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

Dynamics of spontaneous activity in the cerebral cortex across brain states

Spontaneous activity in the cerebral cortex changes in different brain states. During desynchronized brain states (e.g. wakefulness, REM sleep), populations of neurons in the cerebral cortex fire action potentials in a stochastic and uncorrelated manner. In contrast, during synchronized states (e.g. slowwave sleep, anesthesia) cortical neurons display the alternation between quiescent periods (DOWN) and periods of spiking activity (UP) coherently across cortical layers. In recent years, the view has emerged that brain states are not defined in discrete categories, but rather form a continuum of possible states. In this thesis, we address three main questions regarding this phenomenon: How is the oscillatory activity at high frequencies (10-100 Hz) distributed across the cortical laminae during UP states? What are the mechanisms underlying UP and DOWN dynamics in neocortex in vivo? How do brain states shape the statistics of cortical spontaneous activity? First, we analyzed laminar local field potential recordings of spontaneous activity in the visual cortex in vivo and characterized the laminar profile of fast oscillatory activity present during UP states, which showed overall similar spectral properties across layers but were generated independently in two different compartments determined by superficial and deep cortical layers. In order to explore whether this laminar profile of fast oscillatory activity was generated intrinsically by cortical circuitry or by external inputs, we performed simultaneous local field potential recordings in spontaneously active cortical slices in vitro. By manipulating the slices pharmacologically, we concluded that neural excitability can control inter-laminar couplings and oscillatory dynamics in cortical circuits. Second, we made a quantitative analysis of UP and DOWN dynamics in vivo by analyzing multiple single-unit cortical recordings during synchronized states. The classic view about what causes cortical UP and DOWN dynamics during synchronized states implicates a "fatigue" or adaptation process (such as spike frequency adaptation or synaptic depression), but our results were inconsistent with a dominant role for this mechanism. Using a low dimensional modeling approach, we proposed a rate model that displays UP and DOWN dynamics, in which bistability can be obtained at arbitrarily low rates. With this model we explored the role and interplay of adaptation and external fluctuations in shaping the statistics of UP and DOWN state dynamics, and determined that a regime of weak adaptation and strong fluctuations is necessary to qualitatively reproduce the statistical features of the experimental data. Finally, we studied the impact of brain states in cortical dynamics. Under urethane anesthesia, spontaneous transitions between synchronized states (with UP and DOWN state dynamics) and desynchronized states (with sporadic or absent DOWN states) are observable, and these transitions resemble those observed from slow-wave to REM sleep states. Investigating multiple single-unit recordings during these transitions, we found that the statistics of UP and DOWN states are largely determined by the brain state in a continuous manner, consistently across experiments and cortical areas. This constrains the possible cortical mechanisms modulated during transitions between desynchronized and synchronized states, as revealed in a low-dimensional firing rate network model.La actividad espontánea en la corteza cerebral cambia en diferentes estados cerebrales. Durante estados desincronizados (e.g. estado de vigilia, sueño MOR), las poblaciones de neuronas en los potenciales de acción en una manera aparentemente estocástica y no correlacionada. Por el contrario, durante estados sincronizados (e.g. sueño de ondas lentas, anestesia) las neuronas corticales muestran la alternancia entre periodos de reposo (DOWN) y los períodos de actividad (UP) de manera coherente a través de las capas corticales. En los últimos años, ha emergido la visión de que los estados cerebrales no están definidos en categorías discretas, sino que forman un continuo de estados posibles. En esta tesis, nos dirigimos a tres preguntas principales con respecto a este fenómeno: ¿Cómo es la actividad oscilatoria a altas frecuencias (10-100 Hz) distribuída a través de las capas de la neocorteza durante los períodos UP? ¿Cuáles son los mecanismos que subyacen a la dinámica UP y DOWN en el neocórtex in vivo? ¿Cómo se determinan los estados cerebrales estadísticas de actividad espontánea cortical? En primer lugar, analizamos registros de potencial de campo local en la corteza visual in vivo y caracterizamos el perfil laminar de actividad oscilatoria rápida durante los estados UP, que mostraron en general propiedades espectrales similares a través de las distintas capas, pero generadas de forma independiente en dos compartimentos distintos determinados por capas corticales superficiales y profundas. Con el fin de explorar si este perfil laminar de la actividad oscilatoria rápida es generada intrínsecamente por los circuitos corticales o por inputs externos, se realizaron registros de potencial de campo local en rebanadas corticales espontáneamente activas in vitro. Mediante la manipulación farmacológica in vitro, se concluyó que la excitabilidad neuronal puede controlar los acoplamientos entre capas y dinámica oscilatoria en los circuitos corticales. En segundo lugar, realizamos un análisis cuantitativo de la dinámica UP y DOWN in vivo mediante el análisis de registros corticales múltiples de una sola unidad durante estados sincronizados. El punto de vista clásico sobre las causas de esta dinámica durante los estados sincronizados implica un mecanismo de "fatiga" o proceso de adaptación (e.g. adaptación de frecuencia disparo o depresión sináptica), pero los resultados que observamos resultan inconsistentes con un papel dominante de este mecanismo. Utilizando un enfoque de modelado de baja dimensión, propusimos un modelo que muestra dinámica UP y DOWN, en la que biestabilidad se puede conseguir a tasas de descarga arbitrariamente bajas. Con este modelo hemos explorado el papel y la interacción de la adaptación y las fluctuaciones externas en la conformación de las estadísticas de la dinámica del estado UP y DOWN, y determinamos un régimen de adaptación débil pero con fluctuaciones fuertes es necesario para reproducir cualitativamente la estadística de los datos experimentales. Por último, transiciones espontáneas entre estados sincronizados (con la dinámica del estado UP y DOWN) y estados desincronizados (con los períodos DOWN esporádicos o ausentes) son observables bajo la influencia del anestésico uretano, y estas transiciones se asemejan a las observadas a partir de ondas lentas de los estados de sueño REM. Investigando registros múltiples de una sola unidad durante estas transiciones, encontramos que la estadísticas de la dinámica UP y DOWN está determinada en gran medida por el estado del cerebro de forma continua, de manera consistente a través de experimentos y áreas corticales. Esto limita los posibles mecanismos corticales modulados durante las transiciones entre estados desincronizados y sincronizados, tal como lo revela el uso de un modelo de baja dimensión

