Biology subjects

Scheller, M. F.

Publications and source records attributed to Scheller, M. F..

3 recordsLinked to original sources

bioRxiv2026

Error-driven representation learning in the mesolimbic system

In reinforcement learning, an agent learns to map representations of the environment state to predictions of future reward. Most prior work in neuroscience has assumed a fixed representation and studied how reward prediction errors (thought to be conveyed by phasic dopamine signals) are used to update the mapping from representations to predictions. However, work in machine learning has demonstrated that much more powerful predictive systems can be learned by using the errors to update the representations themselves. We study whether the brain does something similar by leveraging simultaneous recordings of striatal projection neurons in the olfactory tubercle (putatively representing state features) and dopamine neurons in the ventral tegmental area. We show that trial-by-trial changes in striatal activity are more consistent with dopamine-driven representation learning than a variety of alternative updating schemes. This result suggests a convergence of representation learning principles in biological and artificial systems.

neuroscience↗

bioRxiv2026

Sniffing Shapes Dopamine Signals for Reward Prediction

Adaptive behaviors depend on predicting outcomes from sensory evidence. Dopamine neurons in the ventral tegmental area (VTA) broadcast reward-prediction signals that guide learning. Yet the principles functionally coordinating information flow from input regions to VTA are incompletely understood. In the olfactory system, the sniff cycle structures sampling and odor encoding. We therefore asked whether this rhythm also entrains the ventral striatum to VTA communication and if so, how this shapes the implementation of predictive coding in dopamine neurons. We recorded identified dopamine neurons throughout olfactory conditioning and found that their firing shifted systematically to the post-inspiratory phase of the sniff cycle with learning. This temporal realignment predicted a neurons engagement in value encoding along the optimism-pessimism-spectrum of distributional reinforcement learning. This is associated with an enhanced phase-gated communication channel from the striatal olfactory tubercle to dopamine neurons, the strength of which predicts task performance. Thus, the sniffing rhythm provides a scaffold for information flow, revealing a phase-gating mechanism for the integration of outcome predicting sensory evidence to dopamine neurons during reinforcement learning. Significance StatementPredicting the future from sensory cues is central to adaptive behaviors. We show that sniffing temporally organizes the flow of information between the olfactory tubercle of ventral striatum and midbrain dopamine neurons during odor-guided learning in mice. Phase-specific coupling in the respiratory cycle determines when sensory information reaches dopamine neurons and how predictive signals are encoded. These findings link active-sensing rhythms to predictive reinforcement signals. This temporal scaffold yields a gradient of "optimistic" to "pessimistic" predictions consistent with distributional reinforcement-learning theories. These insights contribute to a better understanding of the large-scale computations across multiple brain regions to predict future outcomes.

neuroscience↗

bioRxiv2025

Stable clique membership in mouse societies requires oxytocin-enabled social sensory states

The ability to form stable de novo relationships in complex environments is essential for social functioning and is impaired in severe psychiatric disorders including autism. Yet, the neurobiological basis and cognitive processes enabling the formation of stable bonds in larger groups remain poorly understood, thereby limiting our ability to develop effective therapies. Here, we establish a semi-naturalistic model of clique formation in mouse societies, where individuals are tracked longitudinally from massive video data. Small, stable rich-clubs develop within these mouse social networks. Consistent with human rich-clubs, these cohesive cliques tended to have high social rank and exerted influence on non-members. Interestingly, neither prior rich-club-membership in a different group nor kinship facilitated entry into rich-clubs. Mimicking sparse population genetics, we probed the open question whether a subtle neuro-cognitive phenotype, namely impaired induction of social sensory processing states by cortical oxytocin signaling, disrupts higher-order social bonding in these complex social environments. Despite preserved social motivation, mice with alterations in this oxytocin subsystem failed to join rich-clubs. They approached group members less consistently, and connections from others towards them fluctuated more as well. This reciprocal disorganization highlights how interactional dynamics within social networks can amplify individual-level deficits, consistent with models of emergent properties of social behavior. These findings underscore the role of oxytocin in tuning sensory systems into a social processing state. Its dysfunction affects an individuals ability to establish stable relationships in complex social networks, with profound implications for social functioning deficits in psychiatric disorders.

neuroscience↗