Skip to main content

Main menu

  • HOME
  • CONTENT
    • Early Release
    • Featured
    • Current Issue
    • Issue Archive
    • Blog
    • Collections
    • Podcast
  • TOPICS
    • Cognition and Behavior
    • Development
    • Disorders of the Nervous System
    • History, Teaching and Public Awareness
    • Integrative Systems
    • Neuronal Excitability
    • Novel Tools and Methods
    • Sensory and Motor Systems
  • ALERTS
  • FOR AUTHORS
  • ABOUT
    • Overview
    • Editorial Board
    • For the Media
    • Privacy Policy
    • Contact Us
    • Feedback
  • SUBMIT

User menu

Search

  • Advanced search
eNeuro

eNeuro

Advanced Search

 

  • HOME
  • CONTENT
    • Early Release
    • Featured
    • Current Issue
    • Issue Archive
    • Blog
    • Collections
    • Podcast
  • TOPICS
    • Cognition and Behavior
    • Development
    • Disorders of the Nervous System
    • History, Teaching and Public Awareness
    • Integrative Systems
    • Neuronal Excitability
    • Novel Tools and Methods
    • Sensory and Motor Systems
  • ALERTS
  • FOR AUTHORS
  • ABOUT
    • Overview
    • Editorial Board
    • For the Media
    • Privacy Policy
    • Contact Us
    • Feedback
  • SUBMIT
PreviousNext
Research ArticleMethods/New Tools, Novel Tools and Methods

Multimodal Characterization of Neural Networks Using Highly Transparent Electrode Arrays

Mary J. Donahue, Attila Kaszas, Gergely F. Turi, Balázs Rózsa, Andrea Slézia, Ivo Vanzetta, Gergely Katona, Christophe Bernard, George G. Malliaras and Adam Williamson
eNeuro 21 December 2018, 5 (6) ENEURO.0187-18.2018; DOI: https://doi.org/10.1523/ENEURO.0187-18.2018
Mary J. Donahue
1Department of Bioelectronics, Ecole Nationale Supérieure des Mines, Centre of Microelectronics in Provence, Gardanne 13541, France
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Mary J. Donahue
Attila Kaszas
2Aix Marseille Univ, CNRS, INT, Inst Neurosci Timone, Marseille, France
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Attila Kaszas
Gergely F. Turi
3Department of Psychiatry, Division of Systems Neuroscience, Columbia University and Research Foundation for Mental Hygiene, New York State Psychiatric Institute, New York, NY 10032
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Gergely F. Turi
Balázs Rózsa
4Laboratory of 3D Functional Network and Dendritic Imaging, Institute of Experimental Medicine, Hungarian Academy of Sciences, Budapest H-1083, Hungary
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Andrea Slézia
5Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
6Neuroengineering Research Group, Interdisciplinary Excellence Center, Department of Medical Microbiology and Immunobiology, University of Szeged, Szeged 6720, Hungary
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Andrea Slézia
Ivo Vanzetta
2Aix Marseille Univ, CNRS, INT, Inst Neurosci Timone, Marseille, France
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Gergely Katona
7Two-Photon Measurement Technology Research Group, Pázmány Péter Catholic University, Budapest H-1083, Hungary
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Christophe Bernard
5Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Christophe Bernard
George G. Malliaras
8Electrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge CB3 0FA, United Kingdom
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for George G. Malliaras
Adam Williamson
5Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
6Neuroengineering Research Group, Interdisciplinary Excellence Center, Department of Medical Microbiology and Immunobiology, University of Szeged, Szeged 6720, Hungary
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Info & Metrics
  • eLetters
  • PDF
Loading

Visual Abstract

Figure
  • Download figure
  • Open in new tab
  • Download powerpoint

Abstract

Transparent and flexible materials are attractive for a wide range of emerging bioelectronic applications. These include neural interfacing devices for both recording and stimulation, where low electrochemical electrode impedance is valuable. Here the conducting polymer poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) is used to fabricate electrodes that are small enough to allow unencumbered optical access for imaging a large cell population with two-photon (2P) microscopy, yet provide low impedance for simultaneous high quality recordings of neural activity in vivo. To demonstrate this, pathophysiological activity was induced in the mouse cortex using 4-aminopyridine (4AP), and the resulting electrical activity was detected with the PEDOT:PSS-based probe while imaging calcium activity directly below the probe area. The induced calcium activity of the neuronal network as measured by the fluorescence change in the cells correlated well with the electrophysiological recordings from the cortical grid of PEDOT:PSS microelectrodes. Our approach provides a valuable vehicle for complementing classical high temporal resolution electrophysiological analysis with optical imaging.

  • electrophysiology
  • neuroengineering
  • organic electronics
  • PEDOT:PSS
  • transparent electronics
  • two-photon imaging

Significance Statement

Electrophysiological recordings, with varying degrees of invasiveness, are the traditional method for measuring neural activity, possessing the capability to measure both individual neurons and populations of neurons. Imaging methods, such as computed tomography scans and functional magnetic resonance imaging, have been developed to accomplish less invasive characterization of neuronal activity; traditionally offering good spatial or relatively high temporal resolution, yet resolution of individual neurons cannot be achieved. Two-photon (2P) imaging enables network-wide analysis with cellular resolution on a faster timescale with high spatial fidelity. This study presents a method for the combination of 2P imaging and electrophysiological recordings with highly transparent arrays of organic electrodes, presenting a powerful tool to simultaneously acquire the electrical and optical activity of neural circuits.

Introduction

Network-level brain functions result from the activity of large populations of neurons. Optical and electrophysiological techniques have been developed to interrogate the functions of the interconnected neurons within networks and to track the activity of as many individual neurons as possible. High-density neural probes for electrophysiological applications record hundreds of neurons simultaneously. This technique allows for the direct assessment of individual neuronal activity (firing of action potentials) as well as population activity of many neurons (field potentials; Buzsáki and Draguhn, 2004). The main disadvantage of electrophysiological recordings is poor spatial resolution (Taketani and Baudry, 2010). For example, implantable probe geometry does not allow the recording of all neurons belonging to one functional unit, such as a cortical column. Calcium (Ca2+) imaging records large populations of neurons with high spatial resolution, offering an option to overcome this disadvantage (Stosiek et al., 2003). The Ca2+ signal, however, is an indirect measure of cellular activity, thus it would be ideal to combine physiologic and optical techniques. To achieve this combination, the electrophysiological signal should be measured where the optical signal is obtained. This approach requires a highly transparent electrophysiological device to allow efficient collection of the optical signal. Although recent developments for this scenario have been demonstrated in vitro (Chang et al., 2011; Benfenati et al., 2013; Scott et al., 2013), the simultaneous acquisition of neural activity in vivo has remained a technical challenge.

