Post-natal development of high-level visual representation in primates

灵长类动物产后高级视觉表征的发育

• 批准号: 9316254
• 负责人: James J DiCarlo
• 金额: $ 19.34万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-04-01 至 2019-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9316254
• 关键词: Adolescent; Adult; Amblyopia; Animals; Area; Autistic Disorder; Behavioral; Benchmarking; Biological; Biological Neural Networks; Brain; Categories; Chronic; Collaborations; Complex; Computer Vision Systems; Conflict (Psychology); Data; Data Set; Decision Making; Development; Electrodes; Exhibits; Eye; Face; Functional Magnetic Resonance Imaging; Future; Goals; Head; Human; Image; Implant; Inferior; Learning; Literature; Macaca; Measurement; Measures; Methods; Modeling; Monkeys; Motivation; Motor; Nature; Neural Network Simulation; Neurodevelopmental Disorder; Neurons; Neurosciences; Operative Surgical Procedures; Performance; Population; Primates; Procedures; Process; Research; Rewards; Sensory; Site; Stimulus; Stream; Supervision; System; Techniques; Temporal Lobe; Testing; Time; Training; Variant; Visual; Visual Cortex; Visual system structure; Work; awake; base; cognitive task; computational neuroscience; computerized tools; experience; experimental study; extrastriate visual cortex; improved; juvenile animal; learning network; mature animal; multi-electrode arrays; network models; neural correlate; nonhuman primate; novel; object recognition; postnatal; receptive field; relating to nervous system; response; statistics; vision development

View-invariant object recognition is a complex cognitive task that is critical to everyday functioning. A key neural correlate of high-level object recognition is inferior temporal (IT) cortex, a brain area present in both humans and non-human primates. Recent advances in visual systems neuroscience have begun to uncover how images are encoded in the adult IT object representation, however the learning rules by which high level visual areas (especially IT) develop remain mysterious, with both the magnitude and qualitative nature of developmental changes remaining almost completely unknown — in part because, over the last thirty years, there have been practically no studies of spiking neural responses in the higher ventral cortical areas of developing primates. There is thus a significant gap in our understanding of how visual development proceeds. This exploratory proposal aims to characterize how representation in higher primate visual cortex changes during development. We first aim (Aim 1) to implant chronic electrode arrays to record hundreds of IT neuronal sites in response to thousands of image stimuli in awake behaving juvenile macaques. These data will comprise a snapshot of the developing primate visual representation, and will be particularly powerful because we have already extensively measured adult monkey IT using the same stimuli and methods. By comparing juvenile and adult neuronal responses at both single site and population levels, we will obtain a unprecedentedly large-scale and detailed picture of the neural correlates of high-level visual development (Aim 2). Aims 1 and 2 are exploratory, but potentially transformative – they will result in publicly available neuronal IT development benchmarks against which any proposed model of high level visual development can be rigorously tested, and will spur the development of those models in our lab and others. In that context, we will also seek (Aim 3) to improve known semi- and un-supervised learning rules from the computer vision and computational neuroscience literature, and to compare them to both recent high-performing (but biologically implausible) supervised models as well to the rich developmental measurements obtained in Aims 1 and 2. Establishing experimental and surgical procedures for juvenile array recordings will create the future opportunity to observe changes in high level neural visual representations while experience is manipulated in early development, and will enable experiments in other sensory, motor, or decision making domains. If successful, the proposed work will yield a deeper understanding of the principles underlying visual cortex development, understanding which will in turn be helpful for treating neurodevelopmental disorders that implicate cortical circuits, including amblyopia and autism.

视角不变物体识别是一项复杂的认知任务，对日常功能至关重要。一个关键 高级物体识别的神经相关是下颞叶（IT）皮层，这是一个存在于两个区域的大脑区域。 人类和非人类灵长类动物。视觉系统神经科学的最新进展已经开始揭示 如何在成人IT对象表示中编码图像，然而， 视觉领域（特别是IT）的发展仍然是神秘的，无论是数量和质量的性质， 发展变化仍然几乎完全未知-部分原因是，在过去的三十年里， 实际上还没有研究过大脑中更高的腹侧皮质区的尖峰神经反应， 进化中的灵长类动物因此，我们对视觉发育的理解存在很大的差距。 收益。 这个探索性的建议旨在描述高级灵长类动物视觉皮层中的表征 发展过程中的变化。我们的第一个目标（目标1）是植入慢性电极阵列，以记录数百个 IT神经元的网站，在清醒的少年猕猴响应成千上万的图像刺激。这些 数据将包括发育中的灵长类动物视觉表示的快照，并且将特别 强大，因为我们已经使用相同的刺激广泛测量了成年猴子IT， 方法.通过在单个位点和群体水平上比较幼年和成年神经元的反应， 将获得一个前所未有的大规模和详细的图片的神经相关的高级视觉 发展（目标2）。 目标1和2是探索性的，但可能是变革性的-它们将导致公开可用的神经元 IT开发基准，任何建议的高级可视化开发模型都可以 经过严格的测试，并将刺激我们实验室和其他实验室的这些模型的发展。为此，我们 还将寻求（目标3）从计算机视觉中改进已知的半监督和无监督学习规则， 计算神经科学文献，并将它们与最近的高性能（但生物学） 令人难以置信的）监督模型以及目标1和2中获得的丰富的发展测量。 建立少年阵列记录的实验和外科手术程序将创造未来 有机会观察高级神经视觉表征的变化，而经验是操纵， 早期发展，并将使其他感官，运动，或决策领域的实验。如果 如果成功，这项工作将使我们对视觉皮层的基本原理有更深的理解 发展，理解这将反过来有助于治疗神经发育障碍， 包括弱视和自闭症在内的大脑皮层回路。