Conservación de la biodiversidad: estrategias y financiación

La conservación y gestión de la biodiversidad constituyen un objeto clave en las distintas instituciones políticas a nivel mundial, es por ello que todas ellas han creado directrices y medidas para su preservación y protección

Robust Off- and Online Separation of Intracellularly Recorded Up and Down Cortical States

BACKGROUND: The neuronal cortical network generates slow (<1 Hz) spontaneous rhythmic activity that emerges from the recurrent connectivity. This activity occurs during slow wave sleep or anesthesia and also in cortical slices, consisting of alternating up (active, depolarized) and down (silent, hyperpolarized) states. The search for the underlying mechanisms and the possibility of analyzing network dynamics in vitro has been subject of numerous studies. This exposes the need for a detailed quantitative analysis of the membrane fluctuating behavior and computerized tools to automatically characterize the occurrence of up and down states. METHODOLOGY/PRINCIPAL FINDINGS: Intracellular recordings from different areas of the cerebral cortex were obtained from both in vitro and in vivo preparations during slow oscillations. A method that separates up and down states recorded intracellularly is defined and analyzed here. The method exploits the crossover of moving averages, such that transitions between up and down membrane regimes can be anticipated based on recent and past voltage dynamics. We demonstrate experimentally the utility and performance of this method both offline and online, the online use allowing to trigger stimulation or other events in the desired period of the rhythm. This technique is compared with a histogram-based approach that separates the states by establishing one or two discriminating membrane potential levels. The robustness of the method presented here is tested on data that departs from highly regular alternating up and down states. CONCLUSIONS/SIGNIFICANCE: We define a simple method to detect cortical states that can be applied in real time for offline processing of large amounts of recorded data on conventional computers. Also, the online detection of up and down states will facilitate the study of cortical dynamics. An open-source MATLAB toolbox, and Spike 2-compatible version are made freely available

Explicit-Duration Hidden Markov Model Inference of UP-DOWN States from Continuous Signals

Neocortical neurons show UP-DOWN state (UDS) oscillations under a variety of conditions. These UDS have been extensively studied because of the insight they can yield into the functioning of cortical networks, and their proposed role in putative memory formation. A key element in these studies is determining the precise duration and timing of the UDS. These states are typically determined from the membrane potential of one or a small number of cells, which is often not sufficient to reliably estimate the state of an ensemble of neocortical neurons. The local field potential (LFP) provides an attractive method for determining the state of a patch of cortex with high spatio-temporal resolution; however current methods for inferring UDS from LFP signals lack the robustness and flexibility to be applicable when UDS properties may vary substantially within and across experiments. Here we present an explicit-duration hidden Markov model (EDHMM) framework that is sufficiently general to allow statistically principled inference of UDS from different types of signals (membrane potential, LFP, EEG), combinations of signals (e.g., multichannel LFP recordings) and signal features over long recordings where substantial non-stationarities are present. Using cortical LFPs recorded from urethane-anesthetized mice, we demonstrate that the proposed method allows robust inference of UDS. To illustrate the flexibility of the algorithm we show that it performs well on EEG recordings as well. We then validate these results using simultaneous recordings of the LFP and membrane potential (MP) of nearby cortical neurons, showing that our method offers significant improvements over standard methods. These results could be useful for determining functional connectivity of different brain regions, as well as understanding network dynamics

Activity of cortical and thalamic neurons during the slow (<1 Hz) rhythm in the mouse in vivo

During NREM sleep and under certain types of anaesthesia, the mammalian brain exhibits a distinctive slow (<1 Hz) rhythm. At the cellular level, this rhythm correlates with so-called UP and DOWN membrane potential states. In the neocortex, these UP and DOWN states correspond to periods of intense network activity and widespread neuronal silence, respectively, whereas in thalamocortical (TC) neurons, UP/DOWN states take on a more stereotypical oscillatory form, with UP states commencing with a low-threshold Ca2+ potential (LTCP). Whilst these properties are now well recognised for neurons in cats and rats, whether or not they are also shared by neurons in the mouse is not fully known. To address this issue, we obtained intracellular recordings from neocortical and TC neurons during the slow (<1 Hz) rhythm in anaesthetised mice. We show that UP/DOWN states in this species are broadly similar to those observed in cats and rats, with UP states in neocortical neurons being characterised by a combination of action potential output and intense synaptic activity, whereas UP states in TC neurons always commence with an LTCP. In some neocortical and TC neurons, we observed ‘spikelets’ during UP states, supporting the possible presence of electrical coupling. Lastly, we show that, upon tonic depolarisation, UP/DOWN states in TC neurons are replaced by rhythmic high-threshold bursting at ~5 Hz, as predicted by in vitro studies. Thus, UP/DOWN state generation appears to be an elemental and conserved process in mammals that underlies the slow (<1 Hz) rhythm in several species, including humans

