Grid-like Neural Representations Support Olfactory Navigation of a Two-Dimensional Odor Space
Grid-like Neural Representations Support Olfactory Navigation of a Two-Dimensional Odor Space
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DOI：
10.1016/j.neuron.2019.03.034
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发表时间：
2019-06-05
期刊：
影响因子：
16.2
通讯作者：
Gottfried, Jay A.
中科院分区：
文献类型：
--
作者：
Bao, Xiaojun;Gjorgieva, Eva;Gottfried, Jay A.
寻找食物、朋友和伴侣往往始于空气中的气味。重要的是，气味浓度上升与物理接近的气味源，这表明一个框架内的嗅觉景观，以优化行为的方向。在这里，我们创建了一个纯粹由气味刺激组成的二维气味空间，以模拟导航员如何在自然环境中遇到气味。我们表明，人类受试者可以学习在嗅觉空间中导航，并形成对将要遇到的气味的预测。在导航过程中，内嗅皮层和腹内侧前额叶皮层的功能磁共振成像反应的形式与六边形的周期性和内嗅网格强度缩放跨学科的行为表现的网格状表示。识别嗅觉网格状代码与6重对称性突出了一个独特的神经机制，气味信息可以组装成空间导航的认知地图，优化方向，并寻找路径的气味源。
Searching for food, friends, and mates often begins with an airborne scent. Importantly, odor concentration rises with physical proximity to an odorous source, suggesting a framework for orienting within olfactory landscapes to optimize behavior. Here, we created a two-dimensional odor space composed purely of odor stimuli to model how a navigator encounters smells in a natural environment. We show that human subjects can learn to navigate in olfactory space and form predictions of to-be-encountered smells. During navigation, fMRI responses in entorhinal cortex and ventromedial prefrontal cortex take the form of grid-like representations with hexagonal periodicity and entorhinal grid strength scaled with behavioral performance across subjects. The identification of olfactory grid-like codes with 6-fold symmetry highlights a unique neural mechanism by which odor information can be assembled into spatially navigable cognitive maps, optimizing orientation, and path finding toward an odor source.