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

Radivojević, Miloš; Jäckel, David; Altermatt, Michael; Müller, Jan; Viswam, Vijay; Hierlemann, Andreas; Bakkum, Douglas J.

doi:10.1038/srep31332

Cited by 51 publications

(116 citation statements)

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“…Axonal signals across a branching point were recorded by simultaneously using 841 electrodes. The action potential waveforms that have been recorded from the electrodes marked in red in Additionally, CMOS microtransducer arrays and integrated microsystems offer the capability to bidirectionally interact, also in closed loop and real time, with potentially every single neuron in a given neuronal network [17,27,44]. We investigated the relationship between stimulation location and reliability of neuronal responses to high-frequency threshold stimulations.…”

Section: Measurements and Resultsmentioning

confidence: 99%

“…To verify that classified signals matched neuronal morphology, we superimposed spike-triggered average footprints and micrographs of lipofected neurons (Fig. 6a) [44]. We produced excitability profiles and defined stimulation thresholds for the respective electrodes.…”

Section: Measurements and Resultsmentioning

confidence: 99%

“…(c) Excitability profiles for stimulation through the 7 center electrodes. Numbers correspond to those in (b) [44].…”

Section: Discussionmentioning

confidence: 99%

“…Only signals exceeding 50 μV are displayed for clarity [28]. Selective stimulation of single neurons [44]. (a) Spontaneous activity footprint (black traces) superimposed over the morphology of the respective neuron and its proximal compartments (colored in gray).…”

Section: Discussionmentioning

confidence: 99%

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Direct interfacing of neurons to highly integrated microsystems

Hierlemann

2017

2017 IEEE 30th International Conference on Micro Electro Mechanical Systems (MEMS)

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The use of large high-density transducer arrays enables fundamentally new neuroscientific insights through enabling high-throughput monitoring of action potentials of larger neuronal networks (> 1000 neurons) over extended time to see effects of disturbances or developmental effects, and through facilitating detailed investigations of neuronal signaling characteristics at subcellular level, for example, the study of axonal signal propagation that has been largely inaccessible to established methods. Applications include research in neural diseases and pharmacology.

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Section: Measurements and Resultsmentioning

confidence: 99%

Section: Measurements and Resultsmentioning

confidence: 99%

“…(c) Excitability profiles for stimulation through the 7 center electrodes. Numbers correspond to those in (b) [44].…”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Direct interfacing of neurons to highly integrated microsystems

Hierlemann

2017

2017 IEEE 30th International Conference on Micro Electro Mechanical Systems (MEMS)

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“…[60]) is immediately available within our framework: indeed, preliminary results with denser arrays (30μm spacing between electrodes) revealed that due to the increased proximity between the stimulating electrode and its neighboring electrodes, those electrodes also possessed large artifacts and were subject to the effect of breakpoints. Then, we can proceed exactly as we did in Simplifications and extensions for local return, by considering different models for the stimulating electrode and its neighbors.…”

Section: Limitationsmentioning

confidence: 99%

Electrical Stimulus Artifact Cancellation and Neural Spike Detection on Large Multi-Electrode Arrays

Mena

Grosberg

Hottowy³

et al. 2016

Preprint

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Simultaneous electrical stimulation and recording using multi-electrode arrays can provide a valuable technique for studying circuit connectivity and engineering neural interfaces. However, interpreting these measurements is challenging because the spike sorting process (identifying and segregating action potentials arising from different neurons) is greatly complicated by electrical stimulation artifacts across the array, which can exhibit complex and nonlinear waveforms, and overlap temporarily with evoked spikes. Here we develop a scalable algorithm based on a structured Gaussian Process model to estimate the artifact and identify evoked spikes. The effectiveness of our methods is demonstrated in both real and simulated 512-electrode recordings in the peripheral primate retina with single-electrode and several types of multi-electrode stimulation. We establish small error rates in the identification of evoked spikes, with a computational complexity that is compatible with real-time data analysis. This technology may be helpful in the design of future high-resolution sensory prostheses based on tailored stimulation (e.g., retinal prostheses), and for closed-loop neural stimulation at a much larger scale than currently possible. Author summarySimultaneous electrical stimulation and recording using multi-electrode arrays can provide a valuable technique for studying circuit connectivity and engineering neural interfaces. However, interpreting these recordings is challenging because the spike sorting process (identifying and segregating action potentials arising from different neurons) is largely stymied by electrical stimulation artifacts across the array, which are typically larger than the signals of interest. We develop a novel computational framework to estimate and subtract away this contaminating artifact, enabling the large-scale analysis of responses of possibly hundreds of cells to tailored stimulation. Importantly, we suggest PLOS Computational Biology | https://doi

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Electrical Imaging: Investigating Cellular Function at High Resolution

et al. 2017

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recently membrane currents from skeletal myotubes, [7] from glia or from glia-derived cancerogenic glioma cells [8] or from pancreatic beta cells [9] have been reported. In brain or muscle tissues different cell types interact. As a consequence the generated electrical signals comprise a rich frequency content ranging from few Hertz to several kilohertz. [10] Electrical signaling on sub-millisecond time scale occurs during so-called action potentials, when the transmembrane potential changes rapidly due to the opening and closing of voltagegated sodium channels.In this review we will discuss biotechnological aspects relevant for the "electrical imaging" technique and highlight applications in neuroscience. Related recent reviews discussed some of the technological backgrounds of microelectrode arrays [11] and some of their applications. [6] To estimate the requirements needed to image the electrical activity in neurons and networks, we summarize important scales and numbers. A typical neuron comprises a cell body, which integrates the presynaptic signals using an elaborate dendritic network (dendritic tree) and sends an action potential (stereotyped transmembrane voltage signal) activity to synaptically connected neurons using a thin axonal cable-like fiber. Mammalian cell bodies are typically about 10-20 µm in diameter, while the cable-like dendritic and axonal structures have diameters ranging between a few tens of nanometers up to several micrometers. [12] The entire dendritic tree of one neuron or of a synaptically connected neuronal network may cover an area ranging between few tens of micrometers up to tens of square millimeter. [12] Within the retinal ganglion cell layer or hippocampal cell layers the neuronal density may be as high as 5000-10 000 cells mm −2 (mouse retinal ganglion cells, [13] granule cells), [14] to name just two prominent neural tissues studied so far using electrical imaging. These numbers highlight the spatial range and resolution to be achieved for imaging the electrically activity generated and propagating therein at (sub) cellular resolution.Optical imaging-the most common imaging modality in life sciences-achieves high-resolution digital imaging by magnifying and recording the light signal using a complementary metal-oxide semiconductor (CMOS) camera chip. Relevant parameters for optical imaging comprise (i) a large field of view, (ii) a high signal-to-noise ratio (SNR), and (iii) high spatial and (iv) high temporal resolution. The ratio between the sensitivity of the CMOS sensors (i.e., minimal number of detected photons) and the corresponding pixel noise sets the sensitivity limit.Electrical imaging-potentially a complementary or alternative technique of optical imaging-deals with the same constrains. Here, instead of a light-detecting CMOS camera chip, the changing Electrical imaging of extracellular potentials reveals the activity of electrogenic cells and of networks thereof over several orders of magnitude, both in space and time. On a spatial scale, electrical activity pro...

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

Cited by 51 publications

References 63 publications

Direct interfacing of neurons to highly integrated microsystems

Direct interfacing of neurons to highly integrated microsystems

Electrical Stimulus Artifact Cancellation and Neural Spike Detection on Large Multi-Electrode Arrays

Electrical Imaging: Investigating Cellular Function at High Resolution

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