人类大脑的计算能力
1Institute of Psychopharmacology, Central Institute of Mental Health, Faculty of Medicine, University of Heidelberg, Mannheim, Germany.
Frontiers in cellular neuroscience
|August 23, 2023
概括
大脑利用模拟和数字过程进行计算,挑战纯数字图灵机模型. 这种复杂的相互作用,涉及神经元,星细胞和表观遗传因素,是记忆和高级认知功能的基础.
科学领域:
- 计算神经科学是一种神经科学.
- 神经生物学 神经生物学 神经生物学
- 人工智能的人工智能
背景情况:
- 20世纪的数字系统在很大程度上取代了在计算中的模拟系统,因为它们具有更高的功率.
- 大脑的计算性质,无论是模拟还是数字,仍然是一个关键问题,最初的理论倾向于类似于图灵机的数字模型.
- 最近的AI进步整合了数字和模拟过程,促使人们重新评估生物计算.
研究的目的:
- 将计算的数学模型与大脑计算的生物现实进行比较.
- 突出中央神经系统中数字和模拟过程的存在和意义.
- 区分人工 (in silico) 和生物系统之间的计算原理.
主要方法:
- 在中枢神经系统内的细胞和分子相互作用中识别和分析数字和模拟过程.
- 检查神经元和星球细胞中用于模拟信息处理的电突突触和间隙连接.
- 分析神经元动作潜力 (尖峰),突触传输 (包括三方突触) 和突触可塑性 (LTP/LTD) 的计算特征.
- 包括记忆存储机制 (例如,振荡,恩格拉姆,天体细胞同位素) 和表观遗传影响.
主要成果:
- 模拟处理发生在电突触和间隙连接处,而神经元动作潜力 (尖峰) 代表数字事件.
- 幅度和宽度的尖峰变化影响发射器释放,突触传输由星体细胞 (三方突触) 调节.
- 记忆形成涉及突触可塑性 (LTP/LTD),表观遗传因素,基因转录/翻译以及各种存储机制.
结论:
- 大脑计算不仅仅是模拟或数字,而是两者的复杂组合,并行运行.
- 生物计算表现出比当前的人工系统更高的复杂度.
- 了解大脑计算需要考虑分子,细胞和网络层面的复杂相互作用.
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