在自然主义电影中的大脑-人工智能对齐
Muwei Li1,2
1Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA.
bioRxiv : the preprint server for biology
|December 19, 2025
概括
像双子座这样的大型语言模型可以从语义上说明电影剪辑,将人工智能 (AI) 功能与大脑活动联系起来. 这种AI-大脑对齐预测神经反应和认知能力,为理解认知提供了一个新的框架.
科学领域:
- 认知神经科学 认知神经科学
- 人工智能的人工智能
- 神经成像是一种神经成像.
背景情况:
- 自然主义的刺激,如电影,为人类认知提供了丰富的见解.
- 将复杂的电影内容与大脑活动 (fMRI) 和认知表现联系起来仍然具有挑战性.
- 解释分布式大脑对动态刺激的反应需要先进的分析工具.
研究的目的:
- 使用多式大型语言模型 (LLM) 作为自动语义注释器.
- 为了弥合自然主义的电影刺激,大脑活动和认知表现.
- 在自然环境中量化大脑-人工智能对齐.
主要方法:
- 细分电影片段,并促使LLM (双子座) 在11个心理维度上对它们进行评分.
- 从fMRI数据中提取了BOLD (血液氧气水平依赖) 的剪贴智能激活模式.
- 适应线性回归模型以使用LLM衍生的语义特征预测大脑反应.
主要成果:
- 从LLM衍生出来的特征在关联皮层 (时间,,额叶) 中强有力的预测大脑活动.
- 预测能力在单模传感和岛屿区域较低.
- 大脑-人工智能对齐与静止状态连接性相关,并预测了认知能力 (流体和结晶).
结论:
- 基础模型提供了一个可扩展的框架来量化大脑-AI对齐.
- 从LLM中快速定义,可解释的特征可以跨越生物和人工语义表示.
- 这种方法为分析大脑对自然刺激的反应提供了一种实用方法.
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