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van Albada S.J.,Jülich Research Center | van Albada S.J.,University of Sydney | van Albada S.J.,University of Western Sydney | Robinson P.A.,University of Sydney | And 2 more authors.
Frontiers in Human Neuroscience | Year: 2013

The degree to which electroenencephalographic (EEG) spectral peaks are independent, and the relationships between their frequencies have been debated. A novel fitting method was used to determine peak parameters in the range 2-35 Hz from a large sample of eyes-closed spectra, and their interrelationships were investigated. Findings were compared with a mean-field model of thalamocortical activity, which predicts near-harmonic relationships between peaks. The subject set consisted of 1424 healthy subjects from the Brain Resource International Database. Peaks in the theta range occurred on average near half the alpha peak frequency, while peaks in the beta range tended to occur near twice and three times the alpha peak frequency on an individual-subject basis. Moreover, for the majority of subjects, alpha peak frequencies were significantly positively correlated with frequencies of peaks in the theta and low and high beta ranges. Such a harmonic progression agrees semiquantitatively with theoretical predictions from the mean-field model. These findings indicate a common or analogous source for different rhythms, and help to define appropriate individual frequency bands for peak identification. © 2013 Van_albada and Robinson.


Phillips A.J.K.,University of Sydney | Phillips A.J.K.,Harvard University | Robinson P.A.,University of Sydney | Robinson P.A.,Center for Integrated Research and Understanding of Sleep | And 2 more authors.
PLoS Computational Biology | Year: 2010

Mammalian sleep varies widely, ranging from frequent napping in rodents to consolidated blocks in primates and unihemispheric sleep in cetaceans. In humans, rats, mice and cats, sleep patterns are orchestrated by homeostatic and circadian drives to the sleep-wake switch, but it is not known whether this system is ubiquitous among mammals. Here, changes of just two parameters in a recent quantitative model of this switch are shown to reproduce typical sleep patterns for 17 species across 7 orders. Furthermore, the parameter variations are found to be consistent with the assumptions that homeostatic production and clearance scale as brain volume and surface area, respectively. Modeling an additional inhibitory connection between sleep-active neuronal populations on opposite sides of the brain generates unihemispheric sleep, providing a testable hypothetical mechanism for this poorly understood phenomenon. Neuromodulation of this connection alone is shown to account for the ability of fur seals to transition between bihemispheric sleep on land and unihemispheric sleep in water. Determining what aspects of mammalian sleep patterns can be explained within a single framework, and are thus universal, is essential to understanding the evolution and function of mammalian sleep. This is the first demonstration of a single model reproducing sleep patterns for multiple different species. These wide-ranging findings suggest that the core physiological mechanisms controlling sleep are common to many mammalian orders, with slight evolutionary modifications accounting for interspecies differences. © 2010 Phillips et al.


Phillips A.J.K.,Harvard University | Fulcher B.D.,University of Oxford | Robinson P.A.,University of Sydney | Robinson P.A.,Center for Integrated Research and Understanding of Sleep | Klerman E.B.,Harvard University
PLoS Computational Biology | Year: 2013

Circadian rhythms are fundamental to life. In mammals, these rhythms are generated by pacemaker neurons in the suprachiasmatic nucleus (SCN) of the hypothalamus. The SCN is remarkably consistent in structure and function between species, yet mammalian rest/activity patterns are extremely diverse, including diurnal, nocturnal, and crepuscular behaviors. Two mechanisms have been proposed to account for this diversity: (i) modulation of SCN output by downstream nuclei, and (ii) direct effects of light on activity. These two mechanisms are difficult to disentangle experimentally and their respective roles remain unknown. To address this, we developed a computational model to simulate the two mechanisms and their influence on temporal niche. In our model, SCN output is relayed via the subparaventricular zone (SPZ) to the dorsomedial hypothalamus (DMH), and thence to ventrolateral preoptic nuclei (VLPO) and lateral hypothalamus (LHA). Using this model, we generated rich phenotypes that closely resemble experimental data. Modulation of SCN output at the SPZ was found to generate a full spectrum of diurnal-to-nocturnal phenotypes. Intriguingly, we also uncovered a novel mechanism for crepuscular behavior: if DMH/VLPO and DMH/LHA projections act cooperatively, daily activity is unimodal, but if they act competitively, activity can become bimodal. In addition, we successfully reproduced diurnal/nocturnal switching in the rodent Octodon degu using coordinated inversions in both masking and circadian modulation. Finally, the model correctly predicted the SCN lesion phenotype in squirrel monkeys: loss of circadian rhythmicity and emergence of ∼4-h sleep/wake cycles. In capturing these diverse phenotypes, the model provides a powerful new framework for understanding rest/activity patterns and relating them to underlying physiology. Given the ubiquitous effects of temporal organization on all aspects of animal behavior and physiology, this study sheds light on the physiological changes required to orchestrate adaptation to various temporal niches. © 2013 Phillips et al.


