English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints

MPS-Authors
/persons/resource/persons19539

Bacha-Trams,  Mareike
Institute of Neuroscience and Medicine, Research Center Jülich, Germany;
Department Neuropsychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

/persons/resource/persons19643

Friederici,  Angela D.
Department Neuropsychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

Locator
There are no locators available
Fulltext (public)

Zilles_2015.pdf
(Publisher version), 6MB

Supplementary Material (public)
There is no public supplementary material available
Citation

Zilles, K., Bacha-Trams, M., Palomero-Gallagher, N., Amunts, K., & Friederici, A. D. (2015). Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints. Cortex, 63, 79-89. doi:10.1016/j.cortex.2014.07.007.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0019-F4D2-D
Abstract
The language network is a well-defined large-scale neural network of anatomically and functionally interacting cortical areas. The successful language process requires the transmission of information between these areas. Since neurotransmitter receptors are key molecules of information processing, we hypothesized that cortical areas which are part of the same functional language network may show highly similar multireceptor expression pattern (“receptor fingerprint”), whereas those that are not part of this network should have different fingerprints. Here we demonstrate that the relation between the densities of 15 different excitatory, inhibitory and modulatory receptors in eight language-related areas are highly similar and differ considerably from those of 18 other brain regions not directly involved in language processing. Thus, the fingerprints of all cortical areas underlying a large-scale cognitive domain such as language is a characteristic, functionally relevant feature of this network and an important prerequisite for the underlying neuronal processes of language functions.