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一种用于内嗅网格模块自组织的几何吸引子机制。

A geometric attractor mechanism for self-organization of entorhinal grid modules.

机构信息

David Rittenhouse Laboratories, University of Pennsylvania, Philadelphia, United States.

Redwood Center for Theoretical Neuroscience, University of California, Berkeley, Berkeley, United States.

出版信息

Elife. 2019 Aug 2;8:e46687. doi: 10.7554/eLife.46687.

Abstract

Grid cells in the medial entorhinal cortex (MEC) respond when an animal occupies a periodic lattice of 'grid fields' in the environment. The grids are organized in modules with spatial periods, or scales, clustered around discrete values separated on average by ratios in the range 1.4-1.7. We propose a mechanism that produces this modular structure through dynamical self-organization in the MEC. In attractor network models of grid formation, the grid scale of a single module is set by the distance of recurrent inhibition between neurons. We show that the MEC forms a hierarchy of discrete modules if a smooth increase in inhibition distance along its dorso-ventral axis is accompanied by excitatory interactions along this axis. Moreover, constant scale ratios between successive modules arise through geometric relationships between triangular grids and have values that fall within the observed range. We discuss how interactions required by our model might be tested experimentally.

摘要

网格细胞在中脑内侧缰核(MEC)中响应,当动物占据环境中的周期性“网格场”时。这些网格以具有空间周期或尺度的模块组织,围绕离散值聚类,平均间隔比在 1.4-1.7 范围内。我们提出了一种通过 MEC 中的动力学自组织产生这种模块化结构的机制。在网格形成的吸引器网络模型中,单个模块的网格尺度由神经元之间的递归抑制距离决定。我们表明,如果在其背腹轴上抑制距离的平滑增加伴随着沿该轴的兴奋性相互作用,则 MEC 会形成离散模块的层次结构。此外,通过三角形网格之间的几何关系产生连续模块之间的恒定比例,并且值落在观察到的范围内。我们讨论了我们的模型所需的相互作用如何通过实验进行测试。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1dc5/6776444/5fda1098dc7e/elife-46687-fig1.jpg

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