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bioRxiv · 10.1101/2023.01.20.523817

Adaptive robustness through incoherent signaling mechanisms in a regenerative brain

Wang, B.·Bray, S. R.·Wyss, L. S.·Chai, C.·Lozada, M. E.
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Abstract

Animal behavior emerges from collective dynamics of interconnected neurons, making it vulnerable to connectome damage. Paradoxically, many organisms maintain significant behavioral output after large-scale neural injury. Molecular underpinnings of this extreme robustness remain largely unknown. Here, we develop a quantitative behavioral analysis pipeline to measure previously uncharacterized long-lasting latent memory states in planarian flatworms during whole-brain regeneration. By combining >20,000 animal trials with neural population dynamic modeling, we show that long-range volumetric peptidergic signals allow the planarian to rapidly reestablish latent states and restore coarse behavior after large structural perturbations to the nervous system, while small-molecule neuromodulators gradually refine the precision. The different time and length scales of neuropeptide and small-molecule transmission generate incoherent patterns of neural activity which competitively regulate behavior and memory. Controlling behavior through opposing communication mechanisms creates a more robust system than either alone and may serve as a generic approach to construct robust neural networks.

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Wang, B., Bray, S. R., Wyss, L. S., Chai, C., Lozada, M. E.. 2023-01-21. Adaptive robustness through incoherent signaling mechanisms in a regenerative brain. https://doi.org/10.1101/2023.01.20.523817

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