CRCNS: Formation of stimulus selective neural assemblies in piriform cortex

CRCNS：梨状皮层刺激选择性神经组件的形成

基本信息

批准号：
9049840
负责人：
Brent D. Doiron
金额：
$ 28.59万
依托单位：
UNIVERSITY OF PITTSBURGH AT PITTSBURGH
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-08-01 至 2018-07-31
项目状态：
已结题

项目摘要

Sensory cortex decomposes complex inputs into feature-based components, and distributes their representation over populations of neurons. In special cases this distribution is very clear--for instance the visual and auditory system respectively map retinal image and acoustic frequency along a spatial dimension within cortex. In general, however, rich sensory scenes are a mixture of features, and it remains unclear how the cortex mingles and segregates aspects of a complex sensory representation across neural populations. Olfactory stimuli are extraordinarily complex, with distinct odors comprised from a mixture of compounds. The circuitry in olfactory cortex is equally intricate, with populations of neurons coupling to one another with seemingly random rules, and receiving similarly random projections from lower centers. The combination of these two facts obfuscates the organization of odor representation. Our proposal leverages advances in experimental circuit identification and manipulation, as well as theoretical frameworks for large-scale cortical networks, to establish principles for the distribution of odor identity and concentration coding across olfactory cortex. Specifically, we aim to establish the following links between olfactory circuitry and odor coding: 1 )There exists a graded distribution of specific inhibitory sub-circuits along the rostral-caudal axis of the olfactory cortex. 2) The rostral-caudal distribution of inhibition interacts with Hebbian plasticity mechanisms so as to shape the odor selectivity of cells along the rostral-caudal axis. These advances will provide much needed insights into how cortical structures represent and process distinct aspects of an odor scene.

感觉皮层将复杂的输入分解为基于特征的组件，并将其表示分布在神经元群体中，在特殊情况下，这种分布非常清晰——例如，视觉和听觉系统分别沿空间维度映射视网膜图像和声频。然而，一般来说，丰富的感觉场景是多种特征的混合体，目前尚不清楚皮层如何在神经群体中混合和分离复杂的感觉表征的各个方面。嗅觉刺激非常复杂，由多种化合物的混合物组成，嗅觉皮层的电路同样复杂，神经元群体以看似随机的规则相互耦合，并且同样接收来自较低中心的随机预测的组合。这两个事实混淆了气味表示的组织，我们的建议利用实验电路识别和操作的进步，以及大规模皮层网络的理论框架，来建立气味身份和浓度编码的分布原则。具体来说，我们的目标是在嗅觉电路和气味编码之间建立以下联系： 1）沿着嗅觉皮层的头尾轴存在特定抑制子回路的分级分布。 2）抑制的头尾分布与赫布可塑性机制相互作用，从而沿着头尾轴塑造细胞的气味选择性。这些进步将为皮层结构如何表示和处理气味场景的不同方面提供急需的见解。