Transformation of neuronal modes associated with low-Mg2 + /high-K +  conditions in an in vitro model of epilepsy

Kang, Eunji; Zalay, Osbert C.; Cotic, Marija; Carlen, Peter L.; Bardakjian, Berj L.

doi:10.1007/s10867-009-9144-1

Cited by 7 publications

(4 citation statements)

References 26 publications

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“…Visually, the first-order kernels estimated under low-Mg 2+ /high-K + conditions were typically broader and slightly larger in amplitude relative to kernels measured under standard ACSF perfusion (figure 2(B)) (see Kang et al 2010). These observations were validated by measuring increases in the peak amplitude and time duration of the post-treatment kernels (figures 2(B) and (C)), which were statistically significant (p = 0.0014 and p < 0.0001, respectively).…”

Section: System Characterization Of Neuronal Excitabilitymentioning

confidence: 87%

System characterization of neuronal excitability in the hippocampus and its relevance to observed dynamics of spontaneous seizure-like transitions

et al. 2010

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Most forms of epilepsy are marked by seizure episodes that arise spontaneously. The low-magnesium/high-potassium (low-Mg(2+)/high-K(+)) experimental model of epilepsy is an acute model that produces spontaneous, recurring seizure-like events (SLEs). To elucidate the nature of spontaneous seizure transitions and their relationship to neuronal excitability, whole-cell recordings from the intact hippocampus were undertaken in vitro, and the response of hippocampal CA3 neurons to Gaussian white noise injection was obtained before and after treatment with various concentrations of low-Mg(2+)/high-K(+) solution. A second-order Volterra kernel model was estimated for each of the input-output response pairs. The spectral energy of the responses was also computed, providing a quantitative measure of neuronal excitability. Changes in duration and amplitude of the first-order kernel correlated positively with the spectral energy increase following treatment with low-Mg(2+)/high-K(+) solution, suggesting that variations in neuronal excitability are coded by the system kernels, in part by differences to the profile of the first-order kernel. In particular, kernel duration was more sensitive than amplitude to changes in spectral energy, and correlated more strongly with kernel area. An oscillator network model of the hippocampal CA3 was constructed to investigate the relationship of kernel duration to network excitability, and the model was able to generate spontaneous, recurrent SLEs by increasing the duration of a mode function analogous to the first-order kernel. Results from the model indicated that disruption to the dynamic balance of feedback was responsible for seizure-like transitions and the observed intermittency of SLEs. A physiological candidate for feedback imbalance consistent with the network model is the destabilizing interaction of extracellular potassium and paroxysmal neuronal activation. Altogether, these results (1) validate a mathematical model for epileptiform activity in the hippocampus by quantifying and subsequently correlating its behavior with an experimental, in vitro model of epilepsy; (2) elucidate a possible mechanism for epileptogenesis; and (3) pave the way for control studies in epilepsy utilizing the herein proposed experimental and mathematical setup.

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Section: System Characterization Of Neuronal Excitabilitymentioning

confidence: 87%

System characterization of neuronal excitability in the hippocampus and its relevance to observed dynamics of spontaneous seizure-like transitions

et al. 2010

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“…The low Mg 2+ model of epilepsy is commonly used in experimental research [17][18][19]. Cultured The CREB decreased 3 hours (3h time point) after exposing to the low Mg 2+ condition compared to the control.…”

Section: Discussionmentioning

confidence: 99%

“…Increased δ subunit level during diestrus stage of ovarian cycle has been associated with less seizure activities in kainic acid-induced epilepsy models [16]. Low Mg 2+ model of epilepsy is commonly used in experimental research [17][18][19]. Cultured hippocampal neurons under low Mg 2+ display spontaneous recurrent epileptic discharges after a 3-h exposure to Mg 2+ -free solution [20].…”

Section: Introductionmentioning

confidence: 99%

Increased GABA (A) Receptors alpha1, gamma2, delta Subunits might be Associated with the Activation of the CREB Gene in Low Mg2+ Model of Epilepsy

