在漂移和重定位过程中,头向神经元的群体动态
Zaki Ajabi1,2,3, Alexandra T Keinath4, Xue-Xin Wei5,6,7,8
1Department of Psychiatry, Douglas Hospital Research Centre, McGill University, Verdun, Quebec, Canada. zaki_ajabi@hms.harvard.edu.
Nature
|March 23, 2023
概括
大脑的内部指南针或头部方向 (HD) 系统使用第二维网络增益来定位和记忆. 这挑战了一维模型并揭示了经验依赖的重新校准.
科学领域:
- 神经科学
- 计算神经科学
- 系统神经科学
背景情况:
- 头部方向 (HD) 系统作为大脑的内部指南针,通常以一维网络为模型.
- 这种系统依赖于本地线索作为参考, 与全球磁性指南针不同.
- 在HD系统中提示定和漂移的机制需要在种群层面进行调查.
研究的目的:
- 为了研究甲状腺疾病细胞的群体水平活动.
- 探索活动的第二个维度,称为网络增益,在HD系统功能中的作用.
- 了解HD系统如何与环境线索结合并漂移.
主要方法:
- 通过成像测试,记录了体的HD细胞.
- 在实验中控制视觉地标的旋转.
- 分析群体活动变化,包括网络增益,在暗中和暗中操作.
主要成果:
- 在第二个维度 (网络增益) 上,特别是在提示冲突期间,HD细胞群活动有所变化.
- 网络增益预测的调整和漂移动态,包括调整速度.
- 网络增强保持了以前在黑暗中查看的地标的记忆痕迹.
- HD系统表现出经验依赖的重新校准,在连续地标旋转后持续的表示转移.
结论:
- 高频系统的活动不是严格单维的,网络增益起着至关重要的作用.
- 网络增强方便对环境线索进行定,并表现出内存特性.
- HD系统可以经过经验依赖的重新校准,挑战经典模型.
- 提出了一个计算模型来解释神经指南针灵活适应不断变化的线索.
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