Dataset Information

Electrical Identification and Selective Microstimulation of Neuronal Compartments Based on Features of Extracellular Action Potentials.

ABSTRACT: A detailed, high-spatiotemporal-resolution characterization of neuronal responses to local electrical fields and the capability of precise extracellular microstimulation of selected neurons are pivotal for studying and manipulating neuronal activity and circuits in networks and for developing neural prosthetics. Here, we studied cultured neocortical neurons by using high-density microelectrode arrays and optical imaging, complemented by the patch-clamp technique, and with the aim to correlate morphological and electrical features of neuronal compartments with their responsiveness to extracellular stimulation. We developed strategies to electrically identify any neuron in the network, while subcellular spatial resolution recording of extracellular action potential (AP) traces enabled their assignment to the axon initial segment (AIS), axonal arbor and proximal somatodendritic compartments. Stimulation at the AIS required low voltages and provided immediate, selective and reliable neuronal activation, whereas stimulation at the soma required high voltages and produced delayed and unreliable responses. Subthreshold stimulation at the soma depolarized the somatic membrane potential without eliciting APs.

SUBMITTER: Radivojevic M

PROVIDER: S-EPMC4980679 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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Electrical Identification and Selective Microstimulation of Neuronal Compartments Based on Features of Extracellular Action Potentials.

Radivojevic Milos M Jäckel David D Altermatt Michael M Müller Jan J Viswam Vijay V Hierlemann Andreas A Bakkum Douglas J DJ

Scientific reports 20160811

A detailed, high-spatiotemporal-resolution characterization of neuronal responses to local electrical fields and the capability of precise extracellular microstimulation of selected neurons are pivotal for studying and manipulating neuronal activity and circuits in networks and for developing neural prosthetics. Here, we studied cultured neocortical neurons by using high-density microelectrode arrays and optical imaging, complemented by the patch-clamp technique, and with the aim to correlate mo ...[more]

PMID: 27510732

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Project description:Nowadays, high-density microelectrode arrays provide unprecedented possibilities to precisely activate spatially well-controlled central nervous system (CNS) areas. However, this requires optimizing stimulating devices, which in turn requires a good understanding of the effects of microstimulation on cells and tissues. In this context, modeling approaches provide flexible ways to predict the outcome of electrical stimulation in terms of CNS activation. In this paper, we present state-of-the-art modeling methods with sufficient details to allow the reader to rapidly build numerical models of neuronal extracellular microstimulation. These include (1) the computation of the electrical potential field created by the stimulation in the tissue, and (2) the response of a target neuron to this field. Two main approaches are described: First we describe the classical hybrid approach that combines the finite element modeling of the potential field with the calculation of the neuron's response in a cable equation framework (compartmentalized neuron models). Then, we present a "whole finite element" approach allowing the simultaneous calculation of the extracellular and intracellular potentials, by representing the neuronal membrane with a thin-film approximation. This approach was previously introduced in the frame of neural recording, but has never been implemented to determine the effect of extracellular stimulation on the neural response at a sub-compartment level. Here, we show on an example that the latter modeling scheme can reveal important sub-compartment behavior of the neural membrane that cannot be resolved using the hybrid approach. The goal of this paper is also to describe in detail the practical implementation of these methods to allow the reader to easily build new models using standard software packages. These modeling paradigms, depending on the situation, should help build more efficient high-density neural prostheses for CNS rehabilitation.

Project description:Neuromodulations are an important component of extracellular electrical potentials (EEP), such as the Electroencephalogram (EEG), Electrocorticogram (ECoG) and Local Field Potentials (LFP). This spatially temporal organized multi-frequency transient (phasic) activity reflects the multiscale spatiotemporal synchronization of neuronal populations in response to external stimuli or internal physiological processes. We propose a novel generative statistical model of a single EEP channel, where the collected signal is regarded as the noisy addition of reoccurring, multi-frequency phasic events over time. One of the main advantages of the proposed framework is the exceptional temporal resolution in the time location of the EEP phasic events, e.g., up to the sampling period utilized in the data collection. Therefore, this allows for the first time a description of neuromodulation in EEPs as a Marked Point Process (MPP), represented by their amplitude, center frequency, duration, and time of occurrence. The generative model for the multi-frequency phasic events exploits sparseness and involves a shift-invariant implementation of the clustering technique known as k-means. The cost function incorporates a robust estimation component based on correntropy to mitigate the outliers caused by the inherent noise in the EEP. Lastly, the background EEP activity is explicitly modeled as the non-sparse component of the collected signal to further improve the delineation of the multi-frequency phasic events in time. The framework is validated using two publicly available datasets: the DREAMS sleep spindles database and one of the Brain-Computer Interface (BCI) competition datasets. The results achieve benchmark performance and provide novel quantitative descriptions based on power, event rates and timing in order to assess behavioral correlates beyond the classical power spectrum-based analysis. This opens the possibility for a unifying point process framework of multiscale brain activity where simultaneous recordings of EEP and the underlying single neuron spike activity can be integrated and regarded as marked and simple point processes, respectively.

