缓慢的升级源于神经网络的自发波动
bioRxiv : the preprint server for biology
|July 3, 2023
概括
研究人员发现了一种在自愿运动之前缓慢放缓信号的机制,这表明缓慢的突触如何稳定神经活动. 这一发现在人类大脑记录中得到证实,解释了神经元在开始行动之前如何协调.
科学领域:
- 神经科学是一个神经科学.
- 计算神经科学是一种神经科学.
背景情况:
- 自发的自愿行为对于目标导向的行为至关重要.
- 中部前额皮层在自愿运动之前表现出缓慢动的活动,但其潜在机制尚不清楚.
研究的目的:
- 在自发的自愿运动之前,阐明缓慢放缓信号背后的机制.
- 开发和验证一个解释这些神经动态的计算模型.
主要方法:
- 开发了一个尖的神经网络模型来模拟自发的缓慢升活动.
- 通过从中部额叶皮层的人类单个神经元记录进行验证的模型预测.
- 使用EEG代理信号来重建准备能力.
主要成果:
- 该模型成功地在单个神经元和人口活动中产生了自发的缓慢升活动.
- 证实神经元在拉开始之前一起呈现相关的激发模式.
- 证明缓慢的突触可以稳定神经网络内的自发波动.
结论:
- 缓慢升级信号反映了集群网络中由准获胜者获取全部动态控制的有限自发波动.
- 这些动态的时间稳定是通过缓慢作用的突触实现的.
- 这些发现为自愿运动启动的神经前体提供了机制性的解释.
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