Statistical parametric mapping: Difference between revisions

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{{Short description|Statistical technique}}

{{Other uses|SPM (disambiguation){{!}}SPM}}

{{unreferencedmore citations needed|date=NovemberJanuary 20102021}}

'''Statistical parametric mapping''' ('''SPM''') is a [[statistical]] technique for examining differences in [[brain]] activity recorded during [[functional neuroimaging]] experiments. It was created by [[Karl Friston]]. It may alternatively refer to software created by the ''Wellcome Department of Imaging Neuroscience'' (at [[University College London]]) to carry out such analyses.

==Approach==

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Images from the scanner may be pre-processed to remove noise or correct for sampling errors.

A study usually scans a subject several times. To account for the motion of the head between scans, the images are typically adjusted so voxels in each image correspond (approximately) to the same site in the brain. This is referred to as ''realignment'' or ''motion correction'', see image realignment.

Functional neuroimaging studies usually involve multiple participants, each of whom have differently shaped brains. All are likely to have the same gross anatomy, saving minor differences in overall brain size, individual variation in topography of the [[gyri]] and [[Sulcus (neuroanatomy)|sulci]] of the [[cerebral cortex]], and morphological differences in deep structures such as the [[corpus callosum]]. To aid comparisons, the 3D image of each brain is transformed so that superficial structures line up, via ''[[spatial normalization]]''. Such normalization typically involves translation, rotation and scaling and nonlinear warping of the brain surface to match a standard template. Standard brain maps such as the [[Talairach coordinates|Talairach-Tournoux]] or templates from the [[Montréal Neurological Institute]] (MNI) allow researchers from across the world to compare their results.

Images can be smoothed to make the data less noisy (similar to the 'blur' effect used in some image-editing software) by which voxels are averaged with their neighbours, typically using a [[Gaussian]] filter]] or by [[wavelet]] transformation.

===Statistical comparison===

[[Parametric statistics|Parametric statistical]] models are assumed at each voxel, using the [[general linear model]] to describe the data variability in terms of experimental and confounding effects, with residual variability. Hypotheses expressed in terms of the model parameters are assessed at each voxel with [[Univariate (statistics)|univariate statistics]].

Analyses may examine differences over [[time series|time]] (i.e. correlations between a task variable and brain activity in a certain area) using linear [[convolution]] models of how the measured signal is caused by underlying changes in neural activity.

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[[Image:Functional magnetic resonance imaging.jpg|thumb|right|Brain activation from fMRI shown as patch of colour on MRI scan]]

Differences in measured brain activity can be represented in various ways.

They can be presented as a table, displaying coordinates that show the most significant differences in activity between tasks. Alternatively, differences in brain activity can be shown as patches of colour on a brain 'slice', with the colours representing the ___location of voxels with statistically significant differences between conditions. The color gradient is mapped to statistical values, such as t-values or z-scores. This creates an intuitive and visually appealing map of the relative statistical strength of a given area.

Differences in activity can be represented as a 'glass brain', a representation of three outline views of the brain as if it were transparent. Only the patches of activation are visible as areas of shading. This is useful as a means of summarizing the total area of significant change in a given statistical comparison.

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* [[Analysis of Functional NeuroImages|AFNI]]

* [[FreeSurfer]]

* [[Computational anatomy toolbox]]

* [[FMRIB Software Library|FSL]]

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* [http://www.mccauslandcenter.sc.edu/CRNL/ fMRI guide by Chris Rorden]

* [http://cogprints.org/6193/ Introduction to fMRI: experimental design and data analysis]

* [http://www.mrc-cbu.cam.ac.uk/Imaging/Common/ Cambridge Imagers] - Neuroimaging information and tutorials.

* [http://www.fil.ion.ucl.ac.uk/~mgray/Presentations/Buttons%20in%20SPM5.ppt Buttons in SPM5] PowerPoint presentation from the SPM for dummies course

* [http://spect.yale.edu ISAS (Ictal-Interictal SPECT Analysis by SPM)] - Yale University

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[[Category:Biostatistics]]

[[Category:Computing in medical imaging]]

[[Category:Neuroimaging]]

[[Category:Neuroimaging software]]