Neurophysiological Characteristics of Adaptive Reasoning for Creative Problem-Solving Strategy
On the map: LLM reasoning → Reasoning benchmarks and evaluation
Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Reasoning benchmarks and evaluation, one of 17 directions in LLM reasoning. Builds on 8 of its 35 references that are in the map. First posted on arXiv 11 Nov 2025.
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- 2022Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolutioncited by 78
- 2020Deep Reinforcement Learning and its Neuroscientific Implicationscited by 33
- 2024Reasoning Limitations of Multimodal Large Language Models. A Case Study of Bongard Problemscited by 15
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- 2021A brain basis of dynamical intelligence for AI and computational neuroscience
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