Voxel-based morphometry of the human brain: Methods and applications

In recent years, a whole-brain unbiased objective technique, known as voxel-based morphometry (VBM), has been developed to characterise brain differences in vivo using structural magnetic resonance images. The present review provides a brief description of VBM and then focuses on exemplar applications in healthy and diseased subjects. The procedure involves normalising high-resolution structural magnetic resonance images to a standard template in stereotactic space. Normalised images are then segmented into gray and white matter and smoothed using an isotropic Gaussian kernel. Finally, a series of voxel-wise comparisons of gray and white matter in different groups of subjects are performed, using Random Field theory to correct for multiple comparisons. VBM has been useful in characterizing subtle changes in brain structure in a variety of diseases associated with neurological and psychiatric dysfunction. These include schizophrenia, developmental and congenital disorders, temporal lobe epilepsy and even cluster headache. In addition, VBM has been successful in identifying gross structural abnormalities, such as those observed in herpes simplex encephalitis, multiple sclerosis and Alzheimer's disease. Studies of normal subjects, on the other hand, have focussed on the impact of learning and practice on brain structure. These studies have led to the finding that environmental demands may be associated with changes in gray and white matter. For instance, it has been reported that the structure of the brain alters when human beings learn to navigate, read music, speak a second language and even perform a complex motor task such as juggling. We conclude the present review by discussing the potential limitations of the technique.

[1]  Karl J. Friston,et al.  Why Voxel-Based Morphometry Should Be Used , 2001, NeuroImage.

[2]  Karl J. Friston,et al.  A Voxel-Based Morphometric Study of Ageing in 465 Normal Adult Human Brains , 2001, NeuroImage.

[3]  Fred L. Bookstein,et al.  “Voxel-Based Morphometry” Should Not Be Used with Imperfectly Registered Images , 2001, NeuroImage.

[4]  Nick C Fox,et al.  Serial magnetic resonance imaging of cerebral atrophy in preclinical Alzheimer's disease , 1999, The Lancet.

[5]  T. Smulders,et al.  Seasonal variation in hippocampal volume in a food-storing bird, the black-capped chickadee. , 1995, Journal of neurobiology.

[6]  A. Stoll,et al.  Frontal lobe gray matter density decreases in bipolar I disorder , 2004, Biological Psychiatry.

[7]  Karl J. Friston,et al.  Voxel-Based Morphometry—The Methods , 2000, NeuroImage.

[8]  Karl J. Friston,et al.  Correlation between structural and functional changes in brain in an idiopathic headache syndrome , 1999, Nature Medicine.

[9]  Dinggang Shen,et al.  Automated morphometric study of brain variation in XXY males , 2004, NeuroImage.

[10]  Karl J. Friston,et al.  Voxel-Based Morphometry of Herpes Simplex Encephalitis , 2001, NeuroImage.

[11]  M. Weiner,et al.  Cognition and anatomy in three variants of primary progressive aphasia , 2004, Annals of neurology.

[12]  A R Damasio,et al.  The limbic system and the localisation of herpes simplex encephalitis. , 1985, Journal of neurology, neurosurgery, and psychiatry.

[13]  C D Good,et al.  The distribution of structural neuropathology in pre-clinical Huntington's disease. , 2002, Brain : a journal of neurology.

[14]  Karl J. Friston,et al.  A Voxel-Based Method for the Statistical Analysis of Gray and White Matter Density Applied to Schizophrenia , 1995, NeuroImage.

[15]  Nick C. Fox,et al.  Global and local gray matter loss in mild cognitive impairment and Alzheimer's disease , 2004, NeuroImage.

[16]  U. C. Wieshmann,et al.  Comparison of standard and optimized voxel-based morphometry for analysis of brain changes associated with temporal lobe epilepsy , 2004, NeuroImage.

[17]  G. Schlaug,et al.  Brain Structures Differ between Musicians and Non-Musicians , 2003, The Journal of Neuroscience.

