1
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Cartiglia M, Costa F, Narayanan S, Bui CVH, Ulusan H, Risi N, Haessig G, Hierlemann A, Cardes F, Indiveri G. A 4096 channel event-based multielectrode array with asynchronous outputs compatible with neuromorphic processors. Nat Commun 2024; 15:7163. [PMID: 39169023 PMCID: PMC11339437 DOI: 10.1038/s41467-024-50783-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Accepted: 07/19/2024] [Indexed: 08/23/2024] Open
Abstract
Bio-signal sensing is pivotal in medical bioelectronics. Traditional methods focus on high sampling rates, leading to large amounts of irrelevant data and high energy consumption. We introduce a self-clocked microelectrode array (MEA) that digitizes bio-signals at the pixel level by encoding changes as asynchronous digital address-events only when they exceed a threshold, significantly reducing off-chip data transmission. This novel MEA comprises a 64 × 64 electrode array, an asynchronous 2D-arbiter, and an Address-Event Representation (AER) communication block. Each pixel operates autonomously, monitoring voltage fluctuations from cellular activity and producing digital pulses for significant changes. Positive and negative signal changes are encoded as "up" and "down" events and are routed off-chip via the asynchronous arbiter. We present results from chip characterization and experimental measurements using electrogenic cells. Additionally, we interface the MEA to a mixed-signal neuromorphic processor, demonstrating a prototype for end-to-end event-based bio-signal sensing and processing.
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Affiliation(s)
- Matteo Cartiglia
- Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland.
| | - Filippo Costa
- Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland
- Department of Neurosurgery, University Hospital Zurich, Zurich, Switzerland
| | - Shyam Narayanan
- Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Cat-Vu H Bui
- Department of Biosystems Science and Engineering, ETH Zurich, Zurich, Switzerland
| | - Hasan Ulusan
- Department of Biosystems Science and Engineering, ETH Zurich, Zurich, Switzerland
| | - Nicoletta Risi
- Bio-Inspired Circuits and Systems Lab, Zernike Institute for Advanced Materials, University of Groningen, Groningen, Netherlands
- Groningen Cognitive Systems and Materials Center, University of Groningen, Groningen, Netherlands
| | - Germain Haessig
- Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Andreas Hierlemann
- Department of Biosystems Science and Engineering, ETH Zurich, Zurich, Switzerland
| | - Fernando Cardes
- Department of Biosystems Science and Engineering, ETH Zurich, Zurich, Switzerland
| | - Giacomo Indiveri
- Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland
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2
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Kelly AR, Glover DJ. Information Transmission through Biotic-Abiotic Interfaces to Restore or Enhance Human Function. ACS APPLIED BIO MATERIALS 2024; 7:3605-3628. [PMID: 38729914 DOI: 10.1021/acsabm.4c00435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/12/2024]
Abstract
Advancements in reliable information transfer across biotic-abiotic interfaces have enabled the restoration of lost human function. For example, communication between neuronal cells and electrical devices restores the ability to walk to a tetraplegic patient and vision to patients blinded by retinal disease. These impactful medical achievements are aided by tailored biotic-abiotic interfaces that maximize information transfer fidelity by considering the physical properties of the underlying biological and synthetic components. This Review develops a modular framework to define and describe the engineering of biotic and abiotic components as well as the design of interfaces to facilitate biotic-abiotic information transfer using light or electricity. Delineating the properties of the biotic, interface, and abiotic components that enable communication can serve as a guide for future research in this highly interdisciplinary field. Application of synthetic biology to engineer light-sensitive proteins has facilitated the control of neural signaling and the restoration of rudimentary vision after retinal blindness. Electrophysiological methodologies that use brain-computer interfaces and stimulating implants to bypass spinal column injuries have led to the rehabilitation of limb movement and walking ability. Cellular interfacing methodologies and on-chip learning capability have been made possible by organic transistors that mimic the information processing capacity of neurons. The collaboration of molecular biologists, material scientists, and electrical engineers in the emerging field of biotic-abiotic interfacing will lead to the development of prosthetics capable of responding to thought and experiencing touch sensation via direct integration into the human nervous system. Further interdisciplinary research will improve electrical and optical interfacing technologies for the restoration of vision, offering greater visual acuity and potentially color vision in the near future.
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Affiliation(s)
- Alexander R Kelly
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, NSW 2052, Australia
| | - Dominic J Glover
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, NSW 2052, Australia
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3
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Buccino AP, Damart T, Bartram J, Mandge D, Xue X, Zbili M, Gänswein T, Jaquier A, Emmenegger V, Markram H, Hierlemann A, Van Geit W. A Multimodal Fitting Approach to Construct Single-Neuron Models With Patch Clamp and High-Density Microelectrode Arrays. Neural Comput 2024; 36:1286-1331. [PMID: 38776965 DOI: 10.1162/neco_a_01672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 02/20/2024] [Indexed: 05/25/2024]
Abstract
In computational neuroscience, multicompartment models are among the most biophysically realistic representations of single neurons. Constructing such models usually involves the use of the patch-clamp technique to record somatic voltage signals under different experimental conditions. The experimental data are then used to fit the many parameters of the model. While patching of the soma is currently the gold-standard approach to build multicompartment models, several studies have also evidenced a richness of dynamics in dendritic and axonal sections. Recording from the soma alone makes it hard to observe and correctly parameterize the activity of nonsomatic compartments. In order to provide a richer set of data as input to multicompartment models, we here investigate the combination of somatic patch-clamp recordings with recordings of high-density microelectrode arrays (HD-MEAs). HD-MEAs enable the observation of extracellular potentials and neural activity of neuronal compartments at subcellular resolution. In this work, we introduce a novel framework to combine patch-clamp and HD-MEA data to construct multicompartment models. We first validate our method on a ground-truth model with known parameters and show that the use of features extracted from extracellular signals, in addition to intracellular ones, yields models enabling better fits than using intracellular features alone. We also demonstrate our procedure using experimental data by constructing cell models from in vitro cell cultures. The proposed multimodal fitting procedure has the potential to augment the modeling efforts of the computational neuroscience community and provide the field with neuronal models that are more realistic and can be better validated.
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Affiliation(s)
- Alessio Paolo Buccino
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, 4056 Basel, Switzerland
| | - Tanguy Damart
- Blue Brain Project, École polytechnique fédérale de Lausanne, Campus Biotech, 1202 Geneva, Switzerland
| | - Julian Bartram
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, 4056 Basel, Switzerland
| | - Darshan Mandge
- Blue Brain Project, École polytechnique fédérale de Lausanne, Campus Biotech, 1202 Geneva, Switzerland
| | - Xiaohan Xue
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, 4056 Basel, Switzerland
| | - Mickael Zbili
- Blue Brain Project, École polytechnique fédérale de Lausanne, Campus Biotech, 1202 Geneva, Switzerland
| | - Tobias Gänswein
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, 4056 Basel, Switzerland
| | - Aurélien Jaquier
- Blue Brain Project, École polytechnique fédérale de Lausanne, Campus Biotech, 1202 Geneva, Switzerland
| | - Vishalini Emmenegger
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, 4056 Basel, Switzerland
| | - Henry Markram
- Blue Brain Project, École polytechnique fédérale de Lausanne, Campus Biotech, 1202 Geneva, Switzerland
| | - Andreas Hierlemann
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, 4056 Basel, Switzerland
| | - Werner Van Geit
- Blue Brain Project, École polytechnique fédérale de Lausanne, Campus Biotech, 1202 Geneva, Switzerland Present address: Foundation for Research on Information Technologies in Society (IT'IS), Zurich 8004, Switzerland
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4
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Fenton TA, Haouchine OY, Hallam EL, Smith EM, Jackson KC, Rahbarian D, Canales C, Adhikari A, Nord AS, Ben-Shalom R, Silverman JL. Hyperexcitability and translational phenotypes in a preclinical mouse model of SYNGAP1-Related Intellectual Disability. RESEARCH SQUARE 2024:rs.3.rs-4067746. [PMID: 38562838 PMCID: PMC10984035 DOI: 10.21203/rs.3.rs-4067746/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Disruption of SYNGAP1 directly causes a genetically identifiable neurodevelopmental disorder (NDD) called SYNGAP1-related intellectual disability (SRID). Without functional SynGAP1 protein, individuals are developmentally delayed and have prominent features of intellectual disability, motor impairments, and epilepsy. Over the past two decades, there have been numerous discoveries indicting the critical role of Syngap1. Several rodent models with a loss of Syngap1 have been engineered identifying precise roles in neuronal structure and function, as well as key biochemical pathways key for synapse integrity. Homozygous loss of SYNGAP1/Syngap1 is lethal. Heterozygous mutations of Syngap1 result in a broad range of behavioral phenotypes. Our in vivo functional data, using the original mouse model from the Huganir laboratory, corroborated behaviors including robust hyperactivity and deficits in learning and memory in young adults. Furthermore, we described impairments in the domain of sleep, characterized using neurophysiological data collected with wireless, telemetric electroencephalography (EEG). Syngap1+/- mice exhibited elevated spiking events and spike trains, in addition to elevated power, most notably in the delta power frequency. For the first time, we illustrated primary neurons from Syngap1+/- mice displayed increased network firing activity, greater bursts, and shorter inter-burst intervals between peaks by employing high density microelectrode arrays (HD-MEA). Our work bridges in-vitro electrophysiological neuronal activity and function with in vivo neurophysiological brain activity and function. These data elucidate quantitative, translational biomarkers in vivo and in vitro that can be utilized for the development and efficacy assessment of targeted treatments for SRID.
