Cerebral chemoarchitecture shares organizational traits with brain structure and function
Abstract
Chemoarchitecture, the heterogeneous distribution of neurotransmitter transporter and receptor molecules, is a relevant component of structure-function relationships in the human brain. Here, we studied the organization of the receptome, a measure of interareal chemoarchitectural similarity, derived from Positron-Emission Tomography imaging studies of 19 different neurotransmitter transporters and receptors. Nonlinear dimensionality reduction revealed three main spatial gradients of cortical chemoarchitectural similarity - a centro-temporal gradient, an occipito-frontal gradient, and a temporo-occipital gradient. In subcortical nuclei, chemoarchitectural similarity distinguished functional communities and delineated a striato-thalamic axis. Overall, the cortical receptome shared key organizational traits with functional and structural brain anatomy, with node-level correspondence to functional, microstructural, and diffusion MRI-based measures decreasing along a primary-to-transmodal axis. Relative to primary and paralimbic regions, unimodal and heteromodal regions showed higher receptomic diversification, possibly supporting functional flexibility.
Data availability
All data and software used in this study is openly accessible. PET data is available at https://github.com/netneurolab/hansen_receptors. FC, SC and MPC data is available at https://portal.conp.ca/dataset?id=projects/mica-mics. ENIGMA data is available through enigmatoolbox (https://github.com/MICA-MNI/ENIGMA). Meta-analytical functional activation data is available through Neurosynth (https://neurosynth.org/analyses/topics/v5-topics-50). The code used to perform the analyses can be found at https://github.com/CNG-LAB/cngopen/receptor_similarity.
-
Mapping neurotransmitter systems to the structural and functional organization of the human neocortexgithub, https://doi.org/10.1101/2021.10.28.466336.
-
MICA-MICs: a dataset for Microstructure-Informed ConnectomicsCONP, https://n2t.net/ark:/70798/d72xnk2wd397j190qv.
-
The ENIGMA Toolbox: multiscale neural contextualization of multisite neuroimaging datasetsgithub, https://doi.org/10.1038/s41592-021-01186-4.
-
Large-scale automated synthesis of human functional neuroimaging dataneurosynth, https://doi.org/10.1038/nmeth.1635.
Article and author information
Author details
Funding
Max-Planck-Institut für Kognitions- und Neurowissenschaften (Open Access funding)
- Sofie Louise Valk
FRQ-S
- Boris C Bernhardt
Tier-2 Canada Research Chairs program
- Boris C Bernhardt
Human Brain Project
- Simon B Eickhoff
Max Planck Gesellschaft (Otto Hahn award)
- Sofie Louise Valk
Helmholtz International Lab grant agreement (InterLabs-0015)
- Boris C Bernhardt
- Simon B Eickhoff
- Sofie Louise Valk
Canada First Research Excellence Fund (CFREF Competition 2,2015-2016)
- Boris C Bernhardt
- Simon B Eickhoff
- Sofie Louise Valk
European Union's Horizon 2020 (No. 826421 TheVirtualBrain-Cloud"")
- Juergen Dukart
Helmholtz International BigBrain Analytics & Laboratory
- Justine Y Hansen
- Boris C Bernhardt
- Simon B Eickhoff
- Sofie Louise Valk
Natural Sciences and Engineering Research Council of Canada
- Justine Y Hansen
- Boris C Bernhardt
- Bratislav Misic
Canadian Institutes of Health Research
- Boris C Bernhardt
- Bratislav Misic
Brain Canada Foundation Future Leaders Fund
- Boris C Bernhardt
- Bratislav Misic
Canada Research Chairs
- Bratislav Misic
Michael J. Fox Foundation for Parkinson's Research
- Bratislav Misic
SickKids Foundation (NI17-039)
- Boris C Bernhardt
Azrieli Center for Autism Research (ACAR-TACC)
- Boris C Bernhardt
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Birte U Forstmann, University of Amsterdam, Netherlands
Ethics
Human subjects: The current research complies with all relevant ethical regulations as set by The Independent Research Ethics Committee at the Medical Faculty of the Heinrich-Heine-University of Duesseldorf (study number 2018-317). The current data was based on open access resources, and ethic approvals of the individual datasets are available in the original publications of each data source.
Version history
- Preprint posted: August 26, 2022 (view preprint)
- Received: September 30, 2022
- Accepted: July 12, 2023
- Accepted Manuscript published: July 13, 2023 (version 1)
- Version of Record published: July 26, 2023 (version 2)
Copyright
© 2023, Hänisch et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 1,128
- views
-
- 218
- downloads
-
- 7
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Biochemistry and Chemical Biology
- Neuroscience
In most mammals, conspecific chemosensory communication relies on semiochemical release within complex bodily secretions and subsequent stimulus detection by the vomeronasal organ (VNO). Urine, a rich source of ethologically relevant chemosignals, conveys detailed information about sex, social hierarchy, health, and reproductive state, which becomes accessible to a conspecific via vomeronasal sampling. So far, however, numerous aspects of social chemosignaling along the vomeronasal pathway remain unclear. Moreover, since virtually all research on vomeronasal physiology is based on secretions derived from inbred laboratory mice, it remains uncertain whether such stimuli provide a true representation of potentially more relevant cues found in the wild. Here, we combine a robust low-noise VNO activity assay with comparative molecular profiling of sex- and strain-specific mouse urine samples from two inbred laboratory strains as well as from wild mice. With comprehensive molecular portraits of these secretions, VNO activity analysis now enables us to (i) assess whether and, if so, how much sex/strain-selective ‘raw’ chemical information in urine is accessible via vomeronasal sampling; (ii) identify which chemicals exhibit sufficient discriminatory power to signal an animal’s sex, strain, or both; (iii) determine the extent to which wild mouse secretions are unique; and (iv) analyze whether vomeronasal response profiles differ between strains. We report both sex- and, in particular, strain-selective VNO representations of chemical information. Within the urinary ‘secretome’, both volatile compounds and proteins exhibit sufficient discriminative power to provide sex- and strain-specific molecular fingerprints. While total protein amount is substantially enriched in male urine, females secrete a larger variety at overall comparatively low concentrations. Surprisingly, the molecular spectrum of wild mouse urine does not dramatically exceed that of inbred strains. Finally, vomeronasal response profiles differ between C57BL/6 and BALB/c animals, with particularly disparate representations of female semiochemicals.
-
- Neuroscience
Midbrain dopamine neurons impact neural processing in the prefrontal cortex (PFC) through mesocortical projections. However, the signals conveyed by dopamine projections to the PFC remain unclear, particularly at the single-axon level. Here, we investigated dopaminergic axonal activity in the medial PFC (mPFC) during reward and aversive processing. By optimizing microprism-mediated two-photon calcium imaging of dopamine axon terminals, we found diverse activity in dopamine axons responsive to both reward and aversive stimuli. Some axons exhibited a preference for reward, while others favored aversive stimuli, and there was a strong bias for the latter at the population level. Long-term longitudinal imaging revealed that the preference was maintained in reward- and aversive-preferring axons throughout classical conditioning in which rewarding and aversive stimuli were paired with preceding auditory cues. However, as mice learned to discriminate reward or aversive cues, a cue activity preference gradually developed only in aversive-preferring axons. We inferred the trial-by-trial cue discrimination based on machine learning using anticipatory licking or facial expressions, and found that successful discrimination was accompanied by sharper selectivity for the aversive cue in aversive-preferring axons. Our findings indicate that a group of mesocortical dopamine axons encodes aversive-related signals, which are modulated by both classical conditioning across days and trial-by-trial discrimination within a day.