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Scanning electron microscope images of neurons grown on a matrix of gMμPs.: (a) A low magnification image of a neuron’s cell body and an extending neurite on a matrix of large gMμPs. (b) Neurites growing on top of large gMμPs as well as on the flat substrate in between the microprotrusions. (c) Neurites that extend on top of a mushroom cap appear to tightly adhere to the gold surface (labeled yellow) of a small gMμP. Calibration bars: 5 μm for (a,b), and 0.5 μm for (c).
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The development of multi-electrode array platforms for large scale recording of neurons is at the forefront of neuro-engineering research efforts. Recently we demonstrated, at the proof-of-concept level, a breakthrough neuron-microelectrode interface in which cultured Aplysia neurons tightly engulf gold mushroom-shaped microelectrodes (gMμEs). Whil...
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... electron microscopy (SEM) of the cultures revealed that independent of the gMμ P cap diameter, cell bodies and neurites adhere to the flat substrate in between the microprotrusions and to the caps or stalks of the gMμ Ps (Fig. ...
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... study the effects of gMμ P size on the extent of their engulfment by the neurons, we character- ized the neuron-gMμ P interfaces by measuring the thickness (width) of the cleft formed between the neuronal plasma membrane and the gMμ P surfaces (Figs. 3 and 4 and Supplementary Figs. 2-4). Since we were interested in examining how the size of the gMμ P caps affects its active engulfment by the neurons, only cell bodies and large neurites that formed at least a single discernible physical contact (0-10 nm cleft) with the protruding structure were included in the quantitative analysis (Figs. 3 and 4). Measurements were ...
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... the electrodes. The data were clustered to represent different areas of the gMμ P: (a) the upper part of the mushroom cap that faces the junctional membrane of the neurons, (b) the mushroom stalk, (c) the substrate surface that corresponds to the diameter of the mushroom cap, and (d) the lower part of the mushroom cap that faces the substrate ( Supplementary Figs. 2-4). When the cleft thickness between the gold surface and the cells exceeded 300 nm it was not included in the calculations of the average cleft size. The fraction (in percent) of gMμ P surface with a cleft thickness smaller than 300 nm served as the "engulfment-level" parameter (Fig. ...
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... of the tight contact formed between the neuron membrane and the upper surface of the gMμ P cap revealed an identical ultrastructure independent of the cap diameter (Figs. 3 and 4 and Supplementary Figs. 2-4). The tight contacts appearing along stretches of 0.2-1 μ m were interposed by short clefts of 5-10 μ m. The fact that independent of the cap diameter, a 0-10 nm narrow cleft is formed between the cell's plasma membrane and the upper surface of the gMμ P suggests that the rough surface of the cap (Fig. 1) facilitates membrane adhesion ...
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... the improved source separation of the electrophysiological signaling with respect to classical large surface planar electrodes. Nevertheless, the transmission electron images described in the first part of this manuscript revealed that a single gMμ P may be contacted or partially engulfed by a number of neuronal elements (neurites or cell bodies Figs. 2,3c and 4a). Thus, we next estimated the CC formed between neurons or neurites and gMμ Es as a function of the "engulfment level" (the percentage of the electrode surface area directly in contact with the neuron) and thereby estimated the expected amplitudes that can be recorded by gMμ Es that are contacted by a number of ...
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... of cleft width from TEM images were done digitally using the image analysis program ImageJ and Photoshop CS6 (Fig. 4, Supplementary Fig. 2-4). The cleft width was measured every 50 nm perpendicularly to the gMμ P surface. The significance of the differences between average cleft width values of the different areas was analyzed using student T tests and one-way ...
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... simulation. Computer simulations were done using SPICE (Tanner EDA v.15), and the passive analog electrical circuit depicting a gMμ E interfaced with a neuron as shown in Fig. 6 8,28,29 . Calculations and graphs presentations were made using MATLAB (20014A). The main purpose of the simulations was to quantitatively characterize the relationships between the dimensions and shape of gMμ E and the CC levels between the electrodes and cultured rat hippocampal neurons. The simulated gMμ Es were constructed of ...
Citations
... Most circuits rely on the point contact model [21]: the electrode and the junctional portion of the neuron membrane (i.e., that interfaced to the electrode) are lumped together into a netlist node, under the assumption that the interface is far away from the ground. The electrode is commonly described by passive elements whereas the membrane is represented with different levels of accuracy and complexity (in decreasing order): i) Hodgkin-Huxley (HH) [33] and HH-like models [29] [34], [35] [32], [36], [37]; ii) RC passive driven by voltage/current sources with HH-like waveforms [4], [5], [38]; iii) RC passive with AC input drive [5], [31], [39]. Still, the non-junctional membrane (i.e., that not facing the electrode) can be described by one or more compartments [30], [40]. ...
