Neurophysiological Characteristics of Adaptive Reasoning for Creative Problem-Solving Strategy
This research addresses the problem of understanding the neural basis of human adaptive reasoning for cognitive science and AI, but it is incremental as it builds on existing paradigms and comparisons with AI models.
The study investigated the neurophysiological mechanisms of adaptive reasoning in humans using EEG and a card-sorting paradigm, revealing coordinated delta-theta-alpha dynamics linked to rule inference and attention stabilization, while a multimodal large language model showed only short-term adjustments without genuine adaptive reasoning.
Adaptive reasoning enables humans to flexibly adjust inference strategies when environmental rules or contexts change, yet its underlying neural dynamics remain unclear. This study investigated the neurophysiological mechanisms of adaptive reasoning using a card-sorting paradigm combined with electroencephalography and compared human performance with that of a multimodal large language model. Stimulus- and feedback-locked analyses revealed coordinated delta-theta-alpha dynamics: early delta-theta activity reflected exploratory monitoring and rule inference, whereas occipital alpha engagement indicated confirmatory stabilization of attention after successful rule identification. In contrast, the multimodal large language model exhibited only short-term feedback-driven adjustments without hierarchical rule abstraction or genuine adaptive reasoning. These findings identify the neural signatures of human adaptive reasoning and highlight the need for brain-inspired artificial intelligence that incorporates oscillatory feedback coordination for true context-sensitive adaptation.