Brain Connectivity Dissociates Responsiveness from Drug Exposure during Propofol-Induced Transitions of Consciousness.

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.This work was supported by grants from the James S. McDonnell Foundation, the Wellcome Trust [WT093811MA to TAB], and the British Oxygen Professorship from the Royal College of Anaesthetists [to DKM]. The research was also supported by the NIHR Brain Injury Healthcare Technology Co-operative based at Cambridge University Hospitals NHS Foundation Trust and University of Cambridge. The views expressed are those of the authors and not necessarily those of the UK National Health Service, the NIHR or the UK Department of Health. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.This is the final version of the article. It was first available from PLOS via http://dx.doi.org/10.1371/journal.pcbi.100466

Changes in resting neural connectivity during propofol sedation.

BACKGROUND: The default mode network consists of a set of functionally connected brain regions (posterior cingulate, medial prefrontal cortex and bilateral parietal cortex) maximally active in functional imaging studies under "no task" conditions. It has been argued that the posterior cingulate is important in consciousness/awareness, but previous investigations of resting interactions between the posterior cingulate cortex and other brain regions during sedation and anesthesia have produced inconsistent results. METHODOLOGY/PRINCIPAL FINDINGS: We examined the connectivity of the posterior cingulate at different levels of consciousness. "No task" fMRI (BOLD) data were collected from healthy volunteers while awake and at low and moderate levels of sedation, induced by the anesthetic agent propofol. Our data show that connectivity of the posterior cingulate changes during sedation to include areas that are not traditionally considered to be part of the default mode network, such as the motor/somatosensory cortices, the anterior thalamic nuclei, and the reticular activating system. CONCLUSIONS/SIGNIFICANCE: This neuroanatomical signature resembles that of non-REM sleep, and may be evidence for a system that reduces its discriminable states and switches into more stereotypic patterns of firing under sedation

Propofol sedation-induced alterations in brain connectivity reflect parvalbumin interneurone distribution in human cerebral cortex.

BACKGROUND: Propofol, a commonly used intravenous anaesthetic, binds to type A gamma aminobutyric acid (GABA) receptors in mammalian brain. Previous work on its anaesthetic action has characterised either the biochemistry underlying propofol binding or the associated changes in brain network dynamics during sedation. Despite these advances, no study has focused on understanding how propofol action at the cellular level results in changes in brain network connectivity. METHODS: We used human whole-brain microarray data to generate distribution maps for genes that mark the primary GABAergic cortical interneurone subtypes (somatostatin, parvalbumin [PV], and 5-hydroxytryptamine 3A. Next, 25 healthy participants underwent propofol-induced sedation during resting state functional MRI scanning. We used partial least squares analysis to identify the brain regions in which connectivity patterns were most impacted by propofol sedation. We then correlated these multimodal cortical patterns to determine if a specific interneurone subtype was disproportionately expressed in brain regions in which connectivity patterns were altered during sedation. RESULTS: Brain networks that were significantly altered by propofol sedation had a high density of PV-expressing GABAergic interneurones. Brain networks that anticorrelated during normal wakefulness, namely the default mode network and attentional and frontoparietal control networks, increased in correlation during sedation. CONCLUSIONS: PV-expressing interneurones are highly expressed in brain regions with altered connectivity profiles during propofol-induced sedation. This study also demonstrates the utility of leveraging multiple datasets to address multiscale neurobiological problems.This work was supported by a grant from the Wellcome Trust: Clinical Research Training Fellowship to RA.(Contract grant number: O8366O/Z/O7/Z); the National Institute for Health Research (NIHR, UK), Cambridge Biomedical Research Centre and NIHR Senior Investigator Awards to DKM; The Canadian Institute for Advanced Research (CIFAR) to DKM and EAS (RCZB/O72 RG93l93); the Stephen Erskine Fellowship (Queens' College, Cambridge) to EAS; the British Oxygen Professorship of the Royal College of Anaesthetists to DKM. MC was supported by the Cambridge International Trust and the Howard Sidney Sussex Research Studentship. IP was supported by Downing College, University of Cambridge through a Treherne Studentship; This work was also supported by the NIHR Brain Injury Healthcare Technology Co-operative based at Cambridge University Hospitals NHS Foundation Trust and University of Cambridge

A comparison of AC and HVDC options for the connection of offshore wind generation in Great Britain

This paper presents a comparison of two forms of cable connection of a distant offshore wind farm to a transmission system: AC and HVDC. The requirements of relevant industry standards in Great Britain (GB) that drive a connection design and, hence, its cost are highlighted along with an analysis of the ways in which AC cable connections might be made to comply while facilitating export of active power. Dynamic studies investigating responses to grid-side short circuit faults show that, in the particular scenarios studied, an AC connection of a wind farm in the place of a large synchronous generator is marginally detrimental while an HVDC connection is beneficial. A comparison of costs shows that the cross-over distance at which HVDC is cheaper than AC for wind farms of different sizes occurs at longer distances than have hitherto commonly been assumed, and AC connections benefit from reactive compensation not only at the point of common coupling and wind farm end but also at the connection mid-point

Factoring the brain signatures of anesthesia concentration and level of arousal across individuals.

Combining resting-state functional magnetic resonance imaging (fMRI) connectivity and behavioral analysis during sedation, we factored out general effects of the anesthetic drug propofol and a specific index of conscious report, participants' level of responsiveness. The factorial analysis shows that increasing concentration of propofol in blood specifically decreases the connectivity strength of fronto-parietal cortical loops. In contrast, loss of responsiveness is indexed by a functional disconnection between the thalamus and the frontal cortex, balanced by an increase in connectivity strength of the thalamus to the occipital and temporal regions of the cortex

Fractal dimension of cortical functional connectivity networks & severity of disorders of consciousness.

