Perceptual functions of the human lateral geniculate nucleus

人类外侧膝状核的知觉功能

• 批准号: 10224205
• 负责人: FRANK TONG
• 金额: $ 38.06万
• 依托单位: VANDERBILT UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10224205
• 关键词: Address; Affect; Amblyopia; Appearance; Area; Attention; Behavior; Clinical; Code; Complex; Data; Detection; Development; Evaluation; Eye; Feedback; Functional Magnetic Resonance Imaging; Future; Goals; Grain; Health; Human; Image; Impairment; Intervention; Investigation; Knowledge; Lateral Geniculate Body; Lead; Maps; Measures; Methods; Modeling; Monkeys; Neurons; Perception; Performance; Peripheral; Population; Process; Psychophysics; Residual state; Resolution; Retina; Retinal Diseases; Role; Shapes; Signal Transduction; Site; Stimulus; Techniques; Testing; Vision Disorders; Visual; Visual Cortex; Visual Fields; Visual Pathways; Visual Perception; Visual system structure; Visualization; Work; advanced analytics; analytical method; area V1; area striata; base; clinically relevant; experimental study; extrastriate visual cortex; imaging modality; insight; monocular; neuroimaging; neurophysiology; novel; predictive modeling; receptive field; relating to nervous system; response; selective attention; theories; visual feedback; visual information; visual process; visual processing

The lateral geniculate nucleus (LGN) is classically portrayed as a relay station that simply serves to transfer signals from the retina to the primary visual cortex. According to this account, the LGN passively provides the necessary feedforward input to the visual cortex, but has no direct involvement in more complex perceptual processes. However, such an account fails to explain why the LGN receives far more afferents from the visual cortex than from the retina; moreover, it ignores the possibility that top-down feedback signals from the visual cortex to the LGN could have an important role in perceptual coding and in shaping the complex topography of responses that arise from the early visual system. According to neural theories of predictive coding, neurons in higher visual areas with large receptive fields can process more global information and send predictions about the input they receive to the lower visual area providing input. Any local errors in these globally informed predictions are then computed as residual error signals in the lower area. According to this account, portions of a visual scene that appear irregular or less expected, such as a figure that differs in featural content from its surround, may be highlighted at this lower site by additional residual processing. A far-reaching implication of this theory is that these top-down predictions may propagate to the lowest possible site of the visual hierarchy, modulating the response of the LGN to figural regions that differ in appearance from the adjacent background. This project will provide a novel evaluation of the functional role of the LGN in figure-ground processing, characterizing the impact of feedback modulation at the earliest possible site of the human visual pathway. We will use high-resolution fMRI at 7 Tesla to investigate multiple aspects of figure-ground processing in the LGN and V1. In Specific Aim 1, we will determine whether figure-selective enhancement in the early visual system depends on automatic perceptual processes or a mechanism of spatial attentional feedback. In Specific Aim 2, we will apply population coding models and multivariate regression techniques to characterize the spatial profile of figure-ground processes in the LGN and V1, and test for distinct mechanisms of boundary detection and figure enhancement. In Specific Aim 3, we will evaluate whether modulatory figure-ground effects in the LGN can be attributed to top-down feedback from binocularly sensitive visual cortex, and provide fine-grained characterization of the tuning profile of this feedback modulation. The results of this project will provide new insights into the perceptual functions of the human LGN, which are poorly understood, and yield critical new data to inform current models of predictive coding and figure-ground processing. The development of high- resolution fMRI methods to characterize and reconstruct LGN and V1 responses in image space is also of considerable health relevance. Future applications of this approach could be used to construct detailed visual- field maps of LGN and V1 responses associated with damage to the peripheral retina, impairments of central visual processing such as amblyopia, as well as the impact of clinical interventions.

外侧膝状体核（LGN）被经典地描绘成一个中继站， 从视网膜到初级视觉皮层的信号。根据这一说法，LGN被动地提供了 必要的前馈输入到视觉皮层，但没有直接参与更复杂的感知 流程.然而，这样的解释无法解释为什么LGN从视觉接收更多的传入 此外，它忽略了自上而下的反馈信号从视觉的可能性， LGN的皮层可能在感知编码和塑造复杂的地形中起重要作用。 这是由早期视觉系统引起的。根据预测编码的神经理论， 具有较大感受野的较高视觉区域可以处理更多的全局信息，并发送关于 它们接收到的输入到提供输入的较低视觉区域。在这些全局通知中的任何本地错误 然后将预测计算为下部区域中的残余误差信号。根据这份报告， 一种不规则的或不太令人期待的视觉场景，如一个人物的特征内容与其 环绕，可以通过附加的残余处理在该较低位置处突出显示。一个深远的影响， 该理论是这些自上而下的预测可以传播到视觉分级结构的最低可能位置， 调制所述LGN对在外观上不同于所述相邻背景的图形区域的响应。 该项目将提供一个新的评价功能的作用，LGN在图形背景处理， 表征反馈调制在人类视觉通路的最早可能位置处的影响。我们 将使用7特斯拉的高分辨率fMRI来研究LGN中图形-背景处理的多个方面 和V1。在具体目标1中，我们将确定早期视觉系统中的图形选择性增强是否 取决于自动感知过程或空间注意力反馈机制。在具体目标2中， 我们将应用人口编码模型和多元回归技术来表征空间分布， LGN和V1中图形-背景过程的轮廓，以及边界检测的不同机制的测试 和身材增强。在具体目标3中，我们将评估是否调制图形-背景效应， LGN可以归因于来自双眼敏感的视觉皮层的自上而下的反馈，并且提供细粒度的 这是对这种反馈调制的调谐曲线的表征。该项目的成果将提供新的 深入了解人类LGN的感知功能，这是知之甚少，并产生关键的新 数据，以告知预测编码和图形背景处理的当前模型。发展高- 在图像空间中表征和重建LGN和V1响应的分辨率fMRI方法也是 相当大的健康相关性。这种方法的未来应用可以用来构建详细的视觉- LGN和V1反应的场图与周边视网膜损伤、中央视网膜损伤、 视觉处理，如弱视，以及临床干预的影响。