Determinants of Signal Characteristics in a Retinal Network: Contribution of Local Field Potentials and Spike Trains.

视网膜网络中信号特征的决定因素：局部场电位和尖峰序列的贡献。

• 批准号: RGPIN-2015-04250
• 负责人: Tremblay, Francois
• 金额: $ 1.75万
• 依托单位: Dalhousie University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=630717
• 关键词: Determinants; Signal; Characteristics; Retinal; Network

The teamwork research taking place in my lab share the common objective of a better comprehension of how the neural activity of the various cell populations of the retina translates a visual stimulus into a neural code that can be understood by the brain. We have been using for many years the electroretinogram (ERG), a composite signal collected non-invasively at the surface of the cornea, to decipher the relative contribution of different cell population. More recently, we have gained expertise in the multi electrode array (MEA), a technology that allows the ex-vivo (isolated retina) recording of both the ERG-like signal and the spiking activity of the ganglion cells, the population giving rise to the efferent message of the retina.

在我的实验室进行的团队合作研究有一个共同的目标，即更好地理解视网膜各种细胞群的神经活动如何将视觉刺激转化为大脑可以理解的神经代码。多年来，我们一直使用视网膜电图（ERG），一种在角膜表面非侵入性收集的复合信号，来破译不同细胞群的相对贡献。最近，我们获得了多电极阵列（MEA）的专业知识，该技术允许离体（离体视网膜）记录ERG样信号和神经节细胞的尖峰活动，该群体产生视网膜的传出信息。