Abstract
The study of brain activity and its function requires the development of computational models alongside experimental investigations to explore different effects of multiple mechanisms at play in the central nervous system. Chemical neuromodulators, such as dopamine, play central roles in regulating the dynamics of neuronal populations. In this work, we propose a modular framework to capture the effects of neuromodulators at the neural mass level. Using this framework, we formulate a specific model for dopamine dynamics affecting D1-type receptors. We detail the dynamical repertoire associated with dopamine concentration evolution and characterize the transitions across qualitatively different oscillatory states as a function of relevant parameters, along with the variations in frequency of the emergent multi-scale oscillations.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 23-43 |
| Number of pages | 21 |
| Journal | Journal of Computational Neuroscience |
| Volume | 54 |
| Issue number | 1 |
| DOIs | |
| State | Published - Mar 2026 |
Bibliographical note
Publisher Copyright:© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2026.
Keywords
- Dopamine
- Mean-field
- Neural mass model
- Neuromodulation
PubMed: MeSH publication types
- Journal Article
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