THEMATIC PROGRAMS

September  1, 2014
THE FIELDS INSTITUTE
FOR RESEARCH IN MATHEMATICAL SCIENCES
Focus Program on "Towards Mathematical Modeling of Neurological Disease fromCellular Perspectives"
Anesthesiology/Sleep Disorders Workshop
June 4-5, 2012


Abtracts

Maxim Bazhenov, University of California- Riverside
Sleep spindle oscillations - new insights on an old topic

Spindle oscillations are commonly observed during stage two of non-REM sleep. During sleep spindles, the cerebral cortex and thalamus interact through feedback connections. Both initiation and termination of spindle oscillations are thought to originate in the thalamus, based on thalamic recordings and computational models. Drawing on results obtained with large-scale biophysical network models of the thalamocortical system, I will discuss the role of corticothalamic influences on initiation, termination and synchronization of sleep spindles.

Victoria Booth, University of Michigan
Modeling the temporal architecture of sleep-wake transition dynamics

Sleep and wake states are regulated by the interactions among a number of brainstem and hypothalamic neuronal populations and the expression of their neurotransmitters. Based on different experimental studies, several different structures have been proposed for this sleep-wake regulatory network with particular debate over components involved in rapid-eye movement (REM) sleep regulation. We have developed a mathematical modeling framework that is uniquely suited for investigating the structure and dynamics of proposed sleep-wake regulatory networks. Using this framework, we constructed a sleep-wake regulatory network model based on the reciprocal interaction hypothesis for REM sleep regulation. I will discuss our analysis to determine how the structure of the sleep-wake regulatory network determines sleep-wake behavior and the dynamics of behavioral state transitions. I will also discuss the deterministic and stochastic model properties necessary to generate realistic rat sleep-wake temporal architecture as assessed by both standard summary statistics and survival analysis of bout distributions.

ShiNung Ching, Massachusetts General Hospital & Harvard Medical School
Biophysical models of neuronal dynamics during general anesthesia and burst suppression

Recent research has revealed new electrophysiological oscillations that are associated with unconsciousness under general anesthesia. We are using biophysical modeling to elucidate how the molecular actions of anesthetic drugs manifest in larger neuronal networks to create such brain dynamics. As an example, I will first present recent modeling of an 'alpha' (9-12Hz) EEG oscillation that appears during surgical levels of propofol-induced general anesthesia. Such oscillations differ from classical 'alpha' oscillations in their frequency and spatial location. Using conductance-based neuronal models, we have shown how propofol - an agonist of GABAergic neurotransmission - can promote highly synchronous alpha oscillations in thalamocortical networks, leading to the observed phenomenology. These oscillations may impede normal thalamocortical dynamics and thus, correlate with reductions in arousal.

I will then discuss recent models for the state of burst suppression, which consists of high voltage EEG activity (bursts) that alternates with isoelectric quiescence (suppression). Burst suppression occurs at deep levels of general anesthesia and also in pathological conditions such as coma. Our modeling suggests that the dynamics of burst suppression arise not simply from neuromodulatory effects, but also from changes in brain metabolism. Specifically, I will discuss how a lowered cerebral metabolic rate can lead to epochs of burst and suppression by inducing transient reductions in cerebral ATP and subsequent gating of neuronal potassium channels. This model provides a unified mechanism of burst suppression that is consistent with each of its etiologies and provides a platform to study the brain network dynamics associated with other anesthetic drugs and related pathological states.

Jeffrey Ellenbogen, Harvard University
Oscillatory activity of the brain predicts sound sleep on noisy nights

Human sleep can be defined as a natural, transient state of reduced responsiveness. This perspective operationally explains sleep as a state with diminished processing of external stimuli, such as noises that we encounter every day (e.g., alarms, people talking, etc). But in fact, there is a wide range of responsiveness to noises within sleep, both across a single night and between different people. Some moments of sleep, and some sleepers themselves, are more resistant to disruption due to noise. What are the biological drivers of these phenomena that protect sleep or render it fragile? Can they be quantified through signal-processing techniques of human electroencephalography (EEG)? I will discuss some current techniques, and some novel ones, that are employed to analyze human EEG of sleep. I will demonstrate their effectiveness and limitations at examining sleep depth by showing experimental data of people awoken from sleep from various noises. I will also discuss future implications, including real-time analysis techniques that might interface with novel therapies for disrupted sleep.

