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Nierwetberg, S.

Publications and source records attributed to Nierwetberg, S..

2 recordsLinked to original sources

Learning temporal structure engages hippocampus and guides value-based behaviour

The ability to learn and exploit structured relationships between events is fundamental to adaptive behaviour and episodic-like memory, yet the neural mechanisms that support such learning remain poorly understood. Progress has been limited by the difficulty of dissociating relational structure from sensory cues, value, and motor output in experimentally tractable tasks. Here we introduce a temporally structured olfactory task for mice that isolates relational structure from cue identity and reward statistics. Mice rapidly learned to use the ordered relationship between two sequentially presented odours to predict outcome. Because individual odours were equally associated with reward across contexts, their predictive value depended entirely on their relationship to preceding cues. Behavioural analyses and reinforcement learning models revealed a gradual shift to the use of structured representations as learning progressed. Dopamine activity in the nucleus accumbens reflected this transition. Over learning, identical sensory inputs became associated with opposite predicted outcomes depending only on their temporal position, consistent with dopamine prediction errors reflecting latent task structure rather than cue identity. Trial-by-trial variability in dopamine dynamics was quantitatively captured by the same models that described behavioural strategy, linking dopamine prediction errors directly to these learned structural representations. Finally, using a matched control task that preserved sensory input and reward statistics while eliminating structure, we found that learning and using temporal structure selectively increased ventral hippocampal activity. Together, these results establish a minimal, non-spatial paradigm for studying structural learning in mice, link behavioural representations to dopamine signalling, and show that isolating relational structure from sensory and reward confounds selectively recruits hippocampal circuitry long theorised to support it.

neuroscience↗

Aeon: an open-source platform to study the neural basis of ethological behaviours over naturalistic timescales

Ethological behaviours are a powerful tool for neuroscience since they leverage the robust neural computations shaped by the species evolution to study the neural basis of cognitive functions. However, such behaviours are often transitory and dependent on factors that vary over space, time and number of individuals, making them difficult to capture with standard laboratory tasks. Here we present Aeon, an open-source platform designed for continuous, long-term study of self-guided behaviours in multiple mice and simultaneous recording of brain activity within large, customizable habitats. By integrating specialized modules for navigation, nesting and sleeping, escaping, foraging, and social interaction, Aeon enables the expression of key ethological behaviours while achieving experimental control and multi-dimensional quantifications from sub-millisecond to month-long durations. Its software architecture ensures robust data acquisition via many synchronized data streams and delivers a new standardised, unified data format that yields seamless, integrated analysis pipelines. Using assays such as digging-to-threshold and social foraging, Aeon reveals how mice adapt strategies in a changing environment and in response to conspecifics. Aeon bridges ecological relevance with rigorous experimental control to advance our understanding of how neural circuit activity gives rise to a range of highly conserved and adaptive behaviours.

neuroscience↗