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Affiliation(s)
- Timothy A Fenton
- MIND Institute, University of California Davis School of Medicine, Sacramento, CA 95817
- Department of Psychiatry and Behavioral Sciences, University of California Davis School of Medicine, Sacramento, CA 95817
| | - Olivia Y Haouchine
- MIND Institute, University of California Davis School of Medicine, Sacramento, CA 95817
- Department of Psychiatry and Behavioral Sciences, University of California Davis School of Medicine, Sacramento, CA 95817
| | - Elizabeth L Hallam
- MIND Institute, University of California Davis School of Medicine, Sacramento, CA 95817
- Department of Psychiatry and Behavioral Sciences, University of California Davis School of Medicine, Sacramento, CA 95817
| | - Emily M Smith
- UC Davis Center for Neuroscience; Department of Psychiatry and Behavioral Sciences & Department of Neurobiology, Physiology and Behavior, University of California Davis, Davis, CA 95616
| | - Kiya C. Jackson
- UC Davis Center for Neuroscience; Department of Psychiatry and Behavioral Sciences & Department of Neurobiology, Physiology and Behavior, University of California Davis, Davis, CA 95616
| | - Darlene Rahbarian
- UC Davis Center for Neuroscience; Department of Psychiatry and Behavioral Sciences & Department of Neurobiology, Physiology and Behavior, University of California Davis, Davis, CA 95616
| | - Cesar Canales
- Department of Psychiatry and Behavioral Sciences, University of California Davis School of Medicine, Sacramento, CA 95817
- UC Davis Center for Neuroscience; Department of Psychiatry and Behavioral Sciences & Department of Neurobiology, Physiology and Behavior, University of California Davis, Davis, CA 95616
| | - Anna Adhikari
- MIND Institute, University of California Davis School of Medicine, Sacramento, CA 95817
- Department of Psychiatry and Behavioral Sciences, University of California Davis School of Medicine, Sacramento, CA 95817
| | - Alexander S. Nord
- MIND Institute, University of California Davis School of Medicine, Sacramento, CA 95817
- Department of Psychiatry and Behavioral Sciences, University of California Davis School of Medicine, Sacramento, CA 95817
- UC Davis Center for Neuroscience; Department of Psychiatry and Behavioral Sciences & Department of Neurobiology, Physiology and Behavior, University of California Davis, Davis, CA 95616
| | - Roy Ben-Shalom
- MIND Institute, University of California Davis School of Medicine, Sacramento, CA 95817
- Department of Neurology, University of California Davis School of Medicine, Sacramento, CA 95817
| | - Jill L Silverman
- MIND Institute, University of California Davis School of Medicine, Sacramento, CA 95817
- Department of Psychiatry and Behavioral Sciences, University of California Davis School of Medicine, Sacramento, CA 95817
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5
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Donati E, Valle G. Neuromorphic hardware for somatosensory neuroprostheses. Nat Commun 2024; 15:556. [PMID: 38228580 PMCID: PMC10791662 DOI: 10.1038/s41467-024-44723-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 01/03/2024] [Indexed: 01/18/2024] Open
Abstract
In individuals with sensory-motor impairments, missing limb functions can be restored using neuroprosthetic devices that directly interface with the nervous system. However, restoring the natural tactile experience through electrical neural stimulation requires complex encoding strategies. Indeed, they are presently limited in effectively conveying or restoring tactile sensations by bandwidth constraints. Neuromorphic technology, which mimics the natural behavior of neurons and synapses, holds promise for replicating the encoding of natural touch, potentially informing neurostimulation design. In this perspective, we propose that incorporating neuromorphic technologies into neuroprostheses could be an effective approach for developing more natural human-machine interfaces, potentially leading to advancements in device performance, acceptability, and embeddability. We also highlight ongoing challenges and the required actions to facilitate the future integration of these advanced technologies.
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Affiliation(s)
- Elisa Donati
- Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland.
| | - Giacomo Valle
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago, IL, USA.
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6
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Elliott MAT, Schweiger HE, Robbins A, Vera-Choqqueccota S, Ehrlich D, Hernandez S, Voitiuk K, Geng J, Sevetson JL, Core C, Rosen YM, Teodorescu M, Wagner NO, Haussler D, Mostajo-Radji MA. Internet-Connected Cortical Organoids for Project-Based Stem Cell and Neuroscience Education. eNeuro 2023; 10:ENEURO.0308-23.2023. [PMID: 38016807 PMCID: PMC10755643 DOI: 10.1523/eneuro.0308-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Revised: 10/16/2023] [Accepted: 11/20/2023] [Indexed: 11/30/2023] Open
Abstract
The introduction of Internet-connected technologies to the classroom has the potential to revolutionize STEM education by allowing students to perform experiments in complex models that are unattainable in traditional teaching laboratories. By connecting laboratory equipment to the cloud, we introduce students to experimentation in pluripotent stem cell (PSC)-derived cortical organoids in two different settings: using microscopy to monitor organoid growth in an introductory tissue culture course and using high-density (HD) multielectrode arrays (MEAs) to perform neuronal stimulation and recording in an advanced neuroscience mathematics course. We demonstrate that this approach develops interest in stem cell and neuroscience in the students of both courses. All together, we propose cloud technologies as an effective and scalable approach for complex project-based university training.
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Affiliation(s)
- Matthew A T Elliott
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA 95060
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95060
| | - Hunter E Schweiger
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA 95060
- Department of Molecular, Cell and Developmental Biology, University of California Santa Cruz, Santa Cruz, CA 95060
| | - Ash Robbins
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA 95060
- Department of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA 95060
| | - Samira Vera-Choqqueccota
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA 95060
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95060
| | - Drew Ehrlich
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA 95060
- Department of Computational Media, University of California Santa Cruz, Santa Cruz, CA 95060
| | - Sebastian Hernandez
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA 95060
- Department of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA 95060
| | - Kateryna Voitiuk
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA 95060
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95060
| | - Jinghui Geng
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA 95060
- Department of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA 95060
| | - Jess L Sevetson
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060
- Department of Molecular, Cell and Developmental Biology, University of California Santa Cruz, Santa Cruz, CA 95060
| | - Cordero Core
- Scientific Software Engineering Center, eScience Institute, University of Washington, Seattle, WA 98195
| | - Yohei M Rosen
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA 95060
| | - Mircea Teodorescu
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA 95060
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95060
- Department of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA 95060
| | - Nico O Wagner
- College of Arts and Sciences, University of San Francisco, San Francisco, CA 94117
| | - David Haussler
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA 95060
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95060
| | - Mohammed A Mostajo-Radji
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA 95060
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7
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Duru J, Maurer B, Giles Doran C, Jelitto R, Küchler J, Ihle SJ, Ruff T, John R, Genocchi B, Vörös J. Investigation of the input-output relationship of engineered neural networks using high-density microelectrode arrays. Biosens Bioelectron 2023; 239:115591. [PMID: 37634421 DOI: 10.1016/j.bios.2023.115591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 07/25/2023] [Accepted: 08/10/2023] [Indexed: 08/29/2023]
Abstract
Bottom-up neuroscience utilizes small, engineered biological neural networks to study neuronal activity in systems of reduced complexity. We present a platform that establishes up to six independent networks formed by primary rat neurons on planar complementary metal-oxide-semiconductor (CMOS) microelectrode arrays (MEAs). We introduce an approach that allows repetitive stimulation and recording of network activity at any of the over 700 electrodes underlying a network. We demonstrate that the continuous application of a repetitive super-threshold stimulus yields a reproducible network answer within a 15 ms post-stimulus window. This response can be tracked with high spatiotemporal resolution across the whole extent of the network. Moreover, we show that the location of the stimulation plays a significant role in the networks' early response to the stimulus. By applying a stimulation pattern to all network-underlying electrodes in sequence, the sensitivity of the whole network to the stimulus can be visualized. We demonstrate that microchannels reduce the voltage stimulation threshold and induce the strongest network response. By varying the stimulation amplitude and frequency we reveal discrete network transition points. Finally, we introduce vector fields to follow stimulation-induced spike propagation pathways within the network. Overall we show that our defined neural networks on CMOS MEAs enable us to elicit highly reproducible activity patterns that can be precisely modulated by stimulation amplitude, stimulation frequency and the site of stimulation.
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Affiliation(s)
- Jens Duru
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, University and ETH Zurich, Gloriastrasse 35, Zurich, 8092, Switzerland.
| | - Benedikt Maurer
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, University and ETH Zurich, Gloriastrasse 35, Zurich, 8092, Switzerland.
| | - Ciara Giles Doran
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, University and ETH Zurich, Gloriastrasse 35, Zurich, 8092, Switzerland.
| | - Robert Jelitto
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, University and ETH Zurich, Gloriastrasse 35, Zurich, 8092, Switzerland.
| | - Joël Küchler
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, University and ETH Zurich, Gloriastrasse 35, Zurich, 8092, Switzerland.
| | - Stephan J Ihle
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, University and ETH Zurich, Gloriastrasse 35, Zurich, 8092, Switzerland.
| | - Tobias Ruff
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, University and ETH Zurich, Gloriastrasse 35, Zurich, 8092, Switzerland.
| | - Robert John
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, University and ETH Zurich, Gloriastrasse 35, Zurich, 8092, Switzerland.
| | - Barbara Genocchi
- Computational Biophysics and Imaging Group, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.
| | - János Vörös
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, University and ETH Zurich, Gloriastrasse 35, Zurich, 8092, Switzerland.