Fung P.K.,University of Sydney | Haber A.L.,University of Sydney | Robinson P.A.,University of Sydney | Robinson P.A.,Center for Integrated Research and Understanding of Sleep
Journal of Theoretical Biology | Year: 2013

A generalized timing-dependent plasticity rule is incorporated into a recent neural field theory to explore synaptic plasticity in the cerebral cortex, with both excitatory and inhibitory populations included. Analysis in the time and frequency domains reveals that cortical network behavior gives rise to a saddle-node bifurcation and resonant frequencies, including a gamma-band resonance. These system resonances constrain cortical synaptic dynamics and divide it into four classes, which depend on the type of synaptic plasticity window. Depending on the dynamical class, synaptic strengths can either have a stable fixed point, or can diverge in the absence of a separate saturation mechanism. Parameter exploration shows that time-asymmetric plasticity windows, which are signatures of spike-timing dependent plasticity, enable the richest variety of synaptic dynamics to occur. In particular, we predict a zone in parameter space which may allow brains to attain the marginal stability phenomena observed experimentally, although additional regulatory mechanisms may be required to maintain these parameters. © 2012 Elsevier Ltd.


Phillips A.J.K.,Harvard University | Robinson P.A.,University of Sydney | Robinson P.A.,Center for Integrated Research and Understanding of Sleep | Klerman E.B.,Harvard University
Journal of Theoretical Biology | Year: 2013

Human sleep episodes are characterized by an approximately 90-min ultradian oscillation between rapid eye movement (REM) and non-REM (NREM) sleep stages. The source of this oscillation is not known. Pacemaker mechanisms for this rhythm have been proposed, such as a reciprocal interaction network, but these fail to account for documented homeostatic regulation of both sleep stages. Here, two candidate mechanisms are investigated using a simple model that has stable states corresponding to Wake, REM sleep, and NREM sleep. Unlike other models of the ultradian rhythm, this model of sleep dynamics does not include an ultradian pacemaker, nor does it invoke a hypothetical homeostatic process that exists purely to drive ultradian rhythms. Instead, only two inputs are included: the homeostatic drive for Sleep and the circadian drive for Wake. These two inputs have been the basis for the most influential Sleep/Wake models, but have not previously been identified as possible ultradian rhythm generators. Using the model, realistic ultradian rhythms are generated by arousal state feedback to either the homeostatic or circadian drive. For the proposed 'homeostatic mechanism', homeostatic pressure increases in Wake and REM sleep, and decreases in NREM sleep. For the proposed 'circadian mechanism', the circadian drive is up-regulated in Wake and REM sleep, and is down-regulated in NREM sleep. The two mechanisms are complementary in the features they capture. The homeostatic mechanism reproduces experimentally observed rebounds in NREM sleep duration and intensity following total sleep deprivation, and rebounds in both NREM sleep intensity and REM sleep duration following selective REM sleep deprivation. The circadian mechanism does not reproduce sleep state rebounds, but more accurately reproduces the temporal patterns observed in a normal night of sleep. These findings have important implications in terms of sleep physiology and they provide a parsimonious explanation for the observed ultradian rhythm of REM/NREM sleep. © 2012 Elsevier Ltd.


Fung P.K.,University of Sydney | Robinson P.A.,University of Sydney | Robinson P.A.,Center for Integrated Research and Understanding of Sleep
Journal of Theoretical Biology | Year: 2013

Calcium dependent plasticity (CaDP), a physiologically realistic plasticity mechanism in the microscopic regime, is incorporated into a neural field theory to explore system-level plasticity. This system-level plasticity model is capable of reproducing the characteristic plasticity window of spike-timing dependent plasticity (STDP) in paired associative stimulation (PAS), where a peripheral electric pulse stimulation is paired to transcranial magnetic stimulation (TMS) in the cortex, and rTMS frequency dependent plasticity, where low and high frequency rTMS trains induce depression and potentiation, respectively. These thus reproduce experimental results for system-level plasticity for the first time. This also bridges the gap between microscopic plasticity theory and system-level plasticity observed experimentally, and addresses long standing problems of stability and adaptability by predicting stable plasticity, a possible seizure state where neurons fire at a high rate, and spike-rate adaptation. © 2013 Elsevier Ltd.


