Complexity of Brain Dynamics as a Correlate of Consciousness in Anaesthetized Monkeys

The use of anaesthesia is a fundamental tool in the investigation of consciousness. Anesthesia procedures allow to investigate different states of consciousness from sedation to deep anesthesia within controlled scenarios. In this study we use information quantifiers to measure the complexity of electrocorticogram recordings in monkeys. We apply these metrics to compare different stages of general anesthesia for evaluating consciousness in several anesthesia protocols. We find that the complexity of brain activity can be used as a correlate of consciousness. For two of the anaesthetics used, propofol and medetomidine, we find that the anaesthetised state is accompanied by a reduction in the complexity of brain activity. On the other hand we observe that use of ketamine produces an increase in complexity measurements. We relate this observation with increase activity within certain brain regions associated with the ketamine used doses. Our measurements indicate that complexity of brain activity is a good indicator for a general evaluation of different levels of consciousness awareness, both in anesthetized and non anesthetizes states.Fil: Fuentes, Nicolás. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; ArgentinaFil: Garcia, Alexis. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; ArgentinaFil: Guevara, Ramón. Università di Padova; ItaliaFil: Orofino, Roberto. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños Pedro Elizalde (ex Casa Cuna); Argentina. Hospital Español de Buenos Aires;Fil: Mateos, Diego Martín. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Matemática Aplicada del Litoral. Universidad Nacional del Litoral. Instituto de Matemática Aplicada del Litoral; Argentina. Universidad Nacional de Entre Rios. Facultad de Ingeniería. Departamento de Bioingeniería; Argentin

Complexity of multi-dimensional spontaneous EEG decreases during propofol induced general anaesthesia

Emerging neural theories of consciousness suggest a correlation between a specific type of neural dynamical complexity and the level of consciousness: When awake and aware, causal interactions between brain regions are both integrated (all regions are to a certain extent connected) and differentiated (there is inhomogeneity and variety in the interactions). In support of this, recent work by Casali et al (2013) has shown that Lempel-Ziv complexity correlates strongly with conscious level, when computed on the EEG response to transcranial magnetic stimulation. Here we investigated complexity of spontaneous high-density EEG data during propofol-induced general anaesthesia. We consider three distinct measures: (i) Lempel-Ziv complexity, which is derived from how compressible the data are; (ii) amplitude coalition entropy, which measures the variability in the constitution of the set of active channels; and (iii) the novel synchrony coalition entropy (SCE), which measures the variability in the constitution of the set of synchronous channels. After some simulations on Kuramoto oscillator models which demonstrate that these measures capture distinct ‘flavours’ of complexity, we show that there is a robustly measurable decrease in the complexity of spontaneous EEG during general anaesthesia

Prediction of Nociceptive Responses during Sedation by Linear and Non-Linear Measures of EEG Signals in High Frequencies

The level of sedation in patients undergoing medical procedures evolves continuously, affected by the interaction between the effect of the anesthetic and analgesic agents and the pain stimuli. The monitors of depth of anesthesia, based on the analysis of the electroencephalogram (EEG), have been progressively introduced into the daily practice to provide additional information about the state of the patient. However, the quantification of analgesia still remains an open problem. The purpose of this work is to improve the prediction of nociceptive responses with linear and non-linear measures calculated from EEG signal filtered in frequency bands higher than the traditional bands. Power spectral density and auto-mutual information function was applied in order to predict the presence or absence of the nociceptive responses to different stimuli during sedation in endoscopy procedure. The proposed measures exhibit better performances than the bispectral index (BIS). Values of prediction probability of Pk above 0.75 and percentages of sensitivity and specificity above 70% were achieved combining EEG measures from the traditional frequency bands and higher frequency bands

Bispectral and spectral entropy indices at propofol-induced loss of consciousness in young and elderly patients