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8
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Silverman JL, Fenton T, Haouchine O, Hallam E, Smith E, Jackson K, Rahbarian D, Canales C, Adhikari A, Nord A, Ben-Shalom R. Hyperexcitability and translational phenotypes in a preclinical model of SYNGAP1 mutations. RESEARCH SQUARE 2023:rs.3.rs-3246655. [PMID: 37790402 PMCID: PMC10543290 DOI: 10.21203/rs.3.rs-3246655/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
SYNGAP1 is a critical gene for neuronal development, synaptic structure, and function. Although rare, the disruption of SYNGAP1 directly causes a genetically identifiable neurodevelopmental disorder (NDD) called SYNGAP1 -related intellectual disability. Without functional SynGAP1 protein, patients present with intellectual disability, motor impairments, and epilepsy. Previous work using mouse models with a variety of germline and conditional mutations has helped delineate SynGAP1's critical roles in neuronal structure and function, as well as key biochemical signaling pathways essential to synapse integrity. Homozygous loss of SYNGAP1 is embryonically lethal. Heterozygous mutations of SynGAP1 result in a broad range of phenotypes including increased locomotor activity, impaired working spatial memory, impaired cued fear memory, and increased stereotypic behavior. Our in vivo functional data, using the original germline mutation mouse line from the Huganir laboratory, corroborated robust hyperactivity and learning and memory deficits. Here, we describe impairments in the translational biomarker domain of sleep, characterized using neurophysiological data collected with wireless telemetric electroencephalography (EEG). We discovered Syngap1+/- mice exhibited elevated spike trains in both number and duration, in addition to elevated power, most notably in the delta power band. Primary neurons from Syngap1+/- mice displayed increased network firing activity, greater spikes per burst, and shorter inter-burst intervals between peaks using high density micro-electrode arrays (HD-MEA). This work is translational, innovative, and highly significant as it outlines functional impairments in Syngap1 mutant mice. Simultaneously, the work utilized untethered, wireless neurophysiology that can discover potential biomarkers of Syngap1 RI-D, for clinical trials, as it has done with other NDDs. Our work is substantial forward progress toward translational work for SynGAP1R-ID as it bridges in-vitro electrophysiological neuronal activity and function with in vivo neurophysiological brain activity and function. These data elucidate multiple quantitative, translational biomarkers in vivo and in vitro for the development of treatments for SYNGAP1-related intellectual disability.
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Affiliation(s)
- Jill L Silverman
- MIND Institute and Department of Psychiatry and Behavioral Sciences, University of California Davis School of Medicine
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9
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Radivojevic M, Rostedt Punga A. Functional imaging of conduction dynamics in cortical and spinal axons. eLife 2023; 12:e86512. [PMID: 37606618 PMCID: PMC10444024 DOI: 10.7554/elife.86512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 08/09/2023] [Indexed: 08/23/2023] Open
Abstract
Mammalian axons are specialized for transmitting action potentials to targets within the central and peripheral nervous system. A growing body of evidence suggests that, besides signal conduction, axons play essential roles in neural information processing, and their malfunctions are common hallmarks of neurodegenerative diseases. The technologies available to study axonal function and structure integrally limit the comprehension of axon neurobiology. High-density microelectrode arrays (HD-MEAs) allow for accessing axonal action potentials at high spatiotemporal resolution, but provide no insights on axonal morphology. Here, we demonstrate a method for electrical visualization of axonal morphologies based on extracellular action potentials recorded from cortical and motor neurons using HD-MEAs. The method enabled us to reconstruct up to 5-cm-long axonal arbors and directly monitor axonal conduction across thousands of recording sites. We reconstructed 1.86 m of cortical and spinal axons in total and found specific features in their structure and function.
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10
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Fenton TA, Haouchine OY, Hallam EL, Smith EM, Jackson KC, Rahbarian D, Canales C, Adhikari A, Nord AS, Ben-Shalom R, Silverman JL. Hyperexcitability and translational phenotypes in a preclinical model of SYNGAP1 mutations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.24.550093. [PMID: 37546838 PMCID: PMC10402099 DOI: 10.1101/2023.07.24.550093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
SYNGAP1 is a critical gene for neuronal development, synaptic structure, and function. Although rare, the disruption of SYNGAP1 directly causes a genetically identifiable neurodevelopmental disorder (NDD) called SYNGAP1-related intellectual disability. Without functional SynGAP1 protein, patients present with intellectual disability, motor impairments, and epilepsy. Previous work using mouse models with a variety of germline and conditional mutations has helped delineate SynGAP1's critical roles in neuronal structure and function, as well as key biochemical signaling pathways essential to synapse integrity. Homozygous loss of SYNGAP1 is embryonically lethal. Heterozygous mutations of SynGAP1 result in a broad range of phenotypes including increased locomotor activity, impaired working spatial memory, impaired cued fear memory, and increased stereotypic behavior. Our in vivo functional data, using the original germline mutation mouse line from the Huganir laboratory, corroborated robust hyperactivity and learning and memory deficits. Here, we describe impairments in the translational biomarker domain of sleep, characterized using neurophysiological data collected with wireless telemetric electroencephalography (EEG). We discovered Syngap1 +/- mice exhibited elevated spike trains in both number and duration, in addition to elevated power, most notably in the delta power band. Primary neurons from Syngap1 +/- mice displayed increased network firing activity, greater spikes per burst, and shorter inter-burst intervals between peaks using high density micro-electrode arrays (HD-MEA). This work is translational, innovative, and highly significant as it outlines functional impairments in Syngap1 mutant mice. Simultaneously, the work utilized untethered, wireless neurophysiology that can discover potential biomarkers of Syngap1R-ID, for clinical trials, as it has done with other NDDs. Our work is substantial forward progress toward translational work for SynGAP1R-ID as it bridges in-vitro electrophysiological neuronal activity and function with in vivo neurophysiological brain activity and function. These data elucidate multiple quantitative, translational biomarkers in vivo and in vitro for the development of treatments for SYNGAP1-related intellectual disability.
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11
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Elliott MA, Schweiger HE, Robbins A, Vera-Choqqueccota S, Ehrlich D, Hernandez S, Voitiuk K, Geng J, Sevetson JL, Rosen YM, Teodorescu M, Wagner NO, Haussler D, Mostajo-Radji MA. Internet-connected cortical organoids for project-based stem cell and neuroscience education. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.13.546418. [PMID: 37503236 PMCID: PMC10369936 DOI: 10.1101/2023.07.13.546418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
The introduction of internet-connected technologies to the classroom has the potential to revolutionize STEM education by allowing students to perform experiments in complex models that are unattainable in traditional teaching laboratories. By connecting laboratory equipment to the cloud, we introduce students to experimentation in pluripotent stem cell-derived cortical organoids in two different settings: Using microscopy to monitor organoid growth in an introductory tissue culture course, and using high density multielectrode arrays to perform neuronal stimulation and recording in an advanced neuroscience mathematics course. We demonstrate that this approach develops interest in stem cell and neuroscience in the students of both courses. All together, we propose cloud technologies as an effective and scalable approach for complex project-based university training.
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Affiliation(s)
- Matthew A.T. Elliott
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
| | - Hunter E. Schweiger
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
- Department of Molecular, Cell and Developmental Biology, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
| | - Ash Robbins
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
- Department of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
| | - Samira Vera-Choqqueccota
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
| | - Drew Ehrlich
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
- Department of Computational Media, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
| | - Sebastian Hernandez
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
- Department of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
| | - Kateryna Voitiuk
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
| | - Jinghui Geng
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
- Department of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
| | - Jess L. Sevetson
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
- Department of Molecular, Cell and Developmental Biology, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
| | - Yohei M. Rosen
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
| | - Mircea Teodorescu
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
- Department of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
| | - Nico O. Wagner
- College of Arts and Sciences, University of San Francisco, San Francisco, CA, 94117, USA
| | - David Haussler
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
| | - Mohammed A. Mostajo-Radji
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA, 95060, USA
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12
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Suzuki I, Matsuda N, Han X, Noji S, Shibata M, Nagafuku N, Ishibashi Y. Large-Area Field Potential Imaging Having Single Neuron Resolution Using 236 880 Electrodes CMOS-MEA Technology. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023:e2207732. [PMID: 37088859 PMCID: PMC10369302 DOI: 10.1002/advs.202207732] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 03/21/2023] [Indexed: 05/03/2023]
Abstract
The electrophysiological technology having a high spatiotemporal resolution at the single-cell level and noninvasive measurements of large areas provide insights on underlying neuronal function. Here, a complementary metal-oxide semiconductor (CMOS)-microelectrode array (MEA) is used that uses 236 880 electrodes each with an electrode size of 11.22 × 11.22 µm and 236 880 covering a wide area of 5.5 × 5.9 mm in presenting a detailed and single-cell-level neural activity analysis platform for brain slices, human iPS cell-derived cortical networks, peripheral neurons, and human brain organoids. Propagation pattern characteristics between brain regions changes the synaptic propagation into compounds based on single-cell time-series patterns, classification based on single DRG neuron firing patterns and compound responses, axonal conduction characteristics and changes to anticancer drugs, and network activities and transition to compounds in brain organoids are extracted. This detailed analysis of neural activity at the single-cell level using the CMOS-MEA provides a new understanding of the basic mechanisms of brain circuits in vitro and ex vivo, on human neurological diseases for drug discovery, and compound toxicity assessment.
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Affiliation(s)
- Ikuro Suzuki
- Department of Electronics, Graduate School of Engineering, Tohoku Institute of Technology, 35-1 Yagiyama Kasumicho, Taihaku-ku, Sendai, Miyagi, 982-8577, Japan
| | - Naoki Matsuda
- Department of Electronics, Graduate School of Engineering, Tohoku Institute of Technology, 35-1 Yagiyama Kasumicho, Taihaku-ku, Sendai, Miyagi, 982-8577, Japan
| | - Xiaobo Han
- Department of Electronics, Graduate School of Engineering, Tohoku Institute of Technology, 35-1 Yagiyama Kasumicho, Taihaku-ku, Sendai, Miyagi, 982-8577, Japan
| | - Shuhei Noji
- Department of Electronics, Graduate School of Engineering, Tohoku Institute of Technology, 35-1 Yagiyama Kasumicho, Taihaku-ku, Sendai, Miyagi, 982-8577, Japan
| | - Mikako Shibata
- Department of Electronics, Graduate School of Engineering, Tohoku Institute of Technology, 35-1 Yagiyama Kasumicho, Taihaku-ku, Sendai, Miyagi, 982-8577, Japan
| | - Nami Nagafuku
- Department of Electronics, Graduate School of Engineering, Tohoku Institute of Technology, 35-1 Yagiyama Kasumicho, Taihaku-ku, Sendai, Miyagi, 982-8577, Japan
| | - Yuto Ishibashi
- Department of Electronics, Graduate School of Engineering, Tohoku Institute of Technology, 35-1 Yagiyama Kasumicho, Taihaku-ku, Sendai, Miyagi, 982-8577, Japan
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13
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Xu J, Shirinkami H, Hwang S, Jeong HS, Kim G, Jun SB, Chun H. Fast Reconfigurable Electrode Array Based on Titanium Oxide for Localized Stimulation of Cultured Neural Network. ACS APPLIED MATERIALS & INTERFACES 2023; 15:19092-19101. [PMID: 37036145 DOI: 10.1021/acsami.2c21649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Planar microelectrode arrays have become standard tools for in vitro neural-network analysis. However, these predefined micropatterned devices lack adaptability to target-specific cells within a cultured network. Herein, we fabricated a reconfigurable TiO2 electrode array with an anatase-brookite bicrystalline polymorphous mesoporous layer. Because of its selective absorption of ultraviolet (UV) light and corresponding photoconductivity, TiO2 electrode array was identified as a promising tool for high-resolution light-addressing. The TiO2 film was used as a semitransparent semiconductor with a high Roff/Ron ratio of 105 and a fast response time of 400 ms. In addition, the effect of UV radiation on the resistance of the TiO2 film over 30 d in an aqueous environment was analyzed, with the film exhibiting high stability. An arbitrary UV pattern was applied to a reconfigurable TiO2 electrode using a digital micromirror device (DMD), affording highly localized neural stimulation at the single-cell level. The reconfigurable TiO2 electrode with a patterned indium tin oxide (ITO) substrate enabled the independent connection of up to 60 points with external stimulators and signal recorders. We believe this technique would be helpful for electrophysiological research requiring the analysis of cell and neural-network features using a highly localized neural interface.