Abeysuriya R.G.,University of Sydney | Abeysuriya R.G.,Center for Integrated Research and Understanding of Sleep | Rennie C.J.,University of Sydney | Robinson P.A.,University of Sydney | Robinson P.A.,Center for Integrated Research and Understanding of Sleep
Journal of Neuroscience Methods | Year: 2015

A neural field model of the brain is used to represent brain states using physiologically based parameters rather than arbitrary, discrete sleep stages. Each brain state is represented as a point in a physiologically parametrized space. Over time, changes in brain state cause these points to trace continuous trajectories, unlike the artificial discrete jumps in sleep stage that occur with traditional sleep staging. The discrete Rechtschaffen and Kales sleep stages are associated with regions in the physiological parameter space based on their electroencephalographic features, which enables interpretation of traditional sleep stages in terms of physiological trajectories. Wake states are found to be associated with strong positive corticothalamic feedback compared to sleep. The existence of physiologically valid trajectories between brain states in the model is demonstrated. Actual trajectories for an individual can be determined by fitting the model using EEG alone, and enable analysis of the physiological differences between subjects. © 2015 Elsevier B.V..


Abeysuriya R.G.,University of Sydney | Abeysuriya R.G.,Center for Integrated Research and Understanding of Sleep | Rennie C.J.,University of Sydney | Robinson P.A.,University of Sydney | And 3 more authors.
Clinical Neurophysiology | Year: 2014

Objective: To investigate the properties of a sleep spindle harmonic oscillation previously predicted by a theoretical neural field model of the brain.Methods: Spindle oscillations were extracted from EEG data from nine subjects using an automated algorithm. The power and frequency of the spindle oscillation and the harmonic oscillation were compared across subjects. The bicoherence of the EEG was calculated to identify nonlinear coupling.Results: All subjects displayed a spindle harmonic at almost exactly twice the frequency of the spindle. The power of the harmonic scaled nonlinearly with that of the spindle peak, consistent with model predictions. Bicoherence was observed at the spindle frequency, confirming the nonlinear origin of the harmonic oscillation.Conclusions: The properties of the sleep spindle harmonic were consistent with the theoretical modeling of the sleep spindle harmonic as a nonlinear phenomenon.Significance: Most models of sleep spindle generation are unable to produce a spindle harmonic oscillation, so the observation and theoretical explanation of the harmonic is a significant step in understanding the mechanisms of sleep spindle generation. Unlike seizures, sleep spindles produce nonlinear effects that can be observed in healthy controls, and unlike the alpha oscillation, there is no linearly generated harmonic that can obscure nonlinear effects. This makes the spindle harmonic a good candidate for future investigation of nonlinearity in the brain. © 2014 International Federation of Clinical Neurophysiology.


Fung P.K.,University of Sydney | Robinson P.A.,University of Sydney | Robinson P.A.,Center for Integrated Research and Understanding of Sleep
Journal of Theoretical Biology | Year: 2014

Transcranial magnetic stimulation (TMS) is characterized by strong nonlinear plasticity effects. Experimental results that highlight such nonlinearity include continuous and intermittent theta-burst stimulations (cTBS and iTBS, respectively), where depression is induced in the continuous case, but insertion of an off period of around 8. s for every 2. s of stimulation changes the induced plasticity to potentiation in the intermittent case. Another nonlinearity is that cTBS and iTBS exhibit dosage dependency, where doubling of the stimulation duration changes the direction of induced plasticity. Guided by previous experimental results, this study postulates on the characteristics of metaplasticity and formulates a physiological system-level plasticity theory to predict TMS experiments. In this theory, plasticity signaling induces plasticity in NMDA receptors to modulate further plasticity signals, and is followed by a signal transduction delayed plasticity expression. Since this plasticity in NMDA receptor affects subsequent plasticity induction, it is a form of metaplasticity. Incorporating this metaplasticity into a recent neural field theory of calcium dependent plasticity gives a physiological basis for the theory of Bienenstock, Cooper, Munro (1982), where postsynaptic intracellular calcium level becomes the measure of temporal averaged postsynaptic activity, and converges to the plasticity threshold to give homeostatic effects. Simulations of TMS protocol responses show that intracellular calcium oscillations around the threshold predicts the aforementioned nonlinearities in TMS-induced plasticity, as well as the interpersonal TBS response polarity found experimentally, where the same protocol may induce opposite plasticity effect for different subjects. Thereby, recommendations for future experiments and TMS protocol optimizations are made. Input selectivity via spatially extended, mean field neural dynamics is also explored.© 2013 Elsevier Ltd.


Abeysuriya R.G.,University of Sydney | Abeysuriya R.G.,Center for Integrated Research and Understanding of Sleep | Rennie C.J.,University of Sydney | Robinson P.A.,University of Sydney | Robinson P.A.,Center for Integrated Research and Understanding of Sleep
Journal of Theoretical Biology | Year: 2014

This paper examines nonlinear effects in a neural field model of the corticothalamic system to predict the EEG power spectrum of sleep spindles. Nonlinearity in the thalamic relay nuclei gives rise to a spindle harmonic visible in the cortical EEG. By deriving an analytic expression for nonlinear spectrum, the power in the spindle harmonic is predicted to scale quadratically with the power in the spindle oscillation. By isolating sleep spindles from background sleep in experimental EEG data, the spindle harmonic is directly observed. © 2013 Elsevier Ltd.

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