Flexible learning and decision-making are thought to rely on the brain’s capacity to reconfigure synaptic connections in response to experience. Foundational work across sensory systems has long suggested that synaptic plasticity supports both perceptual and associative learning. More recently, studies employing automated and ethologically relevant behavioral paradigms in freely moving animals have begun to uncover how neural circuits adapt perceptual strategies, shift between choice policies, and adjust sensorimotor behavior according to internal states and environmental contingencies.

Beyond specific sensory modalities, comparable computational and physiological principles appear to underlie adaptive decision-making under uncertainty, where neural systems must balance exploration and exploitation as contexts evolve.

Advances that integrate automated behavioral approaches, reinforcement learning models, and predictive coding theory indicate that behavioral flexibility may arise from hierarchical mechanisms of prediction-error minimization. Across species and sensory domains, the nervous system seems to continuously evaluate the precision of its predictions, adjusting learning rates dynamically in response to environmental volatility and internal state.
Neuromodulatory systems, particularly acetylcholine, noradrenaline, dopamine, and serotonin, emerge as central regulators of these adaptive processes. They modulate precision weighting and synaptic gain, influence when and where plasticity occurs, and coordinate oscillatory dynamics that gate information flow and behavioral flexibility. From a predictive processing perspective, these systems are thought to modulate the confidence assigned to sensory evidence versus prior expectations, thereby linking cellular mechanisms of plasticity to higher-order adaptive control. Yet several fundamental questions remain:

i) How do neuromodulatory signals influence plasticity rules across cortical and subcortical circuits?
ii) How are perceptual learning and decision-making modulated by arousal, task structure, or reward contingencies?
iii) How do different neuromodulators coordinate precision weighting to support flexible learning under volatility and uncertainty?
iv) To what extent do findings from rodent models generalize across species, sensory modalities, or cognitive domains?
v) How can predictive, neuromodulator-driven mechanisms be leveraged to enhance rehabilitation, artificial learning systems, or adaptive control?

This Research Topic welcomes contributions integrating synaptic, circuit-level, and behavioral perspectives. We encourage submissions from systems neuroscience, computational modeling, behavioral ecology, and translational research, particularly those addressing predictive learning, decision flexibility, and sensorimotor adaptation through the lens of neuromodulation and plasticity. Studies employing non-invasive neuromodulation techniques such as transcranial electrical stimulation (tES) to examine or enhance neuroplasticity and adaptive learning are also welcome.

Potential subtopics include:

• Neuromodulatory influences on synaptic and circuit plasticity across sensory and association cortices
• Cortical gain modulation and discrimination learning across modalities
• GABAergic circuit plasticity and critical periods in sensory development
• Predictive processing and precision weighting in perceptual and decision learning
• Adaptive learning mechanisms in rodent, primate, and human models
• Dynamic modulation of cortical oscillations during learning and attention
• Exploration–exploitation dynamics and neuromodulator-driven behavioral variability
• Sensorimotor adaptation and target tracking under changing conditions
• Descending control of cortical plasticity from frontal and neuromodulatory centers
• Cross-species and ecological approaches to adaptive learning and uncertainty resolution
• Stochastic resonance and the enhancement of learning through noise and variability
• Cross-modal neuromodulation: integration and gating across sensory systems
• State-dependent learning: the roles of arousal, vigilance, and motivation
• Targeting neuromodulatory systems to enhance rehabilitation and artificial learning
• Non-invasive electrical or magnetic neuromodulation (e.g., tES, TMS) approaches to probe and enhance cortical plasticity.

Are you interested in contributing a manuscript to this Research Topic?

Neuromodulation and plasticity: Gateways to flexible memory and learning