A Cognitive Process-Inspired Architecture for Subject-Agnostic Brain Visual Decoding

📝 Original Info

• Title: A Cognitive Process-Inspired Architecture for Subject-Agnostic Brain Visual Decoding
• ArXiv ID: 2511.02565
• Date: 2025-11-04
• Authors: ** (논문에 명시된 저자 정보가 제공되지 않아 현재 알 수 없음. 논문 원문에서 확인 필요) **

📝 Abstract

Subject-agnostic brain decoding, which aims to reconstruct continuous visual experiences from fMRI without subject-specific training, holds great potential for clinical applications. However, this direction remains underexplored due to challenges in cross-subject generalization and the complex nature of brain signals. In this work, we propose Visual Cortex Flow Architecture (VCFlow), a novel hierarchical decoding framework that explicitly models the ventral-dorsal architecture of the human visual system to learn multi-dimensional representations. By disentangling and leveraging features from early visual cortex, ventral, and dorsal streams, VCFlow captures diverse and complementary cognitive information essential for visual reconstruction. Furthermore, we introduce a feature-level contrastive learning strategy to enhance the extraction of subject-invariant semantic representations, thereby enhancing subject-agnostic applicability to previously unseen subjects. Unlike conventional pipelines that need more than 12 hours of per-subject data and heavy computation, VCFlow sacrifices only 7\% accuracy on average yet generates each reconstructed video in 10 seconds without any retraining, offering a fast and clinically scalable solution. The source code will be released upon acceptance of the paper.

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