CogEEGAgent: LLM-Based Autonomous Cognitive EEG Analysis Tool

A recent study presents CogEEGAgent, an autonomous agent designed for cognitive EEG analysis that utilizes large language models (LLMs) to convert questions posed in natural language into analytical options. Built on MNE-Python, this system incorporates a scientific framework that distinguishes semantic interpretation from scientific validation. The LLM discerns user intent and suggests approved analyses, while deterministic elements ensure the validation of typed contracts, manage access to confirmations, and oversee the release of evidence-bound information. In a predefined routing benchmark, CogEEGAgent demonstrates superior accuracy in mapping language to registered analyses compared to a comparable deterministic method. The research paper can be found on arXiv under ID 2607.25045.