在平衡的皮层 E-I 网络中,接近混乱边缘的最大内存容量
Takashi Kanamaru1,2, Takao K Hensch1,3,4, Kazuyuki Aihara5
1International Research Center for Neurointelligence (WPI-IRCN), UTIAS, University of Tokyo 113-0033, Japan.
Neural computation
|July 11, 2023
概括
神经网络中的最佳激发和抑制 (E-I) 平衡在发展关键时期最大限度地提高了短期记忆能力,突出了这种平衡的关键作用和脆弱性.
科学领域:
- 计算神经科学是一种计算神经科学.
- 发育神经生物学的发展神经生物学
- 网络动态 网络动态
背景情况:
- 大脑发育涉及高度可塑性的关键时期.
- 激发性和抑制性 (E-I) 神经活动之间的平衡对于网络功能至关重要.
- 了解这些时期的信息处理效率是关键.
研究的目的:
- 在发展关键时期调查平衡的EI网络中的信息处理效率.
- 确定E-I活动平衡如何影响网络动态和内存容量.
- 为了确定信息处理的最佳E-I平衡.
主要方法:
- 定义了一个E-I神经元的多模块网络.
- 通过调节E-I活动平衡来检查网络动态.
- 观察到的网络状态包括过渡性混乱同步和常规混乱.
- 在储库计算中使用短期记忆任务来量化信息处理效率.
主要成果:
- 网络动态表现出不同程度的混乱 (高维和常规) 基于E-I平衡.
- 在最佳的E-I平衡下,记忆容量得到最大化.
- 这种最佳平衡强调了在开发过程中E-I动态的关键作用和脆弱性.
结论:
- 在开发神经网络时,EI平衡是有效处理信息的关键因素.
- 偏离最佳的E-I平衡可能会在关键发育时期损害记忆能力.
- 这些发现对理解大脑发育和潜在的干扰有影响.
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