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.
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.
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
-
- 1,495
- views
-
- 276
- downloads
-
- 12
- 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
-
- Neuroscience
Detecting causal relations structures our perception of events in the world. Here, we determined for visual interactions whether generalized (i.e. feature-invariant) or specialized (i.e. feature-selective) visual routines underlie the perception of causality. To this end, we applied a visual adaptation protocol to assess the adaptability of specific features in classical launching events of simple geometric shapes. We asked observers to report whether they observed a launch or a pass in ambiguous test events (i.e. the overlap between two discs varied from trial to trial). After prolonged exposure to causal launch events (the adaptor) defined by a particular set of features (i.e. a particular motion direction, motion speed, or feature conjunction), observers were less likely to see causal launches in subsequent ambiguous test events than before adaptation. Crucially, adaptation was contingent on the causal impression in launches as demonstrated by a lack of adaptation in non-causal control events. We assessed whether this negative aftereffect transfers to test events with a new set of feature values that were not presented during adaptation. Processing in specialized (as opposed to generalized) visual routines predicts that the transfer of visual adaptation depends on the feature similarity of the adaptor and the test event. We show that the negative aftereffects do not transfer to unadapted launch directions but do transfer to launch events of different speeds. Finally, we used colored discs to assign distinct feature-based identities to the launching and the launched stimulus. We found that the adaptation transferred across colors if the test event had the same motion direction as the adaptor. In summary, visual adaptation allowed us to carve out a visual feature space underlying the perception of causality and revealed specialized visual routines that are tuned to a launch’s motion direction.
-
- Neuroscience
Synchronous neuronal activity is organized into neuronal oscillations with various frequency and time domains across different brain areas and brain states. For example, hippocampal theta, gamma, and sharp wave oscillations are critical for memory formation and communication between hippocampal subareas and the cortex. In this study, we investigated the neuronal activity of the dentate gyrus (DG) with optical imaging tools during sleep-wake cycles in mice. We found that the activity of major glutamatergic cell populations in the DG is organized into infraslow oscillations (0.01–0.03 Hz) during NREM sleep. Although the DG is considered a sparsely active network during wakefulness, we found that 50% of granule cells and about 25% of mossy cells exhibit increased activity during NREM sleep, compared to that during wakefulness. Further experiments revealed that the infraslow oscillation in the DG was correlated with rhythmic serotonin release during sleep, which oscillates at the same frequency but in an opposite phase. Genetic manipulation of 5-HT receptors revealed that this neuromodulatory regulation is mediated by Htr1a receptors and the knockdown of these receptors leads to memory impairment. Together, our results provide novel mechanistic insights into how the 5-HT system can influence hippocampal activity patterns during sleep.