Cortical thickness: Difference between revisions
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In brain anatomy, '''cortical thickness''' is a global measure used to describe the combined thickness of the layers of the [[cerebral cortex]]. It is commonly determined from the [[grey matter]] set in [[segmentation|segmented]] [[neuroimaging]] data. Its variation across the human brain follows [[small world|small-world]] principles<ref name=He2007>{{CZ:Ref | In brain anatomy, '''cortical thickness''' is a global measure used to describe the combined thickness of the layers of the [[cerebral cortex]]. It is commonly determined from the [[grey matter]] set in [[segmentation|segmented]] [[neuroimaging]] data. Its variation across the human brain follows [[small world|small-world]] principles<ref name=He2007>{{CZ:Ref:He 2007 Small-World Anatomical Networks in the Human Brain Revealed by Cortical Thickness from MRI}}</ref>, and deviations thereof can be used as diagnostic indicators for [[brain disorder]]s, e.g. in [[lissencephaly]] and [[Williams syndrome]]<ref name=Thompson2005>{{CZ:Ref:Thompson 2005 Abnormal Cortical Complexity and Thickness Profiles Mapped in Williams Syndrome}}</ref>. | ||
==References== | ==References== | ||
{{reflist|2}} | {{reflist|2}} | ||
Revision as of 20:35, 8 March 2009
In brain anatomy, cortical thickness is a global measure used to describe the combined thickness of the layers of the cerebral cortex. It is commonly determined from the grey matter set in segmented neuroimaging data. Its variation across the human brain follows small-world principles[1], and deviations thereof can be used as diagnostic indicators for brain disorders, e.g. in lissencephaly and Williams syndrome[2].
References
- ↑ He, Yong; Zhang J. Chen & Alan C. Evans (2007), "Small-World Anatomical Networks in the Human Brain Revealed by Cortical Thickness from MRI", Cerebral Cortex 17 (10): 2407-2419, DOI:10.1093/cercor/bhl149 [e]
- ↑ Thompson, Paul M.; Agatha D. Lee & Rebecca A. Dutton et al. (2005), "Abnormal Cortical Complexity and Thickness Profiles Mapped in Williams Syndrome", Journal of Neuroscience 25 (16): 4146–4158, DOI:10.1523/JNEUROSCI.0165-05.2005 [e]