... Unless otherwise stated, the equivalent circuit is built following Figure 3 with M=2, N=1 and considering one ion channel depletion conditions to better visualize the curves: µ Na =0.8, µ K =1. Figure 6.a reports the Vsens waveform for a cleft thickness ranging from 10 to 100 nm, and shows excellent agreement between the FEM and the equivalent circuit models in all cases. For thin clefts [39], the electrode is well sealed by the neuron membrane, and the signal increases due to the large cleft resistance seen by the ionic currents through the cleft. At this nanometric distance the steric effects might be dominant and an electrical double layer description for the cleft/electrode could become inappropriate; however, we verified through an extended modified-PNP simulations (see implementation and results in the Supplementary Information) that this is the case only at electrical potentials well beyond the typical extracellular voltage range (i.e., more than tens of mV, see Figures FS1, FS2). ...
... Mushroom electrodes (Figure 2.c) are a promising category of extracellular protruding electrodes for neural sensing [4], [5], [39]. We report in this section a few parametric studies of this electrode morphology. ...
italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Objective
: define a new methodology to build multicompartment lumped-elements equivalent circuit models for the neuron/electrode systems. Methods: the equivalent circuit topology is derived by careful scrutiny of accurate and validated multiphysics finite-elements method (FEM) simulations that couple ion transport in the intra- and extracellular fluids, activation of the neuron membrane ion channels, and signal acquisition by the electronic readout.
Results:
robust and accurate circuit models are systematically derived with the proposed method, suited to represent the dynamics of the sensed extracellular signals over a wide range of geometrical/physical parameters (neuron and electrode sizes, electrolytic cleft thicknesses, readout input impedance, non-uniform ion channel distributions). FEM simulations point out phenomena that escape an accurate description by equivalent circuits; notably: steric effects in the thin electrolytic cleft and the impact of extracellular ion transport on the reversal potentials of the Hodgkin-Huxley neuron model.
Conclusion:
the multi-compartment equivalent circuits derived with our method match with good accuracy the FEM simulations. They unveil the existence of an optimum number of compartments for accurate circuit simulation. FEM simulations suggest that while steric effects are in most instances negligible, the extracellular ion transport remarkably affects the reversal potentials and consequently the recorded signal if the electrolytic cleft becomes thinner than approximately 100 nm.
Significance:
the proposed methodology and circuit models improve upon the existing area and point contact models. The coupling between the extracellular concentrations and reversal potential highlighted by FEM simulations emerges as a challenge for future developments in lumped-element modeling of the neuron/sensor interface.
... [34][35][36] Copyright 2015, 2021, 2012, Elsevier, Forschungszentrum Jülich, Frontiers), or nanotopograhpic shapes (reproduced with permission. [37][38][39][40][41] Copyright 2022, 2015, 2022, 2017, 2019, Springer Nature, Springer Nature, Wiley-VCH GmbH, IOP Publishing, American Chemical Society) to improve cell-adhesion. The insulation around the electrodes, which makes the bulk of the device, can be of various ceramics, elastomers, or even biomimetic materials. ...
Neural interfaces are evolving at a rapid pace owing to advances in material science and fabrication, reduced cost of scalable complementary metal oxide semiconductor (CMOS) technologies, and highly interdisciplinary teams of researchers and engineers that span a large range from basic to applied and clinical sciences. This study outlines currently established technologies, defined as instruments and biological study systems that are routinely used in neuroscientific research. After identifying the shortcomings of current technologies, such as a lack of biocompatibility, topological optimization, low bandwidth, and lack of transparency, it maps out promising directions along which progress should be made to achieve the next generation of symbiotic and intelligent neural interfaces. Lastly, it proposes novel applications that can be achieved by these developments, ranging from the understanding and reproduction of synaptic learning to live‐long multimodal measurements to monitor and treat various neuronal disorders.
... Most circuits rely on the point contact model [21]: the electrode and the junctional portion of the neuron membrane (i.e., that interfaced to the electrode) are lumped together into a netlist node, under the assumption that the interface is far away from the ground. The electrode is commonly described by passive elements whereas the membrane is represented with different levels of accuracy and complexity (in decreasing order): i) Hodgkin-Huxley (HH) [33] and HH-like models [29], [30], [32], [34], [35]; ii) RC passive driven by voltage/current sources with HH-like waveforms [4], [5], [36]; iii) RC passive with AC input drive [5], [31], [37]. Still, the non-junctional membrane (i.e., that not facing the electrode) can be described by one or more compartments [30], [38]. ...
