Mesolimbic dopamine ramps reflect environmental timescales.

Mesolimbic dopamine activity occasionally exhibits ramping dynamics, reigniting debate on theories of dopamine signaling. This debate is ongoing partly because the experimental conditions under which dopamine ramps emerge remain poorly understood. Here, we show that during Pavlovian and instrumental conditioning, mesolimbic dopamine ramps are only observed when the inter-trial interval is short relative to the trial period. These results constrain theories of dopamine signaling and identify a critical variable determining the emergence of dopamine ramps.

Few-shot learning: temporal scaling in behavioral and dopaminergic learning.

How do we learn associations in the world (e.g., between cues and rewards)? Cue-reward associative learning is controlled in the brain by mesolimbic dopamine1-4. It is widely believed that dopamine drives such learning by conveying a reward prediction error (RPE) in accordance with temporal difference reinforcement learning (TDRL) algorithms5. TDRL implementations are "trial-based": learning progresses sequentially across individual cue-outcome experiences. Accordingly, a foundational assumption-often considered a mere truism-is that the more cue-reward pairings one experiences, the more one learns this association. Here, we disprove this assumption, thereby falsifying a foundational principle of trial-based learning algorithms. Specifically, when a group of head-fixed mice received ten times fewer experiences over the same total time as another, a single experience produced as much learning as ten experiences in the other group. This quantitative scaling also holds for mesolimbic dopaminergic learning, with the increase in learning rate being so high that the group with fewer experiences exhibits dopaminergic learning in as few as four cue-reward experiences and behavioral learning in nine. An algorithm implementing reward-triggered retrospective learning explains these findings. The temporal scaling and few-shot learning observed here fundamentally changes our understanding of the neural algorithms of associative learning.

Dopamine D2 receptors in nucleus accumbens cholinergic interneurons increase impulsive choice.

Impulsive choice, often characterized by excessive preference for small, short-term rewards over larger, long-term rewards, is a prominent feature of substance use and other neuropsychiatric disorders. The neural mechanisms underlying impulsive choice are not well understood, but growing evidence implicates nucleus accumbens (NAc) dopamine and its actions on dopamine D2 receptors (D2Rs). Because several NAc cell types and afferents express D2Rs, it has been difficult to determine the specific neural mechanisms linking NAc D2Rs to impulsive choice. Of these cell types, cholinergic interneurons (CINs) of the NAc, which express D2Rs, have emerged as key regulators of striatal output and local dopamine release. Despite these relevant functions, whether D2Rs expressed specifically in these neurons contribute to impulsive choice behavior is unknown. Here, we show that D2R upregulation in CINs of the mouse NAc increases impulsive choice as measured in a delay discounting task without affecting reward magnitude sensitivity or interval timing. Conversely, mice lacking D2Rs in CINs showed decreased delay discounting. Furthermore, CIN D2R manipulations did not affect probabilistic discounting, which measures a different form of impulsive choice. Together, these findings suggest that CIN D2Rs regulate impulsive decision-making involving delay costs, providing new insight into the mechanisms by which NAc dopamine influences impulsive behavior.

Mesolimbic dopamine release conveys causal associations.

Learning to predict rewards based on environmental cues is essential for survival. It is believed that animals learn to predict rewards by updating predictions whenever the outcome deviates from expectations, and that such reward prediction errors (RPEs) are signaled by the mesolimbic dopamine system-a key controller of learning. However, instead of learning prospective predictions from RPEs, animals can infer predictions by learning the retrospective cause of rewards. Hence, whether mesolimbic dopamine instead conveys a causal associative signal that sometimes resembles RPE remains unknown. We developed an algorithm for retrospective causal learning and found that mesolimbic dopamine release conveys causal associations but not RPE, thereby challenging the dominant theory of reward learning. Our results reshape the conceptual and biological framework for associative learning.