。我们的长期目标是为临床医生提供通过访问潜在的神经活动来客观地解释心理图像的能力。当前工作的目的是对视觉特征和心理图像中视觉特征表示的相似性和差异进行基本理解。我们的中心假设是，在心理图像中，在感知过程中表示视觉特征的机制是从根本上保守的，并且将活动与垂直图像联系起来的接受领域应预测精神成像引起的活动。尽管如此，心理图像与垂直图像显然可以区分，我们考虑了三种潜在的差异来源：（1）夸大关注对心理图像的影响的潜力； （2）在心理影像过程中，来自高级视觉区域（相对于视网膜）的高级视觉区域的反馈连接的主要影响； （3）产生心理图像的神经过程与产生视网膜图像的物理过程之间的差异。提出了两个具体的目标，该目标将使用创新的新方法来分析基于接收场的素建模的功能性MRI信号。在这种方法下，为获得的体积中的每个体素构建了一个单独的预测模型。该模型将Voxel中测量的活动链接到特定的视觉特征，包括空间频率，方向，对象类别和对象位置。然后，这些模型可用于解码所测量的大脑活动中感知或回忆的场景。我们预计，我们的贡献将是我们对确定图像和感知过程中活动之间一致性程度的特定因素的理解的进步，以及我们定量对活动最一致的高级视觉领域进行定量模拟的能力的重大进步。这项贡献将是重要的，因为它将花费我们几个必要的步骤，以开发图像接受场预测性的接收场模型，这些模型解释了场景中的视觉特征在以心理图像的形式召回场景时如何驱动场景。用于心理图像的接受现场模型将置于一种解码算法，用于客观地解释甚至在图像上重建心理图像。