Sean Hill, Karolinska Institute
Wakefulness and Sleep: A computational model of thalamocortical circuitry

I will present a model cat visual thalamocortical system (Hill and Tononi, 2005) containing ~65,000 integrate-and-fire neurons and 6 million connections capable of producing rich spontaneous activity as well as orientation-selective responses to visual stimuli during wakefulness. The model encompasses two visual areas divided into three layers (supragranular, infragranular and layer IV) with the associated thalamic and reticular thalamic nuclei. Model neurons (both excitatory and inhibitory) are highly interconnected with patterned thalamocortical, corticothalamic, and intra- and interareal corticocortical connections. The model also incorporates experimentally observed intrinsic currents that are thought to affect sleep rhythms. The model exhibits a waking mode, characterized by highly variable spontaneous activity throughout the cortex as well as orientation selective responses to visual stimuli. Evoked visual activity displayed gamma frequency thalamocortical synchronization. In the sleep mode, the model displays spontaneously occurring slow oscillations that resemble those observed in vivo and in vitro. I will also present results from studies in which this model has been used to explore homeostatic processes and plasticity - including the synaptic homeostasis hypothesis of sleep.

Richard L. Horner, University of Toronto
Sleep: Brain rewiring for flexible behaviour, with implications for the evolutionary trajectory of species

On July 1st 2005 Science published its 125th anniversary issue and highlighted the most compelling but unresolved scientific questions. Why we sleep and why we dream were two of them. This paper will first present a logical construct derived from evolutionary theory that any explanation of sleep must be able to fit in order to be applicable to diverse organisms across the tree of life. This construct is then used to satisfy the identification of the primary function of sleep (defined as the reason that sleep evolved for the function it still serves), and distinguishes this from secondary functions (defined as those that are associated with sleep but which are not part of its fundamental nature). Identification of the primary adaptive property of sleep that is visible to natural selection is then used to explain how sleep powerfully affects the individual fitness of organisms and the evolutionary trajectory of species. This identification of the primary function of sleep explains the diversity of sleep-wake behaviour between species and individuals across the lifespan, and the consequences of sleep disruption and drug-induced sedation on brain activity and behaviour.

L. Stan Leung, University of Western
Basal forebrain participation in general anesthesia

The basal forebrain is highly interconnected with a number of brain regions involved in sleep-wake regulation, including cholinergic inputs from the pedunculopontine nucleus and laterodorsal nucleus of the pons, histaminergic inputs from tuberomammillary nucleus (TM) of the posterior hypothalamus, noradrenergic inputs from the locus coeruleus and serotonergic inputs from the raphe. The basal forebrain nuclei consist of the nucleus basalis (NB) that projects to the neocortex and the medial septum/ diagonal band area (MS) that project to the hippocampus and entorhinal cortex. We have used reversible inactivation (by local brain application GABAA receptor agonist muscimol) and permanent lesion of the basal forebrain, and selective lesion of histaminergic neurons in the TM, to study whether these structures participate in the emergence and induction of general anesthesia in rats. The main indicator of general anesthesia was a loss of righting reflex (LORR); tail pinch response and frontal cortical and hippocampal EEGs were also recorded.

Muscimol inactivation of the MS and NB prolonged the duration of LORR induced by both injectable (propofol, pentobarbital) and volatile anesthetic (isoflurane, halothane). The dose of anesthetic that induced slow delta EEG waves in the frontal cortex or suppress high gamma activity (70-100 Hz) in the hippocampus was reduced when either the MS or NB was inactivated. However, high-amplitude neocortical delta waves could occur in a standing, non-anesthetized rat after inactivation of NB, and thus neocortical delta EEG by itself does not indicate general anesthesia. Selective lesion of cholinergic neurons in the MS and NB, by local infusion of cholinotoxin 192 IgG-saporin, prolonged the duration of LORR following an anesthetic. Lesion of the histaminergic neurons in the TMN by orexin-saporin also delayed emergence (recovery of LORR) following isoflurane in addition to enhance the sensitivity to isoflurane. NB application of histamine facilitated, while H1 receptor antagonist triprolidine delayed, emergence from isoflurane anesthesia.

Other than the basal forebrain, bilateral inactivation of structures in the limbic system, including the nucleus accumbens, ventral tegmental area, ventral pallidum supramammillary area and amygdala prolonged the duration of LORR following pentobarbital or halothane. The latter inactivation, as compared to saline infusion, also increased delta waves and decreased hippocampal theta and gamma waves following a general anesthetic. By contrast, infusion of muscimol in the median raphe did not significantly alter the behavioral or EEG effects of halothane or pentobarbital. Bilateral inactivation of the entorhinal or piriform cortex prolonged the duration of LORR induced by pentobarbital but not halothane. The effect of inactivation on anesthetic-induced LORR may be explained in part by the connection of the brain area to the basal forebrain. Limbic system inactivation also suppressed the delirium state induced by a dose of anesthestic, including that induced by halothane, isoflurane, pentobarbital and ketamine.

Our research suggests that subcortical histaminergic and cholinergic inputs participate in activating the brain during wake and general anesthesia, such that removal of histaminergic or cholinergic activation of the forebrain increases anesthetic sensitivity and delays emergence. Other work suggests that norepinephrinergic and orexinergic pathways also participating in brain activation and general anesthesia. Our work highlights the limbic system, including the medial septum, hippocampus and nucleus accumbens, as important participants in general anesthesia, and in mediating the delirium state.

