Neural mechanisms of active vision in the fovea

中央凹主动视觉的神经机制

• 批准号: 10661104
• 负责人: Jacob L Yates
• 金额: $ 24.9万
• 依托单位: UNIVERSITY OF CALIFORNIA BERKELEY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2025-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10661104
• 关键词: Address; Age related macular degeneration; American; Behavior; Behavioral; Blindness; Brain; Callithrix; Code; Cognitive; Computer Models; Custom; Data; Data Set; Development; Development Plans; Disease; Ensure; Esthesia; Eye; Eye Movements; Foundations; Frequencies; Funding; Goals; Grant; Human; Image; Laboratories; Machine Learning; Measurement; Measures; Mentors; Modeling; Modernization; Monkeys; Motion; Neurons; Outcome; Peripheral; Phase; Physiology; Population; Positioning Attribute; Primates; Process; Recovery; Research; Resolution; Retina; Retinal Diseases; Role; Saccades; Sampling; Series; Signal Transduction; Statistical Models; Stream; System; Techniques; Testing; Training; Universities; V1 neuron; V4 neuron; Vision; Visual; Visual Acuity; Visual Cortex; Visual Fields; Visual Pathways; Visual attention; Work; active vision; area striata; awake; career; career development; central visual field; computerized tools; data-driven model; design; extrastriate; extrastriate visual cortex; flexibility; fovea centralis; improved; interest; lens; neural; neural model; neuromechanism; neurophysiology; new technology; novel; professor; receptive field; repaired; response; retinal imaging; sample fixation; sensor; skills; spatial vision; spatiotemporal; statistics; tool; visual information; visual neuroscience; visual process; visual processing; visual tracking

Neural mechanisms of active vision in the fovea In many ways human vision is like a camera, with a lens that forms an image on a spatially arranged sensor (the retina). However, it is unlike a camera because the sensor has uneven sampling and is constantly moving with the eyes. Recent behavioral and theoretical work suggest these eye movements serve a faciliatory role in high acuity vision – where the eye movements are part of the computations and enhance spatial resolution. However, the neurophysiological mechanisms to support this facilitation remain unknown. More broadly, little is known about the neural mechanisms that integrate across the retinal motion generated by eye movements, especially in the central visual field (the fovea). This is particularly important because over 8 million Americans suffer from central vision loss due to retinal disorders. Even if the retinal signals could be repaired, it is imperative to understand how the brain reads out foveal signals to ensure recovery of high-acuity visual processing, and fixational eye movements are a part of that process. The proposed career development plan aims to address these questions by measuring visual processing in the foveal representation of primary visual cortex (V1) during natural visual behavior. This proposal uses custom high-resolution eye-tracking, a novel visual foraging paradigm, largescale neurophysiology, and state-of-the-art machine learning to make these measurements possible. The proposed research will not only generate fundamental understanding of how eye-movements facilitate visual processing, but also will integrate the experimental and theoretical tools required to support neurophysiological studies of active visual processing without a loss of rigor or detail. The candidate has extensive expertise in awake- behaving neurophysiology and computational modeling and the training plan is designed to support his further training in statistical modeling, high-resolution eye-tracking, and modern machine-learning techniques for analyzing neural population data. The primary mentor, Dr. Daniel Butts, is a world expert in statistical models of neural activity during active vision; Co-mentor, Dr. Michele Rucci, is a world leader in high-resolution eye tracking and theoretical approaches to active vision; and Co-mentor, Dr. Jude Mitchell, is a pioneer in establishing the marmoset model of visual neuroscience and an expert in neurophysiology of visual attention. Together, they will provide the guidance to establish the candidate’s transition to a successful independent research career.

中央凹主动视觉的神经机制 在许多方面，人类视觉就像一台相机，其镜头可以在空间上形成图像 排列的传感器（视网膜）。然而，它与相机不同，因为传感器具有不均匀的 采样并随着眼睛不断移动。最近的行为和理论工作表明 这些眼球运动在高敏锐度视力中发挥着促进作用——眼球运动 是计算的一部分并增强空间分辨率。然而，神经生理学 支持这种便利的机制仍然未知。更广泛地说，人们对此知之甚少 整合眼球运动产生的视网膜运动的神经机制， 尤其是在中央视野（中央凹）。这一点尤其重要，因为超过 8 数以百万计的美国人因视网膜疾病而遭受中央视力丧失。即使视网膜信号 可以修复，必须了解大脑如何读取中央凹信号以确保 恢复高敏锐度视觉处理和注视眼球运动是该过程的一部分。 拟议的职业发展计划旨在通过测量视觉来解决这些问题 自然视觉过程中初级视觉皮层（V1）中央凹表示的处理 行为。该提案使用定制的高分辨率眼动追踪，一种新颖的视觉觅食 范式、大规模神经生理学和最先进的机器学习使这些 可以进行测量。拟议的研究不仅会产生基础 了解眼球运动如何促进视觉处理，而且还将整合 支持主动视觉神经生理学研究所需的实验和理论工具 处理过程不失严谨性或细节。候选人在清醒方面拥有丰富的专业知识 行为神经生理学和计算建模，训练计划旨在 支持他在统计建模、高分辨率眼球追踪和现代技术方面的进一步培训 用于分析神经群体数据的机器学习技术。首席导师 Daniel 博士 巴茨是主动视觉期间神经活动统计模型方面的世界专家；共同导师，博士。 米歇尔·鲁奇 (Michele Rucci) 是高分辨率眼动追踪和理论方法领域的世界领先者 主动视力；共同导师 Jude Mitchell 博士是建立狨猴模型的先驱 视觉神经科学博士和视觉注意力神经生理学专家。他们将一起 为候选人过渡到成功的独立研究提供指导 职业。

项目成果

A dynamic sequence of visual processing initiated by gaze shifts.

由目光转移引发的视觉处理的动态序列。

• DOI: 10.1038/s41593-023-01481-7
• 发表时间: 2023
• 期刊: Nature neuroscience
• 影响因子: 25
• 作者: Parker,PhilipRL;Martins,DylanM;Leonard,EmmalynSP;Casey,NathanM;Sharp,ShelbyL;Abe,ElliottTT;Smear,MatthewC;Yates,JacobL;Mitchell,JudeF;Niell,CristopherM
• 通讯作者: Niell,CristopherM

Activity in primate visual cortex is minimally driven by spontaneous movements.

• DOI: 10.1038/s41593-023-01459-5
• 发表时间: 2023-11
• 期刊: NATURE NEUROSCIENCE
• 影响因子: 25
• 作者: Talluri, Bharath Chandra;Kang, Incheol;Lazere, Adam;Quinn, Katrina R.;Kaliss, Nicholas;Yates, Jacob L.;Butts, Daniel A.;Nienborg, Hendrikje
• 通讯作者: Nienborg, Hendrikje