[<< wikibooks] SPM
SPM (Statistical Parametric Mapping) refers to the construction and assessment of spatially extended statistical processes 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.
SPM is made freely available to the [neuro]imaging community, to promote collaboration and a common analysis scheme across laboratories. The software represents the implementation of the theoretical concepts of Statistical Parametric Mapping in a complete analysis package, as a suite of MATLAB functions and subroutines with some externally compiled C routines.


== Overview ==
SPM website at the Wellcome Centre for Human Neuroimaging, UCL, UK.
Overview of SPM from Wikipedia
Overview of SPM from Scholarpedia
Introduction to Statistical Parametric Mapping
History of Statistical Parametric Mapping in functional neuroimaging


== Installation ==
Overview of SPM installation:

DownloadSystem Requirements (hardware and software):

MATLAB version
Advice on hardware selectionDetailed installation and compilation on:

Windows 64bit
Linux 64bit
macOS 64bitInstructions for older platforms: Windows 32bit, Linux 32bit, MacOS (Intel), MacOS (PowerPc), SunOS / Solaris.
Standalone version using the MATLAB Compiler:

Standalone SPMOptimising your installation:

Optimising MATLAB/SPMContainerisation:

Docker and SingularityMiscellaneous:

GNU Octave
Python
Continuous Integration


== Experimental Design for fMRI ==
Design efficiency
Block design
Event related design


== Data Formats ==
Importing data from the scanner
DICOM Import


== Preprocessing ==
Slice Timing
Normalisation


== Modelling ==
Haemodynamic Response Function
Basis functions
General Linear Model
Correlation and Regression
Covariance
Autocorrelation
Non-sphericity
Session concatenation
Group analysis


== Statistical Inference ==
F and T tests
Contrasts
Inference
Power Analysis
Correlation
Information to include in papers
Calculating Percentage signal change
Comparing a single patient versus a group of controls
Timeseries extraction


== Voxel Based Morphometry ==
VBM (Voxel Based Morphometry)


== Connectivity Analysis ==
Structural Equation Modelling
Psychophysiological Interactions (PPI)
Dynamic Causal Modelling (DCM)
The DCM Equation. 1. Motivation
The DCM Equation. 2. Dynamical Systems
The DCM Equation. 3. Networks and Matrices
The DCM Equation. 4. The State Equation
Two-State DCM for fMRI
Bayesian Parameter Averaging (BPA)
Parametric Empirical Bayes (PEB)


== Misc ==
How-tos
Atlases
Datasets
BIDS
Working with 4D data
Programming intro
Writing batch scripts
No Display Mode
Learning SPM: Courses, books and websites


== Other tools ==
Cogent a MATLAB-based stimulus presentation software
MRIcron and MRIcroGL medical images viewers
MarsBaR region of interest toolbox for SPM
SnPM Statistical nonParametric Mapping
Anatomy SPM Anatomy toolbox
AAL Anatomical Automatic Labeling
WFU_PickAtlas a region of interest toolbox for SPM based on the Talairach Daemon Database
Physiological noise correction
Diffusion tools


== The physics of imaging technologies ==
functional Magnetic Resonance Imaging (fMRI)
Positron Emission Tomography (PET)
Single Photon Emission Computed Tomography (SPECT)
Electroencephalography (EEG)
Magnetoencephalography (MEG)