The development of feature selectivity across the visual system

整个视觉系统特征选择性的发展

• 批准号: RGPIN-2018-03852
• 负责人: Trenholm, Stuart
• 金额: $ 2.77万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=712401
• 关键词: development; feature; selectivity; across; visual

Background: The mammalian visual system is organized in a hierarchical manner, with the complexity of neuronal responses increasing as you move from the retina to higher brain regions. This increase in complexity can be measured via the feature selective responses of neurons in different brain areas, such as center-surround responses in the retina, orientation and direction selective responses in visual cortex, and visual object selective responses in temporal cortex. However, little is known about how complex feature selectivity arises, both within and across brain regions. To gain a better understanding of how feature selectivity is generated, neuronal circuits can be studied at the level of single-cell functional connectivity, by directly comparing the feature selectivity of a single postsynaptic neuron to the feature selectivity of its presynaptic inputs. Objective 1: Compare the feature selectivity of individual layer 4 starter' neurons in primary visual cortex to the feature selectivity of their presynaptic inputs in visual cortex. To do this, we will perform single-cell initiated transsynaptic circuit tracing from layer 4 of visual cortex with modified rabies viruses. We will present mice with visual stimuli and measure the light responses in the synaptically connected neurons using in vivo 2-photon calcium imaging. Objective 2: Compare the feature selectivity of individual layer 4 starter neurons to their presynaptic neurons in the lateral geniculate nucleus (LGN) of the thalamus. Using the same experimental paradigm as outlined in Objective 1, we will monitor the neuronal activity of individual cortical layer 4 starter cells and their presynaptic LGN inputs using in vivo 2-photon calcium imaging. Objective 3: Compare the feature selectivity of the retinal ganglion cells that provide di-synaptic input to individual neurons in layer 4 of visual cortex. We will implement a novel, serial circuit tracing strategy, involving the use of single-cell-initiated rabies virus tracing from individual cells in multiple brain regions, to drive rabies to jump from a single LGN neuron that is presynaptic to the layer 4 cortical starter neuron to presynaptic retinal ganglion cells. We will then perform 2-photon calcium imaging from retinal ganglion cells in vitro during visual stimulation to examine the feature selectivity of these neurons. Outcomes: These experiments will provide strong direct evidence regarding how distinct feature selective responses, in particular orientation and direction selective responses, arise in the early visual system. This will be the first project to directly monitor how a single feature selectivity arises across multiple brain regions by focusing on synaptically connected neurons in three distinct brain regions. In the future, similar approaches could be used to understand more complex feature selective responses, such as visual object selectivity.

背景资料：哺乳动物的视觉系统是以分层的方式组织的，随着你从视网膜向更高的大脑区域移动，神经元反应的复杂性也会增加。这种复杂性的增加可以通过不同脑区神经元的特征选择性反应来测量，例如视网膜中的中心-环绕反应，视觉皮层中的方向和方向选择性反应，以及颞叶皮层中的视觉对象选择性反应。然而，人们对复杂特征选择性是如何产生的知之甚少，无论是在大脑区域内还是在大脑区域之间。为了更好地理解特征选择性是如何产生的，可以在单细胞功能连接的水平上研究神经元回路，方法是直接比较单个突触后神经元的特征选择性与其突触前输入的特征选择性。 目标一：比较初级视皮层中单个第4层起始神经元的特征选择性与它们在视皮层中的突触前输入的特征选择性。为此，我们将用改良的狂犬病毒从视觉皮层第4层进行单细胞启动的跨突触回路追踪。我们将向小鼠提供视觉刺激，并使用体内双光子钙成像测量突触连接神经元的光反应。 目标二：比较丘脑外侧膝状体（LGN）第4层起始神经元与其突触前神经元的特征选择性。使用与目标1中所述相同的实验范例，我们将使用体内双光子钙成像监测单个皮层第4层起始细胞的神经元活动及其突触前LGN输入。 目标三：比较视网膜神经节细胞对视觉皮层第4层中单个神经元提供双突触输入的特征选择性。我们将实施一种新型的串行电路追踪策略，涉及使用单细胞启动的狂犬病病毒追踪多个大脑区域的单个细胞，以驱动狂犬病从突触前的单个LGN神经元跳到第4层皮质启动神经元到突触前视网膜神经节细胞。然后，我们将在视觉刺激期间对体外视网膜神经节细胞进行双光子钙成像，以检查这些神经元的特征选择性。 成果：这些实验将提供强有力的直接证据，关于如何不同的功能选择性反应，特别是方向和方向选择性反应，出现在早期视觉系统。这将是第一个通过关注三个不同大脑区域中突触连接的神经元来直接监测单个特征选择性如何在多个大脑区域中产生的项目。将来，类似的方法可以用来理解更复杂的特征选择性反应，例如视觉对象选择性。