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/ )( _ ( \/ )
__ \ )/ ) ( Statistical Parametric Mapping (/() (_/\/_) SPM - https://www.fil.ion.ucl.ac.uk/spm/ ```

This README gives a brief introduction to the SPM software. Full details can be found on the SPM website.

See also Contents.m, AUTHORS.txt and LICENCE.

SPM

Statistical Parametric Mapping is the construction and assessment of spatially extended statistical processes used to test hypotheses about functional imaging data. These ideas have been instantiated in a free and open source software that is called SPM.

The SPM software package has been designed for the analysis of brain imaging data sequences. The sequences can be a series of images from different cohorts, or time-series from the same subject. The current release is designed for the analysis of fMRI, PET, SPECT, EEG and MEG.

SPM is made freely available to the [neuro]imaging community, to promote collaboration and a common analysis scheme across laboratories.

Software

The SPM software is a suite of MATLAB functions, scripts and data files, with some externally compiled C routines, implementing Statistical Parametric Mapping. For the best experience, we recommend running SPM using MATLAB, a commercial engineering mathematics package. MATLAB is produced by MathWorks, Natick, MA, USA. Standalone versions of SPM that do not require MATLAB are also available.

SPM requires only core MATLAB to run (no special toolboxes are required).

SPM is tested using the versions of MATLAB from the last 4-5 years. Binaries of the external C-MEX routines are provided for Windows, Linux and Mac. The source code is supplied and can be compiled with a C compiler (Makefile provided). See https://www.fil.ion.ucl.ac.uk/spm/software/spm12/ for details.

Although SPM will read image files from previous versions of SPM, there are differences in the algorithms, templates and models used. Therefore, we recommend you use a single SPM version for any given project.

File format

SPM uses the NIFTI-1 data format as standard. Take a look at https://nifti.nimh.nih.gov/ for more information on the NIFTI-1 file format.

The old SPM2 version of Analyze format can be read straight into SPM, but results will be written out as NIFTI-1. If you still use this format, then it is important that you ensure that spm_flip_analyze_images has been set appropriately for your data.

The MINC and ECAT7 formats can not be read straight into SPM, although conversion utilities have been provided. Similarly, a number of DICOM flavours can also be converted to NIFTI-1 using tools in SPM.

Resources

The SPM documentation website is the central repository for SPM resources: https://www.fil.ion.ucl.ac.uk/spm/docs/

Introductory material, installation details, documentation and course details are published on the site.

There is an SPM email discussion list, hosted at spm@jiscmail.ac.uk. The list is monitored by the authors, and discusses theoretical, methodological and practical issues of Statistical Parametric Mapping and SPM. The SPM website has further details: https://www.fil.ion.ucl.ac.uk/spm/support/

Please report bugs via the Issues page on SPM's Github repository.

Authors

SPM is developed under the auspices of the Methods Group at the Functional Imaging Laboratory (FIL), within the Department of Imaging Neuroscience, UCL Queen Square Institute of Neurology, University College London (UCL), UK.

SPM94 was written primarily by Karl Friston in the first half of 1994, with assistance from John Ashburner (MRC-CU), Jon Heather (WDoIN), and Andrew Holmes (Department of Statistics, University of Glasgow). Subsequent development, under the direction of Prof. Karl Friston at the Wellcome Department of Imaging Neuroscience, has benefited from substantial input (technical and theoretical) from: John Ashburner (WDoIN), Andrew Holmes (WDoIN & Robertson Centre for Biostatistics, University of Glasgow, Scotland), Jean-Baptiste Poline (WDoIN & CEA/DRM/SHFJ, Orsay, France), Christian Buechel (WDoIN), Matthew Brett (MRC-CBU, Cambridge, England), Chloe Hutton (WDoIN) and Keith Worsley (Department of Statistics, McGill University, Montreal Canada).

See AUTHORS.txt for a complete list of SPM co-authors.

We would like to thank everyone who has provided feedback on SPM.

Disclaimer, copyright & licencing

SPM is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see https://www.gnu.org/licenses/.

SPM is supplied as is: No formal support or maintenance is provided or implied.

Copyright (C) 1991,1994-2025 Functional Imaging Laboratory