Studies aiming to combine in vivo single cell electrophysiological recordings with 2P imaging use intracellular or extracellular glass electrodes (Helmchen et al., 2001; Svoboda and Yasuda, 2006; Kitamura et al., 2008) employing a Ag/AgCl electrode to close the recording circuit. Alternatively, a metal electrode may be chronically implanted in the contralateral hemisphere, while the image collection is conducted at physical distance (Malvache et al., 2016), a method which assumes high correlation between the two recording sites. These methods have limitations including use of delicate recording pipettes, limited number of recording sites and the necessity to locate the metal parts of the electrode outside the field of view as it is prone to generate noise due to the photoelectric effect (Kozai and Vazquez, 2015). Flexible materials and micro-fabrication techniques have been explored over recent years to solve the former two limitations. The photoelectric effect, however, complicates the simultaneous use of optical and electrophysiological signal recording for a great deal of materials and engineering approaches. An in vitro study by Kuzum et al. (2014) well demonstrated the possibility to image hippocampal slices using confocal and 2P techniques through a flexible graphene electrode array, benefitting from the high-transparency of the electrode material and interconnecting lines. The used Kapton substrate, however, somewhat hinders the overall optical transparency and the 50 × 50 µm electrode surface has high electrochemical impedance (∼500 kΩ at 1 kHz), the main requirement for capturing high-quality electrophysiological signals (Franks et al., 2005; Williams et al., 2007). In a separate study on flexible graphene electrodes, a high level of transparency was exhibited by Park et al. (2014) using a parylene C (PaC) substrate. Fluorescence imaging through the array was possible in vivo, as well as electrophysiological signal recording and optogenetic stimulation of the underlying tissue, however, relatively large electrodes are used (∼150 µm in diameter) with 1-kHz impedance values reduced only to ∼250 kΩ. Recent work has pushed toward improved technologies offering in vivo electrophysiology and optical recording capabilities. These reports include arrays of 100 × 100 µm graphene electrodes (963-kΩ average impedance) with high transparency (Thunemann et al., 2018) as well as a study by Qiang et al. (2018) using a gold nano-mesh patterning technique, creating electrodes with diameters down to 20 µm with an average 1-kHz impedance value of 130.3 kΩ, employing a similar material system to ours. Main differences include: insulation material (SU8 vs PaC), overall higher electrode impedance (∼5×) and device thickness (∼4×), but improved transparency at the mesh’s conduction lines and recording sites.

In this report, we demonstrate an extremely flexible (∼4-µm-thick) cortical microelectrode array (25 × 25 µm electrode size), with moderate channel density deposited on an optically transparent PaC substrate. The high overall transparency in combination with low impedance values (∼25 kΩ at 1 kHz) enables electrophysiological and optical recordings from the same location. To achieve low impedance, we employ the well-known ionic/electronic conducting polymer poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS). PEDOT:PSS is applied at the electrode sites, efficiently reducing the impedance and allowing for minimization of the contact lines and electrode area. With this approach, unobstructed imaging may be performed through >95% of the substrate area intended for optical and electrical measurement. The micron-scale organic electrode grid maximizes the overall optical transparency and allows for simultaneous 2P imaging of the underlying tissue.

Materials and Methods

Device fabrication

The organic electrode grid fabrication process is based on previously reported methods (Khodagholy et al., 2013, Sessolo et al., 2013). An initial PaC film was deposited on glass slides using a SCS Labcoater 2 with a resulting thickness of 2 µm. Once the subsequent fabrication steps are completed, this PaC layer is delaminated from the glass, thus acting as the final substrate and providing the flexibility for the Electrocorticography (ECoG) array. Photolithography and lift-off processes were employed to pattern metal interconnects on top of the PaC substrate. This was performed using a positive photoresist (Shipley MICROPOSIT™ S1813), a SUSS MJB4 UV broadband contact aligner and MF26 developer. A 2-nm chromium adhesion promoting layer and 100 nm of gold were thermally evaporated onto the substrates and the samples were immersed in an acetone bath to define the interconnects through lift-off. To electrically insulate the metal lines, a second PaC film was deposited on the devices to thicknesses of 2 µm, using the same deposition process as before, however with 3-(trimethoxysilyl)propylmethacrylate present in the chamber (by addition of a droplet to the chamber wall) to act as an adhesion promoter. Subsequently, a dilute solution of Micro-90 industrial cleaner was spin coated onto this insulation layer, followed by the deposition of a sacrificial PaC layer (2 µm). These steps allow the sacrificial layer to later be peeled off from the substrate, defining PEDOT:PSS at the electrode recording sites. The PaC layers were etched by reactive ion etching (RIE) in an Oxford 80 Plasmalab plus with an O2/CHF3 plasma to open the electrode sites by creating an opening down to the gold interconnect. AZ9260 photoresist was used as an etch mask, patterned using the UV contact aligner and AZ developer. A dispersion of PEDOT:PSS (CleviosTM PH 1000 from Heraeus Holding GmbH), 5 volume % ethylene glycol, 0.1 volume % dodecyl benzene sulfonic acid, and 1 wt % of (3-glycidyloxypropyl)-trimethoxysilane was spin coated onto the substrates to attain a thickness of 200 nm. The sacrificial PaC layer was peeled off removing superfluous PEDOT:PSS and defining the electrode sites. The devices were baked for 1 h at 140°C to crosslink the film. Finally, the devices were immersed in deionized water (DIW) to remove low molecular weight compounds. This DIW soak also facilitates the delamination of the final flexible electrode array from the glass slide.

Electrophysiological signal acquisition and processing

Neural data were recorded using a RHD2132 Intan technology amplifier board. Zero insertion force clips (ZIF-Clip) were used to connect directly to the ECoG devices, along with an adaptor chip to connect to the Intan technology head stage. A sampling rate of 20 kHz was used and data were stored in 16-bit format. Data analysis was conducted using MATLAB (MathWorks). A 400 Hz low pass filter was applied to the acquired signal.

