传感运动适应机制在语音的层次状态反控制模型中的传感运动适应机制
Kwang S Kim1, Jessica L Gaines2, Benjamin Parrell3
1Department of Speech, Language, and Hearing Sciences, Purdue University, West Lafayette, Indiana, United States of America.
PLoS computational biology
|July 28, 2023
概括
感官运动适应使用预测错误来调整运动. 事实模型显示,这些错误通过更新任务级控制来推动适应,而不仅仅是预测模型,增强语音运动学习.
科学领域:
- 发动机控制器 发动机控制器
- 听觉机器适应的调整
- 语音运动学习的方法
背景情况:
- 感官运动适应可以弥补运动错误.
- 感官预测错误被认为是驱动适应的.
- 将预测错误与适应联系在一起的机制尚不清楚.
研究的目的:
- 检查语音运动适应中的听觉预测错误机制.
- 使用FACTS模型调查预测错误在感觉运动适应中的作用.
- 澄清预测错误如何更新控制机制.
主要方法:
- 使用了反意识控制语音任务 (FACTS) 模型.
- 采用了具有任务级别和表达状态表示的等级架构.
- 通过更新控制机制以传感预测错误来模拟适应.
主要成果:
- 适应性行为仅发生在预测错误更新了表达到任务状态转换时.
- 仅更新前感官预测模型并没有诱导适应.
- 事实证明预测错误通过任务级更新驱动调整.
结论:
- 语音运动适应是由任务级控制的更新驱动的,而不仅仅是前预测模型.
- 该FACTS模型提供了一个层次状态反控制在传感运动适应的框架.
- 该模型为不完整的适应和形成频率变化等现象生成假设.
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