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The brain atlas concordance problem: quantitative comparison of anatomical parcellations.

Bohland JW, Bokil H, Allen CB, Mitra PP - PLoS ONE (2009)

Bottom Line: These analyses result in conditional probabilities that enable mapping between regions across atlases, which also form the input to graph-based methods for extracting higher-order relationships between sets of regions and to procedures for assessing the global similarity between different parcellations of the same brain.At a global scale, the overall results demonstrate a considerable lack of concordance between available parcellation schemes, falling within chance levels for some atlas pairs.At a finer level, this study reveals spatial relationships between sets of defined regions that are not obviously apparent; these are of high potential interest to researchers faced with the challenge of comparing results that were based on these different anatomical models, particularly when coordinate-based data are not available.

View Article: PubMed Central - PubMed

Affiliation: Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America. jbohland@bu.edu

ABSTRACT
Many neuroscientific reports reference discrete macro-anatomical regions of the brain which were delineated according to a brain atlas or parcellation protocol. Currently, however, no widely accepted standards exist for partitioning the cortex and subcortical structures, or for assigning labels to the resulting regions, and many procedures are being actively used. Previous attempts to reconcile neuroanatomical nomenclatures have been largely qualitative, focusing on the development of thesauri or simple semantic mappings between terms. Here we take a fundamentally different approach, discounting the names of regions and instead comparing their definitions as spatial entities in an effort to provide more precise quantitative mappings between anatomical entities as defined by different atlases. We develop an analytical framework for studying this brain atlas concordance problem, and apply these methods in a comparison of eight diverse labeling methods used by the neuroimaging community. These analyses result in conditional probabilities that enable mapping between regions across atlases, which also form the input to graph-based methods for extracting higher-order relationships between sets of regions and to procedures for assessing the global similarity between different parcellations of the same brain. At a global scale, the overall results demonstrate a considerable lack of concordance between available parcellation schemes, falling within chance levels for some atlas pairs. At a finer level, this study reveals spatial relationships between sets of defined regions that are not obviously apparent; these are of high potential interest to researchers faced with the challenge of comparing results that were based on these different anatomical models, particularly when coordinate-based data are not available. The complexity of the spatial overlap patterns revealed points to problems for attempts to reconcile anatomical parcellations and nomenclatures using strictly qualitative and/or categorical methods. Detailed results from this study are made available via an interactive web site at http://obart.info.

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Related in: MedlinePlus

Random parcellations.A: Sections through the AAL parcellation of the test brain with different colors indicating different parcels. B: a random parcellation of the same test brain.
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pone-0007200-g007: Random parcellations.A: Sections through the AAL parcellation of the test brain with different colors indicating different parcels. B: a random parcellation of the same test brain.

Mentions: The values of such scalar indices are typically difficult to interpret in the absence of known distributions of the values expected by chance. To compute such chance concordance distributions, we compared random parcellations of the test brain. We used a simple algorithm (see Materials and Methods) to create random space-filling partitions of the gray matter voxels consisting of N contiguous regions. Fifty random parcellations were generated for each of the atlases examined, with N matched to the number of regions comprising each atlas. Figure 7 shows several sections through an actual parcellation (AAL) as well as a size-matched random parcellation. For each pair of atlases, the similarity indices for 1000 pairs of size-matched random parcellations were calculated, yielding an estimate of the chance distribution specific to each pair-wise comparison.


The brain atlas concordance problem: quantitative comparison of anatomical parcellations.

Bohland JW, Bokil H, Allen CB, Mitra PP - PLoS ONE (2009)

Random parcellations.A: Sections through the AAL parcellation of the test brain with different colors indicating different parcels. B: a random parcellation of the same test brain.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2748707&req=5

pone-0007200-g007: Random parcellations.A: Sections through the AAL parcellation of the test brain with different colors indicating different parcels. B: a random parcellation of the same test brain.
Mentions: The values of such scalar indices are typically difficult to interpret in the absence of known distributions of the values expected by chance. To compute such chance concordance distributions, we compared random parcellations of the test brain. We used a simple algorithm (see Materials and Methods) to create random space-filling partitions of the gray matter voxels consisting of N contiguous regions. Fifty random parcellations were generated for each of the atlases examined, with N matched to the number of regions comprising each atlas. Figure 7 shows several sections through an actual parcellation (AAL) as well as a size-matched random parcellation. For each pair of atlases, the similarity indices for 1000 pairs of size-matched random parcellations were calculated, yielding an estimate of the chance distribution specific to each pair-wise comparison.

Bottom Line: These analyses result in conditional probabilities that enable mapping between regions across atlases, which also form the input to graph-based methods for extracting higher-order relationships between sets of regions and to procedures for assessing the global similarity between different parcellations of the same brain.At a global scale, the overall results demonstrate a considerable lack of concordance between available parcellation schemes, falling within chance levels for some atlas pairs.At a finer level, this study reveals spatial relationships between sets of defined regions that are not obviously apparent; these are of high potential interest to researchers faced with the challenge of comparing results that were based on these different anatomical models, particularly when coordinate-based data are not available.

View Article: PubMed Central - PubMed

Affiliation: Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America. jbohland@bu.edu

ABSTRACT
Many neuroscientific reports reference discrete macro-anatomical regions of the brain which were delineated according to a brain atlas or parcellation protocol. Currently, however, no widely accepted standards exist for partitioning the cortex and subcortical structures, or for assigning labels to the resulting regions, and many procedures are being actively used. Previous attempts to reconcile neuroanatomical nomenclatures have been largely qualitative, focusing on the development of thesauri or simple semantic mappings between terms. Here we take a fundamentally different approach, discounting the names of regions and instead comparing their definitions as spatial entities in an effort to provide more precise quantitative mappings between anatomical entities as defined by different atlases. We develop an analytical framework for studying this brain atlas concordance problem, and apply these methods in a comparison of eight diverse labeling methods used by the neuroimaging community. These analyses result in conditional probabilities that enable mapping between regions across atlases, which also form the input to graph-based methods for extracting higher-order relationships between sets of regions and to procedures for assessing the global similarity between different parcellations of the same brain. At a global scale, the overall results demonstrate a considerable lack of concordance between available parcellation schemes, falling within chance levels for some atlas pairs. At a finer level, this study reveals spatial relationships between sets of defined regions that are not obviously apparent; these are of high potential interest to researchers faced with the challenge of comparing results that were based on these different anatomical models, particularly when coordinate-based data are not available. The complexity of the spatial overlap patterns revealed points to problems for attempts to reconcile anatomical parcellations and nomenclatures using strictly qualitative and/or categorical methods. Detailed results from this study are made available via an interactive web site at http://obart.info.

Show MeSH
Related in: MedlinePlus