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Affiliation(s)
- Jiaxin Xu
- Department of Biomedical Engineering, Korea University, Hana Science Hall, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Korea
| | - Hamidreza Shirinkami
- Department of Biomedical Engineering, Korea University, Hana Science Hall, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Korea
| | - Seoyoung Hwang
- Department of Electronic and Electrical Engineering, Ewha Womans University, Asan Engineering Building, 52 Ewhayeodae-gil, Seodaemun-gu, Seoul 03760, Korea
| | - Hee Soo Jeong
- Department of Electronic and Electrical Engineering, Ewha Womans University, Asan Engineering Building, 52 Ewhayeodae-gil, Seodaemun-gu, Seoul 03760, Korea
| | - Gijung Kim
- Department of Biomedical Engineering, Korea University, Hana Science Hall, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Korea
- BK21 Four Institute of Precision Public Health, Korea University, Hana Science Hall, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Korea
| | - Sang Beom Jun
- Department of Electronic and Electrical Engineering, Ewha Womans University, Asan Engineering Building, 52 Ewhayeodae-gil, Seodaemun-gu, Seoul 03760, Korea
- Graduate Program in Smart Factory, Ewha Womans University, Asan Engineering Building, 52 Ewhayeodae-gil, Seodaemun-gu, Seoul 03760, Korea
| | - Honggu Chun
- Department of Biomedical Engineering, Korea University, Hana Science Hall, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Korea
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14
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Liu Y, Xu S, Yang Y, Zhang K, He E, Liang W, Luo J, Wu Y, Cai X. Nanomaterial-based microelectrode arrays for in vitro bidirectional brain-computer interfaces: a review. MICROSYSTEMS & NANOENGINEERING 2023; 9:13. [PMID: 36726940 PMCID: PMC9884667 DOI: 10.1038/s41378-022-00479-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 10/04/2022] [Accepted: 10/21/2022] [Indexed: 06/18/2023]
Abstract
A bidirectional in vitro brain-computer interface (BCI) directly connects isolated brain cells with the surrounding environment, reads neural signals and inputs modulatory instructions. As a noninvasive BCI, it has clear advantages in understanding and exploiting advanced brain function due to the simplified structure and high controllability of ex vivo neural networks. However, the core of ex vivo BCIs, microelectrode arrays (MEAs), urgently need improvements in the strength of signal detection, precision of neural modulation and biocompatibility. Notably, nanomaterial-based MEAs cater to all the requirements by converging the multilevel neural signals and simultaneously applying stimuli at an excellent spatiotemporal resolution, as well as supporting long-term cultivation of neurons. This is enabled by the advantageous electrochemical characteristics of nanomaterials, such as their active atomic reactivity and outstanding charge conduction efficiency, improving the performance of MEAs. Here, we review the fabrication of nanomaterial-based MEAs applied to bidirectional in vitro BCIs from an interdisciplinary perspective. We also consider the decoding and coding of neural activity through the interface and highlight the various usages of MEAs coupled with the dissociated neural cultures to benefit future developments of BCIs.
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Affiliation(s)
- Yaoyao Liu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190 China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049 PR China
| | - Shihong Xu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190 China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049 PR China
| | - Yan Yang
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190 China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049 PR China
| | - Kui Zhang
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190 China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049 PR China
| | - Enhui He
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190 China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049 PR China
| | - Wei Liang
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190 China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049 PR China
| | - Jinping Luo
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190 China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049 PR China
| | - Yirong Wu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190 China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049 PR China
| | - Xinxia Cai
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190 China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049 PR China
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15
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Kim T, Chen D, Hornauer P, Emmenegger V, Bartram J, Ronchi S, Hierlemann A, Schröter M, Roqueiro D. Predicting in vitro single-neuron firing rates upon pharmacological perturbation using Graph Neural Networks. Front Neuroinform 2023; 16:1032538. [PMID: 36713289 PMCID: PMC9874697 DOI: 10.3389/fninf.2022.1032538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 12/13/2022] [Indexed: 01/12/2023] Open
Abstract
Modern Graph Neural Networks (GNNs) provide opportunities to study the determinants underlying the complex activity patterns of biological neuronal networks. In this study, we applied GNNs to a large-scale electrophysiological dataset of rodent primary neuronal networks obtained by means of high-density microelectrode arrays (HD-MEAs). HD-MEAs allow for long-term recording of extracellular spiking activity of individual neurons and networks and enable the extraction of physiologically relevant features at the single-neuron and population level. We employed established GNNs to generate a combined representation of single-neuron and connectivity features obtained from HD-MEA data, with the ultimate goal of predicting changes in single-neuron firing rate induced by a pharmacological perturbation. The aim of the main prediction task was to assess whether single-neuron and functional connectivity features, inferred under baseline conditions, were informative for predicting changes in neuronal activity in response to a perturbation with Bicuculline, a GABA A receptor antagonist. Our results suggest that the joint representation of node features and functional connectivity, extracted from a baseline recording, was informative for predicting firing rate changes of individual neurons after the perturbation. Specifically, our implementation of a GNN model with inductive learning capability (GraphSAGE) outperformed other prediction models that relied only on single-neuron features. We tested the generalizability of the results on two additional datasets of HD-MEA recordings-a second dataset with cultures perturbed with Bicuculline and a dataset perturbed with the GABA A receptor antagonist Gabazine. GraphSAGE models showed improved prediction accuracy over other prediction models. Our results demonstrate the added value of taking into account the functional connectivity between neurons and the potential of GNNs to study complex interactions between neurons.
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Affiliation(s)
- Taehoon Kim
- Bioengineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- Machine Learning and Computational Biology Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Dexiong Chen
- Machine Learning and Computational Biology Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Philipp Hornauer
- Bioengineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Vishalini Emmenegger
- Bioengineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Julian Bartram
- Bioengineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Silvia Ronchi
- Bioengineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Andreas Hierlemann
- Bioengineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Manuel Schröter
- Bioengineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Damian Roqueiro
- Machine Learning and Computational Biology Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Zurich, Switzerland
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16
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Moore H, Lega BC, Konopka G. Riding brain "waves" to identify human memory genes. Curr Opin Cell Biol 2022; 78:102118. [PMID: 35947942 DOI: 10.1016/j.ceb.2022.102118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 06/24/2022] [Accepted: 06/28/2022] [Indexed: 01/31/2023]
Abstract
While there is extensive research on memory-related oscillations and brain gene expression, the relationship between oscillations and gene expression has rarely been studied. Recently, progress has been made to identify specific genes associated with oscillations that are correlated with episodic memory. Neocortical regions, in particular the temporal pole, have been examined in this line of research due to their accessibility during neurosurgical procedures. By harnessing this accessibility, a unique and powerful study design has allowed gene expression and intracranial oscillatory data to be sourced from the same human patients. These studies have identified a plethora of understudied gene targets that should be further characterized with respect to human brain function. Future work should extend to other brain regions to increase our understanding of the genetic signatures of oscillations and, ultimately, human cognition.
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Affiliation(s)
- Haley Moore
- Department of Neuroscience, UT Southwestern Medical Center, USA; Peter O'Donnell Jr. Brain Institute, UT Southwestern Medical Center, USA; Department of Neurosurgery, UT Southwestern Medical Center, USA
| | - Bradley C Lega
- Peter O'Donnell Jr. Brain Institute, UT Southwestern Medical Center, USA; Department of Neurosurgery, UT Southwestern Medical Center, USA.
| | - Genevieve Konopka
- Department of Neuroscience, UT Southwestern Medical Center, USA; Peter O'Donnell Jr. Brain Institute, UT Southwestern Medical Center, USA.
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17
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Joshi PS, Hu K, Larkin JW, Rosenstein JK. Programmable Electrochemical Stimulation on a Large-Scale CMOS Microelectrode Array. IEEE BIOMEDICAL CIRCUITS AND SYSTEMS CONFERENCE : HEALTHCARE TECHNOLOGY : [PROCEEDINGS]. IEEE BIOMEDICAL CIRCUITS AND SYSTEMS CONFERENCE 2022; 2022:439-443. [PMID: 37126479 PMCID: PMC10148594 DOI: 10.1109/biocas54905.2022.9948674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
In this paper we present spatio-temporally controlled electrochemical stimulation of aqueous samples using an integrated CMOS microelectrode array with 131,072 pixels. We demonstrate programmable gold electrodeposition in arbitrary spatial patterns, controllable electrolysis to produce microscale hydrogen bubbles, and spatially targeted electrochemical pH modulation. Dense spatially-addressable electrochemical stimulation is important for a wide range of bioelectronics applications.
