Dynamical prefrontal population coding during defensive behaviours.

Coping with threatening situations requires both identifying stimuli that predict danger and selecting adaptive behavioural responses to survive1. The dorsomedial prefrontal cortex (dmPFC) is a critical structure that is involved in the regulation of threat-related behaviour2-4. However, it is unclear how threat-predicting stimuli and defensive behaviours are associated within prefrontal networks to successfully drive adaptive responses. Here we used a combination of extracellular recordings, neuronal decoding approaches, pharmacological and optogenetic manipulations to show that, in mice, threat representations and the initiation of avoidance behaviour are dynamically encoded in the overall population activity of dmPFC neurons. Our data indicate that although dmPFC population activity at stimulus onset encodes sustained threat representations driven by the amygdala, it does not predict action outcome. By contrast, transient dmPFC population activity before the initiation of action reliably predicts avoided from non-avoided trials. Accordingly, optogenetic inhibition of prefrontal activity constrained the selection of adaptive defensive responses in a time-dependent manner. These results reveal that the adaptive selection of defensive responses relies on a dynamic process of information linking threats with defensive actions, unfolding within prefrontal networks.

Modulation of cortical slow oscillatory rhythm by GABAB receptors: an in vitro experimental and computational study.

KEY POINTS: We confirm that GABAB receptors (GABAB -Rs) are involved in the termination of Up-states; their blockade consistently elongates Up-states. GABAB -Rs also modulate Down-states and the oscillatory cycle, thus having an impact on slow oscillation rhythm and its regularity. The most frequent effect of GABAB -R blockade is elongation of Down-states and subsequent decrease of oscillatory frequency, with an increased regularity. In a quarter of cases, GABAB -R blockade shortened Down-states and increased oscillatory frequency, changes that are independent of firing rates in Up-states. Our computer model provides mechanisms for the experimentally observed dynamics following blockade of GABAB -Rs, for Up/Down durations, oscillatory frequency and regularity. The time course of excitation, inhibition and adaptation can explain the observed dynamics of the network. This study brings novel insights into the role of GABAB -R-mediated slow inhibition on the slow oscillatory activity, which is considered the default activity pattern of the cortical network. ABSTRACT: Slow wave oscillations (SWOs) dominate cortical activity during deep sleep, anaesthesia and in some brain lesions. SWOs are composed of periods of activity (Up states) interspersed with periods of silence (Down states). The rhythmicity expressed during SWOs integrates neuronal and connectivity properties of the network and is often altered under pathological conditions. Adaptation mechanisms as well as synaptic inhibition mediated by GABAB receptors (GABAB -Rs) have been proposed as mechanisms governing the termination of Up states. The interplay between these two mechanisms is not well understood, and the role of GABAB -Rs controlling the whole cycle of the SWO has not been described. Here we contribute to its understanding by combining in vitro experiments on spontaneously active cortical slices and computational techniques. GABAB -R blockade modified the whole SWO cycle, not only elongating Up states, but also affecting the subsequent Down state duration. Furthermore, while adaptation tends to yield a rather regular behaviour, we demonstrate that GABAB -R activation desynchronizes the SWOs. Interestingly, variability changes could be accomplished in two different ways: by either shortening or lengthening the duration of Down states. Even when the most common observation following GABAB -Rs blocking is the lengthening of Down states, both changes are expressed experimentally and also in numerical simulations. Our simulations suggest that the sluggishness of GABAB -Rs to follow the excitatory fluctuations of the cortical network can explain these different network dynamics modulated by GABAB -Rs.

Dopamine D2 receptors in WFS1-neurons regulate food-seeking and avoidance behaviors.

