Effective Dimensionality Reduction for Visualizing Neural Dynamics by Laplacian Eigenmaps.

Journal: Neural computation
Published Date: May 21, 2019

Abstract

With the development of neural recording technology, it has become possible to collect activities from hundreds or even thousands of neurons simultaneously. Visualization of neural population dynamics can help neuroscientists analyze large-scale neural activities efficiently. In this letter, Laplacian eigenmaps is applied to this task for the first time, and the experimental results show that the proposed method significantly outperforms the commonly used methods. This finding was confirmed by the systematic evaluation using nonhuman primate data, which contained the complex dynamics well suited for testing. According to our results, Laplacian eigenmaps is better than the other methods in various ways and can clearly visualize interesting biological phenomena related to neural dynamics.

Authors

  • G Sun
    Qiushi Academy for Advanced Studies, Key Laboratory of Biomedical Engineering of Education Ministry, Zhejiang University, and Department of Biomedical Engineering, Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Zhejiang University, Hangzhou 310027, China sghsgh_007@163.com.
  • S Zhang
    Department of Pathology, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China.
  • Y Zhang
    University Technology Sydney, 15 Broadway, Ultimo, NSW Australia.
  • K Xu
    Qiushi Academy for Advanced Studies, Key Laboratory of Biomedical Engineering of Education Ministry, Zhejiang University, and Department of Biomedical Engineering, Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Zhejiang University, Hangzhou 310027, China xykd@zju.edu.cn.
  • Q Zhang
    Department of Radiology, People's Hospital of Qinghai Province, Xining 810000, China.
  • T Zhao
    Howard Hughes Medical Institute, Janelia Research Campus, Ashburn, VA 20147, U.S.A. zhaot@janelia.hhmi.org.
  • X Zheng
    Qiushi Academy for Advanced Studies, Key Laboratory of Biomedical Engineering of Education Ministry, Zhejiang University, and Department of Biomedical Engineering, Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Zhejiang University, Hangzhou 310027, China shaomin@zju.edu.cn.

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