Evolving Structure-Function Mappings in Cognitive Neuroscience Using Genetic Programming
Evolving Structure-Function Mappings in Cognitive Neuroscience Using Genetic Programming
复制标题
使用遗传编程进化认知神经科学中的结构功能映射
DOI：
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复制
发表时间：
2005
期刊：
影响因子：
--
通讯作者：
A. Parker
中科院分区：
文献类型：
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作者：
F. Gobet;A. Parker
心理学和神经科学的一个具有挑战性的目标是将认知功能映射到神经解剖结构上。本文展示了基于进化算法的计算方法如何通过有效地将神经解剖学和生理学（结构）的约束与行为实验（功能）的约束相结合来促进令人满意的映射的搜索。该方法涉及为已知的神经解剖学和生理学限制、由原始认知功能组成的心理程序以及其行为结果的典型实验创建数据库编码。进化算法进化了将结构映射到函数的理论，以优化与实际数据的拟合。这些理论带来了新的、可通过经验检验的预测。以人类前额皮质的作用为例进行讨论。该方法可以单独应用于结构或功能的研究，也可以用于研究其他复杂系统。
A challenging goal of psychology and neuroscience is to map cognitive functions onto neuroanatomical structures. This paper shows how computational methods based upon evolutionary algorithms can facilitate the search for satisfactory mappings by efficiently combining constraints from neuroanatomy and physiology (the structures) with constraints from behavioural experiments (the functions). This methodology involves creation of a database coding for known neuroanatomical and physiological constraints, for mental programs made of primitive cognitive functions, and for typical experiments with their behavioural results. The evolutionary algorithms evolve theories mapping structures to functions in order to optimize the fit with the actual data. These theories lead to new, empirically testable predictions. The role of the prefrontal cortex in humans is discussed as an example. This methodology can be applied to the study of structures or functions alone, and can also be used to study other complex systems.
DOI：
10.1098/rstb.1996.0138
发表时间：
1996-10-29
影响因子：
6.3
作者：
Cohen, JD;Braver, TS;OReilly, RC
通讯作者：
OReilly, RC