视觉和触觉路径集成及其与任务相关的调制的神经相关物
Lisa Rosenblum1,2, Alexander Kreß3,4, B Ezgi Arikan4,5
1Department Neurophysics, Philipps-Universität Marburg, Karl-Von-Frisch-Straße 8a, 35043, Marburg, Germany. rosenblu@staff.uni-marburg.de.
Scientific reports
|June 19, 2023
概括
这项研究探讨了大脑如何处理自我运动,如视觉和触觉线索,以及任务需求如何影响这一点. 研究结果显示了主动与被动自动运动的独特大脑活动模式,突出显示下侧顶叶片.
科学领域:
- 神经科学是一个神经科学.
- 认知科学 认知科学
- 感官处理 感官处理
背景情况:
- 准确的自我运动感知 (路径集成) 需要区分自我生成与外部感官信号.
- 预测编码可能会减轻自动运动反应,但任务相关性可以改变这种效应.
- 了解预测和任务需求如何调节跨感官的自我运动处理至关重要.
研究的目的:
- 研究视觉和触觉自动运动处理的神经机制.
- 检查任务需求如何调节不同感官模式的自我运动感知.
- 探索预测编码和任务相关性在自我运动感知中的作用.
主要方法:
- 功能性磁共振成像 (fMRI) 用于研究视觉和触觉自动运动任务期间的大脑活动.
- 视觉刺激模拟了前进的自我运动;触觉刺激使用了在额头上的空气流.
- 任务要么复制一个被动的移位 (高需求),要么旅行一个自我选择的距离 (低需求).
主要成果:
- 积极的自动运动试验 (与被动相比) 在两种模式中都显示了早期视觉区域的增强活动和下叶 (IPL) 的抑制.
- 对高和低要求的活跃试验进行比较时,发现前面的胰岛的超模态增强.
- IPL抑制表明它在将感官自动运动信号与预测进行比较方面的作用.
结论:
- 大脑不同处理主动与被动自动运动,视觉皮层和皮层中具有不同的神经特征.
- 任务要求显著调节自动运动处理,涉及诸如前面岛屿之类的超模态区域.
- 下叶似乎对于将传入的自我运动感官数据与内部预测进行比较至关重要.
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