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User:I5gach/sandbox

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Developer(s)Structural Brain Mapping Group
Christian Gaser
Robert Dahnke
Stable release
12.9 / 25 May 2024; 5 months ago (2024-05-25)
Repositorygithub.com/ChristianGaser/cat12
Written inMatlab, C
Operating systemLinux, macOS, Windows
PlatformMATLAB, SPM
TypeNeuroimaging data analysis
LicenseGNU_General_Public_License
Websiteneuro-jena.github.io/cat

CAT (Computational Anatomy Toolbox) is a free and open source software package used for the analysis of structural brain imaging data, in particular magnetic resonance imaging (MRI) [1]. Developed by Christian Gaser and Robert Dahnke of the Structural Brain Mapping Group at the University of Jena, CAT is an extension of the SPM software platform. It is widely recognised in the neuroscience and neuroimaging communities as a robust and versatile tool for studying brain morphology.

Features

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  • Voxel-Based Morphometry (VBM): Provides tools for analysing brain tissue volume, focusing on gray matter, white matter, and cerebrospinal fluid.
  • Surface-Based Morphometry (SBM): Offers capabilities for cortical surface analysis, including measurements of cortical thickness [2], folding [3], and gyrification [4].
  • Region- or Label-Based Morphometry: Allows for structural assessments within predefined brain regions or anatomical labels.
  • Integrated Quality Control: Automated pipelines ensure high-quality data preprocessing and analysis.
  • Longitudinal Analysis: Supports the study of brain changes over time through longitudinal data analysis [5].

Applications

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CAT is widely used to study brain structure in various populations, including studies of neurodevelopment, ageing, neurodegenerative diseases, and mental disorders [6]. Its integration with SPM makes it a versatile tool for both basic research and clinical studies.

Integration with SPM

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CAT is designed to work within the SPM environment, taking advantage of SPM's statistical analysis, image preprocessing, and data visualisation capabilities. This integration allows users to combine the structural analysis capabilities of CAT with the functional and statistical tools provided by SPM.

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See Also

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References

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  1. ^ Gaser C, Dahnke R, Thompson PM, et al. (Aug 2024). "CAT: a computational anatomy toolbox for the analysis of structural MRI data". Gigascience. 13: giae049. doi:10.1093/gigascience/giae049. PMC 11299546. PMID 39102518.
  2. ^ Dahnke R, Yotter RA, Gaser C (Jan 2013). "Cortical thickness and central surface estimation". Neuroimage. 65: 336–48. doi:10.1016/j.neuroimage.2012.09.050. PMID 23041529.
  3. ^ Yotter RA, Nenadic I, Ziegler G, et al. (Jun 2011). "Local cortical surface complexity maps from spherical harmonic reconstructions". Neuroimage. 56 (3): 961–73. doi:10.1016/j.neuroimage.2011.02.007. PMID 21315159.
  4. ^ Luders E, Thompson PM, Narr KL, et al. (Jul 2009). "A curvature-based approach to estimate local gyrification on the cortical surface". Neuroimage. 29 (4): 1224–30. doi:10.1016/j.neuroimage.2005.08.049. PMID 16223589.
  5. ^ Draganski B, Gaser C, Busch V, et al. (Jan 2004). "Neuroplasticity: changes in grey matter induced by training". Nature. 427 (6972): 311–2. doi:10.1038/427311a. PMID 14737157.
  6. ^ Koutsouleris N, Meisenzahl EM, Davatzikos C, et al. (Jul 2009). "Use of neuroanatomical pattern classification to identify subjects in at-risk mental states of psychosis and predict disease transition". Arch Gen Psychiatry. 66 (7): 700–12. doi:10.1001/archgenpsychiatry.2009.62. PMC 4135464. PMID 19581561.