Orbitofrontal noradrenaline supports adaptive learning-rate adjustment in probabilistic reversal learning - Hadrien Plat; Coline Chevallier; Alessandro Piccin; Alain R. Marchand; Jérémie Naudé; Etienne Coutureau (Proceedings of the National Academy of Sciences, 2026)
Adaptive decision-making in dynamic environments requires flexible adjustment of learning speed to balance stability and flexibility. When outcomes are highly stochastic, learners must avoid over-interpreting noise and update more slowly, whereas in volatile environments where contingencies change frequently, learning should accelerate to rapidly incorporate new evidence. Theories propose that internal estimates of uncertainty tune learning rates through neuromodulation-dependent mechanisms. Here, we investigated how noradrenergic inputs from the locus coeruleus (LC) to the orbitofrontal cortex (OFC) support adaptive learning under uncertainty. We show that, in a probabilistic reversal learning task performed across different levels of stochasticity, rats exhibited behavior best explained by an adaptive reinforcement-learning model in which learning rates dynamically adjusted according to model-estimated stochasticity and volatility, outperforming standard fixed-rate models. Noradrenaline release in the OFC closely tracked trial-by-trial, model-derived volatility estimates around contingency changes. Disrupting LC→OFC noradrenergic inputs reproduced the model-predicted impairment in adaptive learning-rate adjustment associated with model-estimated volatility. Together, these findings identify OFC noradrenergic signaling as a key circuit mechanism supporting learning-rate adjustment in response to internal estimates of volatility during adaptive decision-making under uncertainty.