spike amplitude
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2021 ◽  
Author(s):  
Carol Upchurch ◽  
Crescent L. Combe ◽  
Christopher Knowlton ◽  
Valery G. Rousseau ◽  
Sonia Gasparini ◽  
...  

The hippocampus is involved in memory and spatial navigation. Many CA1 pyramidal cells function as place cells, increasing their firing rate when a specific place field is traversed. The dependence of CA1 place cell firing on position within the place field is asymmetric. We investigated the source of this asymmetry by injecting triangular depolarizing current ramps to approximate the spatially-tuned, temporally-diffuse depolarizing synaptic input received by these neurons while traversing a place field. Ramps were applied to rat CA1 pyramidal neurons in vitro (slice electrophysiology) and in silico (multi-compartmental NEURON model). Under control conditions, CA1 neurons fired more action potentials at higher frequencies on the up-ramp versus the down-ramp. This effect was more pronounced for dendritic compared to somatic ramps. We incorporated a five-state Markov scheme for NaV1.6 channels into our model and calibrated the spatial dependence of long-term inactivation according to the literature; this spatial dependence was sufficient to explain the difference in dendritic versus somatic ramps. Long-term inactivation reduced the firing frequency by decreasing open-state occupancy, and reduced spike amplitude during trains by decreasing occupancy in closed states, which comprise the available pool. PKC activators like phorbol ester phorbol-dibutyrate (PDBu) are known to reduce NaV long-term inactivation. PDBu application removed spike amplitude attenuation during spike trains in vitro, more visibly in dendrites, consistent with decreased NaV long-term inactivation. Moreover, PDBu greatly reduced adaptation, consistent with our hypothesized mechanism. Our synergistic experimental/computational approach shows that long-term inactivation of NaV1.6 is the primary mechanism of adaptation in CA1 pyramidal cells.


Genetics ◽  
2020 ◽  
Vol 215 (4) ◽  
pp. 1055-1066
Author(s):  
David A. Dyment ◽  
Sarah C. Schock ◽  
Kristen Deloughery ◽  
Minh Hieu Tran ◽  
Kerstin Ure ◽  
...  

Dravet syndrome is a developmental epileptic encephalopathy caused by pathogenic variation in SCN1A. To characterize the pathogenic substitution (p.H939R) of a local individual with Dravet syndrome, fibroblast cells from the individual were reprogrammed to pluripotent stem cells and differentiated into neurons. Sodium currents of these neurons were compared with healthy control induced neurons. A novel Scn1aH939R/+ mouse model was generated with the p.H939R substitution. Immunohistochemistry and electrophysiological experiments were performed on hippocampal slices of Scn1aH939R/+ mice. We found that the sodium currents recorded in the proband-induced neurons were significantly smaller and slower compared to wild type (WT). The resting membrane potential and spike amplitude were significantly depolarized in the proband-induced neurons. Similar differences in resting membrane potential and spike amplitude were observed in the interneurons of the hippocampus of Scn1aH939R/+ mice. The Scn1aH939R/+ mice showed the characteristic features of a Dravet-like phenotype: increased mortality and both spontaneous and heat-induced seizures. Immunohistochemistry showed a reduction in amount of parvalbumin and vesicular acetylcholine transporter in the hippocampus of Scn1aH939R/+ compared to WT mice. Overall, these results underline hyper-excitability of the hippocampal CA1 circuit of this novel mouse model of Dravet syndrome which, under certain conditions, such as temperature, can trigger seizure activity. This hyper-excitability is due to the altered electrophysiological properties of pyramidal neurons and interneurons which are caused by the dysfunction of the sodium channel bearing the p.H939R substitution. This novel Dravet syndrome model also highlights the reduction in acetylcholine and the contribution of pyramidal cells, in addition to interneurons, to network hyper-excitability.


2019 ◽  
Author(s):  
A.V. Paraskevov ◽  
T.S. Zemskova

AbstractThe classical biophysical Morris-Lecar model of neuronal excitability predicts that upon stimulation of the neuron with a sufficiently large constant depolarizing current there exists a finite interval of the current values where periodic spike generation occurs. Above the upper boundary of this interval there is a four-stage damping of the spike amplitude: 1) minor primary damping, which reflects a typical transient to stationary state, 2) plateau of nearly undamped periodic oscillations, 3) strong damping, and 4) reaching a constant stationary asymptotic value Vst of the neuron potential. We have linearized the Morris-Lecar model equations at the vicinity of Vst and have shown that the linearized equations can be reduced to a standard equation for exponentially damped harmonic oscillations. Importantly, all coefficients of this equation can be explicitly expressed through parameters of the original Morris-Lecar model, enabling direct comparison (i.e. without any fitting) of the numerical and analytical solutions for the neuron potential dynamics at later stages of the spike amplitude damping. This allows to explore quantitatively the applicability boundary of linear stability analysis that implies exponential damping.


