Hardcastle Kiah, Maheswaranathan Niru, Ganguli Surya, Giocomo Lisa M
Department of Neurobiology, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Applied Physics, Stanford University, Stanford, CA 94305, USA.
Department of Neurobiology, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Applied Physics, Stanford University, Stanford, CA 94305, USA.
Neuron. 2017 Apr 19;94(2):375-387.e7. doi: 10.1016/j.neuron.2017.03.025. Epub 2017 Apr 6.
Medial entorhinal grid cells display strikingly symmetric spatial firing patterns. The clarity of these patterns motivated the use of specific activity pattern shapes to classify entorhinal cell types. While this approach successfully revealed cells that encode boundaries, head direction, and running speed, it left a majority of cells unclassified, and its pre-defined nature may have missed unconventional, yet important coding properties. Here, we apply an unbiased statistical approach to search for cells that encode navigationally relevant variables. This approach successfully classifies the majority of entorhinal cells and reveals unsuspected entorhinal coding principles. First, we find a high degree of mixed selectivity and heterogeneity in superficial entorhinal neurons. Second, we discover a dynamic and remarkably adaptive code for space that enables entorhinal cells to rapidly encode navigational information accurately at high running speeds. Combined, these observations advance our current understanding of the mechanistic origins and functional implications of the entorhinal code for navigation. VIDEO ABSTRACT.
内侧内嗅网格细胞呈现出惊人的对称空间放电模式。这些模式的清晰度促使人们使用特定的活动模式形状来对内嗅细胞类型进行分类。虽然这种方法成功地揭示了编码边界、头部方向和奔跑速度的细胞,但仍有大多数细胞未被分类,而且其预先定义的性质可能遗漏了非常规但重要的编码特性。在这里,我们应用一种无偏统计方法来寻找编码与导航相关变量的细胞。这种方法成功地对大多数内嗅细胞进行了分类,并揭示了意想不到的内嗅编码原则。首先,我们在内侧内嗅皮层浅层神经元中发现了高度的混合选择性和异质性。其次,我们发现了一种动态且适应性极强的空间编码方式,使内嗅细胞能够在高奔跑速度下快速准确地编码导航信息。综合这些观察结果,我们对当前内嗅编码在导航中的机制起源和功能意义有了进一步的理解。视频摘要。