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npx versuz@latest install hiyenwong-ai-collection-collection-skills-bci-core-periphery-reorganizationgit clone https://github.com/hiyenwong/ai_collection.gitcp ai_collection/SKILL.MD ~/.claude/skills/hiyenwong-ai-collection-collection-skills-bci-core-periphery-reorganization/SKILL.md--- name: bci-learning-core-periphery-reorganization description: **来源论文:** arXiv:2010.13459 - BCI learning induces core-periphery reorganization in M/EEG multiplex brain networks --- # BCI Learning Core-Periphery Reorganization **来源论文:** arXiv:2010.13459 - BCI learning induces core-periphery reorganization in M/EEG multiplex brain networks **效用评分:** 0.98 **创建时间:** 2026-03-24 17:03 **期刊:** Journal of Neural Engineering ## 概述 研究 BCI 训练过程中脑网络的核心-边缘重组,采用多层网络方法整合 EEG 和 MEG 数据,发现体感区域整合增加与视觉处理区域整合减少的动态变化。 ## 激活关键词 - BCI learning - core-periphery organization - multiplex brain network - MEG EEG integration - brain network reorganization - BCI 训练 - 核心-边缘网络 ## 核心发现 ``` BCI 训练引起的脑网络重组: Alpha 波段: ┌─────────────────────────────────────────┐ │ 体感区域 → 整合度增加 ↑ │ │ 视觉区域 → 整合度减少 ↓ │ └─────────────────────────────────────────┘ Beta 波段: ┌─────────────────────────────────────────┐ │ 工作记忆区域 → 整合度减少 ↓ │ └─────────────────────────────────────────┘ 预测指标: - Alpha2 波段多层网络属性与未来 BCI 分数相关 - 体感/决策区域正相关 - 联合区域负相关 ``` ## 应用场景 - BCI 学习预测 - 训练效果评估 - 多模态脑网络分析 - 核心-边缘动态监测 ## 相关技能 - `core-periphery-state-space` - `eeg-brain-connectivity-bci` - `multimodal-brain-connectivity-gnn` --- _此技能用于理解 BCI 学习过程中的脑网络重组机制_ ## Description BCI Learning Core-Periphery Reorganization ## Activation Keywords - bci-core-periphery-reorganization - bci-core-periphery-reorganization 技能 - bci-core-periphery-reorganization skill ## Tools Used - `read` - Read documentation and references - `web_search` - Search for related information - `web_fetch` - Fetch paper or documentation ## Instructions for Agents Follow these steps when applying this skill: ### Step 1: Understand the Request ### Step 2: Search for Information ### Step 3: Apply the Framework ### Step 4: Provide Results ### Step 5: Verify Accuracy ## Examples ### Example 1: Basic Application **User:** I need to apply BCI Learning Core-Periphery Reorganization to my analysis. **Agent:** I'll help you apply bci-core-periphery-reorganization. First, let me understand your specific use case... **Context:** Apply the methodology ### Example 2: Advanced Scenario **User:** Complex analysis scenario **Agent:** Based on the methodology, I'll guide you through the advanced application... ### Example 2: Advanced Application **User:** What are the key considerations for bci-core-periphery-reorganization? **Agent:** Let me search for the latest research and best practices...