Surgical procedure

Transgenic Thy1-GCaMP6f mice (Dana et al., 2014) with neurons expressing a fluorescent calcium indicator (14–16 weeks old, three males) were housed according to institutional regulations in the animal facilities of corresponding universities. On the day of surgery, animals were sedated with 2% isoflurane, then fixed in a stereotactic frame and kept under 4% sevoflurane anesthesia. After a subcutaneous lidocaine injection, the skull was exposed and a cranial window (4 mm in diameter) was drilled above the somatosensory cortex. A head plate was mounted onto the skull by dental acrylic, and the animal was placed into the microscope setup using the head plate. The temperature of the mouse was monitored and controlled using a rectal probe and heated mouse pad set to 38°C. During the recording procedure the anesthesia was maintained with a 1.2% isoflurane and oxygen mixture. The surface probe was positioned onto the craniotomy and covered with artificial cerebrospinal fluid, containing: 124 mM NaCl, 26 mM NaHCO3, 3.5 mM KCl, 1 mM MgCl2, 1 mM CaCl2, and 10 mM D-glucose. A coverslip was gently placed on top of the surface probe, and a tile map was acquired by an infrared CCD camera through a 4× objective. 4-Aminopyridine (4AP) was used to evoke seizure-like activity in the cortex. The drug was pressure injected via a glass pipette containing 50 mM 4AP with 20 µM Alexa Fluor 594 as a red dye for marking the injection site. The drug injection was positioned underneath both the cover glass and the probe ∼500 µm away from the imaging field of view, at a depth of 500 µm, using a micromanipulator (PatchStar, Scientifica). All procedures were approved by the Aix-Marseille Université ethical committee and were in accordance with guidelines of the corresponding institutes.

2P imaging

At the beginning of the experiments, a reference z-stack of the volume was acquired on a dual-scanhead 2P microscope (FemtoS-Dual, Femtonics Ltd) equipped with a femtosecond pulsed laser tuned to 920 nm (Mai Tai HP, SpectraPhysics) using a Nikon LWD 16x/0.8 NA objective. A single acquisition plane was selected and full-frame imaging was started in resonant scanning mode at 30.9375 Hz. The control of imaging and the trigger of electrophysiological recordings was done using the microscope’s acquisition software (MESc). We used the MESc and the MES software packages (Femtonics Ltd) to analyze imaging data (Katona et al., 2012).

Results

The developed organic electrode device, produced through the microfabrication steps described in the Materials and Methods section, is presented in Figure 1. Figure 1A shows the schematic outline of the fabrication process. The dashed line in Figure 1B corresponds to the cross-sectional area shown in Figure 1A. Optical images of the resulting grid of organic electrodes are given in Figure 1B,C. Overall, the micro-electrode grid consists of gold lines and 16 PEDOT:PSS recording sites patterned on a flexible PaC substrate. The interconnects are insulated using a secondary layer of PaC, resulting in a thin (∼4 µm) overall final device, extremely conformable to the surface of the brain. Openings etched in a third sacrificial layer of PaC (and through the insulation layer) are used to selectively pattern PEDOT:PSS to the desired electrode sites through a previously developed peel-off method (Khodagholy et al., 2013; Sessolo et al., 2013). Figure 1B shows the resulting 16-electrode array patterned on a 2.5-mm diameter PaC substrate area. Each electrode recording site is 25 × 25 µm, with an interelectrode spacing of 400 µm. A close-up view of a representative area indicated in blue is shown in Figure 1C, with the conducting polymer coating visible on four electrode sites. A scanning electrode microscope (SEM) image of the entire eletrode array is shown in Figure 1D, with a zoomed-in view of one electrode in the inset. Utilization of PEDOT:PSS at the recording sites is integral for this probe, making it possible to maintain low electrochemical electrode impedance. The 1-kHz impedance values of 64 electrodes from four devices are shown in Figure 1F, all below 50 kΩ with an average impedance of 25.8 kΩ; a value very well suited for electrophysiological recordings. The possibility to attain this impedance range with electrodes and interconnects on the tens of micrometers range allows for maximizing the area of transparent substrate which can be used for imaging. The transparency facilitates straightforward alignment and orientation of the array with biological structures below the grid. Figure 1E demonstrates these features, with the electrode grid placed on one eye of a Lego toy figure.

Figure 1.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 1.

Organic cortical electrode grid. A, Cross-sectional schematic of the microfabrication process corresponding to the area in B indicated by the red dotted line. Note: illustrative view is not to scale B, Top view of the electrode array. C, Microscopic image of individual organic PEDOT:PSS electrode sites in the area of the array indicated by the blue square in B. D, Scanning electron microscope image of the full ECoG array with a zoomed-in view of one recording site in the inset. E, Eye of a Lego toy clearly visible through the device (transparent area intended for imaging centered on the eye; note the bundle of contact lines visible extending to the left of the toy). F, Histogram of 64 electrode impedances from four devices at 1 kHz with an example electrochemical impedance spectrum in the inset.

As seen in Figure 2, the implemented grid of electrodes with 16 recording sites is placed on the surface of the cortex, directly in the path of the 2P scan. This provides multiple sites for electrophysiological measurements during 2P calcium imaging, representing a significant advantage over a single electrophysiological recording site of a glass pipette. Figure 2A,B shows the layout of the experimental setup. The anesthetized mouse was head-fixed in the 2P setup and the grid of organic electrodes was placed over the visual cortex. The flexibility of the organic electrodes and the substrate allows for continuous contact with the brain surface, ensuring a good electrochemical interface between the tissue and the probe. The surface probe was covered with a glass cranial window carefully aligned to leave ample space for an entry point of a glass injection pipette used to deliver 4-AP (50 mM), a well-known method to induce epileptiform activity (Voskuyl and Albus, 1985; Szente and Baranyi, 1987; Avoli et al., 2002). During 2P imaging sessions, the emitted green fluorescence of the neuronal calcium indicator under the flexible grid was recorded simultaneously with the electrophysiological activity (Fig. 3).

Figure 2.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 2.

Layout of the recording setup with 2P-compatible electrode array. Head-fixed, anesthetized animal under the 2P microscope with the grid of organic electrodes in place, monitoring electrophysiological activity of the cortex. A, Photo of anesthetized animal’s headplate with the probe positioned on the cortex under the objective. B, The infrared laser beam (pseudo-color red) can pass through the grid of organic electrodes, as well as the subsequent visible emitted fluorescence, measured at a depth of up to 1mm into the tissue, monitoring activity across the entire scanned plane (blue). Cortical electrophysiological recordings are then compared to the calcium signal measured by the 2P system for dual characterization of the neural network activity.

Figure 3.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 3.

