Mapping neurotransmitter systems to the structural and functional organization of the human neocortex

Abstract

Neurotransmitter receptors support the propagation of signals in the human brain. How receptor systems are situated within macroscale neuroanatomy and how they shape emergent function remains poorly understood, and there exists no comprehensive atlas of receptors. Here we collate positron emission tomography scans in >1200 healthy individuals to construct a whole-brain 3-D normative atlas of 18 receptors and transporters across 9 different neurotransmitter systems. We find that receptor profiles align with structural connectivity and mediate function, including neurophysiological oscillatory dynamics and resting state hemodynamic functional connectivity. Using the Neurosynth cognitive atlas, we uncover a topographic gradient of overlapping receptor distributions that separates extrinsic and intrinsic psychological processes. Finally, we find both expected and novel associations between receptor distributions and cortical thinning patterns across 13 disorders. We replicate all findings in an independently collected autoradiography dataset. This work demonstrates how chemoarchitecture shapes brain structure and function, providing a new direction for studying multi-scale brain organization.

Hospitalisation for COVID-19 predicts long lasting cerebrovascular impairment: A prospective observational cohort study

“…Spatial correlation between Covid19 severity-induced cerebrovascular burden map and spatial patterns associated with a range of neurotransmitter receptor/transporters (Hansen et al, 2021b), selective genes relevant to SARS-CoV-2 brain entry (Iadecola et al, 2020) and brain metabolism parameters (Vaishnavi et al, 2010). Neurotransmitter receptors and transporters were selective to serotonin (5-HT1a, 5-HT1b, 5-HT2a, 5-HT4, 5-HT6, 5-HTT), norepinephrine (NET), histamine (H3), acetylcholine (ACh, A4B2, M1, VAChT), cannabinoid (CB1), opioid (MOR), glutamate (mGluR5), GABA (GABAa/bz) and dopamine (D1, D2, DAT).…”

“…We further assessed the spatial overlap between COVID-19-related cerebrovascular burden maps and a range of brain metabolic, neurotransmitter, protein expression and cell-type parameters, including i) existing receptor/metabolic templates and ii) gene transcription profiling maps. Templates of interest included metabolic rates of glucose, oxygen, and aerobic glycolysis (Vaishnavi et al, 2010) and receptor and transmitter maps across nine different neurotransmitter systems (Hansen et al, 2021b), all measured by positron emission tomography (PET). Gene expression maps (Hawrylycz et al, 2012) were based on key proteins implicated in SARS-Cov-2 cellular attachment (angiotensin converting enzyme-2, ACE2; neuropilin-1, NRP1; neuropilin-2, NRP2), processing (cathepsin-B, CTSB; cathepsin-L, CTSL) and viral defence (interferon type 2 receptors, IFNAR2; lymphocyte antigen 6-family member E, LY6E) (Iadecola et al, 2020; Yang et al, 2021).…”

Whole-brain modeling explains the context-dependent effects of cholinergic neuromodulation

“…We found that segregation is a signature of in-task performance, showing a link between functional network topology and behavior. Finally, under the hypothesis that nicotine decreases global correlations, we verified if the regional density of cholinergic-related receptors obtained by positron emission tomography (PET) [36][37][38][39][40][41] correlates with regional changes in FC. We observed that changes in nodal strength correlate with both the nodal SC strength, and the regional density of the α 4 β 2 nicotinic acetylcholine receptor.…”

“…To assess this possibility, we tested if the regional density of cholinergic-related receptors can explain the effects of nicotine on FC. We used regional density maps, obtained with PET [36][37][38][39][40][41], to test what acetylcholine-related receptors are associated with the changes in FC observed in the empirical data. Specifically, we considered density maps -parcellated using AAL90-for the α 4 β 2 nicotinic receptor, the M 1 muscarinic receptor, and the vesicular acetylcholine transporter (VAChT).…”

“…We informed the model with acetylcholine-related receptors maps obtained by PET [36][37][38][39][40][41]. Specifically, we used the nicotinic α 4 β 2 receptor density map into AAL90 parcellation.…”