scholarly journals Electrophysiological Recording From Drosophila Labellar Taste Sensilla

10.3791/51355 ◽  
2014 ◽  
Author(s):  
Rebecca Delventhal ◽  
Aidan Kiely ◽  
John R. Carlson
Keyword(s):  
Electrophysiological Recording ◽  
Taste Sensilla

Electrophysiological Recording from Drosophila Taste Sensilla

2011 ◽  
Vol 2011 (7) ◽  
pp. pdb.prot5631-pdb.prot5631 ◽  
Author(s):  
R. Benton ◽  
A. Dahanukar
Keyword(s):  
Electrophysiological Recording ◽  
Taste Sensilla

Fate of sperm membrane in fertilized ova

1993 ◽  
Vol 51 ◽  
pp. 40-41
Author(s):  
Frank J. Longo
Keyword(s):  
Electron Microscopy ◽  
Electrical Activity ◽  
Sea Urchins ◽  
Morphological Changes ◽  
Integrated System ◽  
Electrophysiological Recording ◽  
Experimental Conditions ◽  
The Status ◽  
Sperm Membrane ◽  
Temporal And Spatial

Measurement of the egg's electrical activity, the fertilization potential or the activation current (in voltage clamped eggs), provides a means of detecting the earliest perceivable response of the egg to the fertilizing sperm. By using the electrical physiological record as a “real time” indicator of the instant of electrical continuity between the gametes, eggs can be inseminated with sperm at lower, more physiological densities, thereby assuring that only one sperm interacts with the egg. Integrating techniques of intracellular electrophysiological recording, video-imaging, and electron microscopy, we are able to identify the fertilizing sperm precisely and correlate the status of gamete organelles with the first indication (fertilization potential/activation current) of the egg's response to the attached sperm. Hence, this integrated system provides improved temporal and spatial resolution of morphological changes at the site of gamete interaction, under a variety of experimental conditions. Using these integrated techniques, we have investigated when sperm-egg plasma membrane fusion occurs in sea urchins with respect to the onset of the egg's change in electrical activity.

scholarly journals Implantable Optrode Array for Optogenetic Modulation and Electrical Neural Recording

Micromachines ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 725
Author(s):  
Saeyeong Jeon ◽  
Youjin Lee ◽  
Daeho Ryu ◽  
Yoon Kyung Cho ◽  
Yena Lee ◽  
...  
Keyword(s):  
Light Emitting Diode ◽  
Neural Recording ◽  
Electrophysiological Recording ◽  
Light Emitting ◽  
Technological Advances ◽  
Neuroscience Research ◽  
Cell Type Specific ◽  
Novel Design

During the last decade, optogenetics has become an essential tool for neuroscience research due to its unrivaled feature of cell-type-specific neuromodulation. There have been several technological advances in light delivery devices. Among them, the combination of optogenetics and electrophysiology provides an opportunity for facilitating optogenetic approaches. In this study, a novel design of an optrode array was proposed for realizing optical modulation and electrophysiological recording. A 4 × 4 optrode array and five-channel recording electrodes were assembled as a disposable part, while a reusable part comprised an LED (light-emitting diode) source and a power line. After the characterization of the intensity of the light delivered at the fiber tips, in vivo animal experiment was performed with transgenic mice expressing channelrhodopsin, showing the effectiveness of optical activation and neural recording.

scholarly journals High-Performance Computing Framework Based on Distributed Systems for Large-Scale Neurophysiological Data

2021 ◽  
Author(s):  
Mohsen Hadianpour ◽  
Ehsan Rezayat ◽  
Mohammad-Reza Dehaqani
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
Large Scale ◽  
Electrophysiological Recording ◽  
Neural Data ◽  
Data Framework ◽  
Neurophysiological Data ◽  
Computing Framework ◽  
Performance Computing ◽  
Neuroscience Community

Abstract Due to the significantly drastic progress and improvement in neurophysiological recording technologies, neuroscientists have faced various complexities dealing with unstructured large-scale neural data. In the neuroscience community, these complexities could create serious bottlenecks in storing, sharing, and processing neural datasets. In this article, we developed a distributed high-performance computing (HPC) framework called `Big neuronal data framework' (BNDF), to overcome these complexities. BNDF is based on open-source big data frameworks, Hadoop and Spark providing a flexible and scalable structure. We examined BNDF on three different large-scale electrophysiological recording datasets from nonhuman primate’s brains. Our results exhibited faster runtimes with scalability due to the distributed nature of BNDF. We compared BNDF results to a widely used platform like MATLAB in an equitable computational resource. Compared with other similar methods, using BNDF provides more than five times faster performance in spike sorting as a usual neuroscience application.

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