A framework to reconcile frequency scaling measurements, from intracellular recordings, local-field potentials, up to EEG and MEG signals

In this viewpoint article, we discuss the electric properties of the medium around neurons, which are important to correctly interpret extracellular potentials or electric field effects in neural tissue. We focus on how these electric properties shape the frequency scaling of brain signals at different scales, such as intracellular recordings, the local field potential (LFP), the electroencephalogram (EEG) or the magnetoencephalogram (MEG). These signals display frequency-scaling properties which are not consistent with resistive media. The medium appears to exert a frequency filtering scaling as $1/\sqrt{f}$, which is the typical frequency scaling of ionic diffusion. Such a scaling was also found recently by impedance measurements in physiological conditions. Ionic diffusion appears to be the only possible explanation to reconcile these measurements and the frequency-scaling properties found in different brain signals. However, other measurements suggest that the extracellular medium is essentially resistive. To resolve this discrepancy, we show new evidence that metal-electrode measurements can be perturbed by shunt currents going through the surface of the brain. Such a shunt may explain the contradictory measurements, and together with ionic diffusion, provides a framework where all observations can be reconciled. Finally, we propose a method to perform measurements avoiding shunting effects, thus enabling to test the predictions of this framework.Comment: (in press

Microscale Inhomogeneity of Brain Tissue Distorts Electrical Signal Propagation

Interpretations of local field potentials (LFPs) are typically shaped on an assumption that the brain is a homogenous conductive milieu. However, microscale inhomogeneities including cell bodies, dendritic structures, axonal fiber bundles and blood vessels are unequivocally present and have different conductivities and permittivities than brain extracellular fluid. To determine the extent to which these obstructions affect electrical signal propagation on a microscale, we delivered electrical stimuli intracellularly to individual cells while simultaneously recording the extracellular potentials at different locations in a rat brain slice. As compared with relatively unobstructed paths, signals were attenuated across frequencies when fiber bundles were in between the stimulated cell and the extracellular electrode. Across group of cell bodies, signals were attenuated at low frequencies, but facilitated at high frequencies. These results show that LFPs do not reflect a democratic representation of neuronal contributions, as certain neurons may contribute to the LFP more than others based on the local extracellular environment surrounding them

Etude expérimentale et théorique de la genèse des potentiels de champs locaux par les neurones corticaux

Local field potentials (LFPs) are low-frequency (< 200-500 Hz) events resulting from brain activity. Their meaning and the mechanisms shaping them have been highly debated for decades. The existence and importance of a frequency-dependant filtering of ionic currents by brain tissue is controversial. Some authors conclude that the medium is resistive, while others suggest that brain tissue may exert significative low-pass filtering on electrical currents. A new measurement method is presented here, relying on the concept of natural impedance, which is measured using a neuron as an ''electrode''. This allows to obtain the most relevant impedance from a physiological point of view, in terms of electrode-medium interface, current intensity and spatial scale. The measured impedance is stable, reproducible, stronger than what is traditionally measured, and has a 1/\√f frequency dependance. A physical model, taking into account ionic diffusion in the medium, is able to reproduce this impedance. A similar method allows to compute the transfer function between the intra- and extracellular potentials of a neuron. Models are proposed to explain its structure, predict LFPs from cell activity and vice-versa. These results may help interpreting LFP and electroencephalography signals, yielding a deeper understanding of the physiological and pathological brain function.Les potentiels de champs locaux (LFP) sont des événements de fréquence inférieure à 200-500 Hz, résultant de l'activité cérébrale. Leur signification et les mécanismes contribuant à leur formation sont encore très débattus. Ainsi, l'existence et l'importance d'un filtrage des courants ioniques par le tissu cérébral est controversée. Certains auteurs concluent que le milieu est résistif, alors que d'autres suggèrent que le tissu cérébral pourrait exercer un filtrage passe-bas significatif sur les courants électriques. Une méthode de mesure nouvelle est présentée ici, s'appuyant sur le concept d'impédance naturelle, mesurée en utilisant un neurone comme " électrode " . Ceci permet d'obtenir l'impédance la plus pertinente d'un point de vue physiologique, en termes d'interface électrode-milieu, d'intensité des courants et d'échelle spatiale. L'impédance mesurée est stable, reproductible, plus forte que celle mesurée traditionnellement, et possède une dépendance en fréquence en 1/vf. Un modèle physique prenant en compte la diffusion ionique dans le milieu est capable de reproduire cette impédance. Une méthode similaire permet de calculer la fonction de transfert entre les potentiels intra- et extracellulaire d'un neurone. Des modèles sont proposés pour expliquer sa forme, prédire les LFP d'après l'activité cellulaire et vice-versa. Ces résultats pourraient aider à l'interprétation des signaux de LFP et d'électroencéphalographie, permettant une compréhension plus profonde du fonctionnement cérébral physiologique et pathologique

