4 papers
Brain2Text Decoding Model Reveals the Neural Mechanisms of Visual Semantic Processing
Feihan Feng, Jingxin Nie
Decoding sensory experiences from neural activity to reconstruct human-perceived visual stimuli and semantic content remains a challenge in neuroscience and artificial intelligence…
From Flat to Round: Redefining Brain Decoding with Surface-Based fMRI and Cortex Structure
Sijin Yu, Zijiao Chen, Wenxuan Wu +6
Reconstructing visual stimuli from human brain activity (e.g., fMRI) bridges neuroscience and computer vision by decoding neural representations. However, existing methods often ov…
Psychological Counseling Ability of Large Language Models
Fangyu Peng, Jingxin Nie
With the development of science and the continuous progress of artificial intelligence technology, Large Language Models (LLMs) have begun to be widely utilized across various fiel…
Talking to the brain: Using Large Language Models as Proxies to Model Brain Semantic Representation
Xin Liu, Ziyue Zhang, Jingxin Nie
Traditional psychological experiments utilizing naturalistic stimuli face challenges in manual annotation and ecological validity. To address this, we introduce a novel paradigm le…