{"doi":"10.1002/hbm.70442","title":"Characterizing Spatial Associations Between <scp>GluCEST MRI</scp> and Neurotransmitter Receptor Density in the Human Cortex","abstract":"ABSTRACT Glutamate‐weighted Chemical Exchange Saturation Transfer (GluCEST) captures in vivo glutamate (Glu) levels with high spatial resolution and has been used to assess glutamatergic function in healthy and clinical populations. While GluCEST is well‐validated against proton magnetic resonance spectroscopy ( 1 H‐MRS), its correspondence with local expression of glutamatergic neurotransmitter receptors remains unclear. Recent initiatives, such as Neuromaps, have collated positron emission tomography (PET) data into curated, publicly available databases, providing a novel opportunity to establish convergence in the regional distribution of GluCEST and normative receptor density maps. Here, we examine the spatial correspondence between GluCEST signal and PET‐based cortical receptor density levels of N‐methyl‐D‐aspartate (NMDA), metabotropic glutamate receptor 5 (mGluR5), and gamma‐aminobutyric acid A (GABA A ). A cohort of 86 participants (age: 22.7 years [3.7 years], 45% female) included 34 individuals with no psychiatric history, 31 participants with significant sub‐threshold psychosis symptoms, and 21 participants with first‐episode psychosis. All participants underwent 7T GluCEST imaging. Data were processed using in‐house and field‐standard pipelines. Mean receptor density levels were computed using the Neuromaps PET receptor density data. GluCEST and Neuromaps data were parcellated using the Cammoun 500 atlas. Pearson correlations assessed the correspondence between GluCEST signal and PET‐based receptor density, and spin tests were used for empirical significance testing of the spatial correlations across all parcels. Sensitivity analyses examined the effect of age, sex, and diagnosis and other covariates. Exploratory analyses assessed regional variability across cytoarchitecturally defined von Economo regions and overall trends with gene expression. Analyses were performed in Python and R. GluCEST signal converged with the regional distribution of both NMDA ( r = 0.23, p spin = 0.039) and GABA A ( r = 0.35, p spin = 0.004). There was no significant effect for mGluR5 ( r = 0.09, p spin &gt; 0.05). Exploratory analyses indicated that cytoarchitecturally defined von Economo regions showed variable GluCEST‐receptor association patterns across the cortex and that gene expression patterns generally correspond with receptor density findings. Our findings reveal a positive spatial association between GluCEST signal in a transdiagnostic cohort and atlas‐based PET‐derived cortical receptor density of NMDA and GABA A , and a nominal positive association with mGluR5. The association between GluCEST and NMDA suggests that regions with dense ionotropic Glu receptors exhibit higher Glu levels, while the coupling between GluCEST and GABA A may reflect tight regulation of excitation‐inhibition balance. Regional differences in these associations point to the potential influence of local cytoarchitectural specialization on Glu‐receptor dynamics. These results advance our understanding of the neurobiological basis of GluCEST and highlight its potential utility as a non‐invasive tool for probing receptor‐mediated glutamatergic neurotransmission.","journal":"Human Brain Mapping","year":2025,"id":549710,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9505,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":811459,"name":"Golia Shafiei","orcid":"0000-0002-2036-5571","position":1,"is_corresponding":false},{"id":1444837,"name":"Ally Atkins","orcid":null,"position":2,"is_corresponding":false},{"id":263910,"name":"Monica E. Calkins","orcid":"0000-0002-0546-0263","position":3,"is_corresponding":false},{"id":230043,"name":"Ruben C. Gur","orcid":"0000-0002-9657-1996","position":4,"is_corresponding":false},{"id":469610,"name":"Ravi Prakash Reddy Nanga","orcid":"0000-0002-3644-5656","position":5,"is_corresponding":false},{"id":1444838,"name":"Ravinder K. Reddy","orcid":null,"position":6,"is_corresponding":false},{"id":371332,"name":"Melanie A. Matyi","orcid":"0000-0002-4623-2080","position":7,"is_corresponding":false},{"id":1444839,"name":"Jacquelyn Stifelman","orcid":null,"position":8,"is_corresponding":false},{"id":394691,"name":"Heather Robinson","orcid":"0000-0002-3566-2253","position":9,"is_corresponding":false},{"id":274059,"name":"Erica B. Baller","orcid":"0000-0002-7987-3773","position":10,"is_corresponding":false},{"id":52271,"name":"Russell T. Shinohara","orcid":"0000-0001-8627-8203","position":11,"is_corresponding":false},{"id":275711,"name":"Kosha Ruparel","orcid":"0000-0001-9274-4303","position":12,"is_corresponding":false},{"id":103392,"name":"Kristin A. Linn","orcid":"0000-0001-8463-8084","position":13,"is_corresponding":false},{"id":230041,"name":"Daniel H. Wolf","orcid":"0000-0002-9731-8781","position":14,"is_corresponding":false},{"id":1444840,"name":"T. E. Satterthwaite","orcid":null,"position":15,"is_corresponding":false},{"id":227422,"name":"Corey T. McMillan","orcid":"0000-0002-7581-6405","position":16,"is_corresponding":false},{"id":235291,"name":"David R. Roalf","orcid":"0000-0002-1728-9782","position":17,"is_corresponding":false},{"id":261875,"name":"Maggie Pecsok","orcid":"0000-0001-6806-5423","position":0,"is_corresponding":true}],"reference_count":67,"raw_metadata":null,"created_at":"2026-07-19T02:54:12.321988Z","pmid":"41437520","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}