IBRO Reports ◽  
2019 ◽  
Vol 7 ◽  
pp. 108-116
Author(s):  
Raquel Martínez-Méndez ◽  
Daniel Pérez-Torres ◽  
Margarita Gómez-Chavarín ◽  
Patricia Padilla-Cortés ◽  
Tatiana Fiordelisio ◽  
...  

Author(s):  
O. Díaz-Hernández ◽  
Elizeth Ramírez-Álvarez ◽  
A. Flores-Rosas ◽  
C. I. Enriquez-Flores ◽  
M. Santillán ◽  
...  

In this work, we study the interplay between intrinsic biochemical noise and the diffusive coupling, in an array of three stochastic Brusselators that present a limit-cycle dynamics. The stochastic dynamics is simulated by means of the Gillespie algorithm. The intensity of the intrinsic biochemical noise is regulated by changing the value of the system volume (Ω), while keeping constant the chemical species' concentration. To characterize the system behavior, we measure the average spike amplitude (ASA), the order parameter R, the average interspike interval (ISI), and the coefficient of variation (CV) for the interspike interval. By analyzing how these measures depend on Ω and the coupling strength, we observe that when the coupling parameter is different from zero, increasing the level of intrinsic noise beyond a given threshold suddenly drives the spike amplitude, SA, to zero and makes ISI increase exponentially. These results provide numerical evidence that amplitude death (AD) takes place via a homoclinic bifurcation.


2018 ◽  
Vol 370 ◽  
pp. 248-263
Author(s):  
Adam J. Peterson ◽  
Antoine Huet ◽  
Jérôme Bourien ◽  
Jean-Luc Puel ◽  
Peter Heil

2018 ◽  
Author(s):  
Marom Bikson ◽  
Ana Ruiz-Nuño ◽  
Dolores Miranda ◽  
Greg Kronberg ◽  
Premysl Jiruska ◽  
...  

AbstractIt is well established that non-synaptic mechanisms can generate electrographic seizures after blockade of synaptic function. We investigated the interaction of intact synaptic activity with non-synaptic mechanisms in the isolated CA1 region of rat hippocampal slices using the “elevated-K+” model of epilepsy. Elevated K+ ictal bursts share waveform features with other models of electrographic seizures, including non-synaptic models where chemical synaptic transmission is suppressed, such as the low-Ca2+model. These features include a prolonged (several seconds) negative field shift associated with neuronal depolarization and superimposed population spikes. When population spikes are disrupted for up to several seconds, intracellular recording demonstrated that the prolonged suppression of population spikes during ictal activity was due to depolarization block of neurons. Elevated-K+ ictal bursts were often preceded by a build-up of “pre-ictal” epileptiform discharges that were characterized as either “slow-transition” (localized and with a gradual increase in population spike amplitude, reminiscent non-synaptic neuronal aggregate formation, presumed mediated by extracellular K+ concentrations ([K+])o accumulation), or “fast-transition” (with a sudden increase in population spike amplitude, presumed mediated by field effects). When ictal activity had a fast-transition it was preceded by fast-transition pre-ictal activity; otherwise population spikes developed gradually at ictal event onset. Addition of bicuculline, a GABAA receptor antagonist, suppressed population spike generation during ictal activity, reduced pre-ictal activity, and increased the frequency of ictal discharges. Nipecotic acid and NNC-711, both of which block GABA re-uptake, increased population spike amplitude during ictal bursts and promoted the generation of preictal activity. By contrast, addition of ionotropic glutamate-receptor antagonists (NBQX, D-APV) had no consistent effect on ictal burst waveform or frequency and did not fully suppress pre-ictal activity. Similarly, CGP 55848, a GABAB receptor antagonist, has no significant effect on pre-ictal activity or burst frequency (although it did increase burst duration slightly). Our results are consistent with the hypothesis that non-synaptic mechanisms underpin the generation of ictal bursts in CA1 and that GABAA synaptic mechanisms can shape event development by delaying event initiation and counteracting depolarization block.


2015 ◽  
Vol 4 (2) ◽  
pp. 12-25 ◽  
Author(s):  
Natarajan Sriraam ◽  
B. R. Purnima ◽  
Uma Maheswari Krishnaswamy

Electroencephalogram (EEG) based sleep stage analysis considered to be the gold standard method for assessment of sleep architecture. Of importance, transition between the first two stages, wake-sleep stage 1 found to be reliable quantitative tool for drowsiness and fatigue detection. The selection of appropriate feature pattern for EEGs is a quite challenging task due to its non-linear and non-stationary nature of the EEG signals. This research work attempts to provide a comparative study of time influence of time domain feature, relative spike amplitude (RSA) with entropy feature, fuzzy entropy(FE) for recognizing the transition between wake and sleep stage 1. EEGs extracted from offline polysomnography database is used and the extracted RSA and FE wake-sleep stage 1 derived EEG features are further classified using a feedback recurrent Elman neural network (REN) classifier. EEGs are segmented into 1s pattern. Simulation of the REN classifier revealed that the FE feature with REN yields a CA of 99.6% compared to that of with RSA feature.


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