Simultaneous in vivo 2P imaging and cortical electrophysiological recording. A, Infrared camera picture montage of the flexible 16-channel cortical electrode array positioned in a craniotomy above the primary visual cortex of a Thy1-GCaMP6f mouse. B, Average image of 60 frames from a 2P time sequence measurement of GCaMP6f (green) and Alexa Fluor 594 (red) labeling. The selected cells (n = 63, white circles) were located 200 µm below the cortical surface. Electrode locations in this area are indicated. C, LFP recordings from channels depicted in A. D, E, Simultaneous LFP recording (D, left) and calcium imaging (E, left) from single cells (gray) and the average (black) of interictal and ictal periods evoked by 50 mM 4-AP injection. Right panels, Corresponding continuous 1-D wavelet transform analysis. F, G, Zoomed-in view of ictal events on LFP (F, left) and calcium traces (G, left) for single cells (G, gray) or the population average (G, black). Right panels, Corresponding continuous 1-D wavelet transform analysis.

The orientation of the flexible grid of organic electrodes on the surface of the cortex is shown in Figure 3A. The inset of Figure 3A and zoomed view in Figure 3B show the average of 60 frames from a 2P time sequence measurement, imaged through the electrode grid 200 µm below the cortical surface. Neurons here expressed GCaMP6f (green) as a calcium indicator, while Alexa Fluor 594 (red) labeling as a fluorescent marker was used to follow the spread of the 4-AP solution after injection. While Figure 3A numbers all available electrode sites used for recording, the numbering indicated in Figure 3B shows those electrodes that were located in the 2P field-of-view. Electrophysiological local field potential (LFP) recordings for nearby electrodes are shown in Figure 3C, with a zoomed view of electrode 4 in Figure 3D, as this electrode is the most relevant regarding spatial proximity. The data represent an example of seizure activity within the tissue induced by an injection of 50 mM 4-AP (injection pipette shown in Fig. 3A). The LFP recording of electrode 4 is compared with 2P calcium imaging data in Figure 3D–G. Fluorescence changes, arising from fluctuations in intracellular calcium concentrations (Fig. 3E, left), clearly correspond to the simultaneously recorded electrophysiological fluctuations (Fig. 3D, left). Calcium imaging data are shown for single cells (gray, n = 63) as well as the average of the population response (black). Figure 3D,E, right panels, shows the corresponding continuous 1-D wavelet transform analysis, for the frequency analysis of the average responses. Figure 3F,G presents a zoomed-in view of the area indicated in red in Figure 3D,E. On this timescale ictal events on LFP (Fig. 3F) and calcium traces (Fig. 3G) for both single cells (gray traces) and the population average (black trace) are also very well correlated. These measurements demonstrate the simultaneous monitoring of neural activity both optically and electrically, and open further possibilities for a wide variety of studies to be explored in the future.

Discussion

The aim of this work was to demonstrate the feasibility to record optical and electrophysiological signals for the same site simultaneously in vivo. Previously, this has been problematic due to the highly reflective inorganic materials used to create electrodes and the photoelectric effect caused by the laser light beam at conduction lines and recording sites. We minimized these issues by making use of an organic array of electrodes on an optically transparent substrate. To accomplish this, a low impedance PEDOT:PSS-based microelectrode array was developed (Fig. 1) to ensure that a high level (>95%) of the area of interest remains unobstructed for laser scanning, allowing for simultaneous fluorescence signal collection through 2P microscopy (Fig. 2). The mixed conduction PEDOT:PSS material system has received a great deal of attention due to its excellent electronic and mechanical properties, and the resulting practicality and commercial availability (Elschner et al., 2011). The material flexibility is an additional benefit, providing excellent contact with the cortical surface and reduced invasiveness compared to traditionally stiffer implantable devices (Khodagholy et al., 2015).

Over the past decades, neural interfacing systems using various types of transparent and flexible materials have increased in number (Stieglitz et al., 1997; Rodger et al., 2008; Ledochowitsch et al., 2011). To meet the needs of a wide-range of applications, there have been significant advances in graphene/carbon-based neural probes (David-Pur et al., 2013; Du et al., 2015) as well as those based on conjugated polymer systems (Mercanzini et al., 2008; Khodagholy et al., 2016). The advantages of PEDOT:PSS in neural interfacing studies have been previously demonstrated as well, showing improvement in recording quality while reducing tissue reactions (Khodagholy et al., 2011; Someya et al., 2016; Williamson et al., 2015). This mixed conduction material system has received a great deal of attention due to its excellent electronic and mechanical properties, and the resulting practicality and commercial availability (Elschner et al., 2011).Additionally, as a result of the success of PEDOT:PSS, a great deal of research has gone into understanding this polymer system and optimizing its mechanical and electrical properties (Crispin et al., 2006; Martin et al., 2010; Proctor et al., 2016; Rivnay et al., 2016). The progress made in this area to date is significant for the field of bioelectronics (Rivnay et al., 2014). Making use of the development and optimization of PEDOT:PSS, electrodes of very small size can be engineered, while retaining low electrochemical impedance and thus maintaining excellent neural recording ability. These properties were taken advantage of here to enable simultaneous optical and electrical characterization of neural networks.

In this study, we were able to show seizure events with electrophysiological recordings and the corresponding optical signals form many neurons (Fig. 3). Comparison was made between optical data that were recorded from the same location as the PEDOT:PSS electrode used to obtain the electrical recording, i.e., Figure 3A,B. The simultaneous electrophysiological and optical recording strategy could be employed in future applications to extrapolate seizure foci in pathophysiological networks and, using readily available transgenic animals, to identify the exact neuronal cell types behind the pathologic activity using imaging in vivo. Moreover, because of the high scalability of this approach, it will be useful to investigate healthy physiologic systems. The size and shape of the of the overall grid are extremely adjustable and may be easily altered depending on the targeted application. In addition, the density of electrode sites may be adapted to optimize recording from specific brain regions. For example, the design and implementation of a grid that could cover the entire visual cortex, or simply particular sub-regions, is straightforward. Whereas previous studies have used relatively large electrode surfaces (on the scale of 50 to several hundred micrometers; Kuzum et al., 2014; Lu et al., 2016), micro-fabricated PEDOT:PSS electrodes easily allow for reduced electrode size to the 10-µm scale while keeping the impedance in the biologically relevant/desired range. Furthermore, although the metal contact lines will become problematic at very high site densities as a result of optical path obstruction and the photoelectric effect, the possibility to stack conduction lines vertically using these materials (Donahue et al., 2017) may be employed to increase site density while retaining high transparency. In addition to the low impedance of PEDOT:PSS electrode sites, which maintains the recording capability for biological signals, these sites can also be used for electrical stimulation (Wilks et al., 2009; Williamson et al., 2015). It could therefore be conceivable to take the advantage of this option of the micro-grid and combine local stimulation with simultaneous 2P imaging to assess signal propagation in neuronal networks. Lastly, as PEDOT:PSS electrodes have demonstrated good biocompatibility (Berggren and Richter-Dahlfors, 2007) as well as the ability to retain recording capability from weeks up to multiple months in vivo (Khodagholy et al., 2015; Kozai et al., 2016), this type of probe could also be employed for chronic implantation.