Beverly Orser, University of Toronto
Atypical GABA-A receptors regulate the memory blocking properties of general anesthetics

Memory blockade is one of the most potent and essential properties of general anesthetics. Unfortunately, some patients experience persistent memory deficits long after the anesthetic has been eliminated. Paradoxically, other patients experience inadequate memory loss leading to “intraoperative awareness”. The molecular mechanisms underlying the memory blocking properties of anesthetics remain poorly understood and have been a focus of our research. I will present studies that identify a subtype of inhibitory GABAA receptor that is highly sensitive to up-regulation by inhaled and intravenous anesthetics. The role of these receptors in normal memory processes and persistent memory deficits after exposure to anesthetics will be discussed.

Patrick L. Purdon, Ph.D., Massachusetts General Hospital, Harvard Medical School
Electroencephalogram Signatures of Loss and Recovery of Consciousness During Propofol-Induced General Anesthesia

How can anesthesiologists tell when patients are unconscious under general anesthesia? Since the 1930's, stereotyped electroencephalogram (EEG) patterns have been observed during general anesthesia, yet the specific signals that demarcate loss and recovery of consciousness have remained elusive. In this talk, I will be presenting results from human studies showing behavioral changes and EEG signatures that occur in the transition between consciousness and unconsciousness during gradual induction and emergence from general anesthesia. We characterized level of consciousness using an auditory response task, and observed that the probability of response decreased gradually in the transitions to and from unconsciousness. The transition to loss of consciousness was marked by increased gamma and beta power that decreased in center frequency and bandwidth as the probability of response decreased. At loss of consciousness, low-frequency and globally-coherent frontal alpha oscillations developed, while occipital alpha oscillations were abolished. During emergence from propofol anesthesia, these EEG patterns reversed. These results establish electrophysiological signatures that can be used to monitor and manage the state of unconsciousness under general anesthesia, and provide important insights into the mechanisms underlying this state.

Igor Timofeev, The Centre de Recherche Institut Universitaire en Santé Mentale de Québec (CRIUSMQ), Laval University
Slow-wave activity during sleep and ketamine-xylazine anesthesia

Deep anesthesia is commonly used as a model of slow-wave sleep (SWS). Ketamine-xylazine anesthesia reproduces the main features of sleep slow oscillation: slow, large amplitude waves in field potential, which are generated by the alternation of hyperpolarized and depolarized states of cortical neurons. However, detailed comparison of field potential and membrane potential fluctuations during natural sleep and anesthesia was absent tile resent, so it remaine unclear how well the properties of sleep slow oscillation are reproduced by the ketamine-xylazine anesthesia model of slow-wave sleep. I will present resent data on field potential and intracellular recordings in different cortical areas in the cat, to directly compare properties of slow oscillation during natural sleep and ketamine-xylazine anesthesia. During SWS cortical activity showed higher power in the slow/delta (0.1-4 Hz) and spindle (8-14 Hz) frequency range, while under anesthesia the power in the gamma band (30-100 Hz) was higher. During anesthesia, slow waves were more rhythmic and more synchronous across the cortex. Intracellular recordings revealed that silent states were longer and the amplitude of membrane potential around transition between active and silent states was bigger under anesthesia. Slow waves were largely uniform across cortical areas under anesthesia, but in SWS they were most pronounced in associative and visual areas, but smaller and less regular in somatosensory and motor cortices. We conclude that although the main features of the slow oscillation in sleep and anesthesia appear similar, multiple cellular and network features are differently expressed during natural SWS as compared to ketamine-xylazine anesthesia.

Martin Wechselberger, University of Sydney
Canard theory and neuronal dynamics

An important feature of most physiological systems is that they evolve on multiple scales. For example, the bursting activity of neurons consists of a long interval of quasi steady-state followed by an interval of rapid variation, which is the burst itself. It is the interplay of the dynamics on different temporal or spatial scales that creates complicated rhythms and patterns.

Multiple scales problems of physiological systems are usually modelled by singularly perturbed systems. The geometric theory of multiple scales dynamical systems -- known as Fenichel Theory -- has provided powerful tools for studying singular perturbation problems. In conjunction with the innovative blow-up technique, geometric singular perturbation theory delivers rigorous results on pattern generation in multiple time-scale problems.

As a case study of geometric singular perturbation theory, I will focus on a single neuron model by McCarthy et al. (2008) that looks at the effect of the anesthetic propofol on such a neuron. It is well known that propofol causes paradoxical excitation in low doses. I will show that "canards", exceptional solutions in singular perturbation problems which occur on boundaries of regions corresponding to different dynamic behaviors, provide a possible explanation of the observed paradox.

 

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