fmrireg

Define the temporal structure: 2 runs, 100 scans each, TR = 2s

sframe <- sampling_frame(blocklens = c(100, 100), TR = 2)

Build an event model from an experimental design table

emod <- event_model(onset ~ hrf(condition, basis = "spmg1"), data = design_table, block = ~ run, sampling_frame = sframe)

Add a baseline model with polynomial drift

bmod <- baseline_model(basis = "bs", degree = 5, sframe = sframe)

Combine into a full fMRI model and fit

fmod <- fmri_model(emod, bmod) fit <- fmri_lm(fmod, dataset = dset)

## Key features

- **HRF library** -- SPM canonical, gamma, Gaussian, B-spline, and custom
  basis sets, with decorators for lag, block, and normalization.
- **Formula interface** -- Specify event models with `onset ~ hrf(...)` syntax;
  supports categorical events, continuous modulators, and multi-basis expansions.
- **Contrast system** -- Flexible contrasts via formulas, including pairwise,
  polynomial, and F-contrasts.
- **Robust estimation** -- OLS, iteratively reweighted least squares (IWLS),
  and sandwich variance estimators.
- **AR correction** -- Autoregressive noise modeling via the
  [fmriAR](https://github.com/bbuchsbaum/fmriAR) package.
- **Performance** -- C++ solvers (Rcpp/RcppArmadillo) with optional
  multithreading via RcppParallel.

## Documentation

Full documentation and tutorials are available at
<https://bbuchsbaum.github.io/fmrireg/>. Vignettes include:

- [Package Overview](https://bbuchsbaum.github.io/fmrireg/articles/fmrireg.html)
- [Statistical Contrasts](https://bbuchsbaum.github.io/fmrireg/articles/a_05_contrasts.html)
- [Simulation](https://bbuchsbaum.github.io/fmrireg/articles/a_08_simulation.html)
- [Linear Modeling](https://bbuchsbaum.github.io/fmrireg/articles/a_09_linear_model.html)
- [Dataset Management](https://bbuchsbaum.github.io/fmrireg/articles/a_10_dataset.html)
- [Group Analysis](https://bbuchsbaum.github.io/fmrireg/articles/group_analysis.html)
- [Functional Connectivity](https://bbuchsbaum.github.io/fmrireg/articles/functional_connectivity.html)
- [Sketched GLM](https://bbuchsbaum.github.io/fmrireg/articles/sketched-ar.html)
- [Benchmark Datasets](https://bbuchsbaum.github.io/fmrireg/articles/benchmark_datasets.html)

## Command line

Install the package:

```r
remotes::install_github("bbuchsbaum/fmrireg")

Install the command wrapper:

fmrireg::install_cli("~/.local/bin", overwrite = TRUE)

If needed, add the directory to PATH:

export PATH="$HOME/.local/bin:$PATH"

Check the command:

fmrireg --help

Inspect bundled benchmark datasets:

fmrireg benchmark list
fmrireg benchmark summary --dataset BM_Canonical_HighSNR --json

Reporting

PDF report generation for fmri_lm fits is provided by the separate fmrireport package:

fmrireport::report(fit, output_dir = "results")

Performance configuration

The internal C++ routines use RcppParallel. Control the thread count with:

options(fmrireg.num_threads = 4)

or set the environment variable FMRIREG_NUM_THREADS before loading the package.

Citation

If you use fmrireg in your research, please cite:

Buchsbaum, B. R. (2025). fmrireg: Regression Analysis of Functional
Magnetic Resonance Imaging Data. R package version 0.1.2.
https://github.com/bbuchsbaum/fmrireg

License

MIT

Albers theme

This package uses the albersdown theme. Existing vignette theme hooks are replaced so albers.css and local albers.js render consistently on CRAN and GitHub Pages. The defaults are configured via params$family and params$preset (family = 'red', preset = 'homage'). The pkgdown site uses template: { package: albersdown } together with generated pkgdown/extra.css and pkgdown/extra.js so the theme is linked and activated on site pages.