Brain imaging reveals covert consciousness during behavioral unresponsiveness induced by propofol.
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ABSTRACT:
SUBMITTER: Huang Z
PROVIDER: S-EPMC6123455 | biostudies-literature | 2018 Sep
REPOSITORIES: biostudies-literature
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Project description:Accurately measuring the neural correlates of consciousness is a grand challenge for neuroscience. Despite theoretical advances, developing reliable brain measures to track the loss of reportable consciousness during sedation is hampered by significant individual variability in susceptibility to anaesthetics. We addressed this challenge using high-density electroencephalography to characterise changes in brain networks during propofol sedation. Assessments of spectral connectivity networks before, during and after sedation were combined with measurements of behavioural responsiveness and drug concentrations in blood. Strikingly, we found that participants who had weaker alpha band networks at baseline were more likely to become unresponsive during sedation, despite registering similar levels of drug in blood. In contrast, phase-amplitude coupling between slow and alpha oscillations correlated with drug concentrations in blood. Our findings highlight novel markers that prognosticate individual differences in susceptibility to propofol and track drug exposure. These advances could inform accurate drug titration and brain state monitoring during anaesthesia.
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Project description:Reliable electroencephalography (EEG) signatures of transitions between consciousness and unconsciousness under anaesthesia have not yet been identified. Herein we examined network changes using graph theoretical analysis of high-density EEG during patient-titrated propofol-induced sedation. Responsiveness was used as a surrogate for consciousness. We divided the data into five states: baseline, transition into unresponsiveness, unresponsiveness, transition into responsiveness, and recovery. Power spectral analysis showed that delta power increased from responsiveness to unresponsiveness. In unresponsiveness, delta waves propagated from frontal to parietal regions as a traveling wave. Local increases in delta connectivity were evident in parietal but not frontal regions. Graph theory analysis showed that increased local efficiency could differentiate the levels of responsiveness. Interestingly, during transitions of responsive states, increased beta connectivity was noted relative to consciousness and unconsciousness, again with increased local efficiency. Abrupt network changes are evident in the transitions in responsiveness, with increased beta band power/connectivity marking transitions between responsive states, while the delta power/connectivity changes were consistent with the fading of consciousness using its surrogate responsiveness. These results provide novel insights into the neural correlates of these behavioural transitions and EEG signatures for monitoring the levels of consciousness under sedation.
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Project description:The brain is possibly the most complex system known to mankind, and its complexity has been called upon to explain the emergence of consciousness. However, complexity has been defined in many ways by multiple different fields: here, we investigate measures of algorithmic and process complexity in both the temporal and topological domains, testing them on functional MRI BOLD signal data obtained from individuals undergoing various levels of sedation with the anaesthetic agent propofol, replicating our results in two separate datasets. We demonstrate that the various measures are differently able to discriminate between levels of sedation, with temporal measures showing higher sensitivity. Further, we show that all measures are strongly related to a single underlying construct explaining most of the variance, as assessed by Principal Component Analysis, which we interpret as a measure of "overall complexity" of our data. This overall complexity was also able to discriminate between levels of sedation and serum concentrations of propofol, supporting the hypothesis that consciousness is related to complexity - independent of how the latter is measured.
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Project description:General anesthesia (GA) is a reversible manipulation of consciousness whose mechanism is mysterious at the level of neural networks leaving space for several competing hypotheses. We recorded electrocorticography (ECoG) signals in patients who underwent intracranial monitoring during awake surgery for the treatment of cerebral tumors in functional areas of the brain. Therefore, we recorded the transition from unconsciousness to consciousness directly on the brain surface. Using frequency resolved interferometry; we studied the intermediate ECoG frequencies (4-40?Hz). In the theoretical study, we used a computational Jansen and Rit neuron model to simulate recovery of consciousness (ROC). During ROC, we found that f increased by a factor equal to 1.62?±?0.09, and ?f varied by the same factor (1.61?±?0.09) suggesting the existence of a scaling factor. We accelerated the time course of an unconscious EEG trace by an approximate factor 1.6 and we showed that the resulting EEG trace match the conscious state. Using the theoretical model, we successfully reproduced this behavior. We show that the recovery of consciousness corresponds to a transition in the frequency (f, ?f) space, which is exactly reproduced by a simple time rescaling. These findings may perhaps be applied to other altered consciousness states.
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Project description:BackgroundImpaired consciousness has been associated with impaired cortical signal propagation after transcranial magnetic stimulation (TMS). We hypothesised that the reduced current propagation under propofol-induced unresponsiveness is associated with changes in both feedforward and feedback connectivity across the cortical hierarchy.MethodsEight subjects underwent left occipital TMS coupled with high-density EEG recordings during wakefulness and propofol-induced unconsciousness. Spectral analysis was applied to responses recorded from sensors overlying six hierarchical cortical sources involved in visual processing. Dynamic causal modelling (DCM) of induced time-frequency responses and evoked response potentials were used to investigate propofol's effects on connectivity between regions.ResultsSensor space analysis demonstrated that propofol reduced both induced and evoked power after TMS in occipital, parietal, and frontal electrodes. Bayesian model selection supported a DCM with hierarchical feedforward and feedback connections. DCM of induced EEG responses revealed that the primary effect of propofol was impaired feedforward responses in cross-frequency theta/alpha-gamma coupling and within frequency theta coupling (F contrast, family-wise error corrected P<0.05). An exploratory analysis (thresholded at uncorrected P<0.001) also suggested that propofol impaired feedforward and feedback beta band coupling. Post hoc analyses showed impairments in all feedforward connections and one feedback connection from parietal to occipital cortex. DCM of the evoked response potential showed impaired feedforward connectivity between left-sided occipital and parietal cortex (T contrast P=0.004, Bonferroni corrected).ConclusionsPropofol-induced loss of consciousness is associated with impaired hierarchical feedforward connectivity assessed by EEG after occipital TMS.
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