The selection and optimization of appropriate adaptive responses depends on interoceptive and exteroceptive stimuli as well as on the animal's ability to switch from one behavioral strategy to another. Although growing evidence indicate that dopamine D2R-mediated signaling events ensure the selection of the appropriate strategy for each specific situation, the underlying neural circuits through which they mediate these effects are poorly characterized. Here, we investigated the role of D2R signaling in a mesolimbic neuronal subpopulation expressing the Wolfram syndrome 1 (Wfs1) gene. This subpopulation is located within the nucleus accumbens, the central amygdala, the bed nucleus of the stria terminalis, and the tail of the striatum, all brain regions critical for the regulation of emotions and motivated behaviors. Using a mouse model carrying a temporally controlled deletion of D2R in WFS1-neurons, we demonstrate that intact D2R signaling in this neuronal population is necessary to regulate homeostasis-dependent food-seeking behaviors in both male and female mice. In addition, we found that reduced D2R signaling in WFS1-neurons impaired active avoidance learning and innate escape responses. Collectively, these findings identify a yet undocumented role for D2R signaling in WFS1-neurons as a novel effector through which dopamine optimizes appetitive behaviors and regulates defensive behaviors.

Stable coding of aversive associations in medial prefrontal populations.

The medial prefrontal cortex (mPFC) is at the core of numerous psychiatric conditions, including fear and anxiety-related disorders. Whereas an abundance of evidence suggests a crucial role of the mPFC in regulating fear behaviour, the precise role of the mPFC in this process is not yet entirely clear. While studies at the single-cell level have demonstrated the involvement of this area in various aspects of fear processing, such as the encoding of threat-related cues and fear expression, an increasingly prevalent idea in the systems neuroscience field is that populations of neurons are, in fact, the essential unit of computation in many integrative brain regions such as prefrontal areas. What mPFC neuronal populations represent when we face threats? To address this question, we performed electrophysiological single-unit population recordings in the dorsal mPFC while mice faced threat-predicting cues eliciting defensive behaviours, and performed pharmacological and optogenetic inactivations of this area and the amygdala. Our data indicated that the presence of threat-predicting cues induces a stable coding dynamics of internally driven representations in the dorsal mPFC, necessary to drive learned defensive behaviours. Moreover, these neural population representations primary reflect learned associations rather than specific defensive behaviours, and the construct of such representations relies on the functional integrity of the amygdala.

Le cortex préfrontal médial (CPFm) est au cœur de nombreuses affections psychiatriques, notamment les troubles liés à la peur et à l'anxiété. Alors que de nombreuses preuves suggèrent un rôle crucial du CPFm dans la régulation du comportement de peur, le rôle précis du CPFm dans ce processus n'est pas encore tout à fait clair. En effet, si des études au niveau de la cellule unique ont démontré l'implication de cette zone dans divers aspects du traitement de la peur, tels que l'encodage des indices liés à la menace et l'expression de la peur, l'idée selon laquelle des populations de neurones constituent en fait l'unité de calcul essentielle dans de nombreuses régions cérébrales intégratives, telles que les zones préfrontales, est de plus en plus répandue dans le domaine des neurosciences systémiques. Que représentent les populations de neurones du mPFC lorsque nous sommes confrontés à des menaces  ? Pour répondre à cette question, nous avons effectué des enregistrements électrophysiologiques de populations d'unités uniques dans le CPFm dorsal pendant que des souris étaient confrontées à des signaux de menace suscitant des comportements défensifs, et nous avons procédé à des inactivations pharmacologiques et optogénétiques de cette zone et de l'amygdale. Nos données indiquent que la présence de signaux de menace induit une dynamique de codage stable des représentations internes dans le CPFm dorsal, nécessaire à l'apprentissage de comportements défensifs. De plus, ces représentations neuronales reflètent principalement des associations apprises plutôt que des comportements défensifs spécifiques, et la construction de ces représentations dépend de l'intégrité fonctionnelle de l'amygdale.

Prefrontal circuits encode both general danger and specific threat representations.

Behavioral adaptation to potential threats requires both a global representation of danger to prepare the organism to react in a timely manner but also the identification of specific threatening situations to select the appropriate behavioral responses. The prefrontal cortex is known to control threat-related behaviors, yet it is unknown whether it encodes global defensive states and/or the identity of specific threatening encounters. Using a new behavioral paradigm that exposes mice to different threatening situations, we show that the dorsomedial prefrontal cortex (dmPFC) encodes a general representation of danger while simultaneously encoding a specific neuronal representation of each threat. Importantly, the global representation of danger persisted in error trials that instead lacked specific threat identity representations. Consistently, optogenetic prefrontal inhibition impaired overall behavioral performance and discrimination of different threatening situations without any bias toward active or passive behaviors. Together, these data indicate that the prefrontal cortex encodes both a global representation of danger and specific representations of threat identity to control the selection of defensive behaviors.

