Scientists at Newcastle University's Neural Circuits Laboratory, in collaboration with researchers at the Blue Brain Project (EPFL, Switzerland) and leading institutions in Spain, have published the landmark study that fundamentally advances understanding of the brain's chemical messengers, acetylcholine, dopamine and serotonin, known as neuromodulators.

The research, published in PLOS Computational Biology, combines cutting-edge experimental measurements with some of the most detailed computational models of the brain ever constructed, to reveal precisely how acetylcholine, dopamine and serotonin shape the electrical activity of tens of thousands of neurons simultaneously in the developing brain.

Dr Srikanth Ramaswamy, Senior Author and Head of the Neural Circuits Laboratory, Biosciences Institute, Newcastle University said: "Understanding how the brain's chemical systems regulate consciousness, sleep and attention has been a central challenge in neuroscience for decades. Our work provides a rigorous, quantitative framework for linking the anatomy of these systems to their functional impact - and generates entirely new, testable predictions for the field."

Mapping the brain's chemical blueprint

The team first mapped, with unprecedented precision, the density and spatial distribution of neuromodulatory fibres - the microscopic "wiring" through which these chemical signals are delivered - across all layers of the rat somatosensory cortex.

Using state-of-the-art immunocytochemical staining and stereological techniques, they found that the cholinergic (acetylcholine) system is the dominant neuromodulatory system, with a fibre varicosity density 2.3 times greater than that of the serotonergic system.

These detailed anatomical measurements were then integrated into a biophysically detailed computational model of the cortex, allowing the team to simulate - for the first time -  how activation of these three chemical systems alters the rhythmic electrical activity of a complete cortical microcircuit.

The key findings were:

• Acetylcholine powerfully suppresses slow brain oscillations (delta waves associated with deep sleep), consistent with its well-known role in promoting wakefulness and attention. Critically, the team's simulations suggest this effect is better explained by precise, synapse-to-synapse signalling rather than diffuse "volume" release — resolving a long-standing debate in the field.
• Dopamine and serotonin also desynchronise cortical activity, dampening slow oscillations in sensory brain regions — a role previously underappreciated for these neuromodulators outside of the prefrontal cortex.
• Serotonin uniquely induces faster theta oscillations, pointing to a previously unexplored role in sensory processing that may be relevant to understanding how serotonin-targeting antidepressants exert their therapeutic effects.
• Dopamine exerts the broadest anatomical influence, innervating both excitatory and inhibitory neurons across all cortical layers, suggesting a far-reaching role in regulating overall network state.

All experimental data and the full biophysical computational model have been made freely available to the global research community via open-access repositories, enabling scientists worldwide to build upon and extend these findings immediately upon publication.

Understanding could lead to treatments

Disruptions to neuromodulatory systems — particularly acetylcholine, dopamine and serotonin — underlie some of the most prevalent and debilitating neurological and psychiatric conditions, including Alzheimer's disease, Parkinson's disease, depression and schizophrenia. By providing a detailed, computationally grounded picture of how these systems operate at the level of individual neurons and circuits, this research lays critical groundwork for the development of more targeted and effective therapeutic strategies.

This work also directly informs the growing field of brain-inspired artificial intelligence, providing quantitative principles of neuromodulation that can be translated into next-generation neuromorphic and AI architectures.

Reference: Colangelo C, Muñoz A, Antonietti A, Sood V, Antón-Fernández A, Herttuainen J, Romani A, DeFelipe J, Ramaswamy S. (2026). Quantitative anatomy and biophysical modeling of ascending neuromodulatory systems in the developing rat neocortex. PLOS Computational Biology 22(6): e1014460. https://doi.org/10.1371/journal.pcbi.1014460

Open-access data and code: https://doi.org/10.5281/zenodo.14587678

Image

Image shows: A vertical slice through a single column of simulated cortical tissue, reconstructed from real anatomical and physiological data. Each thread-like strand represents a neuromodulatory fibre — the branching filaments through which the brain's three major "chemical messenger" systems (acetylcholine, dopamine, and serotonin) reach into the cortex. The coloured dots scattered along these fibres mark varicosities, the specialised release points where these chemicals are delivered to surrounding neurons, sculpting how brain circuits behave.

The image reflects the layered organisation of the cortex: near the top of the column, fibres cluster more densely in warmer green and gold tones, while deeper layers show a shift toward blues, magentas, and finally darker, sparser colouring near the base — mirroring how each neuromodulatory system distributes unevenly across the six layers of the neocortex. This visualisation, generated from thousands of digitally reconstructed neurons and fibres, forms the anatomical backbone of a large-scale computer model used to simulate how neuromodulatory signals shape brain activity, including patterns linked to sleep, wakefulness, and attention.