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bioRxiv · 10.1101/272492

A synaptic threshold mechanism for computing escape decisions

Abstract

Escaping from imminent danger is an instinctive behaviour fundamental for survival that requires classifying sensory stimuli as harmless or threatening. The absence of threat allows animals to forage for essential resources, but as the level of threat and potential for harm increases, they have to decide whether or not to seek safety1. Despite previous work on instinctive defensive behaviours in rodents2-13, little is known about how the brain computes the threat level for initiating escape. Here we show that the probability and vigour of escape in mice scale with the intensity of innate threats, and are well described by a theoretical model that computes the distance between threat level and an escape threshold. Calcium imaging and optogenetics in the midbrain of freely behaving mice show that the activity of excitatory VGluT2+ neurons in the deep layers of the medial superior colliculus (mSC) represents the threat stimulus intensity and is predictive of escape, whereas dorsal periaqueductal gray (dPAG) VGluT2+ neurons encode exclusively the escape choice and control escape vigour. We demonstrate a feed-forward monosynaptic excitatory connection from mSC to dPAG neurons that is weak and unreliable, yet necessary for escape behaviour, and which we suggest provides a synaptic threshold for dPAG activation and the initiation of escape. This threshold can be overcome by high mSC network activity because of short-term synaptic facilitation and recurrent excitation within the mSC, which amplifies and sustains synaptic drive to the dPAG. Thus, dPAG VGluT2+ neurons compute escape decisions and vigour using a synaptic mechanism to threshold threat information received from the mSC, and provide a biophysical model of how the brain performs a critical behavioural computation.

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BibTeXRIS

Evans, D. A., Stempel, V., Vale, R., Ruehle, S., Lefler, Y., Branco, T.. 2018-02-27. A synaptic threshold mechanism for computing escape decisions. https://doi.org/10.1101/272492

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