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18
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Lee J, Gänswein T, Ulusan H, Emmenegger V, Saguner AM, Duru F, Hierlemann A. Repeated and On-Demand Intracellular Recordings of Cardiomyocytes Derived from Human-Induced Pluripotent Stem Cells. ACS Sens 2022; 7:3181-3191. [PMID: 36166837 PMCID: PMC7613763 DOI: 10.1021/acssensors.2c01678] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
Pharmaceutical compounds may have cardiotoxic properties, triggering potentially life-threatening arrhythmias. To investigate proarrhythmic effects of drugs, the patch clamp technique has been used as the gold standard for characterizing the electrophysiology of cardiomyocytes in vitro. However, the applicability of this technology for drug screening is limited, as it is complex to use and features low throughput. Recent studies have demonstrated that 3D-nanostructured electrodes enable to obtain intracellular signals from many cardiomyocytes in parallel; however, the tedious electrode fabrication and limited measurement duration still remain major issues for cardiotoxicity testing. Here, we demonstrate how porous Pt-black electrodes, arranged in high-density microelectrode arrays, can be used to record intracellular-like signals of cardiomyocytes at large scale repeatedly over an extended period of time. The developed technique, which yields highly parallelized electroporations using stimulation voltages around 1 V peak-to-peak amplitude, enabled intracellular-like recordings at high success rates without causing significant alteration in key electrophysiological features. In a proof-of-concept study, we investigated electrophysiological modulations induced by two clinically applied drugs, nifedipine and quinidine. As the obtained results were in good agreement with previously published data, we are confident that the developed technique has the potential to be routinely used in in vitro platforms for cardiotoxicity screening.
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Affiliation(s)
- Jihyun Lee
- Corresponding Authors Jihyun Lee — Bio Engineering Laboratory, ETH Zurich, 4058 Basel, Switzerland; ® Phone: +41 (0)61 387 31 28; jihyun.lee@ bsse.ethz.ch; Andreas Hierlemann — Bio Engineering Laboratory, ETH Zurich, 4058 Basel, Switzerland; Phone: +41 (0)61 387 31 50;
| | | | | | | | | | | | - Andreas Hierlemann
- Corresponding Authors Jihyun Lee — Bio Engineering Laboratory, ETH Zurich, 4058 Basel, Switzerland; ® Phone: +41 (0)61 387 31 28; jihyun.lee@ bsse.ethz.ch; Andreas Hierlemann — Bio Engineering Laboratory, ETH Zurich, 4058 Basel, Switzerland; Phone: +41 (0)61 387 31 50;
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19
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Mahadevan A, Codadu NK, Parrish RR. Xenon LFP Analysis Platform Is a Novel Graphical User Interface for Analysis of Local Field Potential From Large-Scale MEA Recordings. Front Neurosci 2022; 16:904931. [PMID: 35844228 PMCID: PMC9285004 DOI: 10.3389/fnins.2022.904931] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Accepted: 06/08/2022] [Indexed: 11/24/2022] Open
Abstract
High-density multi-electrode array (HD-MEA) has enabled neuronal measurements at high spatial resolution to record local field potentials (LFP), extracellular action potentials, and network-wide extracellular recording on an extended spatial scale. While we have advanced recording systems with over 4,000 electrodes capable of recording data at over 20 kHz, it still presents computational challenges to handle, process, extract, and view information from these large recordings. We have created a computational method, and an open-source toolkit built in Python, rendered on a web browser using Plotly’s Dash for extracting and viewing the data and creating interactive visualization. In addition to extracting and viewing entire or small chunks of data sampled at lower or higher frequencies, respectively, it provides a framework to collect user inputs, analyze channel groups, generate raster plots, view quick summary measures for LFP activity, detect and isolate noise channels, and generate plots and visualization in both time and frequency domain. Incorporated into our Graphical User Interface (GUI), we also created a novel seizure detection method, which can be used to detect the onset of seizures in all or a selected group of channels and provide the following measures of seizures: distance, duration, and propagation across the region of interest. We demonstrate the utility of this toolkit, using datasets collected from an HD-MEA device comprising of 4,096 recording electrodes. For the current analysis, we demonstrate the toolkit and methods with a low sampling frequency dataset (300 Hz) and a group of approximately 400 channels. Using this toolkit, we present novel data demonstrating increased seizure propagation speed from brain slices of Scn1aHet mice compared to littermate controls. While there have been advances in HD-MEA recording systems with high spatial and temporal resolution, limited tools are available for researchers to view and process these big datasets. We now provide a user-friendly toolkit to analyze LFP activity obtained from large-scale MEA recordings with translatable applications to EEG recordings and demonstrate the utility of this new graphic user interface with novel biological findings.
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Affiliation(s)
- Arjun Mahadevan
- Department of Cellular and Molecular Biology, Xenon Pharmaceuticals Inc., Burnaby, BC, Canada
| | - Neela K. Codadu
- Department of Clinical and Experimental Epilepsy, Institute of Neurology, University College London, London, United Kingdom
| | - R. Ryley Parrish
- Department of Cellular and Molecular Biology, Xenon Pharmaceuticals Inc., Burnaby, BC, Canada
- *Correspondence: R. Ryley Parrish,
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20
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Schröter M, Wang C, Terrigno M, Hornauer P, Huang Z, Jagasia R, Hierlemann A. Functional imaging of brain organoids using high-density microelectrode arrays. MRS BULLETIN 2022; 47:530-544. [PMID: 36120104 PMCID: PMC9474390 DOI: 10.1557/s43577-022-00282-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 02/02/2022] [Indexed: 05/31/2023]
Abstract
ABSTRACT Studies have provided evidence that human cerebral organoids (hCOs) recapitulate fundamental milestones of early brain development, but many important questions regarding their functionality and electrophysiological properties persist. High-density microelectrode arrays (HD-MEAs) represent an attractive analysis platform to perform functional studies of neuronal networks at the cellular and network scale. Here, we use HD-MEAs to derive large-scale electrophysiological recordings from sliced hCOs. We record the activity of hCO slices over several weeks and probe observed neuronal dynamics pharmacologically. Moreover, we present results on how the obtained recordings can be spike-sorted and subsequently studied across scales. For example, we show how to track single neurons across several days on the HD-MEA and how to infer axonal action potential velocities. We also infer putative functional connectivity from hCO recordings. The introduced methodology will contribute to a better understanding of developing neuronal networks in brain organoids and provide new means for their functional characterization. IMPACT STATEMENT Human cerebral organoids (hCOs) represent an attractive in vitro model system to study key physiological mechanisms underlying early neuronal network formation in tissue with healthy or disease-related genetic backgrounds. Despite remarkable advances in the generation of brain organoids, knowledge on the functionality of their neuronal circuits is still scarce. Here, we used complementary metal-oxide-semiconductor (CMOS)-based high-density microelectrode arrays (HD-MEAs) to perform large-scale recordings from sliced hCOs over several weeks and quantified their activity across scales. Using single-cell and network metrics, we were able to probe aspects of hCO neurophysiology that are more difficult to obtain with other techniques, such as patch clamping (lower yield) and calcium imaging (lower temporal resolution). These metrics included, for example, extracellular action potential (AP) waveform features and axonal AP velocity at the cellular level, as well as functional connectivity at the network level. Analysis was enabled by the large sensing area and the high spatiotemporal resolution provided by HD-MEAs, which allowed recordings from hundreds of neurons and spike sorting of their activity. Our results demonstrate that HD-MEAs provide a multi-purpose platform for the functional characterization of hCOs, which will be key in improving our understanding of this model system and assessing its relevance for translational research. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1557/s43577-022-00282-w.
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Affiliation(s)
- Manuel Schröter
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
| | - Congwei Wang
- NRD, F. Hoffmann-La Roche Ltd., Roche Innovation Center Basel, Basel, Switzerland
| | - Marco Terrigno
- NRD, F. Hoffmann-La Roche Ltd., Roche Innovation Center Basel, Basel, Switzerland
| | - Philipp Hornauer
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
| | - Ziqiang Huang
- EMBL Imaging Centre, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | - Ravi Jagasia
- NRD, F. Hoffmann-La Roche Ltd., Roche Innovation Center Basel, Basel, Switzerland
| | - Andreas Hierlemann
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
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21
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Buccino AP, Yuan X, Emmenegger V, Xue X, Gänswein T, Hierlemann A. An automated method for precise axon reconstruction from recordings of high-density micro-electrode arrays. J Neural Eng 2022; 19:026026. [PMID: 35234667 PMCID: PMC7612575 DOI: 10.1088/1741-2552/ac59a2] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Accepted: 03/01/2022] [Indexed: 11/13/2022]
Abstract
Objective:Neurons communicate with each other by sending action potentials (APs) through their axons. The velocity of axonal signal propagation describes how fast electrical APs can travel. This velocity can be affected in a human brain by several pathologies, including multiple sclerosis, traumatic brain injury and channelopathies. High-density microelectrode arrays (HD-MEAs) provide unprecedented spatio-temporal resolution to extracellularly record neural electrical activity. The high density of the recording electrodes enables to image the activity of individual neurons down to subcellular resolution, which includes the propagation of axonal signals. However, axon reconstruction, to date, mainly relies on manual approaches to select the electrodes and channels that seemingly record the signals along a specific axon, while an automated approach to track multiple axonal branches in extracellular action-potential recordings is still missing.Approach:In this article, we propose a fully automated approach to reconstruct axons from extracellular electrical-potential landscapes, so-called 'electrical footprints' of neurons. After an initial electrode and channel selection, the proposed method first constructs a graph based on the voltage signal amplitudes and latencies. Then, the graph is interrogated to extract possible axonal branches. Finally, the axonal branches are pruned, and axonal action-potential propagation velocities are computed.Main results:We first validate our method using simulated data from detailed reconstructions of neurons, showing that our approach is capable of accurately reconstructing axonal branches. We then apply the reconstruction algorithm to experimental recordings of HD-MEAs and show that it can be used to determine axonal morphologies and signal-propagation velocities at high throughput.Significance:We introduce a fully automated method to reconstruct axonal branches and estimate axonal action-potential propagation velocities using HD-MEA recordings. Our method yields highly reliable and reproducible velocity estimations, which constitute an important electrophysiological feature of neuronal preparations.
