以色列魏茨曼科学研究所Nachum Ulanovsky团队取得一项新突破。他们的研究揭示了蝙蝠飞行过程中海马体对大环境的多尺度表征。相关论文于2021年5月28日发表在《科学》杂志上。

研究人员以无线方式记录了在长隧道（200米）飞行过程中野生蝙蝠海马背侧的CA1神经元。飞行场所的范围大小为0.6到32米。单个位置细胞显示多广度和多尺度表征：同一神经元的位置大小差异高达20倍。从暴露于大环境的第一天开始，在实验室出生未接触大环境的蝙蝠中就能观察到这种多尺度编码。理论解码分析表明，多尺度编码以高精度表征了非常大的环境，其表示方式要比其他代码高很多。总之，通过增加空间比例，研究人员发现了一个与编码经典场所完全不同的神经编码机制。

据悉，个体海马内的位置细胞编码其位置。一般在很小的环境范围内研究位置细胞的功能，而在与人类学相关的大型空间内，人们对位置细胞的功能一无所知。

附：英文原文

Title: Multiscale representation of very large environments in the hippocampus of flying bats

Author: Tamir Eliav, Shir R. Maimon, Johnatan Aljadeff, Misha Tsodyks, Gily Ginosar, Liora Las, Nachum Ulanovsky

Issue&Volume: 2021/05/28

Abstract: Hippocampal place cells encode the animal’s location. Place cells were traditionally studied in small environments, and nothing is known about large ethologically relevant spatial scales. We wirelessly recorded from hippocampal dorsal CA1 neurons of wild-born bats flying in a long tunnel (200 meters). The size of place fields ranged from 0.6 to 32 meters. Individual place cells exhibited multiple fields and a multiscale representation: Place fields of the same neuron differed up to 20-fold in size. This multiscale coding was observed from the first day of exposure to the environment, and also in laboratory-born bats that never experienced large environments. Theoretical decoding analysis showed that the multiscale code allows representation of very large environments with much higher precision than that of other codes. Together, by increasing the spatial scale, we discovered a neural code that is radically different from classical place codes.

DOI: 10.1126/science.abg4020

Source: https://science.sciencemag.org/content/372/6545/eabg4020