Recent evidence suggests that the quantity and quality of conscious experience may be a function of the complexity of activity in the brain and that consciousness emerges in a critical zone between low and high-entropy states. We propose fractal shapes as a measure of proximity to this critical point, as fractal dimension encodes information about complexity beyond simple entropy or randomness, and fractal structures are known to emerge in systems nearing a critical point. To validate this, we tested several measures of fractal dimension on the brain activity from healthy volunteers and patients with disorders of consciousness of varying severity. We used a Compact Box Burning algorithm to compute the fractal dimension of cortical functional connectivity networks as well as computing the fractal dimension of the associated adjacency matrices using a 2D box-counting algorithm. To test whether brain activity is fractal in time as well as space, we used the Higuchi temporal fractal dimension on BOLD time-series. We found significant decreases in the fractal dimension between healthy volunteers (n = 15), patients in a minimally conscious state (n = 10), and patients in a vegetative state (n = 8), regardless of the mechanism of injury. We also found significant decreases in adjacency matrix fractal dimension and Higuchi temporal fractal dimension, which correlated with decreasing level of consciousness. These results suggest that cortical functional connectivity networks display fractal character and that this is associated with level of consciousness in a clinically relevant population, with higher fractal dimensions (i.e. more complex) networks being associated with higher levels of consciousness. This supports the hypothesis that level of consciousness and system complexity are positively associated, and is consistent with previous EEG, MEG, and fMRI studies

Placing meta-stable states of consciousness within the predictive coding hierarchy: The deceleration of the accelerated prediction error.

While many studies have linked prediction errors and event related potentials at a single processing level, few consider how these responses interact across levels. In response, we present a factorial analysis of a multi-level oddball task - the local-global task - and we explore it when participants are sedated versus recovered. We found that the local and global levels in fact interact. This is of considerable current interest, since it has recently been argued that the MEEG response evoked by the global effect corresponds to a distinct processing mode that moves beyond predictive coding. This interaction suggests that the two processing modes are not distinct. Additionally, we observed that sedation modulates this interaction, suggesting that conscious awareness may not be completely restricted to a single (global) processing level

Sedation Modulates Frontotemporal Predictive Coding Circuits and the Double Surprise Acceleration Effect.

Two important theories in cognitive neuroscience are predictive coding (PC) and the global workspace (GW) theory. A key research task is to understand how these two theories relate to one another, and particularly, how the brain transitions from a predictive early state to the eventual engagement of a brain-scale state (the GW). To address this question, we present a source-localization of EEG responses evoked by the local-global task-an experimental paradigm that engages a predictive hierarchy, which encompasses the GW. The results of our source reconstruction suggest three phases of processing. The first phase involves the sensory (here auditory) regions of the superior temporal lobe and predicts sensory regularities over a short timeframe (as per the local effect). The third phase is brain-scale, involving inferior frontal, as well as inferior and superior parietal regions, consistent with a global neuronal workspace (GNW; as per the global effect). Crucially, our analysis suggests that there is an intermediate (second) phase, involving modulatory interactions between inferior frontal and superior temporal regions. Furthermore, sedation with propofol reduces modulatory interactions in the second phase. This selective effect is consistent with a PC explanation of sedation, with propofol acting on descending predictions of the precision of prediction errors; thereby constraining access to the GNW.University if Kent Internal Funds to Dr. Bowma

Consciousness & Brain Functional Complexity in Propofol Anaesthesia

Funder: Oon Khye Beng Ch’Hia Tsio Studentship for Research in Preventive Medicine, administered via Downing CollegeFunder: L’Oréal-Unesco for Women in Science Excellence Research FellowshipFunder: Canadian Institute for Advanced research (CIFAR)Funder: Cambridge Biomedical Research Centre NIHR Senior Investigator AwardsFunder: Stephen Erskine Fellowship at Queens’ College, CambridgeAbstract: 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

Ketamine effects on memory reconsolidation favor a learning model of delusions.

Delusions are the persistent and often bizarre beliefs that characterise psychosis. Previous studies have suggested that their emergence may be explained by disturbances in prediction error-dependent learning. Here we set up complementary studies in order to examine whether such a disturbance also modulates memory reconsolidation and hence explains their remarkable persistence. First, we quantified individual brain responses to prediction error in a causal learning task in 18 human subjects (8 female). Next, a placebo-controlled within-subjects study of the impact of ketamine was set up on the same individuals. We determined the influence of this NMDA receptor antagonist (previously shown to induce aberrant prediction error signal and lead to transient alterations in perception and belief) on the evolution of a fear memory over a 72 hour period: they initially underwent Pavlovian fear conditioning; 24 hours later, during ketamine or placebo administration, the conditioned stimulus (CS) was presented once, without reinforcement; memory strength was then tested again 24 hours later. Re-presentation of the CS under ketamine led to a stronger subsequent memory than under placebo. Moreover, the degree of strengthening correlated with individual vulnerability to ketamine's psychotogenic effects and with prediction error brain signal. This finding was partially replicated in an independent sample with an appetitive learning procedure (in 8 human subjects, 4 female). These results suggest a link between altered prediction error, memory strength and psychosis. They point to a core disruption that may explain not only the emergence of delusional beliefs but also their persistence