什么是 fmri glm analysis guide?
fMRI 通用线性模型规范的领域验证指南:HRF 建模、设计矩阵构造、对比度定义、混杂回归和统计推断 来源:haoxuanlithuai/awesome_cognitive_and_neuroscience_skills。
fMRI 通用线性模型规范的领域验证指南:HRF 建模、设计矩阵构造、对比度定义、混杂回归和统计推断
通过命令行快速安装 fmri glm analysis guide AI 技能到你的开发环境
来源:haoxuanlithuai/awesome_cognitive_and_neuroscience_skills。
The General Linear Model (GLM) is the standard statistical framework for task-based fMRI analysis. It models the observed BOLD time series as a linear combination of expected signal components (task regressors convolved with the hemodynamic response function) plus confound regressors plus noise (Poline & Brett, 2012; Poldrack et al., 2011, Ch. 4).
This skill encodes the domain-specific judgment needed to correctly specify a GLM for fMRI data. A competent programmer without neuroimaging training would get many of these decisions wrong -- choosing the wrong HRF model, setting an inappropriate high-pass filter cutoff, omitting critical confound regressors, or applying invalid statistical thresholds. Each decision described here requires understanding the bioph...
This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please open an issue.
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npx skills add https://github.com/haoxuanlithuai/awesome_cognitive_and_neuroscience_skills --skill fmri glm analysis guideBrowse more skills from haoxuanlithuai/awesome_cognitive_and_neuroscience_skills
fMRI 通用线性模型规范的领域验证指南:HRF 建模、设计矩阵构造、对比度定义、混杂回归和统计推断 来源:haoxuanlithuai/awesome_cognitive_and_neuroscience_skills。
打开你的终端或命令行工具(如 Terminal、iTerm、Windows Terminal 等) 复制并运行以下命令:npx skills add https://github.com/haoxuanlithuai/awesome_cognitive_and_neuroscience_skills --skill fmri glm analysis guide 安装完成后,技能将自动配置到你的 AI 编程环境中,可以在 Claude Code、Cursor 或 OpenClaw 中使用
https://github.com/haoxuanlithuai/awesome_cognitive_and_neuroscience_skills