ArticlePLoS computational biology2025
Noradrenaline and acetylcholine shape functional connectivity organization of NREM substages: An empirical and simulation study.
Article in PLoS computational biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Spatiotemporally dynamic noradrenergic regulation of cortical networks.bioRxiv : the preprint server for biology · 2026Article
- A multi-frequency whole-brain neural mass model with homeostatic feedback inhibition.PLoS computational biology · 2026Article
- Sleep loss induces cholesterol-associated myelin dysfunction.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- A multi-frequency whole-brain neural mass model with homeostatic feedback inhibition.bioRxiv : the preprint server for biology · 2025Article
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9 authors.
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Abstract
Sleep onset is characterized by a departure from arousal, and can be separated into well-differentiated stages: NREM (which encompasses three substages: N1, N2 and N3) and REM (Rapid Eye Movement). Awake brain dynamics are maintained by various wake-promoting mechanisms, particularly the neuromodulators Acetylcholine (ACh) and Noradrenaline (NA), whose levels naturally decrease during the transition to sleep. The combined influence of these neurotransmitters on brain connectivity during sleep remains unclear, as previous models have examined them mostly in isolation or only in deep sleep. In this study, we analyze fMRI data obtained from healthy individuals and employ a whole-brain model to investigate how changes in brain neurochemistry during NREM sleep, specifically involving ACh and NA, affect the Functional Connectivity (FC) of the brain. FC analysis reveals distinct connectivity changes: a decrease in Locus Coeruleus (LC) connectivity with the cortex during N2 and N3, and a decrease in Basal Forebrain (BF) connectivity with the cortex during N3. Additionally, compared to Wakefulness (W), there is a transition to a more integrated state in N1 and a more segregated state in N3. Using a Wilson-Cowan whole-brain model, informed by an empirical connectome and a heterogeneous receptivity map of neuromodulators, we explored possible mechanisms underlying these dynamics. We fit the model adjusting the coupling and input-output slope of the whole-brain model to account for ACh and NA, respectively, and show that region-specific neurotransmitter effect is key to explain their effects on FC. This work enhances our understanding of neurotransmitters' roles in modulating sleep stages and their significant contribution to brain state transitions between different states of consciousness, both in health and disease.
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