Background Bispectral (BIS) and state/response entropy (SE/RE) indices have been widely used to estimate depth of anaesthesia and sedation. In adults, independent of age, adequate and safe depth of anaesthesia for surgery is usually assumed when these indices are between 40 and 60. Since the EEG is changing with increasing age, we investigated the impact of advanced age on BIS, SE, and RE indices during induction. Methods BIS and SE/RE indices were recorded continuously in elderly (≥65 yr) and young (≤40 yr) surgical patients who received propofol until loss of consciousness (LOC) using stepwise increasing effect-site concentrations. LOC was defined as an observer assessment of alertness/sedation score <2, corresponding to the absence of response to mild prodding or shaking. Results We analysed 35 elderly [average age, 78 yr (range, 67-96)] and 34 young [35 (19-40)] patients. At LOC, all indices were significantly higher in elderly compared with young patients: BISLOC, median 70 (range, 58-91) vs 58 (40-70); SELOC, 71 (31-88) vs 55.5 (23-79); and RELOC, 79 (35-96) vs 59 (25-80) (P<0.001 for all comparisons). With all three monitors, only a minority of elderly patients lost consciousness within a 40-60 index range: two (5.7%) with BIS and RE each, and seven (20%) with SE. In young patients, the respective numbers were 20 (58.8%) for BIS, 13 (38.2%) for SE, and nine (26.5%) for RE. Conclusions In adults undergoing propofol induction, BIS, SE, and RE indices at LOC are significantly affected by ag

Active cortical networks promote shunting fast synaptic inhibition in vivo

Fast synaptic inhibition determines neuronal response properties in the mammalian brain and is mediated by chloride-permeable ionotropic GABA-A receptors (GABAARs). Despite their fundamental role, it is still not known how GABAARs signal in the intact brain. Here, we use in vivo gramicidin recordings to investigate synaptic GABAAR signaling in mouse cortical pyramidal neurons under conditions that preserve native transmembrane chloride gradients. In anesthetized cortex, synaptic GABAARs exert classic hyperpolarizing effects. In contrast, GABAAR-mediated synaptic signaling in awake cortex is found to be predominantly shunting. This is due to more depolarized GABAAR equilibrium potentials (EGABAAR), which are shown to result from the high levels of synaptic activity that characterize awake cortical networks. Synaptic EGABAAR observed in awake cortex facilitates the desynchronizing effects of inhibitory inputs upon local networks, which increases the flexibility of spiking responses to external inputs. Our findings therefore suggest that GABAAR signaling adapts to optimize cortical functions

Functional integration in the cortical neuronal network of conscious and anesthetized animals

General anesthesia consists of amnesia, analgesia, areflexia and unconsciousness. How anesthetics suppress consciousness has been a mystery for more than one and a half centuries. The overall goal of my research has been to determine the neural correlates of anesthetic-induced loss of consciousness. I hypothesized that anesthetics induce unconsciousness by interfering with the functional connectivity of neuronal networks of the brain and consequently, reducing the brain\u27s capacity for information processing. To test this hypothesis, I performed experiments in which neuronal spiking activity was measured with chronically implanted microelectrode arrays in the visual cortex of freely-moving rats during wakefulness and at graded levels of anesthesia produced by the inhalational anesthetic agent desflurane. I then applied linear and non-parametric information-theoretic analyses to quantify the concentration-dependent effect of general anesthetics on spontaneous and visually evoked spike firing activity in rat primary visual cortex. Results suggest that desflurane anesthesia disrupts cortical neuronal integration as measured by monosynaptic connectivity, spike burst coherence and information capacity. This research furthers our understanding of the mechanisms involved with the anesthetic-induced LOC which may facilitate in the development of better anesthetic monitoring devices and the creation of effective anesthetic agents that will be free of unwanted side effects

Functional mechanisms of stimulus-specific adaptation and deviance detection in the auditory pathway

Tesis por compendio de publicaciones[ES]En resumen, esta Tesis Doctoral demuestra que la SSA es un mecanismo presente en el cerebro del mamífero y que no se trata de un artefacto generado por la anestesia. Muestra además que la SSA es un mecanismo que puede explicarse perfectamente, a nivel subcortical, por el modelo de los canales de frecuencia. La existencia de controles de ganancia consecutivos ejercidos por el sistema GABAérgico sugiere también la presencia de varios niveles jerárquicos de procesamiento que ayudan a refinar y reducir la información redundante. En conjunto, la SSA parece ser un mecanismo que actúa como filtro preatentivo reduciendo las señales sensoriales irrelevantes, ayudando a los animales a presentar respuestas adecuadas para facilitar su supervivencia

