Giter Club home page Giter Club logo
   ___  ____  __  __
  / __)(  _ \(  \/  )  
  \__ \ )___/ )    (   Statistical Parametric Mapping
  (___/(__)  (_/\/\_)  SPM - https://www.fil.ion.ucl.ac.uk/spm/

Platform: MATLAB Open in MATLAB Online License: GPL Tests

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 refers to the construction and assessment of spatially extended statistical process used to test hypotheses about functional imaging data. These ideas have been instantiated in 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.

Please refer to this version as "SPM12" in papers and communications.

SPM was written to organise and interpret our data (at The Wellcome Centre for Human Neuroimaging). The distributed version is the same as that we use ourselves.

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. MATLAB, a commercial engineering mathematics package, is required to use SPM. MATLAB is produced by MathWorks, Natick, MA, USA.

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

SPM12 is written for MATLAB version 7.4 (R2007a) onwards under Windows, Linux and Mac (SPM12 will not work with versions of MATLAB prior to 7.4). 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.

Later versions of MATLAB (released after SPM12), will probably need additional patches in order to run. Once developed, these will be made available from: https://www.fil.ion.ucl.ac.uk/spm/download/spm12_updates/

Although SPM12 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.

The SPM12 Release Notes can be found online: https://www.fil.ion.ucl.ac.uk/spm/software/spm12/

File format

SPM12 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 SPM12, 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 SPM12, although conversion utilities have been provided. Similarly, a number of DICOM flavours can also be converted to NIFTI-1 using tools in SPM12.

Resources

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

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

There is an SPM email discussion list, hosted at [email protected]. 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 to the authors at [email protected].

Peculiarities may actually be features, and should be raised on the SPM email discussion list, [email protected].

Authors

SPM is developed under the auspices of Functional Imaging Laboratory (FIL), The Wellcome Centre for Human NeuroImaging, in the Queen Square Institute of Neurology at 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) 1991,1994-2023 Wellcome Centre for Human Neuroimaging

SPM's Projects

daiss icon daiss

SPM Toolbox for M/EEG Data Analysis in Source Space (DAiSS)

nipype icon nipype

Workflows and interfaces for neuroimaging packages

spm icon spm

SPM (Statistical Parametric Mapping) - Development Version

spm12 icon spm12

Public Releases of SPM12 - see https://github.com/spm/spm for the Development Version

spm2 icon spm2

SPM2 (Statistical Parametric Mapping)

spm5 icon spm5

SPM5 (Statistical Parametric Mapping)

spm8 icon spm8

SPM8 (Statistical Parametric Mapping)

spm99 icon spm99

SPM99 (Statistical Parametric Mapping)

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.