Decoding defensive systems.

Our understanding of the neuronal circuits and mechanisms of defensive systems has been primarily dominated by studies focusing on the contribution of individual cells in the processing of threat-predictive cues, defensive responses, the extinction of such responses and the contextual modulation of threat-related behavior. These studies have been key in establishing threat-related circuits and mechanisms. Yet, they fall short in answering long-standing questions related to the integrative processing of distinct threatening cues, behavioral states induced by threat-related events, or the bridging from sensory processing of threat-related cues to specific defensive responses. Recent conceptual and technical developments has allowed the monitoring of large populations of neurons, which in addition to advanced analytic tools, have improved our understanding of how collective neuronal activity supports threat-related behaviors. In this review, we discuss the current knowledge of neuronal population codes within threat-related networks, in the context of aversive motivated behavior and the study of defensive systems.

The advent of fear conditioning as an animal model of post-traumatic stress disorder: Learning from the past to shape the future of PTSD research.

Translational research on post-traumatic stress disorder (PTSD) has produced limited improvements in clinical practice. Fear conditioning (FC) is one of the dominant animal models of PTSD. In fact, FC is used in many different ways to model PTSD. The variety of FC-based models is ill defined, creating confusion and conceptual vagueness, which in turn impedes translation into the clinic. This article takes a historical and conceptual approach to provide a comprehensive picture of current research and help reorient the research focus. This work historically reviews the variety of models that have emerged from the initial association of PTSD with FC, highlighting conceptual pitfalls that have limited the translation of animal research into clinical advances. We then provide some guidance on how future translational research could benefit from conceptual and technological improvements to translate basic findings in patients. This objective will require transdisciplinary approaches and should involve physicians, engineers, philosophers, and neuroscientists.

Prefrontal-Periaqueductal Gray-Projecting Neurons Mediate Context Fear Discrimination.

Survival critically depends on selecting appropriate defensive or exploratory behaviors and is strongly influenced by the surrounding environment. Contextual discrimination is a fundamental process that is thought to depend on the prefrontal cortex to integrate sensory information from the environment and regulate adaptive responses to threat during uncertainty. However, the precise prefrontal circuits necessary for discriminating a previously threatening context from a neutral context remain unknown. Using a combination of single-unit recordings and optogenetic manipulations, we identified a neuronal subpopulation in the dorsal medial prefrontal cortex (dmPFC) that projects to the lateral and ventrolateral periaqueductal gray (l/vlPAG) and is selectively activated during contextual fear discrimination. Moreover, optogenetic activation and inhibition of this neuronal population promoted contextual fear discrimination and generalization, respectively. Our results identify a subpopulation of dmPFC-l/vlPAG-projecting neurons that control switching between different emotional states during contextual discrimination.

UP-DOWN cortical dynamics reflect state transitions in a bistable network.

In the idling brain, neuronal circuits transition between periods of sustained firing (UP state) and quiescence (DOWN state), a pattern the mechanisms of which remain unclear. Here we analyzed spontaneous cortical population activity from anesthetized rats and found that UP and DOWN durations were highly variable and that population rates showed no significant decay during UP periods. We built a network rate model with excitatory (E) and inhibitory (I) populations exhibiting a novel bistable regime between a quiescent and an inhibition-stabilized state of arbitrarily low rate. Fluctuations triggered state transitions, while adaptation in E cells paradoxically caused a marginal decay of E-rate but a marked decay of I-rate in UP periods, a prediction that we validated experimentally. A spiking network implementation further predicted that DOWN-to-UP transitions must be caused by synchronous high-amplitude events. Our findings provide evidence of bistable cortical networks that exhibit non-rhythmic state transitions when the brain rests.