Abstract
The quantification of brain asymmetries may provide biomarkers for presurgical localization of language function and can improve our understanding of neural structure-function relationships in health and disease. We propose a new method for studying the asymmetry of the white matter tracts in the entire brain, and we apply it to a preliminary study of normal subjects across the handedness spectrum. Methods for quantifying white matter asymmetry using diffusion MRI tractography have thus far been based on comparing numbers of fibers or volumes of a single fiber tract across hemispheres. We propose a generalization of such methods, where the "number of fibers" laterality measurement is extended to the entire brain using a soft fiber comparison metric. We summarize the distribution of fiber laterality indices over the whole brain in a histogram, and we measure properties of the distribution such as its skewness, median, and inter-quartile range. The whole-brain fiber laterality histogram can be measured in an exploratory fashion without hypothesizing asymmetries only in particular structures. We demonstrate an overall difference in white matter asymmetry in consistent- and inconsistent-handers: the skewness of the fiber laterality histogram is significantly different across handedness groups.
| Original language | English |
|---|---|
| Title of host publication | Medical Image Computing and Computer-Assisted Intervention, MICCAI2010 - 13th International Conference, Proceedings |
| Pages | 225-232 |
| Number of pages | 8 |
| Edition | PART 2 |
| DOIs | |
| State | Published - 22 Nov 2010 |
| Event | 13th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2010 - Beijing, China Duration: 20 Sep 2010 → 24 Sep 2010 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Number | PART 2 |
| Volume | 6362 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | 13th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2010 |
|---|---|
| Country | China |
| City | Beijing |
| Period | 20/09/10 → 24/09/10 |
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The fiber laterality histogram : A new way to measure white matter asymmetry. / O'Donnell, Lauren J.; Westin, Carl Fredrik; Norton, Isaiah; Whalen, Stephen; Rigolo, Laura; Propper, Ruth; Golby, Alexandra J.
Medical Image Computing and Computer-Assisted Intervention, MICCAI2010 - 13th International Conference, Proceedings. PART 2. ed. 2010. p. 225-232 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6362 LNCS, No. PART 2).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
TY - GEN
T1 - The fiber laterality histogram
T2 - A new way to measure white matter asymmetry
AU - O'Donnell, Lauren J.
AU - Westin, Carl Fredrik
AU - Norton, Isaiah
AU - Whalen, Stephen
AU - Rigolo, Laura
AU - Propper, Ruth
AU - Golby, Alexandra J.
PY - 2010/11/22
Y1 - 2010/11/22
N2 - The quantification of brain asymmetries may provide biomarkers for presurgical localization of language function and can improve our understanding of neural structure-function relationships in health and disease. We propose a new method for studying the asymmetry of the white matter tracts in the entire brain, and we apply it to a preliminary study of normal subjects across the handedness spectrum. Methods for quantifying white matter asymmetry using diffusion MRI tractography have thus far been based on comparing numbers of fibers or volumes of a single fiber tract across hemispheres. We propose a generalization of such methods, where the "number of fibers" laterality measurement is extended to the entire brain using a soft fiber comparison metric. We summarize the distribution of fiber laterality indices over the whole brain in a histogram, and we measure properties of the distribution such as its skewness, median, and inter-quartile range. The whole-brain fiber laterality histogram can be measured in an exploratory fashion without hypothesizing asymmetries only in particular structures. We demonstrate an overall difference in white matter asymmetry in consistent- and inconsistent-handers: the skewness of the fiber laterality histogram is significantly different across handedness groups.
AB - The quantification of brain asymmetries may provide biomarkers for presurgical localization of language function and can improve our understanding of neural structure-function relationships in health and disease. We propose a new method for studying the asymmetry of the white matter tracts in the entire brain, and we apply it to a preliminary study of normal subjects across the handedness spectrum. Methods for quantifying white matter asymmetry using diffusion MRI tractography have thus far been based on comparing numbers of fibers or volumes of a single fiber tract across hemispheres. We propose a generalization of such methods, where the "number of fibers" laterality measurement is extended to the entire brain using a soft fiber comparison metric. We summarize the distribution of fiber laterality indices over the whole brain in a histogram, and we measure properties of the distribution such as its skewness, median, and inter-quartile range. The whole-brain fiber laterality histogram can be measured in an exploratory fashion without hypothesizing asymmetries only in particular structures. We demonstrate an overall difference in white matter asymmetry in consistent- and inconsistent-handers: the skewness of the fiber laterality histogram is significantly different across handedness groups.
UR - http://www.scopus.com/inward/record.url?scp=84874396619&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-15745-5_28
DO - 10.1007/978-3-642-15745-5_28
M3 - Conference contribution
SN - 3642157440
SN - 9783642157448
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 225
EP - 232
BT - Medical Image Computing and Computer-Assisted Intervention, MICCAI2010 - 13th International Conference, Proceedings
ER -