... Mushroom electrodes (Figure 2.c) are a promising category of extracellular protruding electrodes for neural sensing [4], [5], [37]. We report in this section a few parametric studies of this electrode morphology. ...
p>A methodology to build multi-compartment lumped elements equivalent circuits for the neuron/electrode systems is proposed. The equivalent circuit topology is derived by careful scrutiny of accurate multiphysics finite-elements method (FEM) simulations that couple ion transport in the intra- and extracellular fluids, activation of ion channels in the cellular membrane, and signal collection by the electronic readout, thus improving upon most common area contact models.
We show that the equivalent circuits derived with our method match with good accuracy the reference FEM simulations over a wide range of geometrical/physical parameters such as the neuron and electrode size, the thickness of the electrolytic cleft, the input impedance of the readout amplifier, even in presence of nonuniform ion channel distributions. The impact of the number of compartments on the model accuracy is also analyzed in detail. We finally illustrate by FEM simulations the effect of extracellular ion transport on the reversal potentials of the Hodgkin-Huxley neuron model and how it can affect the recorded signal for very thin electrolyte clefts between the neuron and the electrode, in a way not yet captured by equivalent circuits of the neuron/electrode system.</p
... Most circuits rely on the point contact model [21]: the electrode and the junctional portion of the neuron membrane (i.e., that interfaced to the electrode) are lumped together into a netlist node, under the assumption that the interface is far away from the ground. The electrode is commonly described by passive elements whereas the membrane is represented with different levels of accuracy and complexity (in decreasing order): i) Hodgkin-Huxley (HH) [33] and HH-like models [29], [30], [32], [34], [35]; ii) RC passive driven by voltage/current sources with HH-like waveforms [4], [5], [36]; iii) RC passive with AC input drive [5], [31], [37]. Still, the non-junctional membrane (i.e., that not facing the electrode) can be described by one or more compartments [30], [38]. ...
... Mushroom electrodes (Figure 2.c) are a promising category of extracellular protruding electrodes for neural sensing [4], [5], [37]. We report in this section a few parametric studies of this electrode morphology. ...
p>A methodology to build multi-compartment lumped elements equivalent circuits for the neuron/electrode systems is proposed. The equivalent circuit topology is derived by careful scrutiny of accurate multiphysics finite-elements method (FEM) simulations that couple ion transport in the intra- and extracellular fluids, activation of ion channels in the cellular membrane, and signal collection by the electronic readout, thus improving upon most common area contact models.
We show that the equivalent circuits derived with our method match with good accuracy the reference FEM simulations over a wide range of geometrical/physical parameters such as the neuron and electrode size, the thickness of the electrolytic cleft, the input impedance of the readout amplifier, even in presence of nonuniform ion channel distributions. The impact of the number of compartments on the model accuracy is also analyzed in detail. We finally illustrate by FEM simulations the effect of extracellular ion transport on the reversal potentials of the Hodgkin-Huxley neuron model and how it can affect the recorded signal for very thin electrolyte clefts between the neuron and the electrode, in a way not yet captured by equivalent circuits of the neuron/electrode system.</p
... Such mushroom-shaped spines typically consist of an expanded head joined to the dendrite shaft by a much narrower neck [205][206][207]. Mushroom spinelike microstructures have been more frequently fabricated via electroplating, in which the growth of gold is guided through photolithographically defined circles defining the stalk and mushroom head diameters [7,[208][209][210]. ...
The development of a functional nervous system requires neurons to interact with and promptly respond to a wealth of biochemical, mechanical and topographical cues found in the neural extracellular matrix (ECM). Among these, ECM topographical cues have been found to strongly influence neuronal function and behavior. Here, we discuss how the blueprint of the architectural organization of the brain ECM has been tremendously useful as a source of inspiration to design biomimetic substrates to enhance neural interfaces and dictate neuronal behavior at the cell-material interface. In particular, we focus on different strategies to recapitulate cell-ECM and cell-cell interactions. In order to mimic cell-ECM interactions, we introduce roughness as a first approach to provide informative topographical biomimetic cues to neurons. We then examine 3D scaffolds and hydrogels, as softer 3D platforms for neural interfaces. Moreover, we will discuss how anisotropic features such as grooves and fibers, recapitulating both ECM fibrils and axonal tracts, may provide recognizable paths and tracks that neuron can follow as they develop and establish functional connections. Finally, we show how isotropic topographical cues, recapitulating shapes, and geometries of filopodia- and mushroom-like dendritic spines, have been instrumental to better reproduce neuron-neuron interactions for applications in bioelectronics and neural repair strategies. The high complexity of the brain architecture makes the quest for the fabrication of create more biologically relevant biomimetic architectures in continuous and fast development. Here, we discuss how recent advancements in two-photon polymerization (2PP) and remotely reconfigurable dynamic interfaces are paving the way towards to a new class of smart biointerfaces for in vitro applications spanning from neural tissue engineering as well as neural repair strategies.