Rol del aprendizaje operante en la cooperación entre animales evaluado con el dilema del prisionero iterado : una teoría computacional

En diversos ambientes biológicos, los sistemas adaptativos han evolucionado con la característica de garantizar su propia estabilidad replicativa. Bajo esta condición, una de las más importantes paradojas de la teoría de la evolución resulta ser la cooperación entre individuos.\nPor otra parte, ante la alternativa de elegir un refuerzo apetitivo pequeño e inmediato o uno mayor pero retardado en el tiempo, los animales optan en general por la primera opción. Este fenómeno, denominado “impulsividad”, ha sido observado en distintas especies, algunas de ellas filogenéticamente muy distantes.\nEste efecto trae importantes consecuencias en el paradigma de cooperación del dilema del prisionero iterado (DPI). Si bien, a nivel teórico la mejor opción bajo condiciones de reciprocidad resulta ser la opción de cooperar (puesto que a largo plazo es la que otorga mayor beneficio mutuo), experimentalmente los animales muestran una fuerte tendencia a la deserción. La devaluación del refuerzo retardado con respecto al inmediato parece jugar en este fenómeno un papel preponderante.\nA su vez existe evidencia experimental en el estudio del comportamiento de urracas azules (Cyanocitta Cristata) en el marco del DPI, indicando que la acumulación de alimento durante un número sucesivo de jugadas es un mecanismo válido para lograr niveles sostenidos de cooperación.\nEn este trabajo se propone la construcción de una teoría computacional utilizando redes neuronales para la formalización de hipótesis neurofisiológicas y conductuales. Utilizando las reglas de aprendizaje Hebbiano y de Rescorla-Wagner para la computación de pesos sinápticos, el modelo propuesto es capaz de predecir los resultados experimentales acerca de los efectos en la devaluación de refuerzos y la acumulación de alimento, permitiendo explicar el fenómeno del altruismo recíproco en un ambiente de condicionamiento operante.Fil:Jercog, Daniel Alejandro. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina

Curr Opin Neurobiol

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.Innovations instrumentales et procédurales en psychopathologie expérimentale chez le rongeu

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 behaviour2,3,4. 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.Rôle de la signalisation dopaminergique dans l'amygdale étendue dans le contrôle de la peur généralisée.Role des projections inhibitrices provenant du cortex préfrontal dans l'expression de la peur conditionnéeInnovations instrumentales et procédurales en psychopathologie expérimentale chez le rongeu

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

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

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.This work was supported by EU H2020 Research and Innovation Programme Grant 945539 (HBP SGA3), BFU2017‐85048‐R (MINECO) and Commission for Universities and Research of the Department of Innovation, Universities, and Enterprise of the Generalitat de Catalunya ‐AGAUR‐ (IU16‐011508) to MVSV and PGC2018‐101992‐B‐100 (MINECO) to NP.Peer reviewe

Nat Neurosci

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. © 2023, The Author(s), under exclusive licence to Springer Nature America, Inc.Innovations instrumentales et procédurales en psychopathologie expérimentale chez le rongeu

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

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.This work was supported by EU H2020 Research and Innovation Programme Grant 945539 (HBP SGA3), BFU2017‐85048‐R (MINECO) and Commission for Universities and Research of the Department of Innovation, Universities, and Enterprise of the Generalitat de Catalunya ‐AGAUR‐ (IU16‐011508) to MVSV and PGC2018‐101992‐B‐100 (MINECO) to NP.Peer reviewe