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Affiliation(s)
| | - Xinyue Yuan
- Department of Biosystems Science and Engineering, ETH Zurich, Switzerland
| | | | - Xiaohan Xue
- Department of Biosystems Science and Engineering, ETH Zurich, Switzerland
| | - Tobias Gänswein
- Department of Biosystems Science and Engineering, ETH Zurich, Switzerland
| | - Andreas Hierlemann
- Department of Biosystems Science and Engineering, ETH Zurich, Switzerland
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22
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Duru J, Küchler J, Ihle SJ, Forró C, Bernardi A, Girardin S, Hengsteler J, Wheeler S, Vörös J, Ruff T. Engineered Biological Neural Networks on High Density CMOS Microelectrode Arrays. Front Neurosci 2022; 16:829884. [PMID: 35264928 PMCID: PMC8900719 DOI: 10.3389/fnins.2022.829884] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 01/27/2022] [Indexed: 12/18/2022] Open
Abstract
In bottom-up neuroscience, questions on neural information processing are addressed by engineering small but reproducible biological neural networks of defined network topology in vitro. The network topology can be controlled by culturing neurons within polydimethylsiloxane (PDMS) microstructures that are combined with microelectrode arrays (MEAs) for electric access to the network. However, currently used glass MEAs are limited to 256 electrodes and pose a limitation to the spatial resolution as well as the design of more complex microstructures. The use of high density complementary metal-oxide-semiconductor (CMOS) MEAs greatly increases the spatial resolution, enabling sub-cellular readout and stimulation of neurons in defined neural networks. Unfortunately, the non-planar surface of CMOS MEAs complicates the attachment of PDMS microstructures. To overcome the problem of axons escaping the microstructures through the ridges of the CMOS MEA, we stamp-transferred a thin film of hexane-diluted PDMS onto the array such that the PDMS filled the ridges at the contact surface of the microstructures without clogging the axon guidance channels. This method resulted in 23 % of structurally fully connected but sealed networks on the CMOS MEA of which about 45 % showed spiking activity in all channels. Moreover, we provide an impedance-based method to visualize the exact location of the microstructures on the MEA and show that our method can confine axonal growth within the PDMS microstructures. Finally, the high spatial resolution of the CMOS MEA enabled us to show that action potentials follow the unidirectional topology of our circular multi-node microstructure.
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Affiliation(s)
- Jens Duru
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Zürich, Switzerland
| | - Joël Küchler
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Zürich, Switzerland
| | - Stephan J. Ihle
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Zürich, Switzerland
| | - Csaba Forró
- Cui Laboratory, Stanford University, Stanford, CA, United States
| | - Aeneas Bernardi
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Zürich, Switzerland
| | - Sophie Girardin
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Zürich, Switzerland
| | - Julian Hengsteler
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Zürich, Switzerland
| | - Stephen Wheeler
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Zürich, Switzerland
| | - János Vörös
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Zürich, Switzerland
| | - Tobias Ruff
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Zürich, Switzerland
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23
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Lee SM, Lee JE, Lee YK, Yoo DA, Seon DB, Lee DW, Kim CB, Choi H, Lee KH. Thermal-Corrosion-Free Electrode-Integrated Cell Chip for Promotion of Electrically Stimulated Neurite Outgrowth. BIOCHIP JOURNAL 2022. [DOI: 10.1007/s13206-022-00049-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
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24
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Sala MR, Skalli O, Sabri F. Optimal structural and physical properties of aerogels for promoting robust neurite extension in vitro. MATERIALS SCIENCE & ENGINEERING. C, MATERIALS FOR BIOLOGICAL APPLICATIONS 2022; 135:112682. [DOI: 10.1016/j.msec.2022.112682] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Revised: 01/15/2022] [Accepted: 01/21/2022] [Indexed: 01/02/2023]
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25
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Kwon J, Lee JS, Lee J, Na J, Sung J, Lee HJ, Kwak H, Cheong E, Cho SW, Choi HJ. Vertical Nanowire Electrode Array for Enhanced Neurogenesis of Human Neural Stem Cells via Intracellular Electrical Stimulation. NANO LETTERS 2021; 21:6343-6351. [PMID: 33998792 DOI: 10.1021/acs.nanolett.0c04635] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Extracellular electrical stimulation (ES) can provide electrical potential from outside the cell membrane, but it is often ineffective due to interference from external factors such as culture medium resistance and membrane capacitance. To address this, we developed a vertical nanowire electrode array (VNEA) to directly provide intracellular electrical potential and current to cells through nanoelectrodes. Using this approach, the cell membrane resistivity and capacitance could be excluded, allowing effective ES. Human fetal neural stem cells (hfNSCs) were cultured on the VNEA for intracellular ES. Combining the structural properties of VNEA and VNEA-mediated ES, transient nanoscale perforation of the electrode was induced, promoting cell penetration and delivering current to the cell. Intracellular ES using VNEA improved the neuronal differentiation of hfNSCs more effectively than extracellular ES and facilitated electrophysiological functional maturation of hfNSCs because of the enhanced voltage-dependent ion-channel activity. The results demonstrate that VNEA with advanced nanoelectrodes serves as a highly effective culture and stimulation platform for stem-cell neurogenesis.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Seung-Woo Cho
- Center for Nanomedicine, Institute for Basic Science (IBS), Seoul 03722, Republic of Korea
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26
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Balch HB, McGuire AF, Horng J, Tsai HZ, Qi KK, Duh YS, Forrester PR, Crommie MF, Cui B, Wang F. Graphene Electric Field Sensor Enables Single Shot Label-Free Imaging of Bioelectric Potentials. NANO LETTERS 2021; 21:4944-4949. [PMID: 34102057 PMCID: PMC8510444 DOI: 10.1021/acs.nanolett.1c00543] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
The measurement of electrical activity across systems of excitable cells underlies current progress in neuroscience, cardiac pharmacology, and neurotechnology. However, bioelectricity spans orders of magnitude in intensity, space, and time, posing substantial technological challenges. The development of methods permitting network-scale recordings with high spatial resolution remains key to studies of electrogenic cells, emergent networks, and bioelectric computation. Here, we demonstrate single-shot and label-free imaging of extracellular potentials with high resolution across a wide field-of-view. The critically coupled waveguide-amplified graphene electric field (CAGE) sensor leverages the field-sensitive optical transitions in graphene to convert electric potentials into the optical regime. As a proof-of-concept, we use the CAGE sensor to detect native electrical activity from cardiac action potentials with tens-of-microns resolution, simultaneously map the propagation of these potentials at tissue-scale, and monitor their modification by pharmacological agents. This platform is robust, scalable, and compatible with existing microscopy techniques for multimodal correlative imaging.
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Affiliation(s)
- Halleh B Balch
- Department of Physics, University of California Berkeley, Berkeley, California 94720, United States
- Kavli Energy NanoSciences Institute at the University of California Berkeley and the Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
- Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Allister F McGuire
- Department of Chemistry, Stanford University, Stanford, California 94305, United States
| | - Jason Horng
- Department of Physics, University of California Berkeley, Berkeley, California 94720, United States
- Kavli Energy NanoSciences Institute at the University of California Berkeley and the Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
- Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Hsin-Zon Tsai
- Department of Physics, University of California Berkeley, Berkeley, California 94720, United States
| | - Kevin K Qi
- Department of Physics, University of California Berkeley, Berkeley, California 94720, United States
| | - Yi-Shiou Duh
- Department of Physics, University of California Berkeley, Berkeley, California 94720, United States
| | - Patrick R Forrester
- Department of Physics, University of California Berkeley, Berkeley, California 94720, United States
| | - Michael F Crommie
- Department of Physics, University of California Berkeley, Berkeley, California 94720, United States
- Kavli Energy NanoSciences Institute at the University of California Berkeley and the Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
- Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Bianxiao Cui
- Department of Chemistry, Stanford University, Stanford, California 94305, United States
| | - Feng Wang
- Department of Physics, University of California Berkeley, Berkeley, California 94720, United States
- Kavli Energy NanoSciences Institute at the University of California Berkeley and the Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
- Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
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27
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Corna A, Ramesh P, Jetter F, Lee MJ, Macke JH, Zeck G. Discrimination of simple objects decoded from the output of retinal ganglion cells upon sinusoidal electrical stimulation. J Neural Eng 2021; 18. [PMID: 34049288 DOI: 10.1088/1741-2552/ac0679] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Accepted: 05/28/2021] [Indexed: 11/12/2022]
Abstract
Objective. Most neuroprosthetic implants employ pulsatile square-wave electrical stimuli, which are significantly different from physiological inter-neuronal communication. In case of retinal neuroprosthetics, which use a certain type of pulsatile stimuli, reliable object and contrast discrimination by implanted blind patients remained challenging. Here we investigated to what extent simple objects can be discriminated from the output of retinal ganglion cells (RGCs) upon sinusoidal stimulation.Approach. Spatially confined objects were formed by different combinations of 1024 stimulating microelectrodes. The RGC activity in theex vivoretina of photoreceptor-degenerated mouse, of healthy mouse or of primate was recorded simultaneously using an interleaved recording microelectrode array implemented in a CMOS-based chip.Main results. We report that application of sinusoidal electrical stimuli (40 Hz) in epiretinal configuration instantaneously and reliably modulates the RGC activity in spatially confined areas at low stimulation threshold charge densities (40 nC mm-2). Classification of overlapping but spatially displaced objects (1° separation) was achieved by distinct spiking activity of selected RGCs. A classifier (regularized logistic regression) discriminated spatially displaced objects (size: 5.5° or 3.5°) with high accuracy (90% or 62%). Stimulation with low artificial contrast (10%) encoded by different stimulus amplitudes generated RGC activity, which was classified with an accuracy of 80% for large objects (5.5°).Significance. We conclude that time-continuous smooth-wave stimulation provides robust, localized neuronal activation in photoreceptor-degenerated retina, which may enable future artificial vision at high temporal, spatial and contrast resolution.
