Circuit Mechanisms Underlying Persistent Activity in a Neural Integrator

神经积分器持续活动背后的电路机制

基本信息

批准号：
10704527
负责人：
Emre R Aksay
金额：
$ 69.9万
依托单位：
WEILL MEDICAL COLL OF CORNELL UNIV
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-08-01 至 2027-07-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10704527
关键词：
3-Dimensional Address Anatomy Behavior Biological Biological Models Brain region Calcium Cells Conceptions Couples Coupling Data Decision Making Dependence Disease Disparate Exhibits Experimental Designs Eye Eye Movements Foundations Functional Imaging Future Genotype Heterogeneity Image Individual Location Maps Mathematics Measurement Memory Modeling Neurons Pattern Physiological Play Population Positioning Attribute Preparation Property Recurrence Resolution Role Short-Term Memory Signal Transduction Specificity Speed Stimulus Synapses System Testing Theoretical Studies Theoretical model Three-Dimensional Imaging Time Transgenic Organisms Vision Visual Visual impairment Work Zebrafish behavior change cell type experimental study eye velocity flexibility gaze imaging study in silico insight motor control network models neural neural patterning oculomotor optical imaging optogenetics postsynaptic predictive modeling reconstruction response simulation theories treatment strategy two-photon

项目摘要

Abstract Short-term memory function is commonly supported through persistent activity, the sustained response of populations of neurons following the offset of a memorized stimulus. This form of activity underlies diverse tasks including navigation, motor control, and decision-making. Classic mechanistic theories have idealized such activity through models that assume strongly homogeneous populations of neurons that encode only a single variable and generate perfectly stable patterns of activity. This contrasts with recent work showing that neurons in real biological memory networks exhibit multiplexed encoding of multiple stimulus attributes, temporally varying responses across the population, and context dependence. Here we address the circuit mechanisms and role of this diversity in function through a combined experimental-theoretical approach. Experiments are conducted in a short-term memory circuit of the larval zebrafish gaze control system that contributes to stable vision by precisely maintaining the eyes on a visual target. Taking advantage of the quantitative precision and experimental tractability of this system, we combine whole-circuit, synapse-resolution anatomy with circuit-wide recordings and perturbations of activity at cellular resolution. In Aim 1, we combine these data into a model of the system in which neurons map in a one-to-one manner with experimentally recorded neurons. This enables us to infer the interactions within and between neurons of different anatomical, genotypic, and functional cell classes and form predictions for how these interactions govern circuit function. In Aim 2, we use 3D cellular resolution optical imaging and stimulating perturbations of neuronal activity to refine our model and test model predictions. In Aim 3, we expand our capacity to form precise characterizations of within and between cell-class interactions by developing and applying 3D suppression of neurons across the memory circuit. Altogether, this work promises to greatly expand our understanding of the circuit mechanisms and role of cell type diversity in persistent firing, short-term memory, and motor control.

抽象的短期记忆功能通常通过持续活动来支持记忆刺激反应后神经元种群的反应。这种形式活动是各种任务的基础，包括导航，运动控制和决策。经典的机械理论通过强烈假设的模型理想化了此类活动仅编码一个变量并完美生成的神经元的均匀种群稳定的活动模式。这与最近的工作形成鲜明对比，表明实际生物学中的神经元存储网络表现出多重刺激属性的多路复用编码，在时间上变化人群之间的反应和上下文依赖性。在这里我们解决电路通过合并的实验理论，这种多样性在功能中的机制和作用方法。实验是在幼虫斑马鱼注视的短期记忆回路中进行的通过精确地将眼睛保持在视觉上，从而有助于稳定视力的控制系统目标。利用该系统的定量精度和实验性障碍性，我们将全部电路，突触分辨解剖结合与电路范围的记录和细胞分辨率的活性扰动。在AIM 1中，我们将这些数据结合到一个模型中神经元以实验记录的神经元以一对一的方式绘制的系统。这使我们能够推断出不同解剖学，基因型的神经元之间和之间的相互作用以及功能性细胞类别，并为这些相互作用如何控制电路函数形成预测。在AIM 2中，我们使用3D细胞分辨率光学成像和刺激神经元的扰动活动以完善我们的模型和测试模型预测。在AIM 3中，我们扩大了形成的能力通过开发和应用细胞类相互作用的精确表征 3D抑制整个内存电路的神经元。总之，这项工作有望极大地扩展我们对电路机制的理解和细胞类型多样性在持久性中的作用射击，短期内存和电动机控制。