[18]  Nick C. Fox,et al.  Voxel-based morphometry detects patterns of atrophy that help differentiate progressive supranuclear palsy and Parkinson's disease , 2004, NeuroImage.

[19]  N. Clayton,et al.  Neurobiological bases of spatial learning in the natural environment: neurogenesis and growth in the avian and mammalian hippocampus. , 1998, Neuroreport.

[20]  K. Svoboda,et al.  Long-term in vivo imaging of experience-dependent synaptic plasticity in adult cortex , 2002, Nature.

[21]  Richard S. J. Frackowiak,et al.  Navigation-related structural change in the hippocampi of taxi drivers. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[22]  Karl J. Friston,et al.  Cortical grey matter and benzodiazepine receptors in malformations of cortical development. A voxel-based comparison of structural and functional imaging data. , 1997, Brain : a journal of neurology.

[23]  Karl J. Friston,et al.  Detecting Activations in PET and fMRI: Levels of Inference and Power , 1996, NeuroImage.

[24]  Martha Elizabeth Shenton,et al.  Voxel-Based Morphometric Analysis of Gray Matter in First Episode Schizophrenia , 2002, NeuroImage.

[25]  Richard S. J. Frackowiak,et al.  Neurolinguistics: Structural plasticity in the bilingual brain , 2004, Nature.

[26]  Bogdan Draganski,et al.  Neuroplasticity: Changes in grey matter induced by training , 2004, Nature.

[27]  Karl J. Friston,et al.  Kallmann’s syndrome , 1999, Neurology.

[28]  M. Andermann,et al.  Detecting Changes In Non-Isotropic Images , 1999 .

[29]  M. Le,et al.  Neurobiological bases of spatial learning in the natural environment: neurogenesis and growth in the avian and mammalian hippocampus. , 1998 .

[30]  G. Kempermann,et al.  Neuroplasticity in old age: Sustained fivefold induction of hippocampal neurogenesis by long‐term environmental enrichment , 2002, Annals of neurology.

[31]  Richard S. Frackowiak,et al.  Superior temporal sulcus anatomical abnormalities in childhood autism: a voxel-based morphometry MRI study , 2004, NeuroImage.

[32]  Karl J. Friston,et al.  Generative and recognition models for neuroanatomy , 2004, NeuroImage.

[33]  Neil Burgess,et al.  Navigation expertise and the human hippocampus: A structural brain imaging analysis , 2003, Hippocampus.

[34]  Karl J. Friston,et al.  The neuroanatomy of autism: a voxel-based whole brain analysis of structural scans. , 1999, Neuroreport.

[35]  J. Ashburner,et al.  Multimodal Image Coregistration and Partitioning—A Unified Framework , 1997, NeuroImage.

[36]  N. Kasthuri,et al.  Long-term dendritic spine stability in the adult cortex , 2002, Nature.

[37]  Karl J. Friston,et al.  Statistical parametric maps in functional imaging: A general linear approach , 1994 .

[38]  A. Toga,et al.  Detection and mapping of abnormal brain structure with a probabilistic atlas of cortical surfaces. , 1997, Journal of computer assisted tomography.

[39]  Karl J. Friston,et al.  A unified statistical approach for determining significant signals in images of cerebral activation , 1996, Human brain mapping.

[40]  Christos Davatzikos,et al.  Voxel-Based Morphometry Using the RAVENS Maps: Methods and Validation Using Simulated Longitudinal Atrophy , 2001, NeuroImage.

[41]  Karl J. Friston,et al.  Distributional Assumptions in Voxel-Based Morphometry , 2002, NeuroImage.

[42]  Nathan S White,et al.  A voxel-based morphometric study of nondemented adults with Down Syndrome , 2003, NeuroImage.

[43]  Alan C. Evans,et al.  Detecting changes in nonisotropic images , 1999, Human brain mapping.

[44]  Christos Davatzikos,et al.  Why voxel-based morphometric analysis should be used with great caution when characterizing group differences , 2004, NeuroImage.