Yu¹,

Liu²,

Wang³

et al. 2018

Neuropsychiatry

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To observe the GABA (A) receptor subunits and the cAMP response element binding protein (CREB) changes and their relationship in low Mg 2+ model of epilepsy. Methods: A total of 36 embryonic rats prepared from adult female SD rats at the age of 90-100 days were used as experimental subjects. Primary rat hippocampal cultures were prepared from the embryonic rats. The cultured hippocampal neurons were then treated with artificial cerebrospinal fluid containing low Mg 2+ solutions to generate a low Mg 2+ model of epilepsy. The low Mg 2+ stimulation lasted for 9 hours, and three time points (3, 6, 9h after the neurons were exposed to the low Mg 2+ solutions) were selected to observe the GABA(A) receptor and the CREB changes. The quantification of the GABA(A) receptor subunit α1, γ2, δ and the CREB were determined by a qRT-PCR and a Western blot method. Results: During the low Mg 2+ stimulation, the GABA (A) receptors increased remarkably compared to the control after the neurons were exposed to the low Mg 2+ solutions for three hours, and then it decreased gradually. A time-dependent decrease was observed during the period of observation. A significant difference was observed among the time points. The CREB decreased significantly compared to the control at 3h time point, and then it increased gradually in a time-dependent manner, and reached to a peak at 9h time point. A significant increase at 6h and 9h time point was observed as compared to the control. All the GABA (A) receptor subunit α1, γ2, δ increased at 9h time point compared to the normal control. The CREB displayed a similar result. Conclusions: The increase of GABA(A) receptors might be associated with the CREB expressions in cultured hippocampal neurons under low Mg 2+ conditions.

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“…The Laguerre basis set, which was first suggested for use in physiological systems by Norbert Wiener Wiener (1966), is defined on [0, ∞], and is composed of increasing oscillations followed by an exponential decay, as is typical of many physiological systems. Indeed, this method, which has been successfully applied to several nonlinear physiological systems, has been shown to drastically reduce the amount of free parameters needed in the 2nd order Volterra model (Valenza et al, 2013; Kang et al, 2010; Marmarelis, 2004). In order to use the LET, one must specify the alpha parameter of the Laguerre basis functions.…”

Section: Methodsmentioning

confidence: 99%

System identification of point-process neural systems using Probability Based Volterra kernels

Sandler

Deadwyler

Hampson

et al. 2015

Journal of Neuroscience Methods

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Background Neural information processing involves a series of nonlinear dynamical input/output transformations between the spike trains of neurons/neuronal ensembles. Understanding and quantifying these transformations is critical both for understanding neural physiology such as short-term potentiation and for developing cognitive neural prosthetics. New method A novel method for estimating Volterra kernels for systems with point-process inputs and outputs is developed based on elementary probability theory. These Probability Based Volterra (PBV) kernels essentially describe the probability of an output spike given q input spikes at various lags t1, t2, …, tq. Results The PBV kernels are used to estimate both synthetic systems where ground truth is available and data from the CA3 and CA1 regions rodent hippocampus. The PBV kernels give excellent predictive results in both cases. Furthermore, they are shown to be quite robust to noise and to have good convergence and overfitting properties. Through a slight modification, the PBV kernels are shown to also deal well with correlated point-process inputs. Comparison with existing methods The PBV kernels were compared with kernels estimated through least squares estimation (LSE) and through the Laguerre expansion technique (LET). The LSE kernels were shown to fair very poorly with real data due to the large amount of input noise. Although the LET kernels gave the best predictive results in all cases, they require prior parameter estimation. It was shown how the PBV and LET methods can be combined synergistically to maximize performance. Conclusions The PBV kernels provide a novel and intuitive method of characterizing point-process input–output nonlinear systems.

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Transformation of neuronal modes associated with low-Mg2 + /high-K + conditions in an in vitro model of epilepsy

Cited by 7 publications

References 26 publications

System characterization of neuronal excitability in the hippocampus and its relevance to observed dynamics of spontaneous seizure-like transitions

System characterization of neuronal excitability in the hippocampus and its relevance to observed dynamics of spontaneous seizure-like transitions

Increased GABA (A) Receptors alpha1, gamma2, delta Subunits might be Associated with the Activation of the CREB Gene in Low Mg2+ Model of Epilepsy

System identification of point-process neural systems using Probability Based Volterra kernels

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