Extracellular recording system based on amplitude modulation for CMOS microelectrode arrays

2010 ◽  
Author(s):  
Neil Joye ◽  
Alexandre Schmid ◽  
Yusuf Leblebici
Keyword(s):  
Amplitude Modulation ◽  
Microelectrode Arrays ◽  
Extracellular Recording ◽  
Recording System

All-inkjet-printed gold microelectrode arrays for extracellular recording of action potentials

2017 ◽  
Vol 2 (3) ◽  
pp. 035003 ◽  
Author(s):  
Bernd Bachmann ◽  
Nouran Y Adly ◽  
Jan Schnitker ◽  
Alexey Yakushenko ◽  
Philipp Rinklin ◽  
...  
Keyword(s):  
Action Potentials ◽  
Microelectrode Arrays ◽  
Extracellular Recording ◽  
Gold Microelectrode

Extracellular recordings of bionic engineered cardiac tissue based on a porous scaffold and microelectrode arrays

2019 ◽  
Vol 11 (46) ◽  
pp. 5872-5879 ◽  
Author(s):  
Xinwei Wei ◽  
Qing Gao ◽  
Chaoqi Xie ◽  
Chenlei Gu ◽  
Tao Liang ◽  
...  
Keyword(s):  
Cardiac Tissue ◽  
Porous Scaffold ◽  
Microelectrode Arrays ◽  
Extracellular Recording ◽  
New Method ◽  
Extracellular Recordings

To mimic the heart in vitro, here, we reported a new method about the extracellular recording of engineered cardiac tissue based on a porous scaffold and microelectrode arrays, and it is expected to be applied to pharmaceutical studies.

Extracellular recording of spatiotemporal patterning in response to odors in the olfactory epithelium by microelectrode arrays

2011 ◽  
Vol 27 (1) ◽  
pp. 12-17 ◽  
Author(s):  
Qingjun Liu ◽  
Ning Hu ◽  
Weiwei Ye ◽  
Hua Cai ◽  
Fenni Zhang ◽  
...  
Keyword(s):  
Olfactory Epithelium ◽  
Microelectrode Arrays ◽  
Extracellular Recording

scholarly journals Amplitude modulation based readout for very dense active microelectrode arrays

2011 ◽  
Vol 8 (1) ◽  
pp. 38-44
Author(s):  
Neil Joye ◽  
Alexandre Schmid ◽  
Yusuf Leblebici
Keyword(s):  
Amplitude Modulation ◽  
Microelectrode Arrays

scholarly journals Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference

2019 ◽  
Author(s):  
Cole L. Hurwitz ◽  
Kai Xu ◽  
Akash Srivastava ◽  
Alessio P. Buccino ◽  
Matthias H. Hennig
Keyword(s):  
Source Localization ◽  
Center Of Mass ◽  
Microelectrode Arrays ◽  
Extracellular Recording ◽  
Neural Circuitry ◽  
Variational Inference ◽  
Bayesian Modelling ◽  
Variational Autoencoder ◽  
Scalable Inference ◽  
Modelling Approach

AbstractDetermining the positions of neurons in an extracellular recording is useful for investigating functional properties of the underlying neural circuitry. In this work, we present a Bayesian modelling approach for localizing the source of individual spikes on high-density, microelectrode arrays. To allow for scalable inference, we implement our model as a variational autoencoder and perform amortized variational inference. We evaluate our method on both biophysically realistic simulated and real extracellular datasets, demonstrating that it is more accurate than and can improve spike sorting performance over heuristic localization methods such as center of mass.

scholarly journals Measuring Neuronal Signals with Microelectrode Arrays: A Finite Element Analysis

2020 ◽  
Author(s):  
R Bestel ◽  
U van Rienen ◽  
C Thielemann ◽  
R Appali
Keyword(s):  
Finite Element ◽  
Electrical Coupling ◽  
Cell Activity ◽  
Microelectrode Arrays ◽  
Neuronal Cell ◽  
Extracellular Recording ◽  
Element Analysis ◽  
Active Neuron ◽  
Electrode Recording ◽  
Neuronal Geometry

AbstractObjectiveMeasuring neuronal cell activity using microelectrode arrays reveals a great variety of derived signal shapes within extracellular recordings. However, possible mechanisms responsible for this variety have not yet been entirely determined, which might hamper any subsequent analysis of the recorded neuronal data. For an investigation of this issue, we propose a computational model based on the finite element method describing the electrical coupling between an electrically active neuron and an extracellular recording electrode in detail. This allows for a systematic study of possible parameters that may play an essential role in defining or altering the shape of the measured electrode potential. Our results indicate that neuronal geometry and neurite structure, as well as the actual pathways of input potentials that evoke action potential generation, have a significant impact on the shape of the resulting extracellular electrode recording and explain most of the known signal shape variety.

Sign in / Sign up

Export Citation Format

Share Document