Project description:The spatial variation of the extracellular action potentials (EAP) of a single neuron contains information about the size and location of the dominant current source of its action potential generator, which is typically in the vicinity of the soma. Using this dependence in reverse in a three-component realistic probe + brain + source model, we solved the inverse problem of characterizing the equivalent current source of an isolated neuron from the EAP data sampled by an extracellular probe at multiple independent recording locations. We used a dipole for the model source because there is extensive evidence it accurately captures the spatial roll-off of the EAP amplitude, and because, as we show, dipole localization, beyond a minimum cell-probe distance, is a more accurate alternative to approaches based on monopole source models. Dipole characterization is separable into a linear dipole moment optimization where the dipole location is fixed, and a second, nonlinear, global optimization of the source location. We solved the linear optimization on a discrete grid via the lead fields of the probe, which can be calculated for any realistic probe + brain model by the finite element method. The global source location was optimized by means of Tikhonov regularization that jointly minimizes model error and dipole size. The particular strategy chosen reflects the fact that the dipole model is used in the near field, in contrast to the typical prior applications of dipole models to EKG and EEG source analysis. We applied dipole localization to data collected with stepped tetrodes whose detailed geometry was measured via scanning electron microscopy. The optimal dipole could account for 96% of the power in the spatial variation of the EAP amplitude. Among various model error contributions to the residual, we address especially the error in probe geometry, and the extent to which it biases estimates of dipole parameters. This dipole characterization method can be applied to any recording technique that has the capabilities of taking multiple independent measurements of the same single units.

Project description:The ability to make electrical measurements inside cells has led to many important advances in electrophysiology. The patch clamp technique, in which a glass micropipette filled with electrolyte is inserted into a cell, offers both high signal-to-noise ratio and temporal resolution. Ideally, the micropipette should be as small as possible to increase the spatial resolution and reduce the invasiveness of the measurement, but the overall performance of the technique depends on the impedance of the interface between the micropipette and the cell interior, which limits how small the micropipette can be. Techniques that involve inserting metal or carbon microelectrodes into cells are subject to similar constraints. Field-effect transistors (FETs) can also record electric potentials inside cells, and because their performance does not depend on impedance, they can be made much smaller than micropipettes and microelectrodes. Moreover, FET arrays are better suited for multiplexed measurements. Previously, we have demonstrated FET-based intracellular recording with kinked nanowire structures, but the kink configuration and device design places limits on the probe size and the potential for multiplexing. Here, we report a new approach in which a SiO2 nanotube is synthetically integrated on top of a nanoscale FET. This nanotube penetrates the cell membrane, bringing the cell cytosol into contact with the FET, which is then able to record the intracellular transmembrane potential. Simulations show that the bandwidth of this branched intracellular nanotube FET (BIT-FET) is high enough for it to record fast action potentials even when the nanotube diameter is decreased to 3 nm, a length scale well below that accessible with other methods. Studies of cardiomyocyte cells demonstrate that when phospholipid-modified BIT-FETs are brought close to cells, the nanotubes can spontaneously penetrate the cell membrane to allow the full-amplitude intracellular action potential to be recorded, thus showing that a stable and tight seal forms between the nanotube and cell membrane. We also show that multiple BIT-FETs can record multiplexed intracellular signals from both single cells and networks of cells.

Dataset Information

Electrical Identification and Selective Microstimulation of Neuronal Compartments Based on Features of Extracellular Action Potentials.

Publications

Electrical Identification and Selective Microstimulation of Neuronal Compartments Based on Features of Extracellular Action Potentials.

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