scholarly journals Tetrode Recording in the Xenopus laevis Visual System Using Multichannel Glass Electrodes

2021 ◽  
Vol 2021 (11) ◽  
pp. pdb.prot107086 ◽  
Author(s):  
Masaki Hiramoto ◽  
Hollis T. Cline

The Xenopus tadpole visual system shows an extraordinary extent of developmental and visual experience–dependent plasticity, establishing sophisticated neuronal response properties that guide essential survival behaviors. The external development and access to the developing visual circuit of Xenopus tadpoles make them an excellent experimental system in which to elucidate plastic changes in neuronal properties and their capacity to encode information about the visual scene. The temporal structure of neural activity encodes a significant amount of information, access to which requires recording methods with high temporal resolution. Conversely, elucidating changes in the temporal structure of neural activity requires recording over extended periods. It is challenging to maintain patch-clamp recordings over extended periods and Ca2+ imaging has limited temporal resolution. Extracellular recordings have been used in other systems for extended recording; however, spike amplitudes in the developing Xenopus visual circuit are not large enough to be captured by distant electrodes. Here we describe a juxtacellular tetrode recording method for continuous long-term recordings from neurons in intact tadpoles, which can also be exposed to diverse visual stimulation protocols. Electrode position in the tectum is stabilized by the large contact area in the tissue. Contamination of the signal from neighboring neurons is minimized by the tight contact between the glass capillaries and the dense arrangement of neurons in the tectum. This recording method enables analysis of developmental and visual experience–dependent plastic changes in neuronal response properties at higher temporal resolution and over longer periods than current methods.

2017 ◽  
Author(s):  
Gonzalo M. Rojas ◽  
Carolina Alvarez ◽  
Carlos Montoya ◽  
María de la Iglesia-Vayá ◽  
Jaime Cisternas ◽  
...  

AbstractElectroencephalography (EEG) is the standard diagnosis method for a wide variety of diseases such as epilepsy, sleep disorders, encephalopathies, and coma, among others. Resting-state functional magnetic resonance (rs-fMRI) is currently a technique used in research in both healthy individuals as well as patients. EEG and fMRI are procedures used to obtain direct and indirect measurements of brain neural activity: EEG measures the electrical activity of the brain using electrodes placed on the scalp, and fMRI detects the changes in blood oxygenation that occur in response to neural activity. EEG has a high temporal resolution and low spatial resolution, while fMRI has high spatial resolution and low temporal resolution. Thus, the combination of EEG with rs-fMRI using different methods could be very useful for research and clinical applications. In this article, we describe and show the results of a new methodology for processing rs-fMRI using seeds positioned according to the 10-10 EEG standard. We analyze the functional connectivity and adjacency matrices obtained using 65 seeds based on 10-10 EEG scheme and 21 seeds based on 10-20 EEG. Connectivity networks are created using each 10-20 EEG seeds and are analyzed by comparisons to the seven networks that have been found in recent studies. The proposed method captures high correlation between contralateral seeds, ipsilateral and contralateral occipital seeds, and some in the frontal lobe.


2010 ◽  
Vol 6 (2) ◽  
pp. 43 ◽  
Author(s):  
Andreas H Mahnken ◽  

Over the last decade, cardiac computed tomography (CT) technology has experienced revolutionary changes and gained broad clinical acceptance in the work-up of patients suffering from coronary artery disease (CAD). Since cardiac multidetector-row CT (MDCT) was introduced in 1998, acquisition time, number of detector rows and spatial and temporal resolution have improved tremendously. Current developments in cardiac CT are focusing on low-dose cardiac scanning at ultra-high temporal resolution. Technically, there are two major approaches to achieving these goals: rapid data acquisition using dual-source CT scanners with high temporal resolution or volumetric data acquisition with 256/320-slice CT scanners. While each approach has specific advantages and disadvantages, both technologies foster the extension of cardiac MDCT beyond morphological imaging towards the functional assessment of CAD. This article examines current trends in the development of cardiac MDCT.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Alexander H. Frank ◽  
Robert van Geldern ◽  
Anssi Myrttinen ◽  
Martin Zimmer ◽  
Johannes A. C. Barth ◽  
...  

AbstractThe relevance of CO2 emissions from geological sources to the atmospheric carbon budget is becoming increasingly recognized. Although geogenic gas migration along faults and in volcanic zones is generally well studied, short-term dynamics of diffusive geogenic CO2 emissions are mostly unknown. While geogenic CO2 is considered a challenging threat for underground mining operations, mines provide an extraordinary opportunity to observe geogenic degassing and dynamics close to its source. Stable carbon isotope monitoring of CO2 allows partitioning geogenic from anthropogenic contributions. High temporal-resolution enables the recognition of temporal and interdependent dynamics, easily missed by discrete sampling. Here, data is presented from an active underground salt mine in central Germany, collected on-site utilizing a field-deployed laser isotope spectrometer. Throughout the 34-day measurement period, total CO2 concentrations varied between 805 ppmV (5th percentile) and 1370 ppmV (95th percentile). With a 400-ppm atmospheric background concentration, an isotope mixing model allows the separation of geogenic (16–27%) from highly dynamic anthropogenic combustion-related contributions (21–54%). The geogenic fraction is inversely correlated to established CO2 concentrations that were driven by anthropogenic CO2 emissions within the mine. The described approach is applicable to other environments, including different types of underground mines, natural caves, and soils.


2021 ◽  
Author(s):  
D. Kersebaum ◽  
S.‐C. Fabig ◽  
M. Sendel ◽  
A. C. Muntean ◽  
R. Baron ◽  
...  

2021 ◽  
Vol 30 ◽  
pp. S205
Author(s):  
N. Lammoza ◽  
P. Ratnakanthan ◽  
T. Moran ◽  
P. O'Sullivan ◽  
K. O'Donnell ◽  
...  

Author(s):  
Wen-Han Zhu ◽  
Wei Sun ◽  
Xiong-Kuo Min ◽  
Guang-Tao Zhai ◽  
Xiao-Kang Yang

AbstractObjective image quality assessment (IQA) plays an important role in various visual communication systems, which can automatically and efficiently predict the perceived quality of images. The human eye is the ultimate evaluator for visual experience, thus the modeling of human visual system (HVS) is a core issue for objective IQA and visual experience optimization. The traditional model based on black box fitting has low interpretability and it is difficult to guide the experience optimization effectively, while the model based on physiological simulation is hard to integrate into practical visual communication services due to its high computational complexity. For bridging the gap between signal distortion and visual experience, in this paper, we propose a novel perceptual no-reference (NR) IQA algorithm based on structural computational modeling of HVS. According to the mechanism of the human brain, we divide the visual signal processing into a low-level visual layer, a middle-level visual layer and a high-level visual layer, which conduct pixel information processing, primitive information processing and global image information processing, respectively. The natural scene statistics (NSS) based features, deep features and free-energy based features are extracted from these three layers. The support vector regression (SVR) is employed to aggregate features to the final quality prediction. Extensive experimental comparisons on three widely used benchmark IQA databases (LIVE, CSIQ and TID2013) demonstrate that our proposed metric is highly competitive with or outperforms the state-of-the-art NR IQA measures.


Author(s):  
Matthew J. Cashman ◽  
Allen Gellis ◽  
Eric Boyd ◽  
Mathias Collins ◽  
Scott Anderson ◽  
...  

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