A.J .D. Nelson
Data showing regional differences in rat brain monoaminergic function
Nelson, A.J .D.; Cassaday, H.J.
Chemical neurotransmitters (such as dopamine) modulate cognitive function via ascending projections to various cortical and sub-cortical brain regions. This report describes and links to a relatively large dataset (up to N=112) compiled from control (untreated) brain samples taken during a series of experimental in vivo studies. The dataset is freely available, to explore the normal interrelationships between levels of neurotransmitter (e.g., dopamine, serotonin), across brain regions implicated in both normal reward and drug addiction, as well as in disorders such as schizophrenia (e.g., nucleus accumbens, frontal cortex). Most experimental studies run with a relatively small control group, so there is a lack of baseline data on the expected levels of neurotransmitters and their metabolites in different brain regions. Accordingly, the available dataset has been compiled from a number of studies run in the same laboratory, and using closely similar behavioural procedures, sampling selected brain regions of a priori interest. These collated data can be used to explore differences in the distribution of the monoamines and their metabolites, patterns of neurotransmitter intercorrelations, both between and within different brain structures and including some consideration of laterality effects.
Nelson, A. .., & Cassaday, H. (2019). Data showing regional differences in rat brain monoaminergic function. Data in Brief, 27, https://doi.org/10.1016/j.dib.2019.104814
|Journal Article Type||Article|
|Acceptance Date||Nov 7, 2019|
|Online Publication Date||Nov 15, 2019|
|Deposit Date||Nov 14, 2019|
|Publicly Available Date||Nov 27, 2019|
|Journal||Data in Brief|
|Peer Reviewed||Peer Reviewed|
|Additional Information||This article is maintained by: Elsevier; Article Title: Data showing regional differences in rat brain monoaminergic function; Journal Title: Data in Brief; CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.dib.2019.104814; Content Type: article; Copyright: © 2019 The Author(s). Published by Elsevier Inc.|
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