通过积极的振动传感,无监督发现和预测蜘蛛猎物捕获的传感运动转换
bioRxiv : the preprint server for biology
|June 12, 2025
概括
蜘蛛使用网络振动来狩猎,根据猎物调整移动.
科学领域:
- 神经科学是一个神经科学.
- 动物行为 动物行为
- 生物声学是一种生物声学.
背景情况:
- 感官运动转换是动物与动态环境互动的关键.
- 了解振动感应中的这些变化至关重要,但有限.
- 对许多无脊椎动物来说,基板传递的振动传感是至关重要的.
研究的目的:
- 用振动传感来剖析蜘蛛捕捉猎物的感觉运动基础.
- 为了识别蜘蛛狩猎序列的行为状态和预测模型.
- 在非视觉系统中探索主动传感和闭环控制.
主要方法:
- 高分辨率的网络振动记录和细度的行为跟踪在Uloborus diversus蜘蛛.
- 无监督建模用于识别捕获序列中的离散行为状态.
- 一个预测框架,结合了通用线性模型 (GLM) 和隐藏的马尔科夫模型 (HMM).
主要成果:
- 识别了结构化蜘蛛捕获序列的离散行为状态,准确度>83%.
- 开发了一个GLM-HMM框架,以基于猎物振动来预测行为转变.
- 观察到与振动功率变化相关的取决于环境的动力过渡 (例如,摇).
- 蜘蛛准确地转向具有最高振动幅度的网半径,以定位猎物.
结论:
- 揭示了一个结构化,预测性的感官运动转换,将振动线索与蜘蛛的行为状态联系起来.
- 经过证明的蜘蛛使用积极的感知行为来增强信号检测.
- 突出了非视觉无脊椎动物系统中闭环控制的一般原则.
- 提供了对物种间传感运动集成的见解.
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