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Connectivity Fingerprints: From Areal Descriptions to Abstract Spaces.
- Source :
-
Trends in Cognitive Sciences . Nov2018, Vol. 22 Issue 11, p1026-1037. 12p. - Publication Year :
- 2018
-
Abstract
- Fifteen years ago, Passingham and colleagues proposed that brain areas can be described in terms of their unique pattern of input and output connections with the rest of the brain, and that these connections are a crucial determinant of their function. We explore how the advent of neuroimaging of connectivity has allowed us to test and extend this proposal. We show that describing the brain in terms of an abstract connectivity space, as opposed to physical locations of areas, provides a natural and powerful framework for thinking about brain function and its variation across the brains of individuals, populations, and species. Highlights The concept of the connectivity fingerprint was described 15 years ago to suggest a crucial relationship between the connections (functional integration) and function (functional segregation) of an area. The advent of neuroimaging now allows for this concept to be applied on a much larger scale, describing brain organization in terms of a connectivity space. Describing brain organization in this space is closer to its functional organization and can predict differences in functional activation and behaviour. By abstracting away into connectivity space one can compare brains across individuals and species. Comparing differences in the connectivity fingerprints of areas or subareal units in terms of gradients, one can investigate which dimension of connectivity space is relevant for understanding particular aspects of brain organization. [ABSTRACT FROM AUTHOR]
- Subjects :
- *HUMAN fingerprints
*COMPARATIVE anatomy
*INDIVIDUAL differences
*BRAIN imaging
Subjects
Details
- Language :
- English
- ISSN :
- 13646613
- Volume :
- 22
- Issue :
- 11
- Database :
- Academic Search Index
- Journal :
- Trends in Cognitive Sciences
- Publication Type :
- Academic Journal
- Accession number :
- 132365350
- Full Text :
- https://doi.org/10.1016/j.tics.2018.08.009