Channel noise effects on first spike latency of a stochastic Hodgkin-Huxley neuron

Abstract

While it is widely accepted that information is encoded in neurons via action potentials or spikes, it is far less understood what specific features of spiking contain encoded information. Experimental evidence has suggested that the timing of the first spike may be an energy-efficient coding mechanism that contains more neural information than subsequent spikes. Therefore, the biophysical features of neurons that underlie response latency are of considerable interest. Here we examine the effects of channel noise on the first spike latency of a Hodgkin-Huxley neuron receiving random input from many other neurons. Because the principal feature of a Hodgkin-Huxley neuron is the stochastic opening and closing of channels, the fluctuations in the number of open channels lead to fluctuations in the membrane voltage and modify the timing of the first spike. Our results show that when a neuron has a larger number of channels, (i) the occurrence of the first spike is delayed and (ii) the variation in the first spike timing is greater. We also show that the mean, median, and interquartile range of first spike latency can be accurately predicted from a simple linear regression by knowing only the number of channels in the neuron and the rate at which presynaptic neurons fire, but the standard deviation (i.e., neuronal jitter) cannot be predicted using only this information. We then compare our results to another commonly used stochastic Hodgkin-Huxley model and show that the more commonly used model overstates the first spike latency but can predict the standard deviation of first spike latencies accurately. We end by suggesting a more suitable definition for the neuronal jitter based upon our simulations and comparison of the two models.

Effect Of Site Selective Ion Channel Blocking on Action Potential

“…Besides it is simply not possible to study all kinds of model and compare them. As we are looking at two criteria mainly: the variety of firing rate dynamics that can be reproduced and the shape of action potentials affected by ion channel blockers, the Hodgkin-Huxley(HH) model is a well accepted model [48] in this regard compared to threshold models such as the Leaky Integrate and Fire(LIF) [49] or the Izhikevich model(IZH) [50], Morris-Lecar model [51], FitzHuge-Nugamo(FHN) [52] because the parameters of the HH model have biophysical significance. Moreover one can modify the original model parameters to easily include the cell response of different systems [53].…”

Periodic spiking by a pair of ionic channels

“…Also mechanical models for the gating dynamics for a K channel have been proposed [7]. In the last years there has been an increasing interest on the role of channel noise in neural firing patterns [8,9,10,11,12,13,14]. Fluctuations have usually been modeled by using either master equations for the gate states [15,16], or by including stochastic terms into the membrane conductivities [17].…”

Análise de sinais eletrofisiológicos obtidos por matrizes microeletrodo, calibradas por testes estocásticos descritivos da estrutura de densidade de probabilidade

“…Os resultados obtidos do trabalho(MAISEL, LINDENBERG, 2017) têm aplicação na facilitação estocástica, ou na melhoria do processamento da informação devido ao ruído. Isto porque, a presença de ruído de canal em neurônio faz com que os spikes requisitos técnicos e metrológicos para utilização e verificação (MENEZES, C. I. C.; SALLES, M. T.;SILVA, 2003).…”