Linked Life Data

11346794

Source:http://linkedlifedata.com/resource/pubmed/id/11346794

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6834
pubmed:dateCreated
2001-5-10
pubmed:abstractText
Comparison of mammalian brain parts has often focused on differences in absolute size, revealing only a general tendency for all parts to grow together. Attempts to find size-independent effects using body weight as a reference variable obscure size relationships owing to independent variation of body size and give phylogenies of questionable significance. Here we use the brain itself as a size reference to define the cerebrotype, a species-by-species measure of brain composition. With this measure, across many mammalian taxa the cerebellum occupies a constant fraction of the total brain volume (0.13 +/- 0.02), arguing against the hypothesis that the cerebellum acts as a computational engine principally serving the neocortex. Mammalian taxa can be well separated by cerebrotype, thus allowing the use of quantitative neuroanatomical data to test evolutionary relationships. Primate cerebrotypes have progressively shifted and neocortical volume fractions have become successively larger in lemurs and lorises, New World monkeys, Old World monkeys, and hominoids, lending support to the idea that primate brain architecture has been driven by directed selection pressure. At the same time, absolute brain size can vary over 100-fold within a taxon, while maintaining a relatively uniform cerebrotype. Brains therefore constitute a scalable architecture.
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
0028-0836
pubmed:author
pubmed:issnType
Print
pubmed:day
10
pubmed:volume
411
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
189-93
pubmed:dateRevised
2010-11-18
pubmed:meshHeading
pubmed:year
2001
pubmed:articleTitle
Scalable architecture in mammalian brains.
pubmed:affiliation
Department of Molecular Biology, Princeton University, Princeton, New Jersey 08544, USA.
pubmed:publicationType
Journal Article, Comparative Study, Research Support, Non-U.S. Gov't