In summary, the present work demonstrates a novel method to perform classical electrophysiology recordings using a state-of-the-art microelectrode array along with 2P imaging of network activity in vivo. Initial results demonstrate good correlation of induced pathologic activity using this dual characterization method, providing the best of the two methods: high spatial resolution from 2P imaging combined with high temporal resolution of the multielectrode array. This approach may be developed further to include depth electrodes to simultaneously capture electrophysiological and 2P measurements of single-cell activity across networks.

Footnotes

  • G.K. and B.R. are owners of Femtonics and the patent WO2010076579. All other authors declare no competing financial interests.

  • This work was supported by the European Research Council (ERC) under the European Union’s Horizon 2020 Research and Innovation Programme (Grant 716867). A.K. was supported by EC Marie Curie Intra-European Fellowship (ImagINE, Grant 625372). M.J.D. was supported by the Fondation pour la Recherche Médicale Grant DBS20131128446. B.R. and K.G. were supported by ERC682426, KFI-2016-0177, GINOP-2016-00979, and NVKP-2016-0043.

This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license, which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.

References

  1. ↵
    Avoli M, D’Antuono M, Louvel J, Köhling R, Biagini G, Pumain R, D’Arcangelo G, Tancredi V (2002) Network and pharmacological mechanisms leading to epileptiform synchronization in the limbic system in vitro. Prog Neurobiol 68:167–207. doi:10.1016/S0301-0082(02)00077-1
    OpenUrlCrossRefPubMed
  2. ↵
    Benfenati V, Toffanin S, Bonetti S, Turatti G, Pistone A, Chiappalone M, Sagnella A, Stefani A, Generali G, Ruani G, Saguatti D, Zamboni R, Muccini M (2013) A transparent organic transistor structure for bidirectional stimulation and recording of primary neurons. Nat Mater 12:672–680. doi:10.1038/nmat3630
    OpenUrlCrossRef
  3. ↵
    Berggren M, Richter-Dahlfors A (2007) Organic bioelectronics. Adv Mater 19:3201–3213. doi:10.1002/adma.200700419
    OpenUrlCrossRef
  4. ↵
    Buzsáki G, Draguhn A (2004) Neuronal oscillations in cortical networks. Science 304:1926–1929. doi:10.1126/science.1099745 pmid:15218136
    OpenUrlAbstract/FREE Full Text
  5. ↵
    Chang WP, Wu JS, Lee CM, Vogt BA, Shyu BC (2011) Spatiotemporal organization and thalamic modulation of seizures in the mouse medial thalamic‐anterior cingulate slice. Epilepsia 52:2344–2355. doi:10.1111/j.1528-1167.2011.03312.x
    OpenUrlCrossRef
  6. ↵
    Crispin X, Jakobsson FLE, Crispin A, Grim PCM, Andersson P, Volodin A, van Haesendonck C, Van der Auweraer M, Salaneck WR, Berggren M (2006) The origin of the high conductivity of poly(3,4-ethylenedioxythiophene)−poly(styrenesulfonate) (PEDOT−PSS) plastic electrodes. Chem Mater 18:4354–4360. doi:10.1021/cm061032+
    OpenUrlCrossRef
  7. ↵
    Dana H, Chen TW, Hu A, Shields BC, Guo C, Looger LL, Kim DS, Svoboda K (2014) Thy1-GCaMP6 transgenic mice for neuronal population imaging in vivo. PloS one. 9:e108697. doi:10.1371/journal.pone.0108697 pmid:25250714
    OpenUrlCrossRefPubMed
  8. ↵
    David-Pur M, Bareket-Keren L, Beit-Yaakov G, Raz-Prag D, Hanein Y (2013) All-carbon-nanotube flexible multi-electrode array for neuronal recording and stimulation. Biomed Microdevices 16:43–53. doi:10.1007/s10544-013-9804-6
    OpenUrlCrossRef
  9. ↵
    Donahue MJ, Williamson A, Strakosas X, Friedlein JT, McLeod RR, Gleskova H, Malliaras GG (2017) High-Performance Vertical Organic Electrochemical Transistors. Adv Mater 30:1705031. doi:10.1002/adma.201705031
    OpenUrlCrossRef
  10. ↵
    Du X, Wu L, Cheng J, Huang S, Cai Q, Jin Q, Zhao J (2015) Graphene microelectrode arrays for neural activity detection. J Biol Phys 41:339–347. doi:10.1007/s10867-015-9382-3
    OpenUrlCrossRef
  11. ↵
    Elschner A, Kirchmeyer S, Lovenich W, Merker U, Reuter K (2011) PEDOT: principles and applications of an intrinsically conductive polymer. Boca Raton, FL: CRC Press.
  12. ↵
    Franks W, Schenker I, Schmutz P, Hierlemann A (2005) Impedance characterization and modeling of electrodes for biomedical applications. IEEE Trans Biomed Eng 52:1295–1302. doi:10.1109/TBME.2005.847523
    OpenUrlCrossRefPubMed
  13. ↵
    Helmchen F, Fee MS, Tank DW, Denk W (2001) A miniature head-mounted two-photon microscope. high-resolution brain imaging in freely moving animals. Neuron 31:903–912. doi:10.1016/S0896-6273(01)00421-4
    OpenUrlCrossRefPubMed
  14. ↵
    Katona G, Szalay G, Maák P, Kaszás A, Veress M, Hillier D, Chiovini B, Vizi ES, Roska B, Rózsa B (2012) Fast two-photon in vivo imaging with three-dimensional random-access scanning in large tissue volumes. Nat Methods 9:201–208. doi:10.1038/nmeth.1851
    OpenUrlCrossRefPubMed
  15. ↵
    Khodagholy D, Doublet T, Gurfinkel M, Quilichini P, Ismailova E, Leleux P, Herve T, Sanaur S, Bernard C, Malliaras GG (2011) Highly conformable conducting polymer electrodes for in vivo recordings. Adv Mater 23:268–272. doi:10.1002/adma.201102378 pmid:21826747
    OpenUrlCrossRefPubMed
  16. ↵
    Khodagholy D, Doublet T, Quilichini P, Gurfinkel M, Leleux P, Ghestem A, Ghestem A, Ismailova E, Hervé T, Sanaur S, Bernard C, Malliaras GG (2013) In vivo recordings of brain activity using organic transistors. Nat Commun 4:1575. doi:10.1038/ncomms2573 pmid:23481383
    OpenUrlCrossRefPubMed
  17. ↵
    Khodagholy D, Gelinas JN, Thesen T, Doyle W, Devinsky O, Malliaras GG, Buzsáki G (2015) NeuroGrid: recording action potentials from the surface of the brain. Nat Neurosci 18:310–315. doi:10.1038/nn.3905
    OpenUrlCrossRefPubMed
  18. ↵
    Khodagholy D, Gelinas JN, Zhao Z, Yeh M, Long M, Greenlee JD, Doyle W, Devinsky O, Buzsáki G (2016) Organic electronics for high-resolution electrocorticography of the human brain. Sci Adv 2:e1601027. doi:10.1126/sciadv.1601027
    OpenUrlFREE Full Text
  19. ↵
    Kitamura K, Judkewitz B, Kano M, Denk W, Häusser M (2008) Targeted patch-clamp recordings and single-cell electroporation of unlabeled neurons in vivo. Nat Methods 5:61–67. doi:10.1038/nmeth1150
    OpenUrlCrossRefPubMed
  20. ↵
    Kozai TDY, Vazquez AL (2015) Photoelectric artefact from optogenetics and imaging on microelectrodes and bioelectronics: new challenges and opportunities. J Mater Chem B 3:4965–4978. doi:10.1039/C5TB00108K
    OpenUrlCrossRefPubMed
  21. ↵
    Kozai TDY, Catt K, Du Z, Na K, Srivannavit O, Haque R-uM, Seymour J, Wise KD, Yoon E, Cui XT (2016) Chronic in vivo evaluation of PEDOT/CNT for stable neural recordings. IEEE Trans Biomed Eng 63:111–119. doi:10.1109/TBME.2015.2445713
