Slow State Transitions of Sustained Neural Oscillations by Activity-Dependent Modulation of Intrinsic Excitability

Fröhlich, Flavio; Bazhenov, Maxim; Timofeev, Igor; Steriade, Mircea; Sejnowski, Terrence J.

doi:10.1523/jneurosci.5509-05.2006

Cited by 90 publications

(85 citation statements)

References 58 publications

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“…The origin of this feature is what one can call a subsequent self-induced depolarization in interaction with the exterior potassium. Note, this result is consistent with previously reported behavior of higher-dimensional quantitative models [19,20,21] …”

Section: B Modelsupporting

confidence: 93%

Dynamical structures in binary media of potassium-driven neurons

et al. 2009

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According to the conventional approach neural ensembles are modeled with fixed ionic concentrations in the extracellular environment. However, in some cases the extracellular concentration of potassium ions can not be regarded as constant. Such cases represent specific chemical pathway for neurons to interact and can influence strongly the behavior of single neurons and of large ensembles. The released chemical agent diffuses in the external medium and lowers thresholds of individual excitable units. We address this problem by studying simplified excitable units given by a modified FitzHugh-Nagumo dynamics. In our model the neurons interact only chemically via the released and diffusing potassium in the surrounding non-active medium and are permanently affected by noise. First we study the dynamics of a single excitable unit embedded in the extracellular matter. That leads to a number of noise-induced effects, like self-modulation of firing rate in an individual neuron. After the consideration of two coupled neurons we consider the spatially extended situation. By holding parameters of the neuron fixed various patterns appear ranging from spirals and traveling waves to oscillons and inverted structures depending on the parameters of the medium.

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Section: B Modelsupporting

confidence: 93%

Dynamical structures in binary media of potassium-driven neurons

et al. 2009

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“…Epilepsy is a network disease involving interactions between many neurons, with pathological alterations in neuronal intrinsic excitability leading to epileptogenesis (2,6). Thus, it is important to understand how the network's structure can affect the chances to observe epileptic-like activity (10,29).…”

Section: Discussionmentioning

confidence: 99%

“…computational model | epilepsy | homeostasis | traumatic brain injury | paroxysmal discharge E pileptic activity in the brain emerges on several organizational levels from hyperexcitable dynamics of single neurons that result from genetic predisposition (1) or pathological alterations in extracellular ionic concentrations (2)(3)(4)(5)(6)(7)(8)(9) to aberrations in network structure that give rise to hypersynchronization of neuronal ensembles and subsequent onset of seizures (10). Such changes in network connectivity and structure may occur after severe brain trauma, which commonly leads to epileptogenesis (11).…”

mentioning

confidence: 99%

Pattern of trauma determines the threshold for epileptic activity in a model of cortical deafferentation

Volman

Bazhenov

Sejnowski

2011

Proc. Natl. Acad. Sci. U.S.A.

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Epileptic activity often occurs in the cortex after a latent period after head trauma; this delay has been attributed to the destabilizing influence of homeostatic synaptic scaling and changes in intrinsic properties. However, the impact of the spatial organization of cortical trauma on epileptogenesis is poorly understood. We addressed this question by analyzing the dynamics of a largescale biophysically realistic cortical network model subjected to different patterns of trauma. Our results suggest that the spatial pattern of trauma can greatly affect the propensity for developing posttraumatic epileptic activity. For the same fraction of lesioned neurons, spatially compact trauma resulted in stronger posttraumatic elevation of paroxysmal activity than spatially diffuse trauma. In the case of very severe trauma, diffuse distribution of a small number of surviving intact neurons alleviated posttraumatic epileptogenesis. We suggest that clinical evaluation of the severity of brain trauma should take into account the spatial pattern of the injured cortex.computational model | epilepsy | homeostasis | traumatic brain injury | paroxysmal discharge E pileptic activity in the brain emerges on several organizational levels from hyperexcitable dynamics of single neurons that result from genetic predisposition (1) or pathological alterations in extracellular ionic concentrations (2-9) to aberrations in network structure that give rise to hypersynchronization of neuronal ensembles and subsequent onset of seizures (10). Such changes in network connectivity and structure may occur after severe brain trauma, which commonly leads to epileptogenesis (11). Traumarelated epileptic activity often occurs after a latent period that offers a potential therapeutic window to reduce the likelihood of later seizure onset. Given this latency, it is imperative to understand how different spatial patterns of trauma affect the propensity of a network (composed of both healthy and traumatized cells) to develop posttraumatic epileptic activity.A likely effect of brain trauma may include damage to synaptic connectivity between neurons. Such damage would lead to reduction of the long-range excitatory inputs to affected areas, therefore creating islands of partially isolated cortical tissue with strongly reduced neuronal activity. Evidence from in vitro studies suggests that chronic blockade of activity may modify synaptic strengths and intrinsic neuronal excitability. After a few days of pharmacological blockade of activity in cortical cell cultures, the amplitudes of excitatory postsynaptic currents (EPSCs) and miniature EPSCs (mEPSCs) in pyramidal cells increase (12, 13), and quantal release probabilities increase as well (14). Conversely, prolonged enhanced activity levels induced by blockade of synaptic inhibition or elevated extracellular potassium ([K + ] o ) reduce the size of mEPSCs (12,15,16). Similar activity-dependent changes in mEPSC size have been observed in spinal cell cultures (17). There is a similar regulation of NMDA receptor...

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“…A computational model of large-scale neuronal network suggested that cortical deafferentation triggered homeostatic up-regulation of neuronal excitability and that was a sufficient factor of epileptogenesis (Fröhlich et al, 2005; Frohlich et al, 2006; Houweling et al, 2005; Volman et al, 2011). In vivo experiments showed that following cortical trauma, neuronal intrinsic currents are also modified to increase the neuronal excitability.…”

Section: The Trauma-induced Epilepsy Modelmentioning

confidence: 99%

In vivo models of cortical acquired epilepsy

Chauvette

Soltani

Seigneur

et al. 2016

Journal of Neuroscience Methods

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The neocortex is the site of origin of several forms of acquired epilepsy. Here we provide a brief review of experimental models that were recently developed to study neocortical epileptogenesis as well as some major results obtained with these methods. Most of neocortical seizures appear to be nocturnal and it is known that neuronal activities reveal high levels of synchrony during slow-wave sleep. Therefore, we start the review with a description of mechanisms of neuronal synchronization and major forms of synchronized normal and pathological activities. Then, we describe three experimental models of seizures and epileptogenesis: ketamine-xylazine anesthesia as feline seizure triggered factor, cortical undercut as cortical penetrating wound model and neocortical kindling. Besides specific technical details describing these models we also provide major features of pathological brain activities recorded during epileptogenesis and seizures. The most common feature of all models of neocortical epileptogenesis is the increased duration of network silent states that up-regulates neuronal excitability and eventually leads to epilepsy.

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Slow State Transitions of Sustained Neural Oscillations by Activity-Dependent Modulation of Intrinsic Excitability

Cited by 90 publications

References 58 publications

Dynamical structures in binary media of potassium-driven neurons

Dynamical structures in binary media of potassium-driven neurons

Pattern of trauma determines the threshold for epileptic activity in a model of cortical deafferentation

In vivo models of cortical acquired epilepsy

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