A functional network analysis of the mouse brain: Insights into sexual imprinting
Neuroscience ePoster by Alessandra Stella, Stefano Zucca, Nicole Mancin, Fabrizio Pizzagalli, Sarah M. Zala, Paolo Peretto and 2 more
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Abstract
Sexual imprinting, a learning process influencing mate choice, is observed across species. However, its neural mechanisms in complex networks like the mammalian brain are largely unexplored (Yamazaki et al. J., 1976; Asaba et al. , 2014.). We investigated how the mouse brain (C57BL/6 and wild house mice) represents imprinted and novel sensory signals, and whether the resulting functional networks display hub features. We captured neuronal activity using whole-brain immunolabeling for the immediate early gene cFos, iDISCO tissue clearing (Renier et al., 2014), and light-sheet fluorescence microscopy. This enabled us to visualize cFos-stained neurons and evaluate their density and average fluorescence intensity across all brain areas (Renier et al., 2016; Lupori et al., 2023). To compare different experimental conditions and mouse strains, we calculated correlations across various brain areas and used mean-centered partial least squares correlation analysis (PLS, Krishnan et al., 2011) to identify a set of latent variables in the multidimensional space formed by the different experimental conditions. By building undirected graphs from the combined results, we identified functional subnetworks and analyzed the graph topology to determine which areas acted as hubs in response to olfactory cues. Our results highlight the potential role of amygdalar and hypothalamic areas in the neural circuits involved in sexual imprinting in the mouse brain. This interdisciplinary approach paves the way for future investigations through miniscope imaging in selected hub areas. This work is supported by the Human Frontier Science Program and Compagnia di San Paolo.
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- Alessandra Stella, Stefano Zucca, Nicole Mancin et al. (2024). A functional network analysis of the mouse brain: Insights into sexual imprinting. FENS Forum 2024. https://doi.org/10.57736/87b6-4410 (opens in a new tab)
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