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Affiliation(s)
- Andrea Corna
- Neurophysics, NMI Natural and Medical Sciences Institute at the University Tübingen, Reutlingen, Germany.,Institute for Ophthalmic Research, University of Tübingen, Tübingen, Germany.,Graduate School of Neural Information Processing/International Max Planck Research School, Tübingen, Germany.,Biomedical Electronics and Systems, EMCE Institute, TU Wien, Wien, Austria
| | - Poornima Ramesh
- Computational Neuroengineering, Technical University München, München, Germany.,Machine Learning in Science, University of Tübingen, Tübingen, Germany
| | - Florian Jetter
- Neurophysics, NMI Natural and Medical Sciences Institute at the University Tübingen, Reutlingen, Germany.,Graduate School of Neural Information Processing/International Max Planck Research School, Tübingen, Germany
| | - Meng-Jung Lee
- Neurophysics, NMI Natural and Medical Sciences Institute at the University Tübingen, Reutlingen, Germany.,Graduate School of Neural Information Processing/International Max Planck Research School, Tübingen, Germany
| | - Jakob H Macke
- Computational Neuroengineering, Technical University München, München, Germany.,Machine Learning in Science, University of Tübingen, Tübingen, Germany.,MPI for Intelligent Systems, Tübingen, Germany
| | - Günther Zeck
- Neurophysics, NMI Natural and Medical Sciences Institute at the University Tübingen, Reutlingen, Germany.,Biomedical Electronics and Systems, EMCE Institute, TU Wien, Wien, Austria
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28
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Canna A, Lehto LJ, Wu L, Sang S, Laakso H, Ma J, Filip P, Zhang Y, Gröhn O, Esposito F, Chen CC, Lavrov I, Michaeli S, Mangia S. Brain fMRI during orientation selective epidural spinal cord stimulation. Sci Rep 2021; 11:5504. [PMID: 33750822 PMCID: PMC7943775 DOI: 10.1038/s41598-021-84873-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2020] [Accepted: 02/17/2021] [Indexed: 11/18/2022] Open
Abstract
Epidural spinal cord stimulation (ESCS) is widely used for chronic pain treatment, and is also a promising tool for restoring motor function after spinal cord injury. Despite significant positive impact of ESCS, currently available protocols provide limited specificity and efficiency partially due to the limited number of contacts of the leads and to the limited flexibility to vary the spatial distribution of the stimulation field in respect to the spinal cord. Recently, we introduced Orientation Selective (OS) stimulation strategies for deep brain stimulation, and demonstrated their selectivity in rats using functional MRI (fMRI). The method achieves orientation selectivity by controlling the main direction of the electric field gradients using individually driven channels. Here, we introduced a similar OS approach for ESCS, and demonstrated orientation dependent brain activations as detected by brain fMRI. The fMRI activation patterns during spinal cord stimulation demonstrated the complexity of brain networks stimulated by OS-ESCS paradigms, involving brain areas responsible for the transmission of the motor and sensory information. The OS approach may allow targeting ESCS to spinal fibers of different orientations, ultimately making stimulation less dependent on the precision of the electrode implantation.
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Affiliation(s)
- Antonietta Canna
- Center for Magnetic Resonance Research (CMRR), Department of Radiology, University of Minnesota, 2021 6th St. SE, Minneapolis, MN, 55455, USA.,Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Lauri J Lehto
- Center for Magnetic Resonance Research (CMRR), Department of Radiology, University of Minnesota, 2021 6th St. SE, Minneapolis, MN, 55455, USA
| | - Lin Wu
- Center for Magnetic Resonance Research (CMRR), Department of Radiology, University of Minnesota, 2021 6th St. SE, Minneapolis, MN, 55455, USA
| | - Sheng Sang
- Center for Magnetic Resonance Research (CMRR), Department of Radiology, University of Minnesota, 2021 6th St. SE, Minneapolis, MN, 55455, USA
| | - Hanne Laakso
- Center for Magnetic Resonance Research (CMRR), Department of Radiology, University of Minnesota, 2021 6th St. SE, Minneapolis, MN, 55455, USA.,A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Jun Ma
- Department of Neurosurgery, University of Minnesota, Minneapolis, MN, USA
| | - Pavel Filip
- Center for Magnetic Resonance Research (CMRR), Department of Radiology, University of Minnesota, 2021 6th St. SE, Minneapolis, MN, 55455, USA.,Department of Neurology, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Yuan Zhang
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Olli Gröhn
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Fabrizio Esposito
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Clark C Chen
- Department of Neurosurgery, University of Minnesota, Minneapolis, MN, USA
| | - Igor Lavrov
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, USA.,Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Shalom Michaeli
- Center for Magnetic Resonance Research (CMRR), Department of Radiology, University of Minnesota, 2021 6th St. SE, Minneapolis, MN, 55455, USA
| | - Silvia Mangia
- Center for Magnetic Resonance Research (CMRR), Department of Radiology, University of Minnesota, 2021 6th St. SE, Minneapolis, MN, 55455, USA.
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29
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Ronchi S, Buccino AP, Prack G, Kumar SS, Schröter M, Fiscella M, Hierlemann A. Electrophysiological Phenotype Characterization of Human iPSC-Derived Neuronal Cell Lines by Means of High-Density Microelectrode Arrays. Adv Biol (Weinh) 2021; 5:e2000223. [PMID: 33729694 PMCID: PMC7610355 DOI: 10.1002/adbi.202000223] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 11/30/2020] [Indexed: 12/11/2022]
Abstract
Recent advances in the field of cellular reprogramming have opened a route to studying the fundamental mechanisms underlying common neurological disorders. High-density microelectrode-arrays (HD-MEAs) provide unprecedented means to study neuronal physiology at different scales, ranging from network through single-neuron to subcellular features. In this work, HD-MEAs are used in vitro to characterize and compare human induced-pluripotent-stem-cell-derived dopaminergic and motor neurons, including isogenic neuronal lines modeling Parkinson's disease and amyotrophic lateral sclerosis. Reproducible electrophysiological network, single-cell and subcellular metrics are used for phenotype characterization and drug testing. Metrics, such as burst shape and axonal velocity, enable the distinction of healthy and diseased neurons. The HD-MEA metrics can also be used to detect the effects of dosing the drug retigabine to human motor neurons. Finally, it is shown that the ability to detect drug effects and the observed culture-to-culture variability critically depend on the number of available recording electrodes.
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Affiliation(s)
- Silvia Ronchi
- Department of Biosystems Science and Engineering, ETH Zürich, Mattenstrasse 26, Basel, 4058, Switzerland
| | - Alessio Paolo Buccino
- Department of Biosystems Science and Engineering, ETH Zürich, Mattenstrasse 26, Basel, 4058, Switzerland
| | - Gustavo Prack
- Department of Biosystems Science and Engineering, ETH Zürich, Mattenstrasse 26, Basel, 4058, Switzerland
| | - Sreedhar Saseendran Kumar
- Department of Biosystems Science and Engineering, ETH Zürich, Mattenstrasse 26, Basel, 4058, Switzerland
| | - Manuel Schröter
- Department of Biosystems Science and Engineering, ETH Zürich, Mattenstrasse 26, Basel, 4058, Switzerland
| | - Michele Fiscella
- Department of Biosystems Science and Engineering, ETH Zürich, Mattenstrasse 26, Basel, 4058, Switzerland
- MaxWell Biosystems AG, Albisriederstrasse 253, Zürich, 8047, Switzerland
| | - Andreas Hierlemann
- Department of Biosystems Science and Engineering, ETH Zürich, Mattenstrasse 26, Basel, 4058, Switzerland
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30
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Barbaglia A, Dipalo M, Melle G, Iachetta G, Deleye L, Hubarevich A, Toma A, Tantussi F, De Angelis F. Mirroring Action Potentials: Label-Free, Accurate, and Noninvasive Electrophysiological Recordings of Human-Derived Cardiomyocytes. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2021; 33:e2004234. [PMID: 33410191 DOI: 10.1002/adma.202004234] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2020] [Revised: 11/15/2020] [Indexed: 05/23/2023]
Abstract
The electrophysiological recording of action potentials in human cells is a long-sought objective due to its pivotal importance in many disciplines. Among the developed techniques, invasiveness remains a common issue, causing cytotoxicity or altering unpredictably cell physiological response. In this work, a new approach for recording intracellular signals of outstanding quality and with noninvasiveness is introduced. By taking profit of the concept of mirror charge in classical electrodynamics, the new proposed device transduces cell ionic currents into mirror charges in a microfluidic chamber, thus realizing a virtual mirror cell. By monitoring mirror charge dynamics, it is possible to effectively record the action potentials fired by the cells. Since there is no need for accessing or interacting with the cells, the method is intrinsically noninvasive. In addition, being based on optical recording, it shows high spatial resolution and high parallelization. As shown through a set of experiments, the presented methodology is an ideal candidate for the next generation devices for the reliable assessment of cardiotoxicity on human-derived cardiomyocytes. More generally, it paves the way toward a new family of in vitro biodevices that will lay a new milestone in the field of electrophysiology.
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Affiliation(s)
- Andrea Barbaglia
- Istituto Italiano di Tecnologia, Via Morego 30, Genova, 16163, Italy
| | - Michele Dipalo
- Istituto Italiano di Tecnologia, Via Morego 30, Genova, 16163, Italy
| | - Giovanni Melle
- Istituto Italiano di Tecnologia, Via Morego 30, Genova, 16163, Italy
| | | | - Lieselot Deleye
- Istituto Italiano di Tecnologia, Via Morego 30, Genova, 16163, Italy
| | | | - Andrea Toma
- Istituto Italiano di Tecnologia, Via Morego 30, Genova, 16163, Italy
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31
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Min S, Lee HJ, Jin Y, Kim YH, Sung J, Choi HJ, Cho SW. Biphasic Electrical Pulse by a Micropillar Electrode Array Enhances Maturation and Drug Response of Reprogrammed Cardiac Spheroids. NANO LETTERS 2020; 20:6947-6956. [PMID: 32877191 DOI: 10.1021/acs.nanolett.0c01141] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Direct reprogramming is an efficient strategy to produce cardiac lineage cells necessary for cardiac tissue engineering and drug testing for cardiac toxicity. However, functional maturation of reprogrammed cardiomyocytes, which is of great importance for their regenerative potential and drug response, still remains challenging. In this study, we propose a novel electrode platform to promote direct cardiac reprogramming and improve the functionality of reprogrammed cardiac cells. Nonviral cardiac reprogramming was improved via a three-dimensional spheroid culture of chemically induced cardiomyocytes exposed to a small-molecule cocktail. A micropillar electrode array providing biphasic electrical pulses mimicking the heartbeat further enhanced maturation and electrophysiological properties of reprogrammed cardiac spheroids, leading to proper responses and increased sensitivity to drugs. On the basis of our results, we conclude that our device may have a wider application in the generation of functional cardiac cells for regenerative medicine and screening of novel drugs.
