Function and circuitry of adaptive inhibition in the retina
Function and circuitry of adaptive inhibition in the retina
批准号:
9057543
负责人:
STEPHEN A BACCUS
金额:
$39.25万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-06-01 至 2018-05-31
关键词:
Amacrine CellsBackBrainCellsCodeComplementComplexComputer SimulationDiseaseElectronicsEnvironmentFutureGoalsHealthIndividualInner Plexiform LayerInterneuronsInterventionKnowledgeLearningMeasuresMethodsModelingMorphologyMusNeuronsNeurophysiology - biologic functionOutputPharmacologyPlayPopulationPopulation HeterogeneityProcessPropertyProsthesisRecording of previous eventsRetinaRetinalRetinal DegenerationRetinal DiseasesRetinal Ganglion CellsRoleSalamanderSensorySignal TransductionStagingStem cellsStimulusStructureSynapsesSystemTestingValidationVisualWhole-Cell Recordingsbasebehavior changecell typedesignfallsganglion cellinformation processingmathematical modelmulti-electrode arraysneural circuitnovelnovel strategiesreceptive fieldrelating to nervous systemresearch studyresponseretinal prosthesissensory inputsensory systemspatiotemporaltherapy designtransmission process
中文摘要
描述(由申请人提供):脊椎动物视网膜的关键功能是基于刺激的最近历史改变其敏感性,以便在环境改变时保持视觉反应。这个过程被称为适应,以多种形式发生,尽管这些计算的细胞和电路起源的许多方面仍然未知。最近,人们发现某些视网膜神经节细胞在强烈刺激后会增加其敏感性。这些敏感神经节细胞对弱刺激保持高敏感性,即使其他类型的神经节细胞适应并低于阈值。该建议旨在分析敏化的自适应计算的电路基础。为了了解敏化的产生,我们开发了一种新的方法来直接测量单个视网膜中间神经元的功能作用。我们记录从一个单一的interneuron细胞内的视觉反应,同时记录从人口的视网膜神经节细胞使用多电极阵列。然后,通过使用注入的电流回放细胞自身信号的改变版本,我们直接探测细胞的输出如何改变电路的行为。数学模型被用来解释中间神经元的反应如何结合在一起,产生神经节细胞的反应联合收割机。无长突细胞是视网膜中抑制性中间神经元的多样性群体,大多数功能未知。已知一些无长突细胞适应刺激的对比度,但这一过程的功能作用尚不清楚。这个提议的目的是测试适应性抑制产生敏化的假设,并开发一个定量的电路水平描述敏化是如何产生的。具体目标是:1)在蝾螈和小鼠视网膜中,我们将测量适应性兴奋和抑制如何联合收割机产生敏化的时空结构,并用计算模型捕捉这些特性。利用药理学,我们将确定广泛的无长突细胞,是必不可少的敏化。2)使用细胞内和多电极记录,我们将测量通过蝾螈视网膜电路的敏化计算,通过记录在敏化过程中从中间神经元,然后直接测量它们的连接到不同类别的神经节细胞。蝾螈和小鼠神经节细胞中的突触电流将使用全细胞记录进行分析。3)我们将直接测量如何从单一的抑制性无长突细胞传输的变化产生敏化在完整的蝾螈视网膜。了解不同的神经元群体如何结合起来执行神经功能是我们理解视网膜机制和涉及视网膜回路变性的疾病的关键障碍。这些发现对于理解视网膜电路如何处理信息的基本机制至关重要,并且在电子视网膜假体系统的设计中将是有用的。
英文摘要
DESCRIPTION (provided by applicant): A critical function of the vertebrate retina is to change its sensitivity based on the recent history of the stimulus in order to maintain a visual response when the environment changes. This process, known as adaptation, occurs in multiple forms, although many aspects of the cellular and circuit origin of these computations remain unknown. Recently, it was found that certain retinal ganglion cells increase their sensitivity following a strong stimulus. These sensitizing ganglion cells maintain a high sensitivity to weak stimuli, even when other types of ganglion cells adapt and fall below threshold. This proposal aims to analyze the circuit basis for the adaptive computation of sensitization. To understand sensitization arises, we have developed a novel approach to directly measure the functional role of individual retinal interneurons. We record the intracellular visual response from a single interneuron, while simultaneously recording from a population of retinal ganglion cells using a multielectrode array. Then, by playing back an altered version of the cell's own signal using injected current, we directly probe how that cell's output changes the behavior of the circuit. Mathematical models are used to explain how the responses of interneurons combine together to yield the responses of ganglion cells. Amacrine cells are a diverse population of inhibitory interneurons in the retina, most with unknown function. Some amacrine cells are known to adapt to the contrast of the stimulus, but the functional role of this process is unknown. The goal of this proposal is test the hypothesis that adaptive inhibition generates sensitization, and to develop a quantitative circuit level description of how sensitization arises. The specific goals are: 1) In the salamander and mouse retina, we will measure the spatiotemporal structure of how adaptive excitation and inhibition combine to generate sensitization, and capture these properties with a computational model. Using pharmacology, we will identify the broad class of amacrine cells that are essential to sensitization. 2) Using intracellular and multielectrode recording, we will measure the computation of sensitization through salamander retinal circuitry by recording from interneurons during sensitization, and then directly measure their connectivity to different classes of ganglion cells. Synaptic currents in salamander and mouse ganglion cells will be analyzed using whole cell recordings. 3) We will directly measure how changes in transmission from single inhibitory amacrine cells generate sensitization in the intact salamander retina. Understanding how a diverse population of neurons combines to perform neural functions is a critical barrier to our understanding of retinal mechanisms and diseases involving the degeneration of the retinal circuitry. These findings will be essential to understanding basic mechanisms of how retinal circuitry processes information and will be useful in the design of electronic retinal prosthesis systems.
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