RESEARCH ARTICLE


Alternating Periods of High and Low-Entropy Neural Ensemble Activity During Image Processing in the Primary Visual Cortex of Rats



Xiaoyuan Li1, Qiwei Li1, Li Shi1, 2, *, Liucheng Jiao1, *
1 School of Electrical Engineering of Zhengzhou University, Zhengzhou 450001, China
2 Department of Automation, Tsinghua University, Beijing, 100000, China


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Creative Commons License
© Li et al.; Licensee Bentham Open.

open-access license: This is an open access article licensed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 International Public License (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/legalcode), which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.

* Address correspondence to these authors at the School of Electrical Engineering of Zhengzhou University, Zhengzhou 450001, China; Email: 1066228536@qq.com


Abstract

The response properties of individual neurons in the primary visual cortex (V1) are among the most thoroughly described in the mammalian central nervous system, but they reveal less about higher-order processes like visual perception. Neural activity is highly nonlinear and non-stationary over time, greatly complicating the relationships among the spatiotemporal characteristics of visual stimuli, local field potential (LFP) signal components, and the underlying neuronal activity patterns. We applied discrete wavelet transformation to detect new features of the LFP that may better describe the association between visual input and neural ensemble activity. The relative wavelet energy (RWE), wavelet entropy (WS), and the mean WS were computed from LFPs recorded in rat V1 during three distinct visual stimuli: low ambient light, a uniform grey computer screen, and simple pictures of common scenes. The time evolution of the RWE within the γ band (31-62.5 Hz) was the dominant component over certain periods during visual stimulation. Mean WS decreased with increasing complexity of the visual image, and the time-dependent WS alternated between periods of highly ordered and disordered population activity. In conclusion, these alternating periods of high and low WS may correspond to different aspects of visual processing, such as feature extraction and perception.

Keywords: Local Field Potential (LFP), time-frequency signal analysis, wavelet transform, wavelet energy, wavelet entropy.