... A good lateral sealing with a reduced cleft thickness of less than 5 nm [21] also beneficially affects sensitivity by short circuiting the electrical double layers (EDLs) at the cleft's interfaces. Local and tight contact with the neuron membrane has been demonstrated, e.g. with mushroom-shaped protrusions [27,[35][36][37], or with nanoneedles/nanowires [27,38,39]. ...
... Mushroom-shaped microelectrodes are engulfed by the cells through an endocytotic-like process [27] facilitated by the mushroom cap's curvature [36], especially if the diameter does not exceed 2-2.5 µm [35] (#1 in table 1). To increase mushrooms' coupling to neurons up to 100-fold, a conductive polymer coating (e.g. ...
... The readout is always represented as a circuit. The neuron soma is sketched as a three-dimensional dome; the needle sensor in (a,b) retains the rectangular symmetry of the underlying FET while the passiveextracellular mushroom-shaped nanoelectrode, inspired by the work of [27,35], has cylindrical symmetry (c,d). ...
Neuron and neural network studies are remarkably fostered by novel stimulation and recording systems, which often make use of biochips fabricated with advanced electronic technologies and, notably, micro- and nanoscale complementary metal-oxide semiconductor (CMOS). Models of the transduction mechanisms involved in the sensor and recording of the neuron activity are useful to optimize the sensing device architecture and its coupling to the readout circuits, as well as to interpret the measured data. Starting with an overview of recently published integrated active and passive micro/nanoelectrode sensing devices for in vitro studies fabricated with modern (CMOS-based) micro-nano technology, this paper presents a mixed-mode device-circuit numerical-analytical multiscale and multiphysics simulation methodology to describe the neuron-sensor coupling, suitable to derive useful design guidelines. A few representative structures and coupling conditions are analysed in more detail in terms of the most relevant electrical figures of merit including signal-to-noise ratio.
This article is part of the theme issue ‘Advanced neurotechnologies: translating innovation for health and well-being’.
... Ultrasmall electrodes which contain high aspect-ratio components such as Ag nanowires or CNTs, or are fabricated in a way to make "mushroom cap" structures, have been able to fuse with cellular membranes. [231][232][233] These patterned interfaces increase the contact surface area between cell and electrode, and have demonstrated in vitro the ability to guide neurite projections and minimize neuronal inflammation. [234,235] By adjusting the electrode shape and its chemical composition, cells can engulf electrodes and these tight seals improve the recorded signal quality. ...
Surface electrode arrays are mainly fabricated from rigid or elastic materials, and precisely manipulated ductile metal films which offer limited stretchability. However, the living tissues to which they are applied are non-linear viscoelastic materials which can undergo significant mechanical deformation in dynamic biological environments. Further, the same arrays and compositions are often repurposed for vastly different tissues rather than optimizing the materials and mechanical properties of the implant for the target application. By first characterizing the desired biological environment, and then designing a technology for a particular organ, surface electrode arrays may be more conformable, and offer better interfaces to tissues while causing less damage. Here, the various materials used in each component of a surface electrode array are first reviewed, and we then describe electrically active implants in three specific biological systems: the nervous system, the muscular system, and skin. We last offer considerations for fabricating next-generation surface arrays that overcome current limitations.
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... A large number of in vitro studies have revealed that the cleft width formed between different cultured cell types and artificial substrates ranges from 20 to 100 nm (Braun and Fromherz, 1998;Iwanaga et al., 2001;Straub et al., 2001;Lambacher and Fromherz, 2002;Brittinger and Fromherz, 2005;Gleixner and Fromherz, 2006;Wrobel et al., 2008) and the contact surface area of these junctions has been estimated. The estimated seal resistance derived in these studies ranged from ∼1 M in the case of planar electrodes (Weis and Fromherz, 1997;Buitenweg et al., 1998Buitenweg et al., , 2002 to ∼40-100 M s for gMµEs (Hai et al., 2009a;Fendyur et al., 2011;Spira and Hai, 2013;Ojovan et al., 2015;Shmoel et al., 2016;Massobrio et al., 2018;Spira et al., 2019). ...
