Slow-wave oscillations in a corticothalamic model of sleep and wake

Zhao, Xuelong; Kim, J.W.; Robinson, P. A.

doi:10.1016/j.jtbi.2015.01.028

Cited by 13 publications

(24 citation statements)

References 44 publications

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“…Our aim is to implement the minimal dynamics necessary to model bursting in a neural field model Zhao et al 2015). Previously, we have shown that bursting dynamics in the reticular nucleus is sufficient to reproduce EEG properties such as time series and spectra similar to those seen in normal arousal states in wake and sleep (Zhao et al 2015), while in the current work we have further extended this to include generalized seizures (Table 1).…”

Section: Methodsmentioning

confidence: 91%

“…Here we briefly outline and review the extended neural field model with bursting dynamics incorporated into the reticular nucleus (Robinson et al , 2004Zhao et al 2015. We then investigate the parameter space and stability of the model that we use to show the transition from normal states to pathological seizures.…”

Section: Methodsmentioning

confidence: 99%

“…In the current work, we study a corticothalamic neural field model (Robinson et al , 2004Robinson 2006) that has recently been extended to include bursting dynamics in the reticular nucleus (Zhao et al 2015). Here, we analyze the corticothalamic dynamics of this extended neural field model to reproduce absence seizures studied under the original neural field model Breakspear et al 2006) while analyzing how bursting dynamics in the reticular nucleus affects such seizures, which links to a previous study of the interplay between network and bursting dynamics (Wu et al 2011).…”

mentioning

confidence: 86%

“…The parameter values provided in the table are sourced from (Breakspear et al 2006;Zhao et al 2015) where a = e, i, r or s. The maximal firing rate at which the sigmoid firing function saturates is Q max a , V a is the average membrane voltage of the population relative to resting, Fig. 1 Summary of the neural field model cycle that determines the interaction of four separate populations.…”

Section: Firing Ratesmentioning

confidence: 99%

“…The parameter values provided in the table are sourced from Robinson et al 2002Robinson et al , 2004Zhao et al 2015 From Robinson et al (2008), these variables slowly modulate a threshold current I θ ,…”

Section: Bursting In the Reticular Nucleusmentioning

confidence: 99%

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Generalized seizures in a neural field model with bursting dynamics

Zhao

Robinson

2015

J Comput Neurosci

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The mechanisms underlying generalized seizures are explored with neural field theory. A corticothalamic neural field model that has accounted for multiple brain activity phenomena and states is used to explore changes leading to pathological seizure states. It is found that absence seizures arise from instabilities in the system and replicate experimental studies in numerous animal models and clinical studies.

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Section: Methodsmentioning

confidence: 91%

Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 86%

Section: Firing Ratesmentioning

confidence: 99%

Section: Bursting In the Reticular Nucleusmentioning

confidence: 99%

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Generalized seizures in a neural field model with bursting dynamics

Zhao

Robinson

2015

J Comput Neurosci

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K-complexes, spindles, and ERPs as impulse responses: unification via neural field theory

et al. 2017

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To interrelate K-complexes, spindles, evoked response potentials (ERPs), and spontaneous electroencephalography (EEG) using neural field theory (NFT), physiology-based NFT of the corticothalamic system is used to model cortical excitatory and inhibitory populations and thalamic relay and reticular nuclei. The impulse response function of the model is used to predict the responses to impulses, which are compared with transient waveforms in sleep studies. Fits to empirical data then allow underlying brain physiology to be inferred and compared with other waves. Spontaneous K-complexes, spindles, and other transient waveforms can be reproduced using NFT by treating them as evoked responses to impulsive stimuli with brain parameters appropriate to spontaneous EEG in sleep stage 2. Using this approach, spontaneous K-complexes and sleep spindles can be analyzed using the same single theory as previously been used to account for waking ERPs and other EEG phenomena. As a result, NFT can explain a wide variety of transient waveforms that have only been phenomenologically classified to date. This enables noninvasive fitting to be used to infer underlying physiological parameters. This physiology-based model reproduces the time series of different transient EEG waveforms; it has previously reproduced experimental EEG spectra, and waking ERPs, and many other observations, thereby unifying transient sleep waveforms with these phenomena.

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Neural field model of seizure-like activity in isolated cortex

Zhao

Robinson

2017

J Comput Neurosci

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Epileptiform discharges on an isolated cortex are explored using neural field theory. A neural field model of the isolated cortex is used that consists of three neural populations, excitatory, inhibitory, and excitatory bursting. Mechanisms by which an isolated cortex gives rise to seizure-like waveforms thought to underly pathological EEG waveforms on the deafferented cortex are explored. It is shown that the model reproduces similar time series and oscillatory frequencies for paroxysmal discharges when compared with physiological recordings both during acute and chronic deafferentation states. Furthermore, within our model ictal activity arises from perturbations to steady-states very close to the dynamical system's instability boundary; hence, these are distinct from corticothalamic seizures observed in the model for the intact brain which involved limit-cycle dynamics. The results are applied to experiments in deafferented cats.

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Slow-wave oscillations in a corticothalamic model of sleep and wake

Cited by 13 publications

References 44 publications

Generalized seizures in a neural field model with bursting dynamics

Generalized seizures in a neural field model with bursting dynamics

K-complexes, spindles, and ERPs as impulse responses: unification via neural field theory

Neural field model of seizure-like activity in isolated cortex

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