认知科学
人类智力
类比
认知
过程(计算)
心理学
认知心理学
计算机科学
跳跃
透视图(图形)
人工智能
神经科学
认识论
哲学
金融经济学
经济
操作系统
标识
DOI:10.1523/jneurosci.1555-24.2025
摘要
What is the secret of human intelligence? A key discovery in psychology is that performance correlations across diverse cognitive tasks are explained by a few broad abilities and one overarching general factor, which is also predictive of real-life achievements. Whether these factors correspond to biological processes is a century-old debate. While previous research focused on localizing their correlates in brain structure, connectivity, and activation levels, the mechanisms of neural information processing related to intelligence are still unexplored. I outline a new approach integrating psychometrics with neuroscientific advances in identifying the computations underlying single tasks from their representational geometry to provide a novel perspective on this topic. In particular, I propose a neural process account of the general factor that builds on the central role of structure mapping-the process of abstracting and reasoning based on relational knowledge-in human cognition. Neural coding properties in the hippocampal and prefrontal-parietal systems that enable inferential leaps through structural abstraction might contribute to the general factor. In general, integrating neuro-representational and psychometric research has the potential to uncover core principles of natural intelligence.
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