Daniel JERCOG




Post-Doctorant

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7 publication(s) depuis Août 2017:


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30/10/2023 | Nat Neurosci
Prefrontal circuits encode both general danger and specific threat representations.
Martin-Fernandez M, Menegolla AP, Lopez-Fernandez G, Winke N, Jercog D, Kim HR, Girard D, Dejean C, Herry C
doi: 10.1038/s41593-023-01472-8

Abstract:
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.




06/07/2022 | Curr Opin Neurobiol
Decoding defensive systems.
Herry C, Jercog D
doi: 10.1016/j.conb.2022.102600

Abstract:
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.




14/07/2021 | Nature
Dynamical prefrontal population coding during defensive behaviours.
Jercog D, Winke N, Sung K, Fernandez MM, Francioni C, Rajot D, Courtin J, Chaudun F, Jercog PE, Valerio S, Herry C
doi: 10.1038/s41586-021-03726-6

Abstract:
Coping with threatening situations requires both identifying stimuli that predict danger and selecting adaptive behavioural responses to survive(1). The dorsomedial prefrontal cortex (dmPFC) is a critical structure that is involved in the regulation of threat-related behaviour(2-4). 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.




Abstract:
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.




08/2020 | J Physiol
Modulation of cortical slow oscillatory rhythm by GABAB receptors: an in vitro experimental and computational study.
Perez-Zabalza M, Reig R, Manrique J, Jercog D, Winograd M, Parga N, Sanchez-Vives MV
doi: 10.1113/JP279476

Abstract:
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.




24/01/2018 | Neuron
Prefrontal-Periaqueductal Gray-Projecting Neurons Mediate Context Fear Discrimination.
Rozeske RR, Jercog D, Karalis N, Chaudun F, Khoder S, Girard D, Winke N, Herry C
doi: 10.1016/j.neuron.2017.12.044

Abstract:
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.




04/08/2017 | eLife
UP-DOWN cortical dynamics reflect state transitions in a bistable network.
Jercog D, Roxin A, Bartho P, Luczak A, Compte A, de la Rocha J
doi: 10.7554/eLife.22425

Abstract:
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.