Psyche, Signals and Systems

For a century or so, the multidisciplinary nature of neuroscience has left the field fractured into distinct areas of research. In particular, the subjects of consciousness and perception present unique challenges in the attempt to build a unifying understanding bridging between the micro-, meso-, and macro-scales of the brain and psychology. This chapter outlines an integrated view of the neurophysiological systems, psychophysical signals, and theoretical considerations related to consciousness. First, we review the signals that correlate to consciousness during psychophysics experiments. We then review the underlying neural mechanisms giving rise to these signals. Finally, we discuss the computational and theoretical functions of such neural mechanisms, and begin to outline means in which these are related to ongoing theoretical research

On the Electrodynamics of Neural Networks

We present a microscopic approach for the coupling of cortical activity, as resulting from proper dipole currents of pyramidal neurons, to the electromagnetic field in extracellular fluid in presence of diffusion and Ohmic conduction. Starting from a full-fledged three-compartment model of a single pyramidal neuron, including shunting and dendritic propagation, we derive an observation model for dendritic dipole currents in extracellular space and thereby for the dendritic field potential that contributes to the local field potential of a neural population. Under reasonable simplifications, we then derive a leaky integrate-and-fire model for the dynamics of a neural network, which facilitates comparison with existing neural network and observation models. In particular, we compare our results with a related model by means of numerical simulations. Performing a continuum limit, neural activity becomes represented by a neural field equation, while an observation model for electric field potentials is obtained from the interaction of cortical dipole currents with charge density in non-resistive extracellular space as described by the Nernst-Planck equation. Our work consistently satisfies the widespread dipole assumption discussed in the neuroscientific literature

神経細胞のマルチコンパートメントモデルにおける細胞外抵抗分布の役割 : 細胞外記録および細胞外電気刺激のための統一形式化

Tohoku University川島隆

Comparative power spectral analysis of simultaneous elecroencephalographic and magnetoencephalographic recordings in humans suggests non-resistive extracellular media

The resistive or non-resistive nature of the extracellular space in the brain is still debated, and is an important issue for correctly modeling extracellular potentials. Here, we first show theoretically that if the medium is resistive, the frequency scaling should be the same for electroencephalogram (EEG) and magnetoencephalogram (MEG) signals at low frequencies (<10 Hz). To test this prediction, we analyzed the spectrum of simultaneous EEG and MEG measurements in four human subjects. The frequency scaling of EEG displays coherent variations across the brain, in general between 1/f and 1/f^2, and tends to be smaller in parietal/temporal regions. In a given region, although the variability of the frequency scaling exponent was higher for MEG compared to EEG, both signals consistently scale with a different exponent. In some cases, the scaling was similar, but only when the signal-to-noise ratio of the MEG was low. Several methods of noise correction for environmental and instrumental noise were tested, and they all increased the difference between EEG and MEG scaling. In conclusion, there is a significant difference in frequency scaling between EEG and MEG, which can be explained if the extracellular medium (including other layers such as dura matter and skull) is globally non-resistive.Comment: Submitted to Journal of Computational Neuroscienc

