竞争性相互作用塑造了物种间的大脑动态和计算
Andrea I Luppi1,2,3, Yonatan Sanz Perl4, Jakub Vohryzek4
1University of Oxford, Oxford, UK.
bioRxiv : the preprint server for biology
|November 1, 2024
概括
大脑平衡合作和竞争,使用模块化,局部连接和分散的,远程连接. 这种网络架构增强了大脑活动,信息处理和计算能力.
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.
- 网络科学 网络科学
背景情况:
- 适应性认知需要分布式大脑电路之间的合作.
- 神经系统为了有限的处理资源而竞争,这对大脑功能构成了挑战.
研究的目的:
- 为了研究大脑的网络架构如何平衡合作和竞争互动.
- 检查哺乳动物连接组中这些相互作用的动态和计算相关性.
主要方法:
- 在人类,和老鼠连接组中利用了计算全脑建模.
- 开发了结合合作和竞争互动的模型来模拟大脑活动.
主要成果:
- 准确复制大脑活动的模型始终结合了模块化的合作相互作用与分散的,远程的竞争性相互作用.
- 具有竞争互动的模型在适应大脑空间和动态特性方面明显优于仅合作的模型.
- 竞争互动增强了协同信息,局部-全球层次结构和计算能力.
结论:
- 建立了哺乳动物大脑网络架构,动态特性和计算能力之间的机械联系.
- 证明合作与竞争的平衡对于高效的大脑功能和计算至关重要.
- 突出了扩散,长距离的竞争互动对于卓越的大脑性能的重要性.
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