Publications (15) View all
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Article: Reconciling power laws in microscopic and macroscopic neural recordings
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ABSTRACT: Power laws, characterized by quantities following 1/x^\alpha{} distributions, are commonly reported when observing nature or society, and the question of their origin has for a long time intrigued physicists. Power laws have also been observed in neural recordings, both at the macroscopic and microscopic levels: at the macroscopic level, the power spectral density (PSD) of the electroencephalogram (EEG) has been seen to follow 1/f^\alpha{} distributions; at the microscopic level similar power laws have been observed in single-neuron recordings of the neuronal soma potential and soma current, yet with different values of the power-law exponent \alpha. In this theoretical study we find that these observed macroscopic and microscopic power laws may, despite the widely different spatial scales and different exponents, have the same source. By a combination of simulation on a biophysical detailed, pyramidal neuron model and analytical investigations of a simplified ball and stick neuron, we find that the transfer functions from current input to the single-neuron contribution to the EEG (transmembrane current dipole moment), the soma potential and soma current all express high-frequency power laws if input currents are homogeneously distributed throughout the neural membrane. This general result pertains regardless of whether the current sources stems from synaptic noise or intrinsic channel noise. Our work is of relevance for 1/f-theory in general: the results for the transfer functions from spatially distributed input currents to the various measurement modalities are general with respect to the frequency spectrum of the input, and we show that the cable equation transfers white noise input into colored 1/f^\alpha-noise where \alpha{} may have any half-numbered value within the interval from 1/2 to 3 for the different measurement modalities.05/2013; -
Article: Arterial stiffening provides sufficient explanation for primary hypertension
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ABSTRACT: Hypertension is one of the most common age-related chronic diseases and by predisposing individuals for heart failure, stroke and kidney disease, it is a major source of morbidity and mortality. Its etiology remains enigmatic despite intense research efforts over many decades. By use of empirically well-constrained computer models describing the coupled function of the baroreceptor reflex and mechanics of the circulatory system, we demonstrate quantitatively that arterial stiffening seems sufficient to explain age-related emergence of hypertension. Specifically, the empirically observed chronic changes in pulse pressure with age, and the impaired capacity of hypertensive individuals to regulate short-term changes in blood pressure, arise as emergent properties of the integrated system. Results are consistent with available experimental data from chemical and surgical manipulation of the cardio-vascular system. In contrast to widely held opinions, the results suggest that primary hypertension can be attributed to a mechanogenic etiology without challenging current conceptions of renal and sympathetic nervous system function. The results support the view that a major target for treating chronic hypertension in the elderly is the reestablishment of a proper baroreflex response.05/2013; -
Article: Electrodiffusive model for astrocytic and neuronal ion concentration dynamics
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ABSTRACT: Electrical neural signalling typically takes place at the time-scale of milliseconds, and is typically modeled using the cable equation. This is a good approximation for processes when ionic concentrations vary little during the time course of a simulation. During periods of intense neural signalling, however, the local extracellular K+ concentration may increase by several millimolars. Clearance of excess K+ likely depends partly on diffusion in the extracellular space, partly on local uptake by- and intracellular transport within astrocytes. This process takes place at the time scale of seconds, and can not be modeled accurately without accounting for the spatiotemporal variations in ion concentrations. The work presented here consists of two main parts: First, we developed a general electrodiffusive formalism for modeling ion concentration dynamics in a one-dimensional geometry, including both an intra- and extracellular domain. The formalism was based on the Nernst-Planck equations. It ensures (i) consistency between the membrane potential and ion concentrations, (ii) global particle/charge conservation, and (iii) accounts for diffusion and concentration dependent variations in resistivities. Second, we applied the formalism to model how astrocytes exchange ions with the ECS, and identified the key astrocytic mechanisms involved in K+ removal from high concentration regions. We found that a local increase in extracellular K\textsuperscript{+} evoked a local depolarization of the astrocyte membrane, which at the same time (i) increased the local astrocytic uptake of K\textsuperscript{+}, (ii) suppressed extracellular transport of K+, (iii) increased transport of K+ within astrocytes, and (iv) facilitated astrocytic relase of K+ in extracellular low concentration regions. In summary, these mechanisms seem optimal for shielding the extracellular space from excess K+.04/2013; -
Article: Pitfalls in the interpretation of multielectrode data: on the infeasibility of the neuronal current-source monopoles.
Journal of Neurophysiology 03/2013; 109(6):1681-2. · 3.32 Impact Factor -
Article: Frequency dependence of signal power and spatial reach of the local field potential
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ABSTRACT: The first recording of electrical potential from brain activity was reported already in 1875, but still the interpretation of the signal is debated. To take full advantage of the new generation of microelectrodes with hundreds or even thousands of electrode contacts, an accurate quantitative link between what is measured and the underlying neural circuit activity is needed. Here we address the question of how the observed frequency dependence of recorded local field potentials (LFPs) should be interpreted. By use of a well-established biophysical modeling scheme, combined with detailed reconstructed neuronal morphologies, we find that correlations in the synaptic inputs onto a population of pyramidal cells may significantly boost the low-frequency components of the generated LFP. We further find that these low-frequency components may be less `local' than the high-frequency LFP components in the sense that (1) the size of signal-generation region of the LFP recorded at an electrode is larger and (2) that the LFP generated by a synaptically activated population spreads further outside the population edge due to volume conduction.02/2013;
