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.

视图不变的物体识别是一项复杂的认知任务，对于日常功能至关重要。 高级物体识别的神经相关性是下颞叶 (IT) 皮层，这是大脑中存在于两侧的区域 人类和非人类灵长类动物的视觉系统神经科学的最新进展已经开始揭示。 图像是如何在成人 IT 对象表示中编码的，但是高级别的学习规则 视觉领域（尤其是 IT）的发展仍然是神秘的，无论是在规模上还是在质量上 发展变化几乎仍然完全未知——部分原因是，在过去三十年里， 实际上还没有关于较高腹侧皮质区域的尖峰神经反应的研究 因此，我们对视觉发育的理解存在很大差距。 收益。 该探索性提案旨在描述高等灵长类动物视觉皮层的表征方式 我们的第一个目标（目标 1）植入慢性电极阵列以记录数百个。 清醒状态下幼年猕猴对数千个图像刺激做出反应的 IT 神经部位。 数据将包括正在发育的灵长类动物视觉表征的快照，并且将特别 之所以强大，是因为我们已经使用相同的刺激广泛测量了成年猴子的信息技术，并且 通过比较单个地点和群体水平上的青少年和成人神经反应，我们 将获得前所未有的大规模和详细的高级视觉神经关联图片 发展（目标 2）。 目标 1 和 2 是探索性的，但具有潜在的变革性——它们将导致公开可用的神经网络 IT 开发基准，任何提出的高级视觉开发模型都可以参照该基准 经过严格测试，并将刺激我们实验室和其他实验室的这些模型的开发。 还将寻求（目标 3）改进计算机视觉中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（但生物学上 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 当经验被操纵时，有机会观察高级神经视觉表征的变化 早期开发，并将在其他感觉、运动或决策领域进行实验。 成功后，拟议的工作将使人们更深入地了解视觉皮层的原理 发育、理解这反过来又有助于治疗神经发育障碍 涉及皮质回路，包括弱视和自闭症。