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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. Source

Aquino K.M.,University of New South Wales | Aquino K.M.,Queensland Institute of Medical Research | Aquino K.M.,University of Western Sydney | Robinson P.A.,University of New South Wales | And 10 more authors.
NeuroImage | Year: 2014

Functional magnetic resonance imaging (fMRI) is a powerful and broadly used means of non-invasively mapping human brain activity. However fMRI is an indirect measure that rests upon a mapping from neuronal activity to the blood oxygen level dependent (BOLD) signal via hemodynamic effects. The quality of estimated neuronal activity hinges on the validity of the hemodynamic model employed. Recent work has demonstrated that the hemodynamic response has non-separable spatiotemporal dynamics, a key property that is not implemented in existing fMRI analysis frameworks. Here both simulated and empirical data are used to demonstrate that using a physiologically based model of the spatiotemporal hemodynamic response function (stHRF) results in a quantitative improvement of the estimated neuronal response relative to unphysical space-time separable forms. To achieve this, an integrated spatial and temporal deconvolution is established using a recently developed stHRF. Simulated data allows the variation of key parameters such as noise and the spatial complexity of the neuronal drive, while knowing the neuronal input. The results demonstrate that the use of a spatiotemporally integrated HRF can avoid "ghost" neuronal responses that can otherwise be falsely inferred. Applying the spatiotemporal deconvolution to high resolution fMRI data allows the recovery of neuronal responses that are consistent with independent electrophysiological measures. © 2014 Elsevier Inc. Source

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. Source

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. Source

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. Source

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