Validating Theoretical Models with Neurophysiology and Optogenetics

用神经生理学和光遗传学验证理论模型

• 批准号: 10438696
• 负责人: Hillel Adesnik
• 金额: $ 37.22万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-15 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10438696
• 关键词: 3-Dimensional; Calcium; Cells; Dimensions; Fire - disasters; Foundations; Goals; Image; Individual; Laws; Membrane Potentials; Modeling; Monitor; Neurons; Optics; Outcome; Photic Stimulation; Photons; Research Project Grants; Resolution; Stimulus; Technology; Testing; Theoretical model; V1 neuron; cell type; experimental study; improved; in vivo; insight; millisecond; movie; neural circuit; neurophysiology; new technology; novel; novel strategies; optogenetics; photoactivation; predictive modeling; preference; relating to nervous system; response; retinotopic; theories

ABSTRACT Theoretical models of neural circuits aim to provide a set of fundamental principles that capture neural dynamics and explain neural computation. While their value scales with the range of dynamics they can capture and explain, the models’ validity depends on their ability to make accurate predictions in the face of defined perturbations. The goal of this specific research project is to employ defined perturbations that definitively test core predictions of the new models. Unquestionably, the most powerful approach for perturbing neural activity is optogenetics, yet one photon optogenetics is not up to the task. Therefore, we will use a novel all-optical multiphoton approach that combines calcium imaging with multiphoton holographic optogenetics. This new technology allows large ensembles of neurons to be targeted with single cell resolution for photo-activation in three dimensions. Using this new approach, we will test a concerted set of concrete predictions with extremely well-defined perturbations, that were never before possible. These optogenetic perturbations thus close the loop of iterative model refinement and testing to arrive at the most powerful and predictive model yet of any cortical circuit.

摘要 神经回路的理论模型旨在提供一套捕捉神经动力学的基本原理 并解释神经计算虽然它们的价值与它们可以捕获的动态范围有关， 解释说，模型的有效性取决于他们在面对定义的问题时做出准确预测的能力。 扰动这个特定研究项目的目标是采用确定的扰动， 新模型的核心预测。毫无疑问，干扰神经活动最有效的方法是 光遗传学，然而单光子光遗传学还不能胜任这项任务。因此，我们将使用一种新型的全光 将钙成像与多光子全息光遗传学相结合的多光子方法。这个新 技术允许以单细胞分辨率靶向大的神经元集合， 三维空间使用这种新方法，我们将测试一组协调一致的具体预测， 定义明确的扰动，这在以前是不可能的。这些光遗传学的扰动因此闭合了这个循环 迭代模型优化和测试，以达到最强大的和预测的模型，但任何皮质 电路.