Pauses in cholinergic interneuron firing exert an inhibitory control on striatal output in vivo

The cholinergic interneurons (CINs) of the striatum are crucial for normal motor and behavioral functions of the basal ganglia. Striatal CINs exhibit tonic firing punctuated by distinct pauses. Pauses occur in response to motivationally significant events, but their function is unknown. Here we investigated the effects of pauses in CIN firing on spiny projection neurons (SPNs) – the output neurons of the striatum – using in vivo whole cell and juxtacellular recordings in mice. We found that optogenetically-induced pauses in CIN firing inhibited subthreshold membrane potential activity and decreased firing of SPNs. During pauses, SPN membrane potential fluctuations became more hyperpolarized and UP state durations became shorter. In addition, short-term plasticity of corticostriatal inputs was decreased during pauses. Our results indicate that, in vivo, the net effect of the pause in CIN firing on SPNs activity is inhibition and provide a novel mechanism for cholinergic control of striatal output

Author response

Spontaneous slow oscillation-associated slow wave activity represents an internally generated state which is characterized by alternations of network quiescence and stereotypical episodes of neuronal activity - slow wave events. However, it remains unclear which macroscopic signal is related to these active periods of the slow wave rhythm. We used optic fiber-based calcium recordings of local neural populations in cortex and thalamus to detect neurophysiologically defined slow calcium waves in isoflurane anesthetized rats. The individual slow wave events were used for an event-related analysis of simultaneously acquired whole-brain BOLD fMRI. We identified BOLD responses directly related to onsets of slow calcium waves, revealing a cortex-wide BOLD correlate: the entire cortex was engaged in this specific type of slow wave activity. These findings demonstrate a direct relation of defined neurophysiological events to a specific BOLD activity pattern and were confirmed for ongoing slow wave activity by independent component and seed-based analyses

Spatio-temporal structure of spontaneous slow-wave oscillations and identification of up and down states in simultaneous intra- and extracellular recordings in vivo

La oscilación lenta, registrada durante la etapa de ondas lentas del sueño y bajo anestesia, constituye un acontecimiento espontáneo estable y sincrónico de la red cortical durante el cual las neuronas de la corteza cerebral alternan de manera coherente entre intervalos de ausencia de actividad (estados hiperpolarizados o Down states) e intervalos donde suelen producirse descargas de potenciales de acción (estados despolarizados o Up states). La presente Tesis Doctoral está motivada por el interés de estudiar la estructura espacio-temporal de la onda lenta espontánea presente en la corteza somato-sensorial de la rata anestesiada y también en el cómo y en qué medida se propaga la actividad por la red cortical. Además del estudio dinámica de la red cortical a través de su actividad oscilatoria lenta emergente, otros objetivos específicos son: (1) estudiar el comportamiento estereotípico de las transiciones espontáneas entre los intervalos de Up y Down presentes en la corteza somato-sensorial de ratas anestesiadas; (2) desarrollar herramientas analíticas adecuadas que faciliten el estudio de la propagación espacio-temporal de las ondas de actividad, tanto a escala micro como mesoscópica, durante la etapa de ondas lentas. Se presentan: a) la definición y la implementación de una metodología que permite detectar las oscilaciones lentas en registros intracelulares, y b) un segundo procedimiento analítico para analizar registros extracelulares múltiples y para medir su correlación, y, finalmente para analizar las propiedades de propagación de esta actividad cortical. Dichas metodologías analíticas se desarrollaron empleando los datos procedentes de registros intra- y extracelulares in vivo simultáneos, y que presentan estados de activación neuronal (Up states) que se alternan con estados silentes (Down states). El método descrito en esta tesis, denominado MAUDS (de acuerdo a las iniciales del inglés Moving Averages for Up and Down Separation) es automático y sencillo de usar, capaz de identificar y separar de forma fiable los dos estados de potencial de membrana alternantes, característicos del sueño de ondas lentas y bajo determinada anestesia incluso en situaciones en las que otros métodos fallan debido a artefactos o interferencias. El método ha sido diseñado para que pueda ser usado tanto off- como online, y permite que se pueda incluir eventos desencadenantes en función de la inicialización o finalización de los estados Up. También permite obtener información inmediata sobre las estadísticas de las transiciones Up a Down. Se describe la metodología experimental para realizar registros intra- y extracelulares in vivo y simultáneos utilizando una matriz multi-electrodo, y el tratamiento analítico al que se ha sometido los datos electrofisiológicos registrados para estudiar la estructura espacio-temporal de la oscilación lenta en una pequeña porción de tejido cortical. Los resultados de este análisis mostraron una considerable variabilidad en la mayoría de los registros con respecto a la estructura espacio-temporal de las ondas de actividad, tanto en cuanto a origen como en cuanto a dirección para todas las muestras de animales incluidos en el estudio. Se ha podido determinar una dirección preferente de propagación de la actividad durante los períodos de registro