Despite increasing use of in vivo multielectrode array (MEA) implants for basic research and medical applications, the critical structural interfaces formed between the implants and the brain parenchyma, remain elusive. Prevailing view assumes that formation of multicellular inflammatory encapsulating-scar around the implants [the foreign body response (FBR)] degrades the implant electrophysiological functions. Using gold mushroom shaped microelectrodes (gMμEs) based perforated polyimide MEA platforms (PPMPs) that in contrast to standard probes can be thin sectioned along with the interfacing parenchyma; we examined here for the first time the interfaces formed between brains parenchyma and implanted 3D vertical microelectrode platforms at the ultrastructural level. Our study demonstrates remarkable regenerative processes including neuritogenesis, axon myelination, synapse formation and capillaries regrowth in contact and around the implant. In parallel, we document that individual microglia adhere tightly and engulf the gMμEs. Modeling of the formed microglia-electrode junctions suggest that this configuration suffice to account for the low and deteriorating recording qualities of in vivo MEA implants. These observations help define the anticipated hurdles to adapting the advantageous 3D in vitro vertical-electrode technologies to in vivo settings, and suggest that improving the recording qualities and durability of planar or 3D in vivo electrode implants will require developing approaches to eliminate the insulating microglia junctions.
... It is The copyright holder for this preprint this version posted October 4, 2021. ; https://doi.org/10.1101/2021.10.03.461535 doi: bioRxiv preprint 1997; Buitenweg et al., 1998;Buitenweg et al., 2002) to ~ 40-100 MΩs for gMµEs (Hai et al., 2009a;Fendyur et al., 2011;Spira and Hai, 2013;Ojovan et al., 2015;Shmoel et al., 2016;Massobrio et al., 2018;Spira et al., 2019). The input resistance of mice microglia (R µg ) was reported to be 2-5 GΩ (Avignone et al., 2008;Schilling and Eder, 2015). ...
Despite increasing use of in-vivo multielectrode array (MEA) implants for basic research and medical applications, the critical structural interfaces formed between the implants and the brain parenchyma, remain elusive. Prevailing view assumes that formation of multicellular inflammatory encapsulating-scar around the implants (the foreign body response) degrades the implant electrophysiological functions. Using gold mushroom shaped microelectrodes (gMμEs) based perforated polyimide MEA platforms (PPMPs) that in contrast to standard probes can be thin sectioned along with the interfacing parenchyma; we examined here for the first time the interfaces formed between brains parenchyma and implanted 3D vertical microelectrode platforms at the ultrastructural level. Our study demonstrates remarkable regenerative processes including neuritogenesis, axon myelination, synapse formation and capillaries regrowth in contact and around the implant. In parallel, we document that individual microglia adhere tightly and engulf the gMμEs. Modeling of the formed microglia-electrode junctions suggest that this configuration suffice to account for the low and deteriorating recording qualities of in vivo MEA implants. These observations help define the anticipated hurdles to adapting the advantageous 3D in-vitro vertical-electrode technologies to in-vivo settings, and suggest that improving the recording qualities and durability of planar or 3D in-vivo electrode implants will require developing approaches to eliminate the insulating microglia junctions.
... e) Reproduced under the terms of the CC-BY Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0). [201] Copyright 2015, Springer Nature. f-h) Reproduced with permission. ...
... Ojovan et al. reported that Au mushroom-shaped protrusions could tightly adhere to the Au surface (Figure 11e). [201] Likewise, Santoro et al. presented Au mushroom-shaped MEA that were arranged in a grid pattern to induce HL-1 cells to be cultured along the grid guidance. [200] Because of the presence of the guidance, cells were attached along the mushroom-shaped electrodes, as illustrated in Figure 11f,g. ...
In recent studies related to bioelectronics, significant efforts have been made to form 3D electrodes to increase the effective surface area or to optimize the transfer of signals at tissue–electrode interfaces. Although bioelectronic devices with 2D and flat electrode structures have been used extensively for monitoring biological signals, these 2D planar electrodes have made it difficult to form biocompatible and uniform interfaces with nonplanar and soft biological systems (at the cellular or tissue levels). Especially, recent biomedical applications have been expanding rapidly toward 3D organoids and the deep tissues of living animals, and 3D bioelectrodes are getting significant attention because they can reach the deep regions of various 3D tissues. An overview of recent studies on 3D bioelectronic devices, such as the use of electrical stimulations and the recording of neural signals from biological subjects, is presented. Subsequently, the recent developments in materials and fabrication processing to 3D micro- and nanostructures are introduced, followed by broad applications of these 3D bioelectronic devices at various in vitro and in vivo conditions.
