{"id":28423884,"url":"https://github.com/bbuchsbaum/fmridenoise","last_synced_at":"2025-08-22T05:38:30.305Z","repository":{"id":293761966,"uuid":"985049995","full_name":"bbuchsbaum/fmridenoise","owner":"bbuchsbaum","description":"denoising workflow for fmri data","archived":false,"fork":false,"pushed_at":"2025-06-22T15:30:20.000Z","size":1830,"stargazers_count":0,"open_issues_count":6,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-06-22T16:33:39.755Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/bbuchsbaum.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-05-17T01:17:05.000Z","updated_at":"2025-06-22T15:30:24.000Z","dependencies_parsed_at":"2025-06-22T16:36:09.132Z","dependency_job_id":null,"html_url":"https://github.com/bbuchsbaum/fmridenoise","commit_stats":null,"previous_names":["bbuchsbaum/fmridenoise"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/bbuchsbaum/fmridenoise","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bbuchsbaum%2Ffmridenoise","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bbuchsbaum%2Ffmridenoise/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bbuchsbaum%2Ffmridenoise/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bbuchsbaum%2Ffmridenoise/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/bbuchsbaum","download_url":"https://codeload.github.com/bbuchsbaum/fmridenoise/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bbuchsbaum%2Ffmridenoise/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":271592467,"owners_count":24786594,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-08-22T02:00:08.480Z","response_time":65,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2025-06-05T09:09:42.551Z","updated_at":"2025-08-22T05:38:30.280Z","avatar_url":"https://github.com/bbuchsbaum.png","language":"R","readme":"# ND-X: Next-Generation fMRI Denoising\n\nND-X implements an iterative denoising workflow for single-subject fMRI data. The package integrates robust PCA, spectral analysis, AR(2) pre-whitening and ridge regression to automatically identify nuisance components and refine task estimates. It aims to surpass existing methods such as GLMdenoise by combining multiple data-adaptive steps.\n\n## Key Functions\n\n- `NDX_Process_Subject()` – run the full denoising workflow for one subject.\n- `ndx_default_user_options()` – return a list of default workflow options.\n- `Auto_Adapt_RPCA_Rank()` – choose an appropriate RPCA rank from singular values.\n- `Select_Significant_Spectral_Regressors()` – pick sine/cosine regressors based on information criteria.\n- `calculate_DES()` – compute the Denoising Efficacy Score.\n- `ndx_generate_html_report()` – create an HTML report of diagnostics.\n\nSee individual function documentation for many other helpers (HRF estimation, whitening, ridge solving, etc.).\n\n## Basic Usage\n\nInputs to `NDX_Process_Subject()` are matrices of fMRI data and motion regressors, an event table and run index, the TR and an optional spike mask. Most behaviour is controlled through the `user_options` list; `ndx_default_user_options()` gives a sensible starting point.\n\n### Quick Start Example\n\n```r\nlibrary(ndx)\n\n# fmri_data, events_df, motion_matrix and run_index should be prepared by the user\nopts \u003c- ndx_default_user_options()\nresults \u003c- NDX_Process_Subject(\n  Y_fmri       = fmri_data,\n  events       = events_df,\n  motion_params = motion_matrix,\n  run_idx      = run_index,\n  TR           = 2,\n  user_options = opts\n)\n```\n\nThe returned list contains estimated HRFs, nuisance components, final betas and diagnostic metrics. Diagnostic plots can be written with `ndx_generate_html_report(results, results$pass0_residuals, TR = 2)`.\n\n## Testing\n\nUnit tests for the package are located under `tests/` and can be run with\n\n```r\nRscript run_tests.R\n```\n\n## License\n\nThis project is released under the MIT license.\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbbuchsbaum%2Ffmridenoise","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbbuchsbaum%2Ffmridenoise","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbbuchsbaum%2Ffmridenoise/lists"}