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Affiliation(s)
- Sungjin Min
- Department of Biotechnology, Yonsei University, Seoul 03722, Republic of Korea
| | - Hyo-Jung Lee
- Department of Materials Science and Engineering, Yonsei University, Seoul 03722, Republic of Korea
| | - Yoonhee Jin
- Department of Biotechnology, Yonsei University, Seoul 03722, Republic of Korea
| | - Yu Heun Kim
- Department of Biotechnology, Yonsei University, Seoul 03722, Republic of Korea
| | - Jaesuk Sung
- Department of Materials Science and Engineering, Yonsei University, Seoul 03722, Republic of Korea
| | - Heon-Jin Choi
- Department of Materials Science and Engineering, Yonsei University, Seoul 03722, Republic of Korea
| | - Seung-Woo Cho
- Department of Biotechnology, Yonsei University, Seoul 03722, Republic of Korea
- Center for Nanomedicine, Institute for Basic Science (IBS), Seoul 03722, Republic of Korea
- Graduate Program of Nano Biomedical Engineering (NanoBME), Advanced Science Institute, Yonsei University, Seoul 03722, Republic of Korea
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32
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Gupta P, Balasubramaniam N, Chang HY, Tseng FG, Santra TS. A Single-Neuron: Current Trends and Future Prospects. Cells 2020; 9:E1528. [PMID: 32585883 PMCID: PMC7349798 DOI: 10.3390/cells9061528] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Revised: 06/15/2020] [Accepted: 06/19/2020] [Indexed: 12/11/2022] Open
Abstract
The brain is an intricate network with complex organizational principles facilitating a concerted communication between single-neurons, distinct neuron populations, and remote brain areas. The communication, technically referred to as connectivity, between single-neurons, is the center of many investigations aimed at elucidating pathophysiology, anatomical differences, and structural and functional features. In comparison with bulk analysis, single-neuron analysis can provide precise information about neurons or even sub-neuron level electrophysiology, anatomical differences, pathophysiology, structural and functional features, in addition to their communications with other neurons, and can promote essential information to understand the brain and its activity. This review highlights various single-neuron models and their behaviors, followed by different analysis methods. Again, to elucidate cellular dynamics in terms of electrophysiology at the single-neuron level, we emphasize in detail the role of single-neuron mapping and electrophysiological recording. We also elaborate on the recent development of single-neuron isolation, manipulation, and therapeutic progress using advanced micro/nanofluidic devices, as well as microinjection, electroporation, microelectrode array, optical transfection, optogenetic techniques. Further, the development in the field of artificial intelligence in relation to single-neurons is highlighted. The review concludes with between limitations and future prospects of single-neuron analyses.
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Affiliation(s)
- Pallavi Gupta
- Department of Engineering Design, Indian Institute of Technology Madras, Tamil Nadu 600036, India; (P.G.); (N.B.)
| | - Nandhini Balasubramaniam
- Department of Engineering Design, Indian Institute of Technology Madras, Tamil Nadu 600036, India; (P.G.); (N.B.)
| | - Hwan-You Chang
- Department of Medical Science, National Tsing Hua University, Hsinchu 30013, Taiwan;
| | - Fan-Gang Tseng
- Department of Engineering and System Science, National Tsing Hua University, Hsinchu 30013, Taiwan;
| | - Tuhin Subhra Santra
- Department of Engineering Design, Indian Institute of Technology Madras, Tamil Nadu 600036, India; (P.G.); (N.B.)
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Shirakawa T, Suzuki I. Approach to Neurotoxicity using Human iPSC Neurons: Consortium for Safety Assessment using Human iPS Cells. Curr Pharm Biotechnol 2020; 21:780-786. [DOI: 10.2174/1389201020666191129103730] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 10/27/2019] [Accepted: 11/03/2019] [Indexed: 01/05/2023]
Abstract
Neurotoxicity, as well as cardiotoxicity and hepatotoxicity, resulting from administration of
a test article is considered a major adverse effect both pre-clinically and clinically. Among the different
types of neurotoxicity occurring during the drug development process, seizure is one of the most serious
one. Seizure occurrence is usually assessed using in vivo animal models, the Functional Observational
Battery, the Irwin test or electroencephalograms. In in vitro studies, a number of assessments can
be performed using animal organs/cells. Interestingly, recent developments in stem cell biology, especially
the development of Human-Induced Pluripotent Stem (iPS) cells, are enabling the assessment of
neurotoxicity in human iPS cell-derived neurons. Further, a Multi-Electrode Array (MEA) using rodent
neurons is a useful tool for identifying seizure-inducing compounds. The Consortium for Safety Assessment
using Human iPS Cells (CSAHi; http://csahi.org/en/) was established in 2013 by the Japan
Pharmaceutical Manufacturers Association (JPMA) to verify the application of human iPS cell-derived
neuronal cells to drug safety evaluation. The Neuro Team of CSAHi has been attempting to evaluate the
seizure risk of compounds using the MEA platform. Here, we review the current status of neurotoxicity
and recent work, including problems related to the use of the MEA assay with human iPS neuronal
cell-derived neurons, and future developments.
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Affiliation(s)
- Takafumi Shirakawa
- Consortium for Safety Assessment using Human iPS Cells (CSAHi), Neuro Team, Japan
| | - Ikuro Suzuki
- Consortium for Safety Assessment using Human iPS Cells (CSAHi), Neuro Team, Japan
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GHz Ultrasonic Chip-Scale Device Induces Ion Channel Stimulation in Human Neural Cells. Sci Rep 2020; 10:3075. [PMID: 32080204 PMCID: PMC7033194 DOI: 10.1038/s41598-020-58133-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Accepted: 01/10/2020] [Indexed: 01/07/2023] Open
Abstract
Emergent trends in the device development for neural prosthetics have focused on establishing stimulus localization, improving longevity through immune compatibility, reducing energy re-quirements, and embedding active control in the devices. Ultrasound stimulation can single-handedly address several of these challenges. Ultrasonic stimulus of neurons has been studied extensively from 100 kHz to 10 MHz, with high penetration but less localization. In this paper, a chip-scale device consisting of piezoelectric Aluminum Nitride ultrasonic transducers was engineered to deliver gigahertz (GHz) ultrasonic stimulus to the human neural cells. These devices provide a path towards complementary metal oxide semiconductor (CMOS) integration towards fully controllable neural devices. At GHz frequencies, ultrasonic wavelengths in water are a few microns and have an absorption depth of 10-20 µm. This confinement of energy can be used to control stimulation volume within a single neuron. This paper is the first proof-of-concept study to demonstrate that GHz ultrasound can stimulate neurons in vitro. By utilizing optical calcium imaging, which records calcium ion flux indicating occurrence of an action potential, this paper demonstrates that an application of a nontoxic dosage of GHz ultrasonic waves [Formula: see text] caused an average normalized fluorescence intensity recordings >1.40 for the calcium transients. Electrical effects due to chip-scale ultrasound delivery was discounted as the sole mechanism in stimulation, with effects tested at α = 0.01 statistical significance amongst all intensities and con-trol groups. Ionic transients recorded optically were confirmed to be mediated by ion channels and experimental data suggests an insignificant thermal contributions to stimulation, with a predicted increase of 0.03 oC for [Formula: see text] This paper paves the experimental framework to further explore chip-scale axon and neuron specific neural stimulation, with future applications in neural prosthetics, chip scale neural engineering, and extensions to different tissue and cell types.
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Bullmann T, Radivojevic M, Huber ST, Deligkaris K, Hierlemann A, Frey U. Large-Scale Mapping of Axonal Arbors Using High-Density Microelectrode Arrays. Front Cell Neurosci 2019; 13:404. [PMID: 31555099 PMCID: PMC6742744 DOI: 10.3389/fncel.2019.00404] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2019] [Accepted: 08/20/2019] [Indexed: 12/30/2022] Open
Abstract
Understanding the role of axons in neuronal information processing is a fundamental task in neuroscience. Over the last years, sophisticated patch-clamp investigations have provided unexpected and exciting data on axonal phenomena and functioning, but there is still a need for methods to investigate full axonal arbors at sufficient throughput. Here, we present a new method for the simultaneous mapping of the axonal arbors of a large number of individual neurons, which relies on their extracellular signals that have been recorded with high-density microelectrode arrays (HD-MEAs). The segmentation of axons was performed based on the local correlation of extracellular signals. Comparison of the results with both, ground truth and receiver operator characteristics, shows that the new segmentation method outperforms previously used methods. Using a standard HD-MEA, we mapped the axonal arbors of 68 neurons in <6 h. The fully automated method can be extended to new generations of HD-MEAs with larger data output and is estimated to provide data of axonal arbors of thousands of neurons within recording sessions of a few hours.
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Affiliation(s)
- Torsten Bullmann
- RIKEN Quantitative Biology Center, RIKEN, Kobe, Japan.,Graduate School of Informatics, Kyoto University, Kyoto, Japan.,Carl Ludwig Institute for Physiology, University of Leipzig, Leipzig, Germany
| | - Milos Radivojevic
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | | | - Kosmas Deligkaris
- RIKEN Quantitative Biology Center, RIKEN, Kobe, Japan.,Graduate School of Frontier Biosciences, Osaka University, Osaka, Japan
| | - Andreas Hierlemann
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Urs Frey
- RIKEN Quantitative Biology Center, RIKEN, Kobe, Japan.,Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.,MaxWell Biosystems AG, Basel, Switzerland
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