Defining rhythmic locomotor burst patterns using a continuous wavelet transform
Defining rhythmic locomotor burst patterns using a continuous wavelet transform
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DOI：
10.1111/j.1749-6632.2010.05437.x
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发表时间：
2010-01-01
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影响因子：
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通讯作者：
Alaynick, William A.
中科院分区：
文献类型：
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作者：
Gallarda, Benjamin W.;Sharpee, Tatyana O.;Alaynick, William A.
我们回顾了一种客观和自动化的方法来分析运动电生理数据，提高了速度和准确性。通过小鼠遗传学操纵中枢模式发生器（CPG）组织是该电路研究的重要进展。更好的运动数据定量测量将进一步增强我们对CPG发育和功能的理解。目前的分析方法旨在测量运动周期、节律性、左右屈伸肌相；然而，这些方法尚未被优化以检测或量化运动输出的细微变化。由于多个实验表明，CPG的发展是稳健的，并且该回路能够通过几种方式实现有组织的行为，因此我们试图找到一种更客观、更敏感的方法来量化运动输出。近年来，连续小波变换（CWT）被应用于脊髓前根记录，取得了良好的效果。CWT提供了更高的周期、相位和节律分辨率，并且被证明是评估由于潜在电路的遗传扰动而引起的运动细微变化的优越技术。
We review an objective and automated method for analyzing locomotor electrophysiology data with improved speed and accuracy. Manipulating central pattern generator (CPG) organization via mouse genetics has been a critical advance in the study of this circuit. Better quantitative measures of the locomotor data will further enhance our understanding of CPG development and function. Current analysis methods aim to measure locomotor cycle period, rhythmicity, and left right and flexor extensor phase; however, these methods have not been optimized to detect or quantify subtle changes in locomotor output. Because multiple experiments suggest that development of the CPG is robust and that the circuit is able to achieve organized behavior by several means, we sought to find a more objective and sensitive method for quantifying locomotor output. Recently, a continuous wavelet transform (CWT) has been applied to spinal cord ventral root recordings with promising results. The CWT provides greater resolution of cycle period, phase, and rhythmicity, and is proving to be a superior technique in assessing subtle changes in locomotion due to genetic perturbations of the underlying circuitry.