Computational Models of Neuromodulation

Neuromodulation refers to the regulation of neural activity by neurotransmitters such as dopamine, serotonin, acetylcholine, and norepinephrine, which influence brain states, behavior, and cognitive functions. Unlike fast synaptic transmission, neuromodulators act over broader spatial and temporal scales, altering neuronal excitability, synaptic strength, and circuit dynamics. Understanding these complex modulatory effects is essential for unraveling mechanisms of attention, learning, emotion, and decision-making, as well as for developing treatments for both psychiatric and neurological disorders. Computational models play a key role in exploring how neuromodulators shape neural function, allowing researchers to simulate their influence on individual neurons, neural networks, and behavior. Furthermore, recent advances in experimental neuroscience and computational techniques have enabled the development of increasingly detailed and mechanistic models of neuromodulation.

Despite their critical role in regulating brain function, the mechanisms by which neuromodulators influence neural activity and behavior remain incompletely understood. Neuromodulatory systems operate on diverse spatial and temporal scales, affecting synaptic plasticity, neuronal excitability, and network dynamics in complex and often nonlinear ways. And whilst experimental studies have made significant progress in mapping neuromodulatory pathways and effects, the integration of this knowledge into cohesive, mechanistic frameworks remains challenging. Yet, Computational modeling offers a powerful approach to address this gap, as models can help simulate the effects of neuromodulators on single neurons, circuits, and behavior, allowing for systematic exploration of their roles in learning, attention, decision-making, and emotional regulation. Recent advances in neuroimaging, optogenetics, and data-driven modeling have provided new opportunities to develop biologically realistic simulations of neuromodulatory processes.

This Research Topic aims to highlight computational studies that investigate the functional impact of neuromodulation. We welcome models of neuromodulatory dynamics, interactions with neural circuits, and implications for cognition or disease. By bringing together theoretical and data-driven approaches, this collection seeks to advance our understanding of how neuromodulators shape brain function and guide adaptive behavior.

We specifically welcome papers on computational models of neuromodulation. We invite studies exploring how modulators like dopamine, serotonin, acetylcholine, and norepinephrine influence neural activity, plasticity, circuits, and behavior. Some potential key themes include modeling their roles in learning, decision-making, emotion, and brain states. Adding to this, contributions may include biophysical models, large-scale simulations, or data-driven approaches. Finally, we also encourage work linking models to experimental data or neuromodulatory dysfunction in disease. Interdisciplinary studies combining neuroscience, biology, and behavior are especially welcome.