fmri_corrmat
============

.. currentmodule:: fmri_toolbox

Description
-----------
FMRI_CORRMAT  Column-wise pattern similarity matrix between two fMRI datasets.
Computes the Pearson correlation between every pair of columns across two
multivariate datasets, yielding an output matrix of size Ncol1 × Ncol2.
Columns can represent time points, trials, conditions, or group-level patterns.
If a single dataset is provided, the result is the autocorrelation matrix
of its columns (e.g., T × T for time points).

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

    c = fmri_corrmat(d1)       % autocorrelation of columns (Ncol × Ncol)
    c = fmri_corrmat(d1, d2)   % cross-correlation between two datasets (Ncol1 × Ncol2)

Inputs
------
- **D1**: Multivariate data (e.g., voxels × columns); correlations are across rows
- **D2**: Optional second dataset (same number of rows). Default: D2 = D1

Outputs
-------
- **C**: Similarity matrix of Pearson correlations between columns of D1 and D2

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

    % Temporal similarity between time points
    c = fmri_corrmat(data);           % T × T matrix
    imagesc(c, [-1 1]); colorbar
    % Cross-condition / trial / group-level similarity
    c = fmri_corrmat(cond_data1, cond_data2);  % C1 × C2 matrix
    imagesc(c, [-1 1]); colorbar

See Also
--------
- fmri_corregressor
- fmri_corrvoldata
- fmri_rv