fmri_corregressor
=================

.. currentmodule:: fmri_toolbox

Description
-----------
FMRI_CORREGRESSOR  Voxelwise correlation of regressor(s) with fMRI data.
Correlates one or more regressors with every voxel in the brain, returning
a brain map of Pearson r values (or Spearman rho if requested). This is
the primary function for univariate GLM-style analysis (e.g. correlating
a stimulus time course, a behavioural score, or a seed-region time series
with the whole brain).

Usage
-----
.. code-block:: matlab

    c = fmri_corregressor(regr, data)
    c = fmri_corregressor(regr, data, method)

Inputs
------
- **REGR**: Regressor matrix (T x R): T time points, R regressors. Will be normalised internally. For a single regressor, a (T x 1) vector is accepted.
- **DATA**: fMRI time series, vectorized (228453 x T). Each row is a voxel, each column a time point.
- **METHOD**: Correlation method: 'pearson' (default) or 'spearman'. Spearman is rank-based and more robust to outliers but slower.

Outputs
-------
- **C**: Correlation map (228453 x R). Each column is the r-map for one regressor. Values are clipped to [-1, 1].

Examples
--------
.. code-block:: matlab

    r = fmri_corregressor(stim_ts, data);
    fmri_showslices(r, 1, 2, [0.2 0.6])
    % Spearman (rank-based, outlier-robust)
    r = fmri_corregressor(score, group_data, 'spearman');
    % Multiple regressors at once
    r = fmri_corregressor([regr1, regr2], data);

See Also
--------
- fmri_corrvoldata
- fmri_xcorr
- fmri_rtop
- fmri_simmat