Characterization of Input-Output Relations in Single Neurons using Spatiotemporal Photo-stimulation

2008 ◽  
pp. 378-379
Author(s):  
M. Krumin ◽  
Shy Shoham
Keyword(s):  
Single Neurons ◽  
Input Output

scholarly journals On the characterization of the Duhem hysteresis operator with clockwise input–output dynamics

2013 ◽  
Vol 62 (3) ◽  
pp. 286-293 ◽  
Author(s):  
Ruiyue Ouyang ◽  
Vincent Andrieu ◽  
Bayu Jayawardhana
Keyword(s):  
Input Output ◽  
Hysteresis Operator

scholarly journals Potential characterization of free-space-wave drop demultiplexer using cavity-resonator-integrated grating input/output coupler

2010 ◽  
Vol 18 (24) ◽  
pp. 25108 ◽  
Author(s):  
Kenji Kintaka ◽  
Katsuya Shimizu ◽  
Yuki Kita ◽  
Satoshi Kawanami ◽  
Junichi Inoue ◽  
...  
Keyword(s):  
Output Coupler ◽  
Free Space ◽  
Cavity Resonator ◽  
Input Output ◽  
Space Wave

scholarly journals Technical Note: Simultaneous fully dynamic characterization of multiple input-output relationships in climate models

2016 ◽  
Author(s):  
Ben Kravitz ◽  
Douglas G. MacMartin ◽  
Philip J. Rasch ◽  
Hailong Wang
Keyword(s):  
Steady State ◽  
Climate Models ◽  
Climate Model ◽  
Climate Science ◽  
Technical Note ◽  
Input Output ◽  
Response Characteristics ◽  
Input Field ◽  
Low Cloud

Abstract. We introduce system identification techniques to climate science wherein multiple dynamic input-output relationships can be simultaneously characterized in a single simulation. This method, involving multiple small perturbations (in space and time) of an input field while monitoring output fields to quantify responses, allows for identification of different timescales of climate response to forcing without substantially pushing the climate far away from a steady state. We use this technique to determine the steady state responses of low cloud fraction and latent heat flux to heating perturbations over 22 regions spanning Earth's oceans. We show that the response characteristics are similar to those of step-change simulations, but in this new method, the responses for 22 regions can be characterized simultaneously. Furthermore, we can estimate the timescale over which the steady state response emerges. The proposed methodology could be useful for a wide variety of purposes in climate science, including characterization of teleconnections and uncertainty quantification to identify the effects of climate model tuning parameters.

scholarly journals Subcellular sequencing of single neurons reveals the dendritic transcriptome of GABAergic interneurons

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Julio D Perez ◽  
Susanne tom Dieck ◽  
Beatriz Alvarez-Castelao ◽  
Georgi Tushev ◽  
Ivy CW Chan ◽  
...  
Keyword(s):  
Hippocampal Neurons ◽  
Large Population ◽  
Cell Types ◽  
Mrna Localization ◽  
Gabaergic Neurons ◽  
Local Translation ◽  
Single Neurons ◽  
Cell Type ◽  
Cell Type Specific

Although mRNAs are localized in the processes of excitatory neurons, it is still unclear whether interneurons also localize a large population of mRNAs. In addition, the variability in the localized mRNA population within and between cell-types is unknown. Here we describe the unbiased transcriptomic characterization of the subcellular compartments of hundreds of single neurons. We separately profiled the dendritic and somatic transcriptomes of individual rat hippocampal neurons and investigated mRNA abundances in the soma and dendrites of single glutamatergic and GABAergic neurons. We found that, like their excitatory counterparts, interneurons contain a rich repertoire of ~4000 mRNAs. We observed more cell type-specific features among somatic transcriptomes than their associated dendritic transcriptomes. Finally, using cell-type specific metabolic labelling of isolated neurites, we demonstrated that the processes of Glutamatergic and, notably, GABAergic neurons were capable of local translation, suggesting mRNA localization and local translation is a general property of neurons.

scholarly journals DESIGN OF DETECTION DEVICE FOR CU CONTAMINATED WATER USING RED DIODA LASER AND PHOTODIODA SENSOR

2018 ◽  
Vol 10 (1) ◽  
pp. 10
Author(s):  
Frida Agung Rakhmadi ◽  
Siti Rofikhoh
Keyword(s):  
Diode Laser ◽  
Detection System ◽  
Data Acquisition System ◽  
Training Sample ◽  
Contaminated Water ◽  
Input Output ◽  
Sample Data ◽  
Water Based ◽  
Five Phases

<p class="abstrak">The research on making detection system of Cu contaminated water based on red diode laser and photodiode sensor has been done. The purpose of this research was to know the characteristic of photodiode sensor, to make and to test the detection system of Cu contaminated water based on red diode laser and photodiode sensor. This research was conducted in five phases: characterization of photodiode sensor, making data acquisition system, processing and analyzing of training sample data, making of the detection system, and implementation of detection system on test samples. The results of research showed that photodiode sensor used in this research has transfer function of  V = 0,0156 * I + 1,1897 with relation of input-output was very strong (r = 0,989); sensitivity was 0,0156 volts / lux; repeatability was 98,31 %; and saturation for the light intensity &gt;200 lux. Meanwhile, the success rate of detection system implementation on Cu contaminated water was 97,5 %.</p>

Characterization of mRNA Expression in Single Neurons

2007 ◽  
pp. 133-152 ◽  
Author(s):  
David M. Lin ◽  
Brandon Loveall ◽  
John Ewer ◽  
David L. Deitcher ◽  
Nikolaus J. Sucher
Keyword(s):  
Mrna Expression ◽  
Single Neurons

Molecular and neuroanatomical characterization of single neurons in the mouse medullary gigantocellular reticular nucleus

2011 ◽  
Vol 519 (13) ◽  
pp. 2574-2593 ◽  
Author(s):  
E.M. Martin ◽  
N. Devidze ◽  
D.N. Shelley ◽  
L. Westberg ◽  
C. Fontaine ◽  
...  
Keyword(s):  
Reticular Nucleus ◽  
Single Neurons ◽  
Gigantocellular Reticular Nucleus
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