Mice identify subgoal locations through an action-driven mapping process

Shamash, Philip; Lee, Sebastian; Saxe, Andrew M.; Branco, Tiago

doi:10.1016/j.neuron.2023.03.034

Cited by 6 publications

(6 citation statements)

References 57 publications

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“…Studies of escape behaviour in the wild have highlighted how flexible the flight action must be since animals often engage in a complex series of stop-and-go events while computing and executing escape trajectories directed to safe locations (1, 10, 19, 73–75). Our results raise the hypothesis that inhibitory neurons in the dPAG might integrate spatial and sensory information to implement flexible speed adjustments during escape and determine when safety has been reached through modulation of their firing rates (41, 76, 77).…”

Section: Discussionsupporting

confidence: 53%

Tonically active GABAergic neurons in the dorsal periaqueductal gray control the initiation and execution of instinctive escape

Stempel,

Evans,

Pavón Arocas

et al. 2023

Preprint

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To avoid predation, animals perform defensive actions that are both instinctive and adaptable to the environment. In mice, the decision to escape from imminent threats is implemented by a feed-forward circuit in the midbrain, where excitatory VGluT2+neurons in the dorsal periaqueductal gray (dPAG) compute escape initiation and escape vigour from threat evidence. Here we show that GABAergic VGAT+neurons in the dPAG dynamically control this process by modulating the excitability of excitatory escape neurons. Usingin vitropatch clamp andin vivoneural activity recordings in freely behaving mice we found that VGAT+dPAG neurons fire action potentials tonically in the absence of synaptic inputs and are a major source of synaptic inhibition to VGluT2+dPAG neurons. Activity in these spontaneously firing VGAT+cells transiently decreases at escape onset and increases during escape, peaking at escape termination. Optogenetically increasing or decreasing VGAT+dPAG activity bidirectionally changes the probability of escape when the stimulation is delivered at the time of threat onset, and the duration of escape when delivered after escape initiation. We conclude that the activity of tonically firing VGAT+dPAG neurons sets a threshold for escape initiation and controls the execution of the flight locomotor action.

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Section: Discussionsupporting

confidence: 53%

Tonically active GABAergic neurons in the dorsal periaqueductal gray control the initiation and execution of instinctive escape

Stempel,

Evans,

Pavón Arocas

et al. 2023

Preprint

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“…For the execution of efficient strategies, the mPFC may integrate several sets of information into the current neural operations. Space-based information and action-based self-motion information are required for spatial learning (Robinson et al, 2020; Shamash et al, 2023). These items of information are represented by neural spiking in the HPC and PPC, respectively (Alexander et al, 2022; Buzsáki & Moser, 2013; Orban et al, 2021; Whitlock, 2017), structures that are anatomically connected with the mPFC (Jay & Witter, 1991; Kolb & Walkey, 1987; Swanson, 1981; Zingg et al, 2014).…”

Section: Discussionmentioning

confidence: 99%

Synchronization of the prefrontal cortex with the hippocampus and posterior parietal cortex is navigation strategy-dependent during spatial learning

García,

Torres,

Chacana-Véliz

et al. 2024

Preprint

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During goal-directed spatial learning, subjects progressively change their navigation strategies to increase their navigation efficiency, an operation supported by the medial prefrontal cortex (mPFC). However, how the mPFC may integrate relevant information in a wider memory networks involving the hippocampus (HPC) and the posterior parietal cortex (PPC) is poorly understood. We recorded local-field potential and neuronal firing simultaneously from the mPFC, HPC and PPC in mice subjected to spatial memory acquisition in the Barnes maze. During navigation trials, animals demonstrated two consecutive behavioral stages: searching and exploration. Throughout training, mice gradually switched from less efficient (non-spatial) to more efficient (spatial) goal-oriented strategies exclusively during the searching stage. 4-Hz and theta (6-12 Hz) oscillations were detected during spatial navigation in the three recorded areas associated with episodes of immobility and locomotion, respectively. The entrainment of prefrontal gamma oscillations (60-100 Hz) by hippocampal and parietal 4-Hz and theta oscillations, as well as the incidence of prefrontal gamma, was higher when mice implemented spatial strategies during the searching stage. Interestingly, 4-Hz and theta from HPC and PPC also synchronized the spike-timing of prefrontal neurons, which was maximum during spatial strategies in the searching stage. Finally, neurons recorded in the mPFC increased their task stage firing selectivity when they used spatial strategy. Altogether, these results provide evidence for the neural mechanisms underlying the prefrontal large-scale coordination with distributed neural networks during spatial learning.

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“…In line with this possibility, not all GD processes are slow and costly (Pacherie, 2018), as complex information integration can lead to fast, implicit, and even unconscious estimates of the best action-outcome option, combining automaticity with optimality (Bechara et al, 1997;Carroll et al, 2019;Custers, 2023;LeDoux & Daw, 2018). Overall, recent research in humans (Fischer et al, 2020;Moors & Fischer, 2019;Sporrer et al, 2023;Wise et al, 2023) and rodents (Campagner et al, 2023;Claudi et al, 2022;Evans et al, 2019;Shamash et al, 2023;Vale et al, 2017) converge in assigning a more important role to GD defensive responses than previously thought, both under low and relatively imminent threat (for reviews, see Cain, 2019;LeDoux & Daw, 2018;Moors, 2017). Although the outcome of an SR and of a GD process may be the same (i.e., avoidance of the threat), the computations underlying the two processes would still differ and imply different degrees of flexibility in action selection.…”

Section: Introductionmentioning

confidence: 99%

Social threat avoidance depends on action-outcome predictability

Sequestro,

Serfaty,

Grèzes

et al. 2024

Preprint

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Adaptative action selection in threatening social contexts, for example when facing aggressive individuals, is core to social behavior. It is debated whether, when facing threat, initial action opportunities are mostly determined by automatic action tendencies – i.e., reactive stimulus-response (SR) associations – or by rapid and implicit goal-directed (GD) processes, which depend on the predicted consequences of available actions. To investigate the balance between SR and GD, we conducted three experiments manipulating the predictability of action-outcomes associations, in a novel approach-avoidance decision task in virtual reality. Participants presented a greater avoidance rate from angry individuals when the action-outcome association was predictable. Computationally, this was subtended by more efficient evidence accumulation, as indicated by an increased drift rate. Furthermore, cardiac deceleration around the time of choice was greater in the predictable condition and allowed the value attributed to the outcome to be better integrated into the decision. Finally, while most participants avoided angry individuals only under predictability, supporting a predominant role of GD processes, a minority of them avoided regardless of predictability. Overall, our results shed light on the computational architecture of social avoidance, opening interesting new research and clinical perspectives.

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Mice identify subgoal locations through an action-driven mapping process

Cited by 6 publications

References 57 publications

Tonically active GABAergic neurons in the dorsal periaqueductal gray control the initiation and execution of instinctive escape

Tonically active GABAergic neurons in the dorsal periaqueductal gray control the initiation and execution of instinctive escape

Synchronization of the prefrontal cortex with the hippocampus and posterior parietal cortex is navigation strategy-dependent during spatial learning

Social threat avoidance depends on action-outcome predictability

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