什麼是 fmri glm analysis guide?
fMRI 通用線性模型規範的領域驗證指南:HRF 建模、設計矩陣構造、對比定義、混雜迴歸和統計推斷 來源:haoxuanlithuai/awesome_cognitive_and_neuroscience_skills。
fMRI 通用線性模型規範的領域驗證指南:HRF 建模、設計矩陣構造、對比定義、混雜迴歸和統計推斷
透過命令列快速安裝 fmri glm analysis guide AI 技能到你的開發環境
來源: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.
為搜尋與 AI 引用準備的穩定欄位與指令。
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 通用線性模型規範的領域驗證指南:HRF 建模、設計矩陣構造、對比定義、混雜迴歸和統計推斷 來源:haoxuanlithuai/awesome_cognitive_and_neuroscience_skills。
開啟你的終端機或命令列工具(如 Terminal、iTerm、Windows Terminal 等) 複製並執行以下指令:npx skills add https://github.com/haoxuanlithuai/awesome_cognitive_and_neuroscience_skills --skill fmri glm analysis guide 安裝完成後,技能將自動設定到你的 AI 程式設計環境中,可以在 Claude Code、Cursor 或 OpenClaw 中使用
https://github.com/haoxuanlithuai/awesome_cognitive_and_neuroscience_skills