Active Electrode Arrays by Chip Embedding in a Flexible Silicone Carrier

Author(s):  
Mathieu Vanden Bulcke ◽  
Kris Baert ◽  
Eric Beyne ◽  
Mario Gonzalez ◽  
Christophe Winters ◽  
...  
2015 ◽  
Vol 17 (6) ◽  
Author(s):  
Vasiliki Giagka ◽  
Andreas Demosthenous ◽  
Nick Donaldson

2021 ◽  
Vol 23 (1) ◽  
pp. 351
Author(s):  
Jae Sik Kim ◽  
Seong Woo Choi ◽  
Yun-Gwi Park ◽  
Sung Joon Kim ◽  
Chang Heon Choi ◽  
...  

Cardiac radioablation is emerging as an alternative option for refractory ventricular arrhythmias. However, the immediate acute effect of high-dose irradiation on human cardiomyocytes remains poorly known. We measured the electrical activities of human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) upon irradiation with 0, 20, 25, 30, 40, and 50 Gy using a multi-electrode array, and cardiomyocyte function gene levels were evaluated. iPSC-CMs showed to recover their electrophysiological activities (total active electrode, spike amplitude and slope, and corrected field potential duration) within 3–6 h from the acute effects of high-dose irradiation. The beat rate immediately increased until 3 h after irradiation, but it steadily decreased afterward. Conduction velocity slowed in cells irradiated with ≥25 Gy until 6–12 h and recovered within 24 h; notably, 20 and 25 Gy-treated groups showed subsequent continuous increase. At day 7 post-irradiation, except for cTnT, cardiomyocyte function gene levels increased with increasing irradiation dose, but uniquely peaked at 25–30 Gy. Altogether, high-dose irradiation immediately and reversibly modifies the electrical conduction of cardiomyocytes. Thus, compensatory mechanisms at the cellular level may be activated after the high-dose irradiation acute effects, thereby, contributing to the immediate antiarrhythmic outcome of cardiac radioablation for refractory ventricular arrhythmias.


2021 ◽  
pp. 108425
Author(s):  
Daniele De Seta ◽  
Hannah Daoudi ◽  
Renato Torres ◽  
Evelyne Ferrary ◽  
Olivier Sterkers ◽  
...  

Lab on a Chip ◽  
2012 ◽  
Vol 12 (21) ◽  
pp. 4397 ◽  
Author(s):  
Dries Braeken ◽  
Danny Jans ◽  
Roeland Huys ◽  
Andim Stassen ◽  
Nadine Collaert ◽  
...  

Author(s):  
Mathieu Vanden Bulcke ◽  
Kris Baert ◽  
Eric Beyne ◽  
Mario Gonzalez ◽  
Christophe Winters ◽  
...  

2016 ◽  
Vol 2 (1) ◽  
pp. 83-86
Author(s):  
Martin Deckert ◽  
Michael Lippert ◽  
Kentaroh Takagaki ◽  
Andreas Brose ◽  
Frank Ohl ◽  
...  

AbstractThe microfabrication and packaging of novel, three-dimensional, polyimide-based, highly flexible, microscale electrocorticography multi-electrode arrays for enhanced epicortical recording of local field potentials is presented. A polyimide foil embeds metallic structures relating to 32 taper-type electrode sites, contact pads as well as interconnecting conductor paths which are integrated in the planar portion of the electrode substrate material. Circular exposed and, thus, active electrode sites are 50 μm in diameter and employed center-to-center pitches range from 250 μm to 1 mm, respectively. As-fabricated 3D-μECoG-MEAs provide taper heights of approximately 4 μm as well as 59 μm being distinguished by characteristic impedances of about 368.9 kΩ at 1 kHz measured in saline electrolyte. The applied packaging strategies favor flip-chip bonding and vapor phase soldering of the polymer substrates to customized printed circuit boards.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Malgorzata Skorupska ◽  
Anna Ilnicka ◽  
Jerzy P. Lukaszewicz

AbstractThe synthesis of metal-free but electrochemically active electrode materials, which could be an important contributor to environmental protection, is the key motivation for this research approach. The progress of graphene material science in recent decades has contributed to the further development of nanotechnology and material engineering. Due to the unique properties of graphene materials, they have found many practical applications: among others, as catalysts in metal-air batteries, supercapacitors, or fuel cells. In order to create an economical and efficient material for energy production and storage applications, researchers focused on the introduction of additional heteroatoms to the graphene structure. As solutions for functionalizing pristine graphene structures are very difficult to implement, this article presents a facile method of preparing nitrogen-doped graphene foam in a microwave reactor. The influence of solvent type and microwave reactor holding time was investigated. To characterize the elemental content and structural properties of the obtained N-doped graphene materials, methods such as elemental analysis, high-resolution transmission electron microscopy, scanning electron microscopy, and Raman spectroscopy were used. Electrochemical activity in ORR of the obtained materials was tested using cyclic voltamperometry (CV) and linear sweep voltamperometry (LSV). The tests proved the materials’ high activity towards ORR, with the number of electrons reaching 3.46 for tested non-Pt materials, while the analogous value for the C-Pt (20 wt% loading) reference was 4.


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Eslam Mounier ◽  
Bassem Abdullah ◽  
Hani Mahdi ◽  
Seif Eldawlatly

AbstractThe Lateral Geniculate Nucleus (LGN) represents one of the major processing sites along the visual pathway. Despite its crucial role in processing visual information and its utility as one target for recently developed visual prostheses, it is much less studied compared to the retina and the visual cortex. In this paper, we introduce a deep learning encoder to predict LGN neuronal firing in response to different visual stimulation patterns. The encoder comprises a deep Convolutional Neural Network (CNN) that incorporates visual stimulus spatiotemporal representation in addition to LGN neuronal firing history to predict the response of LGN neurons. Extracellular activity was recorded in vivo using multi-electrode arrays from single units in the LGN in 12 anesthetized rats with a total neuronal population of 150 units. Neural activity was recorded in response to single-pixel, checkerboard and geometrical shapes visual stimulation patterns. Extracted firing rates and the corresponding stimulation patterns were used to train the model. The performance of the model was assessed using different testing data sets and different firing rate windows. An overall mean correlation coefficient between the actual and the predicted firing rates of 0.57 and 0.7 was achieved for the 10 ms and the 50 ms firing rate windows, respectively. Results demonstrate that the model is robust to variability in the spatiotemporal properties of the recorded neurons outperforming other examined models including the state-of-the-art Generalized Linear Model (GLM). The results indicate the potential of deep convolutional neural networks as viable models of LGN firing.


2021 ◽  
pp. 2004033
Author(s):  
Estelle A. Cuttaz ◽  
Christopher A. R. Chapman ◽  
Omaer Syed ◽  
Josef A. Goding ◽  
Rylie A. Green

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