语言,符号和概念的神经生物学机制:来自大脑受约束的深度神经网络的线索
1Brain Language Laboratory, Department of Philosophy and Humanities, WE4, Freie Universität Berlin, 14195 Berlin, Germany; Berlin School of Mind and Brain, Humboldt Universität zu Berlin, 10099 Berlin, Germany; Einstein Center for Neurosciences Berlin, 10117 Berlin, Germany; Cluster of Excellence 'Matters of Activity', Humboldt Universität zu Berlin, 10099 Berlin, Germany.
大脑受约束的神经网络模仿大脑结构来模拟人类的认知. 这种方法为符号处理,记忆和概念获取提供了神经生物学解释.
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.
- 认知科学 认知科学
背景情况:
- 神经网络模拟认知过程,但缺乏神经生物学现实主义.
- 大脑受约束网络整合了大脑结构和功能,跨越多个尺度.
- 了解人类认知需要反映生物约束的模型.
研究的目的:
- 审查用于研究人类认知的大脑受限神经网络的应用.
- 探索符号和概念处理背后的神经生物学机制.
- 开发用于更高认知能力的in silico模型.
主要方法:
- 在微观,中观和宏观层面实现大脑的相似性.
- 模拟神经元功能,局部连接和大规模的解剖结构.
- 分析神经元组合活动的机械相关性.
主要成果:
- 脑受限网络可以模拟语言工作记忆和词汇学习.
- 这些模型通过符号阐明了语义绑定和注意力调制.
- 这种方法有助于理解由符号表示影响的概念获取.
结论:
- 大脑受约束网络为神经生物学基础的认知建模提供了一个框架.
- 它们提供了基于神经原理的人类特定认知能力的候选解释.
- 这种方法在 silico 研究中向了解认知的生物基础的方向迈进.
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