    OpenUrlCrossRefPubMed
  22. ↵
    Kuzum D, Takano H, Shim E, Reed JC, Juul H, Richardson AG, De Vries J, Bink H, Dichter MA, Lucas TH, Coulter DA, Cubukcu E, Litt B (2014) Transparent and flexible low noise graphene electrodes for simultaneous electrophysiology and neuroimaging. Nat Commun 5:5259. doi:10.1038/ncomms6259 pmid:25327632
    OpenUrlCrossRefPubMed
  23. ↵
    Ledochowitsch P, Olivero E, Blanche T, Maharbiz MM (2011) A transparent μECoG array for simultaneous recording and optogenetic stimulation . Conf Proc IEEE Eng Med Biol Soc 2011:2937–2940. doi:10.1109/iembs.2011.6090808 pmid:22254956
    OpenUrlCrossRefPubMed
  24. ↵
    Lu Y, Lyu H, Richardson AG, Lucas TH, Kuzum D (2016) Flexible neural electrode array based-on porous graphene for cortical microstimulation and sensing. Sci Rep 6. 33526. doi:10.1038/srep33526
    OpenUrlCrossRef
  25. ↵
    Malvache A, Reichinnek S, Villette V, Haimerl C, Cossart R (2016) Awake hippocampal reactivations project onto orthogonal neuronal assemblies. Science 353:1280–1283. doi:10.1126/science.aaf3319 pmid:27634534
    OpenUrlAbstract/FREE Full Text
  26. ↵
    Martin DC, Wu J, Shaw CM, King Z, Spanninga SA, Richardson-Burns S, Hendricks J, Yang J (2010) The morphology of poly(3,4-ethylenedioxythiophene). Polym Rev 50:340–384. doi:10.1080/15583724.2010.495440
    OpenUrlCrossRef
  27. ↵
    Mercanzini A, Cheung K, Buhl DL, Boers M, Maillard A, Colin P, Bensadoun JC, Bertsch A, Renaud P (2008) Demonstration of cortical recording using novel flexible polymer neural probes. Sens Actuators A Phys 143:90–96. doi:10.1016/j.sna.2007.07.027
    OpenUrlCrossRef
  28. ↵
    Park DW, Schendel AA, Mikael S, Brodnick SK, Richner TJ, Ness JP, Hayat MR, Atry F, Frye ST, Pashaie R, Thongpang S, Ma Z, Williams JC (2014) Graphene-based carbon-layered electrode array technology for neural imaging and optogenetic applications. Nat Commun 5:5258. doi:10.1038/ncomms6258 pmid:25327513
    OpenUrlCrossRefPubMed
  29. ↵
    Proctor CM, Rivnay J, Malliaras GG (2016) Understanding volumetric capacitance in conducting polymers. J Polym Sci B Polym Phys 54:1433–1436. doi:10.1002/polb.24038
    OpenUrlCrossRef
  30. ↵
    Qiang Y, Artoni P, Seo KJ, Culaclii S, Hogan V, Zhao X, Zhong Y, Han X, Wang PM, Lo YK, Li Y, Patel HA, Huang Y, Sambangi A, Chu JSV, Liu W, Fagiolini M, Fang H (2018) Transparent arrays of bilayer-nanomesh microelectrodes for simultaneous electrophysiology and two-photon imaging in the brain. Sci Adv 4:eaat0626. doi:10.1126/sciadv.aat0626 pmid:30191176
    OpenUrlFREE Full Text
  31. ↵
    Rivnay J, Owens RM, Malliaras GG (2014) The rise of organic bioelectronics. Chem Mater 26:679–685. doi:10.1021/cm4022003
    OpenUrlCrossRef
  32. ↵
    Rivnay J, Inal S, Collins BA, Sessolo M, Stavrinidou E, Strakosas X, Tassone C, Delongchamp DM, Malliaras GG (2016) Structural control of mixed ionic and electronic transport in conducting polymers. Nat Commun 7:11287. doi:10.1038/ncomms11287
    OpenUrlCrossRefPubMed
  33. ↵
    Rodger DC, Fong AJ, Li W, Ameri H, Ahuja AK, Gutierrez C, Lavrov I, Zhong H, Menon PR, Meng E, Burdick JW, Roy RR, Edgerton VR, Weiland JD, Humayun MS, Tai YC (2008) Flexible parylene-based multielectrode array technology for high-density neural stimulation and recording. Sens Actuators B Chem 132:449–460. doi:10.1016/j.snb.2007.10.069
    OpenUrlCrossRef
  34. ↵
    Scott A, Weir K, Easton C, Huynh W, Moody WJ, Folch A (2013) A microfluidic microelectrode array for simultaneous electrophysiology, chemical stimulation, and imaging of brain slices. Lab Chip 13:527–535. doi:10.1039/C2LC40826K
    OpenUrlCrossRefPubMed
  35. ↵
    Sessolo M, Khodagholy D, Rivnay J, Maddalena F, Gleyzes M, Steidl E, Buisson B, Malliaras GG (2013) Easy-to-fabricate conducting polymer microelectrode arrays. Adv Mater 25:2135–2139. doi:10.1002/adma.201204322
    OpenUrlCrossRefPubMed
  36. ↵
    Someya T, Bao Z, Malliaras GG (2016) The rise of plastic bioelectronics. Nature 540:379–385. doi:10.1038/nature21004
    OpenUrlCrossRef
  37. ↵
    Stieglitz T, Beutel H, Meyer JU (1997) A flexible, light-weight multichannel sieve electrode with integrated cables for interfacing regenerating peripheral nerves. Sens Actuators A Phys 60:240–243. doi:10.1016/S0924-4247(97)01494-5
    OpenUrlCrossRef
  38. ↵
    Stosiek C, Garaschuk O, Holthoff K, Konnerth A (2003) In vivo two-photon calcium imaging of neuronal networks. Proc Natl Acad Sci USA 100:7319–7324. doi:10.1073/pnas.1232232100
    OpenUrlAbstract/FREE Full Text
  39. ↵
    Svoboda K, Yasuda R (2006) Principles of two-photon excitation microscopy and its applications to neuroscience. Neuron 50:823–839. doi:10.1016/j.neuron.2006.05.019
    OpenUrlCrossRefPubMed
  40. ↵
    Szente M, Baranyi A (1987) Mechanism of aminopyridine-induced ictal seizure activity in the cat neocortex. Brain Res 413:368–373. doi:10.1016/0006-8993(87)91031-6
    OpenUrlCrossRefPubMed
  41. ↵
    Taketani M, Baudry M (2010) Advances in network electrophysiology. New York, NY: Springer.
  42. ↵
    Thunemann M, Lu Y, Liu X, Kılıç K, Desjardins M, Vandenberghe M, Sadegh S, Saisan PA, Cheng Q, Weldy KL, Lyu H, Djurovic S, Andreassen OA, Dale AM, Devor A, Kuzum D (2018) Deep 2-photon imaging and artifact-free optogenetics through transparent graphene microelectrode arrays. Nat Commun 9:2035. doi:10.1038/s41467-018-04457-5 pmid:29789548
    OpenUrlCrossRefPubMed
  43. ↵
    Voskuyl RA, Albus H (1985) Spontaneous epileptiform discharges in hippocampal slices induced by 4-aminopyridine. Brain Res 342:54–66. doi:10.1016/0006-8993(85)91352-6
    OpenUrlCrossRefPubMed
  44. ↵
    Wilks SJ, Richardson-Burns SM, Hendricks JL, Martin DC, Otto KJ (2009) Poly(3,4-ethylenedioxythiophene) as a micro-neural interface material for electrostimulation. Front Neuroeng 2:7. doi:10.3389/neuro.16.007.2009 pmid:19543541
    OpenUrlCrossRefPubMed
  45. ↵
    Williams JC, Hippensteel JA, Dilgen J, Shain W, Kipke DR (2007) Complex impedance spectroscopy for monitoring tissue responses to inserted neural implants. J Neural Eng 4:410. doi:10.1088/1741-2560/4/4/007
    OpenUrlCrossRefPubMed
  46. ↵
    Williamson A, Ferro M, Leleux P, Ismailova E, Kaszas A, Doublet T, Quilichini P, Rivnay J, Rózsa B, Katona G, Bernard C, Malliaras GG (2015) Localized neuron stimulation with organic electrochemical transistors on delaminating depth probes. Adv Mater 27:4405–4410. doi:10.1002/adma.201500218
    OpenUrlCrossRef

