scholarly journals Real-Time Analysis of Oxygen Gradient in Oocyte Respiration Using a High-Density Microelectrode Array

Biosensors ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 256
Author(s):  
William Tedjo ◽  
Yusra Obeidat ◽  
Giovana Catandi ◽  
Elaine Carnevale ◽  
Tomas Chen
Keyword(s):  
Real Time ◽  
Oxygen Concentration ◽  
Microelectrode Array ◽  
Temporal Dynamics ◽  
Imaging System ◽  
High Density ◽  
Oxide Semiconductor ◽  
Two Dimensional ◽  
Imaging Results

Physiological events related to oxygen concentration gradients provide valuable information to determine the state of metabolizing biological cells. The existing oxygen sensing methods (i.e., optical photoluminescence, magnetic resonance, and scanning electrochemical) are well-established and optimized for existing in vitro analyses. However, such methods also present various limitations in resolution, real-time sensing performance, complexity, and costs. An electrochemical imaging system with an integrated microelectrode array (MEA) would offer attractive means of measuring oxygen consumption rate (OCR) based on the cell’s two-dimensional (2D) oxygen concentration gradient. This paper presents an application of an electrochemical sensor platform with a custom-designed complementary-metal-oxide-semiconductor (CMOS)-based microchip and its Pt-coated surface MEA. The high-density MEA provides 16,064 individual electrochemical pixels that cover a 3.6 mm × 3.6 mm area. Utilizing the three-electrode configuration, the system is capable of imaging low oxygen concentration (18.3 µM, 0.58 mg/L, or 13.8 mmHg) at 27.5 µm spatial resolution and up to 4 Hz temporal resolution. In vitro oxygen imaging experiments were performed to analyze bovine cumulus-oocytes-complexes cells OCR and oxygen flux density. The integration of a microfluidic system allows proper bio-sample handling and delivery to the MEA surface for imaging. Finally, the imaging results are processed and presented as two-dimensional (2D) heatmaps, representing the dissolved oxygen concentration in the immediate proximity of the MEA. This paper provides the results of real-time 2D imaging of OCR of live cells/tissues to gain spatial and temporal dynamics of target cell metabolism.

scholarly journals Applicability of independent component analysis on high-density microelectrode array recordings

2012 ◽  
Vol 108 (1) ◽  
pp. 334-348 ◽  
Author(s):  
David Jäckel ◽  
Urs Frey ◽  
Michele Fiscella ◽  
Felix Franke ◽  
Andreas Hierlemann
Keyword(s):  
Microelectrode Array ◽  
Simulated Data ◽  
Complementary Metal Oxide Semiconductor ◽  
Simultaneous Recording ◽  
High Density ◽  
Independent Component ◽  
Oxide Semiconductor ◽  
Spike Sorting ◽  
Spatiotemporal Resolution ◽  
Source Signals

Emerging complementary metal oxide semiconductor (CMOS)-based, high-density microelectrode array (HD-MEA) devices provide high spatial resolution at subcellular level and a large number of readout channels. These devices allow for simultaneous recording of extracellular activity of a large number of neurons with every neuron being detected by multiple electrodes. To analyze the recorded signals, spiking events have to be assigned to individual neurons, a process referred to as “spike sorting.” For a set of observed signals, which constitute a linear mixture of a set of source signals, independent component (IC) analysis (ICA) can be used to demix blindly the data and extract the individual source signals. This technique offers great potential to alleviate the problem of spike sorting in HD-MEA recordings, as it represents an unsupervised method to separate the neuronal sources. The separated sources or ICs then constitute estimates of single-neuron signals, and threshold detection on the ICs yields the sorted spike times. However, it is unknown to what extent extracellular neuronal recordings meet the requirements of ICA. In this paper, we evaluate the applicability of ICA to spike sorting of HD-MEA recordings. The analysis of extracellular neuronal signals, recorded at high spatiotemporal resolution, reveals that the recorded data cannot be modeled as a purely linear mixture. As a consequence, ICA fails to separate completely the neuronal signals and cannot be used as a stand-alone method for spike sorting in HD-MEA recordings. We assessed the demixing performance of ICA using simulated data sets and found that the performance strongly depends on neuronal density and spike amplitude. Furthermore, we show how postprocessing techniques can be used to overcome the most severe limitations of ICA. In combination with these postprocessing techniques, ICA represents a viable method to facilitate rapid spike sorting of multidimensional neuronal recordings.

Progress in Two-Dimensional Arrays for Real-Time Volumetric Imaging

1998 ◽  
Vol 20 (1) ◽  
pp. 1-15 ◽  
Author(s):  
E. D. Light ◽  
R. E. Davidsen ◽  
J.O. Fiering ◽  
T. A. Hruschka ◽  
S. W. Smith
Keyword(s):  
Real Time ◽  
Insertion Loss ◽  
Imaging System ◽  
Two Dimensional ◽  
Volumetric Imaging ◽  
Dimensional Array ◽  
Transducer Arrays ◽  
Volumetric Images ◽  
Duke University

The design, fabrication, and evaluation of two dimensional array transducers for real-time volumetric imaging are described. The transducers we have previously described operated at frequencies below 3 MHz and were unwieldy to the operator because of the interconnect schemes used in connecting to the transducer handle. Several new transducers have been developed using new connection technology. A 40 × 40 = 1,600 element, 3.5 MHz array was fabricated with 256 transmit and 256 receive elements. A 60 × 60 = 3,600 element 5.0 MHz array was constructed with 248 transmit and 256 receive elements. An 80 × 80 = 6,400 element, 2.5 MHz array was fabricated with 256 transmit and 208 receive elements. 2-D transducer arrays were also developed for volumetric scanning in an intracardiac catheter, a 10 × 10 = 100 element 5.0 MHz forward-looking array and an 11 × 13 = 143 element 5.0 MHz side-scanning array. The −6 dB fractional bandwidths for the different arrays varied from 50% to 63%, and the 50 Ω insertion loss for all the transducers was about −64 dB. The transducers were used to generate real-time volumetric images in phantoms and in vivo using the Duke University real time volumetric imaging system, which is capable of generating multiple planes at any desired angle and depth within the pyramidal volume.

scholarly journals 3D high-density microelectrode array with optical stimulation and drug delivery for investigating neural circuit dynamics

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Hyogeun Shin ◽  
Sohyeon Jeong ◽  
Ju-Hyun Lee ◽  
Woong Sun ◽  
Nakwon Choi ◽  
...  
Keyword(s):  
Drug Delivery ◽  
Microelectrode Array ◽  
Neural Circuit ◽  
Three Dimensional ◽  
Brain Dysfunction ◽  
High Density ◽  
Optical Stimulation ◽  
Functional Connections ◽  
Neural Activities

AbstractInvestigation of neural circuit dynamics is crucial for deciphering the functional connections among regions of the brain and understanding the mechanism of brain dysfunction. Despite the advancements of neural circuit models in vitro, technologies for both precisely monitoring and modulating neural activities within three-dimensional (3D) neural circuit models have yet to be developed. Specifically, no existing 3D microelectrode arrays (MEAs) have integrated capabilities to stimulate surrounding neurons and to monitor the temporal evolution of the formation of a neural network in real time. Herein, we present a 3D high-density multifunctional MEA with optical stimulation and drug delivery for investigating neural circuit dynamics within engineered 3D neural tissues. We demonstrate precise measurements of synaptic latencies in 3D neural networks. We expect our 3D multifunctional MEA to open up opportunities for studies of neural circuits through precise, in vitro investigations of neural circuit dynamics with 3D brain models.

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