Sep 22 – 24, 2026
SISSA
Europe/Rome timezone

Hippocampal neural representation tracks exploration strategies over time

Sep 22, 2026, 3:30 PM
2h 30m
Aula Magna “Paolo Budinich” (SISSA)

Aula Magna “Paolo Budinich”

SISSA

Via Bonomea 265, Trieste

Speaker

Giulia Lorenzini (Department of Physics, University of Turin, Turin, Italy)

Description

Memory integration in the hippocampus is central to constructing coherent representations of environments that unfold across space and time. Beyond current position, hippocampal activity has been proposed to approximate a predictive, decision-oriented map of future states, supporting anticipation of possible trajectories (Stachenfeld et al., 2017). Here, we asked whether CA1 population dynamics track not only where an animal is, but how its exploratory transition structure reorganizes with experience and context.
We analyzed single-photon calcium imaging from hippocampal CA1 in 13 mice navigating a six-arm maze across three days (Days 1, 3, 5), each with a morning session in an empty maze and an afternoon session enriched with objects. From neuronal coactivity we extracted time-resolved functional connectivity networks, and modeled arm-visit sequences as discrete-state Markov chains to quantify transition probabilities, entropy, spectral gap, and mixing dynamics.
Functional connectivity states recapitulated the maze's spatial organization, with within-arm similarity significantly exceeding cross-arm similarity, and became progressively more stable with experience, while still drifting relative to an early (Day-1) reference. In parallel, the behavioral transition structure became more organized across days and was systematically constrained by object exposure, with ~37% fewer arm transitions, reduced rebound (self-loop) probability, and lower choice entropy (all p < 0.001–0.026), a context-dependent narrowing of the exploratory repertoire. Crucially, this reorganization showed a transient, non-monotonic change at Day 3 (spectral-gap dip Δ = −0.084, p = 0.013; mixing-time peak, p = 0.046), concurrent with reduced FC self-similarity on the same days, suggesting network and behavioral structure reorganize together, not merely share a spatial substrate.
Together, these findings support the view that CA1 population dynamics encode more than current position. Instead, they reflect the evolving structure of possible transitions, consistent with a predictive map in which spatial representations are shaped by experience, context, and future-oriented behavioral organization.

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Author

Giulia Lorenzini (Department of Physics, University of Turin, Turin, Italy)

Co-authors

Dr Giuseppe Gava (Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK) Dr Nicola Pedreschi (Department of Translational Biomedicine and Neuroscience, University of Bari, Italy) Dr Pavel Perestenko (Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK) Prof. Renaud Lambiotte (Mathematical Institute, University of Oxford, Oxford, UK) Prof. Giovanni Petri (NP Lab, Network Science Institute, Northeastern University London, London, UK)

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