Synthesis

Reviewing Editor: Muriel Thoby-Brisson, CNRS UMR 5287 Université Bordeaux

Decisions are customarily a result of the Reviewing Editor and the peer reviewers coming together and discussing their recommendations until a consensus is reached. When revisions are invited, a fact-based synthesis statement explaining their decision and outlining what is needed to prepare a revision will be listed below. The following reviewer(s) agreed to reveal their identity: Duygun Kuzum, Kenneth Shepard.

In this paper, the authors develop a mostly transparent microelectrode array, which has potential to be used for concurrent imaging of the underlying neural networks. The reported electrode array demonstrates high transparency owing to Parylene-C substrate and encapsulation. The sizes of the electrodes and wires are restricted to sub-20-μm scale in order to avoid blocking the field of view under two-photon microscope. Miniaturization of the electrodes through surface coating (PEDOT:PSS) and using highly transparent thin film substrates allows these windows to be large and transparent, which is promising to serve as a novel multimodal surface recording array. In vivo experiments are conducted for simultaneous electrical recording and two-photon calcium imaging of chemically induced epileptiform activities.

Although, this study does not focus on any specific neuroscientific research, smart design and precise fabrication of the array with strong practical implications are believed to fit well for the scope of the journal. However, there are major issues need to be addressed before consideration for publication:

Major concerns:

1. The introduction does not provide an overview of transparent electrodes previously demonstrated in various publications including two photon microscopy, optogenetcis or other optical modalities. Instead, it discusses not so relevant glass pipettes. In order to provide a complete view of the topic, the authors should first discuss that literature on previous reports of transparent electrodes made of various materials and then explain how their approach is different in the intro section of the paper.

In addition, the introduction emphasizes the importance of the high spatial resolution PEDOT:PSS coated micro electrodes has to offer. However, imaging through the array requires a certain level of decrease in the electrode density. Did the authors investigate this further with different inter-electrode spacings? What is the maximum array density that would still allow imaging?

The imaging relies on the transparent windows not electrodes. Yet, the introduction and the title should be adjusted to reflect that partial transparency.

2. In Fig. 3C, why is ephys so noisy? I am assuming scale bar is 200uV (typo : 200V) so peak to peak noise is more than 100uV? Isn't PEDOT very low impedance so should have low noise as well? I don't think the recordings in Fig. 3.C look like epileptiform activity at all. There are no clear epileptic spikes or seizures. Could it be an artifact due to laser scanning across the electode or wires? I think this experiment needs to be repeated with proper controls, such as recording ephys without imaging and recording ephys in saline or on a phantom to make sure that these are biological signals but not pure artifacts.

