LLM自动化标注情绪轨迹fMRI解码方法论。使用多目标回归框架、动态功能连接(DFC)、图论可解释AI解码连续情绪维度。
Scanned 9/11/2026
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---
name: llm-emotion-trajectory-fmri
description: LLM自动化标注情绪轨迹fMRI解码方法论。使用多目标回归框架、动态功能连接(DFC)、图论可解释AI解码连续情绪维度。
platforms: [linux, macos, windows]
tags: [emotion, llm-annotation, dfc, fmri-decoding, regression, xai]
---
# LLM Emotion Trajectory fMRI Decoding
## 论文信息
**标题**: Decoding Naturalistic Emotion Dynamics from the Brain: An LLM-Enhanced Regression Framework
**arXiv**: 2606.07707v1
**作者**: Lemei Zhang, Peng Liu等
**发布**: 2026-06-05
## 核心创新
1. **连续轨迹追踪**: 多目标回归替代离散分类
2. **LLM标注**: 从Alice in Wonderland提取情感profile
3. **DFC优于ROI**: 动态功能连接捕获连续情绪
4. **图论XAI**: 情绪特异性拓扑配置
## 技术要点
### 多目标回归
- 追踪重叠情绪维度
- 正则化+核方法
- 连续神经状态估计
### DFC特征
- 时间快照提取
- 窗口大小30秒
- 捕获快速波动叙事
### 可解释性
- 网络拓扑特征
- 情绪特异性配置
- 支持心理构建主义
## Activation
关键词: llm-emotion, dfc-fmri, sentiment-trajectory, naturalistic-decoding, graph-xai, regression-frameworkIs this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
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