InSpectro-Gadget: A tool for estimating neurotransmitter and neuromodulator receptor distributions for MRS voxels

Nils Muhlert, Niall W. Duncan, Elizabeth Mcmanus-Day

Research output: Other contributionpeer-review

Abstract

Magnetic resonance spectroscopy (MRS) is widely used to estimate concentrations of glutamate and γ-aminobutyric acid (GABA) in specific regions of the living human brain. As cytoarchitectural properties differ across the brain, interpreting these measurements can be assisted by having knowledge of such properties for the MRS region(s) studied. In particular, some knowledge of likely local neurotransmitter receptor patterns can potentially give insights into the mechanistic environment GABA- and glutamatergic neurons are functioning in. This may be of particular utility when comparing two or more regions, given that the receptor populations may differ substantially across them. At the same time, when studying MRS data from multiple participants or timepoints, the homogeneity of the sample becomes relevant, as measurements taken from areas with different cytoarchitecture may be difficult to compare. To provide insights into the likely cytoarchitectural environment of user-defined regions-of-interest, we produced an easy to use tool - InSpectro-Gadget - that interfaces with receptor mRNA expression information from the Allen Human Brain Atlas. This Python tool allows users to input masks and automatically obtain a graphical overview of the receptor population likely to be found within. This includes comparison between multiple masks or participants where relevant. The receptors and receptor subunit genes featured include GABA- and glutamatergic classes, along with a wide range of neuromodulators. The functionality of the tool is explained here and its use is demonstrated through a set of example analyses. The tool is available at https://github.com/lizmcmanus/Inspectro-Gadget.

Original languageEnglish
PublisherNeuroinformatics
DOIs
Publication statusPublished - 22 Feb 2024

Publication series

NameNeuroinformatics
PublisherHumana Press, Inc
ISSN (Print)1539-2791

Keywords

  • Excitation
  • Gene expression
  • Inhibition
  • MRI
  • Spectroscopy

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