3. The authors mention that the induced photoelectric effect caused by scanning over the metallic electrodes. (Kozai et al., 2015). But there is no data in the paper showing whether PEDOT has or does not have photoelectric artifacts. Even though, the imaging does not occur through the electrodes, considering the non-transparent gold interconnects are in the path of the beam, why does it not cause any photo-electric effect as mentioned in the reference? Is the imaging limited to the inter-electrode windows or is it possible to scan the entire surface? This requires further explanation in the script.

4. The validation of the concept is done through chemically induced seizures. Is this because the local calcium signals are needed to be boosted, as the array covering the brain attenuates them? Were the authors able to record and relate any spontaneous activity?

5. In Line 129, in addition to the pictures of the device, the authors should specify the size of the electrode sites and the spacing of the interconnect wires, because it is not easy for the readers to get the accurate readings from the pictures.

6. The reported 16 electrode array is mostly transparent since the electrodes and wires are small in size and the parylene substrate itself is transparent. However, this claim is only valid for low-density arrays. The authors should clearly mention in the discussion that since the electrodes and wires are not transparent, in high density arrays wires will occupy significant area so they will not have this transparency advantage. Therefore the discussions on scalability need to be revised as well.

Some Other Minor Comments

7. In Line 76, the authors mention that 3-(Trimethoxysilyl)propylmethacrylate is present in the chamber as an adhesion promoter. Please specify the use of this adhesion promoter, whether it was mixed with the dimer of Parylene-C in the vaporizer or coated on the sample substrate. References on this promoter are also highly recommended.

8. In Line 83-88, the authors only mention the thickness of the spin-coated layer of PEDOT:PSS without showing the actual thickness of PEDOT:PSS on the electrode sites of the final device, which is probably different from the former thicknesses. The electrochemical impedance is related to the thickness of PEDOT:PSS, because PEDOT:PSS is a volumetric electrode material. The authors should clealy provide the thickness of PEDOT:PSS. Similarly, in the diagram of Figure 1A, the thickness of the spin-coated PEDOT:PSS layer on the Parylene-C layer seems to be the same as it on the electrode sites, which is misleading because these two thicknesses might be different.

9. The picture of Figure 1E is not clear enough to demonstrate the transparency of the electrode and should have higher resolution. The authors could also use a colorful background for better illustration.

10. In Line 100-101, the format of the unit is not correct, “-1”s should be typed as superscript.

11. In Line 81, “O2/CHF3” should have “2” and “3” as subscript.

12. In Line 87, “140C” should have the symbol “{degree sign}”.

Back to top

In this issue

eneuro: 5 (6)
eNeuro
Vol. 5, Issue 6
November/December 2018
  • Table of Contents
  • Index by author
Email

Thank you for sharing this eNeuro article.

NOTE: We request your email address only to inform the recipient that it was you who recommended this article, and that it is not junk mail. We do not retain these email addresses.

Enter multiple addresses on separate lines or separate them with commas.
Multimodal Characterization of Neural Networks Using Highly Transparent Electrode Arrays
(Your Name) has forwarded a page to you from eNeuro
(Your Name) thought you would be interested in this article in eNeuro.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Print
View Full Page PDF
Citation Tools
Multimodal Characterization of Neural Networks Using Highly Transparent Electrode Arrays
Mary J. Donahue, Attila Kaszas, Gergely F. Turi, Balázs Rózsa, Andrea Slézia, Ivo Vanzetta, Gergely Katona, Christophe Bernard, George G. Malliaras, Adam Williamson
eNeuro 21 December 2018, 5 (6) ENEURO.0187-18.2018; DOI: 10.1523/ENEURO.0187-18.2018

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Respond to this article
Share
Multimodal Characterization of Neural Networks Using Highly Transparent Electrode Arrays
Mary J. Donahue, Attila Kaszas, Gergely F. Turi, Balázs Rózsa, Andrea Slézia, Ivo Vanzetta, Gergely Katona, Christophe Bernard, George G. Malliaras, Adam Williamson
eNeuro 21 December 2018, 5 (6) ENEURO.0187-18.2018; DOI: 10.1523/ENEURO.0187-18.2018
Reddit logo Twitter logo Facebook logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Visual Abstract
    • Abstract
    • Significance Statement
    • Introduction
    • Materials and Methods
    • Results
    • Discussion
    • Footnotes
    • References
    • Synthesis
  • Figures & Data
  • Info & Metrics
  • eLetters
  • PDF

Keywords

  • electrophysiology
  • Neuroengineering
  • Organic electronics
  • PEDOT:PSS
  • Transparent electronics
  • two-photon imaging

Responses to this article

Respond to this article

Jump to comment:

No eLetters have been published for this article.

Related Articles

Cited By...

More in this TOC Section

Methods/New Tools

  • Bicistronic expression of a high-performance calcium indicator and opsin for all-optical stimulation and imaging at cellular resolution
  • A Toolbox of Criteria for Distinguishing Cajal–Retzius Cells from Other Neuronal Types in the Postnatal Mouse Hippocampus
  • Superficial Bound of the Depth Limit of Two-Photon Imaging in Mouse Brain
Show more Methods/New Tools

Novel Tools and Methods

  • Behavioral and Functional Brain Activity Alterations Induced by TMS Coils with Different Spatial Distributions
  • Bicistronic expression of a high-performance calcium indicator and opsin for all-optical stimulation and imaging at cellular resolution
  • Synthetic Data Resource and Benchmarks for Time Cell Analysis and Detection Algorithms
Show more Novel Tools and Methods

Subjects

  • Novel Tools and Methods

  • Home
  • Alerts
  • Visit Society for Neuroscience on Facebook
  • Follow Society for Neuroscience on Twitter
  • Follow Society for Neuroscience on LinkedIn
  • Visit Society for Neuroscience on Youtube
  • Follow our RSS feeds

Content

  • Early Release
  • Current Issue
  • Latest Articles
  • Issue Archive
  • Blog
  • Browse by Topic

Information

  • For Authors
  • For the Media

About

  • About the Journal
  • Editorial Board
  • Privacy Policy
  • Contact
  • Feedback
(eNeuro logo)
(SfN logo)

Copyright © 2023 by the Society for Neuroscience.
eNeuro eISSN: 2373-2822

The ideas and opinions expressed in eNeuro do not necessarily reflect those of SfN or the eNeuro Editorial Board. Publication of an advertisement or other product mention in eNeuro should not be construed as an endorsement of the manufacturer’s claims. SfN does not assume any responsibility for any injury and/or damage to persons or property arising from or related to any use of any material contained in eNeuro.