Development of a Novel Platform for in vitro Electrophysiological Recording

The accurate monitoring of cell electrical activity is of fundamental importance for pharmaceutical research and pre-clinical trials that impose to check the cardiotoxicity of all new drugs. Traditional methods for preclinical evaluation of drug cardiotoxicity exploit animal models, which tend to be expensive, low throughput, and exhibit species-specific differences in cardiac physiology (Mercola, Colas and Willems, 2013). Alternative approaches use heterologous expression of cardiac ion channels in non-cardiac cells transfected with genetic material. However, the use of these constructs and the inhibition of specific ionic currents alone is not predictive of cardiotoxicity. Drug toxicity evaluation based on the human ether-\ue0-go-go-related gene (hERG) channel, for example, leads to a high rate of false-positive cardiotoxic compounds, increasing drug attrition at the preclinical stage. Consequently, from 2013, the Comprehensive in Vitro Proarrhythmia Assay (CiPA) initiative focused on experimental methods that identify cardiotoxic drugs and to improve upon prior models that have largely used alterations in the hERG potassium ion channel. The most predictive models for drug cardiotoxicity must recapitulate the complex spatial distribution of the physiologically distinct myocytes of the intact adult human heart. However, intact human heart preparations are inherently too costly, difficult to maintain, and, hence, too low throughput to be implemented early in the drug development pipeline. For these reasons the optimization of methodologies to differentiate human induced Pluripotent Stem Cells (hiPSCs) into cardiomyocytes (CMs) enabled human CMs to be mass-produced in vitro for cardiovascular disease modeling and drug screening (Sharma, Wu and Wu, 2013). These hiPSC-CMs functionally express most of the ion channels and sarcomeric proteins found in adult human CMs and can spontaneously contract. Recent results from the CiPA initiative have confirmed that, if utilized appropriately, the hiPSC-CM platform can serve as a reliable alternative to existing hERG assays for evaluating arrhythmogenic compounds and can sensitively detect the action potential repolarization effects associated with ion channel\u2013blocking drugs (Millard et al., 2018). Data on drug-induced toxicity in hiPSC-CMs have already been successfully collected by using several functional readouts, such as field potential traces using multi-electrode array (MEA) technology (Clements, 2016), action potentials via voltage-sensitive dyes (VSD) (Blinova et al., 2017) and cellular impedance (Scott et al., 2014). Despite still under discussion, scientists reached a consensus on the value of using electrophysiological data from hiPSC-CM for predicting cardiotoxicity and how it\u2019s possible to further optimize hiPSC-CM-based in vitro assays for acute and chronic cardiotoxicity assessment. In line with CiPA, therefore, the use of hiPSC coupled with MEA technology has been selected as promising readout for these kind of experiments. These platforms are used as an experimental model for studying the cardiac Action Potentials (APs) dynamics and for understanding some fundamental principles about the APs propagation and synchronization in healthy heart tissue. MEA technology utilizes recordings from an array of electrodes embedded in the culture surface of a well. When cardiomyocytes are grown on these surfaces, spontaneous action potentials from a cluster of cardiomyocytes, the so called functional syncytium, can be detected as fluctuations in the extracellular field potential (FP). MEA measures the change in FP as the action potential propagates through the cell monolayer relative to the recording electrode, neverthless FP in the MEA do not allows to recapitualte properly the action potential features. It is clear, therefore, that a MEA technology itself is not enough to implement cardiotoxicity assays on hIPSCs-CMs. Under this issue, researchers spread in the world started to think about solutions to achieve a platform able to works both at the same time as a standard MEA and as a patch clamp, allowing the recording of extracellular signals as usual, with the opportunity to switch to intracellular-like signals from the cytosol. This strong interest stimulated the development of methods for intracellular recording of action potentials. Currently, the most promising results are represented by multi-electrode arrays (MEA) decorated with 3D nanostructures that were introduced in pioneering papers (Robinson et al., 2012; Xie et al., 2012), culminating with the recent work from the group of H. Park (Abbott et al., 2017) and of F. De Angelis (Dipalo et al., 2017). In these articles, they show intracellular recordings on electrodes refined with 3D nanopillars after electroporation and laser optoporation from different kind of cells. However, the requirement of 3D nanostructures set strong limitations to the practical spreading of these techniques. Thus, despite pioneering results have been obtained exploiting laser optoporation, these technologies neither been applied to practical cases nor reached the commercial phase. This PhD thesis introduces the concept of meta-electrodes coupled with laser optoporation for high quality intracellular signals from hiPSCs-CM. These signals can be recorded on high-density commercial CMOS-MEAs from 3Brain characterized by thousands of electrode covered by a thin film of porous Platinum without any rework of the devices, 3D nanostructures or circuitry for electroporation7. Subsequently, I attempted to translate these unique features of low invasiveness and reliability to other commercial MEA platforms, in order to develop a new tool for cardiac electrophysiological accurate recordings. The whole thesis is organized in three main sections: a first single chapters that will go deeper in the scientific and technological background, including an explanation of the cell biology of hiPSCs-CM followed by a full overview of MEA technology and devices. Then, I will move on state-of-the-art approaches of intracellular recording, discussing many works from the scientific literature. A second chapter will describe the main objectives of the whole work, and a last chapter with the main results of the activity. A final chapter will resume and recapitulate the conclusion of the work