Effects of local adaptation on parallel pathway circuit computations in the retina

局部适应对视网膜并行通路计算的影响

• 批准号: 9750296
• 负责人: Gabrielle Jacqueline Gutierrez
• 金额: $ 5.22万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-01 至 2022-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9750296
• 关键词: Affect; Area; Biological; Biophysical Process; Biophysics; Brain; Brain Diseases; Code; Complex; Computer Simulation; Cone; Electrophysiology (science); Environment; Goals; Individual; Interdisciplinary Study; Knowledge; Light Adaptations; Medical; Mentors; Modeling; Neurons; Neurophysiology - biologic function; Neurosciences; Pathway interactions; Phase; Photoreceptors; Presynaptic Terminals; Process; Property; Public Health; Research; Retina; Retinal Ganglion Cells; Role; Sensory; Signal Transduction; Stimulus; Technology; Testing; Training; Universities; Vision; Visual; Visual Cortex; Visual system structure; Washington; Work; career development; cell type; design; experimental study; flexibility; ganglion cell; improved; luminance; neural circuit; predictive modeling; receptive field; relating to nervous system; response; retinal rods; skills; spatiotemporal; targeted treatment

The retina is an adaptable circuit that is capable of rapidly changing its processing mode with changing stimulus conditions. This is an enormous undertaking because the retina has to process an unpredictable and wide-ranging assortment of inputs. An understanding of how local neuron dynamics are coordinated to produce and alter global network computations is needed for understanding how neural circuits of the brain are able to flexibly integrate information from many different areas. Advances on this front will have a broad impact on the ability to design targeted therapies to ameliorate brain disorders. The long-term goal of the proposed work is to understand how local adaptation mechanisms impact the computational function of neural circuits like the retina. Signals from the photoreceptors are processed along parallel pathways in the early part of the retina circuit and later combined. The properties of the visual inputs can modulate the how these inputs are processed via local adaptation mechanisms. This kind of adaptation has consequences for the manner in which visual inputs are encoded and processed in the early part of the visual system. The proposed research during the mentored phase aims to characterize the rod pathway adaptation that leads to a switch in computational processing of inputs and to determine the consequences for the spatiotemporal encoding of visual inputs. I will characterize adaptation through the rod-AII pathway for a range of luminance conditions to build a predictive model and to then determine how this adaptation affects the feature-sensitivity of ON α- ganglion cells under different luminance conditions. The independent phase research will build on the progress made during the mentored phase. There are several distinct ganglion cell types that convey information to the brain about particular visual features - similar to the higher order processing that takes place in the visual cortex. I will conduct studies to determine how ON and OFF α-ganglion cell types use the same circuitry to produce computations that are fundamentally distinct beyond their opposite polarities. The objective of this work is to obtain a better understanding of how mechanisms of local adaptation can reconfigure the computational functions of diverse circuit components. The University of Washington offers the ideal environment for my career development and for pursuing this highly interdisciplinary project. I have two outstanding mentors, an experimentalist and a theorist. I will receive training to become proficient in retina electrophysiology experiments and take courses to hone my quantitative skills. This training will prepare me to launch my own lab with an interdisciplinary focus. The proposed research will establish my expertise in the effects of biophysical mechanisms on sensory circuit computation.

视网膜是一个适应性强的电路，能够迅速改变其处理模式， 改变刺激条件。这是一项艰巨的任务，因为视网膜必须处理 不可预测和广泛的输入分类。了解局部神经元动力学 协调来产生和改变全球网络计算， 大脑的神经回路能够灵活地整合来自许多不同区域的信息。 这方面的进展将对设计靶向治疗的能力产生广泛的影响， 改善脑部疾病拟议工作的长期目标是了解当地如何 适应机制会影响像视网膜这样的神经回路的计算功能。信号 在视网膜的早期部分沿着沿着路径处理来自光感受器的信号 循环，然后组合。视觉输入的属性可以调节这些输入如何 通过本地适应机制进行处理。这种适应性会对 视觉输入在视觉系统的早期被编码和处理的方式。的 在指导阶段提出的研究旨在描述视杆细胞通路的适应性， 导致输入的计算处理中的切换，并确定 视觉输入的时空编码。我将通过棒-AII来描述适应 一系列亮度条件的路径，以建立预测模型，然后确定如何 这种适应影响ON α神经节细胞在不同亮度下的特征敏感性 条件独立阶段的研究将建立在指导期间取得的进展的基础上。 相位有几种不同的神经节细胞类型向大脑传递信息， 特定的视觉特征-类似于在视觉中发生的高阶处理 皮层我将进行研究，以确定ON和OFF α-神经节细胞类型如何使用相同的 电路产生的计算是根本不同的超越其相反的极性。 这项工作的目标是更好地了解当地的机制， 自适应可以重新配置不同电路组件的计算功能。的 华盛顿大学为我的职业发展和追求提供了理想的环境 这个高度跨学科的项目。我有两位杰出的导师，一位是实验家， 理论家我将接受培训，成为熟练的视网膜电生理学实验， 参加一些课程来磨练我的量化技能。这次培训将帮助我建立自己的实验室 一个跨学科的焦点。这项拟议中的研究将确立我在影响方面的专业知识 生物物理学机制对感觉电路计算的影响。