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Reinwald, J.

Publications and source records attributed to Reinwald, J..

2 recordsLinked to original sources

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↗

Hierarchical cross-scale analysis identifies parallel ventral striatal networks coding for dynamic and stabilized olfactory reward predictions

The unbiased identification of brain circuits responsible for behavior and their local cellular computations is a challenge for neuroscience. We establish here a hierarchical cross-scale approach from behavioral modeling and fMRI in task-performing mice to cellular network dynamics to identify how reward predictions are represented in the forebrain upon olfactory conditioning. fMRI identified functional segregation in reward prediction and error computations among olfactory cortices and subcortical circuits. Among them, the olfactory tubercle contributed both to dynamic reward predictions and prediction error. In this region, cellular recordings revealed two parallel neuronal populations for prediction coding. One population produced stabilized predictions as distributed stimulus-bound transient network activity; the other evolved during anticipatory waiting and fully reflected predicted value in single-units, dynamically integrating the recent cue-specific history of uncertain outcomes. Thus, the cross-scale approach revealed regional functional differentiation among the distributed forebrain circuits with a limbic hotspot for multiple non-redundant reward prediction coding.

neuroscience↗