Fractal-like correlations of the fluctuating inter-spike membrane potential of a Helix aspersa pacemaker neuron

Seseña-Rubfiaro, Alberto; Godínez‐Fernández, J. Rafael

doi:10.1016/j.compbiomed.2014.08.012

Cited by 4 publications

(3 citation statements)

References 54 publications

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“…Scale-free dynamics has been observed at the level of single neurons, in the fluctuation of the membrane potential between spiking events ( Seseña-Rubfiaro et al. 2014 ; Johnson et al.…”

Section: Scale-free Dynamicsmentioning

confidence: 99%

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The fractal brain: scale-invariance in structure and dynamics

et al. 2022

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The past 40 years have witnessed extensive research on fractal structure and scale-free dynamics in the brain. Although considerable progress has been made, a comprehensive picture has yet to emerge, and needs further linking to a mechanistic account of brain function. Here, we review these concepts, connecting observations across different levels of organization, from both a structural and functional perspective. We argue that, paradoxically, the level of cortical circuits is the least understood from a structural point of view and perhaps the best studied from a dynamical one. We further link observations about scale-freeness and fractality with evidence that the environment provides constraints that may explain the usefulness of fractal structure and scale-free dynamics in the brain. Moreover, we discuss evidence that behavior exhibits scale-free properties, likely emerging from similarly organized brain dynamics, enabling an organism to thrive in an environment that shares the same organizational principles. Finally, we review the sparse evidence for and try to speculate on the functional consequences of fractality and scale-freeness for brain computation. These properties may endow the brain with computational capabilities that transcend current models of neural computation and could hold the key to unraveling how the brain constructs percepts and generates behavior.

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“…Scale-free dynamics has been observed at the level of single neurons, in the fluctuation of the membrane potential between spiking events ( Seseña-Rubfiaro et al. 2014 ; Johnson et al.…”

Section: Scale-free Dynamicsmentioning

confidence: 99%

“…2008 ). In a 2014 study, the inter-spike membrane potential fluctuations were also analyzed using DFA in the pacemaker F1 neuron of the garden snail, “Helix aspersa” ( Seseña-Rubfiaro et al. 2014 ).…”

Section: Scale-free Dynamicsmentioning

confidence: 99%

The fractal brain: scale-invariance in structure and dynamics

et al. 2022

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“…Although several time-domain, frequency-domain and nonlinear techniques have been employed to analyze the HRV [8,10,11,[15][16][17][18][19][20], the scale exponent (α) from detrended fluctuation analysis (DFA) has shown significant advantages over other nonlinear and fractal methods since it allows the detection of long-range correlations embedded in non-stationary time series, while simultaneously avoiding the spurious detection of apparent long-range correlations [9,13,[21][22][23]. Moreover, it has been shown that changes in HRV are better quantified by scaling analysis than by spectral analysis [12].…”

Section: Introductionmentioning

confidence: 99%

Simulating the extrinsic regulation of the sinoatrial node cells using a unified computational model

Castellanos

Godı́nez

2017

Biomed. Phys. Eng. Express

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The aim of this work is to develop a computational model to study the extrinsic regulation of the heart rate variability (HRV) during sympathetic and/or vagal stimulation. The model here proposed is based on two recent models of the sinoatrial node cell (SANC) action potential and the influence of the autonomic nervous system (ANS) on the activity of ionic channels of SANCs. The HRV was simulated by applying a random frequency stimulation using both a normal and a beta probability density function (PDF) for different ranges of stimulation frequencies. The HRV was then analyzed by computing the scale exponent using detrended fluctuation analysis. We found that our model reproduces the value of the scale exponent observed in healthy humans (α=1.07± 0.05) when simultaneous vagal and sympathetic stimulus (with beta and normal PDFs, respectively) over the frequency range from 0 to 10 Hz are applied. Our model also predicts a Brownian motion behavior when the muscarinic receptors are blocked (α=1.8) and the white noise behavior when the b-adrenergic receptors are blocked (α=0.5). Our results shed light on how the ANS regulates the HRV in healthy conditions, where it is not enough to consider only one stimulation pathway with a simple normal PDF.

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Relationship in Pacemaker Neurons Between the Long-Term Correlations of Membrane Voltage Fluctuations and the Corresponding Duration of the Inter-Spike Interval

Rubfiaro

Godinez

2017

J Membrane Biol

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Several studies of the behavior in the voltage and frequency fluctuations of the neural electrical activity have been performed. Here, we explored the particular association between behavior of the voltage fluctuations in the inter-spike segment (VFIS) and the inter-spike intervals (ISI) of F1 pacemaker neurons from H. aspersa, by disturbing the intracellular calcium handling with cadmium and caffeine. The scaling exponent α of the VFIS, as provided by detrended fluctuations analysis, in conjunction with the corresponding duration of ISI to estimate the determination coefficient R (48-50 intervals per neuron, N = 5) were all evaluated. The time-varying scaling exponent α(t) of VFIS was also studied (20 segments per neuron, N = 11). The R obtained in control conditions was 0.683 ([0.647 0.776] lower and upper quartiles), 0.405 [0.381 0.495] by using cadmium, and 0.151 [0.118 0.222] with caffeine (P < 0.05). A non-uniform scaling exponent α(t) showing a profile throughout the duration of the VFIS was further identified. A significant reduction of long-term correlations by cadmium was confirmed in the first part of this profile (P = 0.0001), but no significant reductions were detected by using caffeine. Our findings endorse that the behavior of the VFIS appears associated to the activation of different populations of ionic channels, which establish the neural membrane potential and are mediated by the intracellular calcium handling. Thus, we provide evidence to consider that the behavior of the VFIS, as determined by the scaling exponent α, conveys insights into mechanisms regulating the excitability of pacemaker neurons.

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Fractal-like correlations of the fluctuating inter-spike membrane potential of a Helix aspersa pacemaker neuron

Cited by 4 publications

References 54 publications

The fractal brain: scale-invariance in structure and dynamics

The fractal brain: scale-invariance in structure and dynamics

Simulating the extrinsic regulation of the sinoatrial node cells using a unified computational model

Relationship in Pacemaker Neurons Between the Long-Term Correlations of Membrane Voltage Fluctuations and the Corresponding Duration of the Inter-Spike Interval

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