Nociception level during anaesthesia : analysis and control

Tese de Programa Doutoral. Engenharia Biomédica. Universidade do Porto. Faculdade de Engenharia. 201

Clasificación de la profundidad anestésica en función del procesamiento digital de señales de los sistemas nervioso central y autónomo

194 páginasLa anestesia desempeña un papel fundamental en la práctica clínica, siendo esencial en procedimientos quirúrgicos. Corresponde a un proceso progresivo y reversible inducido por fármacos, en el que se procura un estado de pérdida de conciencia, analgesia e inmovilidad del paciente. El monitoreo de la profundidad anestésica del paciente, así como los mecanismos fisiológicos que subyacen este fenómeno constituyen una dinámica área de investigación. Por lo anterior este trabajo apunta a resolver la pregunta: ¿Es posible clasificar los estados de profundidad anestésica, al evaluar en conjunto la actividad de los sistemas nervioso central y autónomo, en el paciente quirúrgico durante la utilización de anestesia total intravenosa? Inicialmente, los fundamentos de la técnica anestésica junto a los modelos de farmacocinética y farmacodinamia, y la relación con la variabilidad de los índices de entropía de Datex-Ohmeda (Entropía Estado y Entropía de Respuesta) fueron explorados mediante la implementación de un estudio clínico cruzado aleatorizado. Este estudio fue publicado en una revista científica revisada por pares (Anexo 1). El análisis estadístico de este estudio consideró pruebas paramétricas (Entropía de Estado: p=0.64, T=0.54; Entropía de Respuesta: p=0.84, T=0.41) y no paramétricas (Entropía de Estado: p=0.57; Entropía de Respuesta: p=0.77,) para comparar el efecto de los modelos. Los resultados no evidenciaron diferencias estadísticamente significativas (p> 0.05 en todas las comparaciones). Sin embargo, el modelo propuesto por Marsh mostró marcados valores atípicos asociados a la inducción, estos valores y otros parámetros farmacocineticos sugieren una ligera superioridad del modelo de Schnider.Doctorado en BiocienciasDoctor en Biociencia

Symbolic Dynamics applied to Electroencephalographic signals to Predict Response to Noxious Stimulation during Sedation-Analgesia

The level of sedation in patients undergoing medical procedures evolves continuously since the effect of the anesthetic and analgesic agents is counteracted by noxious stimuli. The monitors of depth of anesthesia, based on the analysis of the electroencephalogram (EEG), have been progressively introduced into the daily practice to provide additional information about the state of the patient. However, the quantification of analgesia still remains an open problem. In this project, a methodology based on non-linear techniques signal processing algorithms was developed and applied to the electroencephalogram (EEG) for predicting responses to noxious stimulation during Sedation-Analgesia. Two types of stimuli were performed by the anesthesiologist during the surgery sessions, RSS (Ramsay Sedation Scale) and GAG (gag reflex). These sedation scales are considered gold standard. In this work, the scope of the project includes: EEG preprocessing, processing and analysis of the mentioned signals. The methodology included an EEG signal preprocessing, a time-domain and frequency-domain analysis, the development and application of non-linear techniques, a statistical analysis and finally the validation of the results. Symbolic dynamics methodology, already applied to other kind of signals, was used as a non-linear technique. The aim was to extract a set of patterns from the EEG obtained through two proposed non-linear algorithms. The symbolic dynamics consists of the transformation of the time signal in a series of symbols by an algorithm. From these new series, words of three symbols were constructed with one symbol delay and their occurrence probability was evaluated in the signals variables. Base on this, the Shannon and Rényi entropies were applied to estimate the complexity of the distribution of the variables. Moreover, thresholds on probabilities were used to construct new variables. The analysis was applied to the EEG filtered according to the characteristic frequency bands (EEG rhythms). The parameters involved in the algorithms were statistically adjusted in order to better characterize the nociceptive response. Variables obtained from linear and non-linear methodologies were submitted to a statistical analysis using a nonparametric test and a linear discriminant analyses to assess the quality of the classification. The leaving-one-out method was used as validation criteria. New defined variables were able to describe the different states with p-value 60%, Sen > 60% and Pk > 0,6. This signal processing methodology technically contributes to the prediction of anesthesia depth level during Sedation-Analgesia