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The response clamp: functional characterization of neural systems using closed-loop control

Overview of attention for article published in Frontiers in Neural Circuits, January 2013
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Title
The response clamp: functional characterization of neural systems using closed-loop control
Published in
Frontiers in Neural Circuits, January 2013
DOI 10.3389/fncir.2013.00005
Pubmed ID
Authors

Avner Wallach

Abstract

The voltage clamp method, pioneered by Hodgkin, Huxley, and Katz, laid the foundations to neurophysiological research. Its core rationale is the use of closed-loop control as a tool for system characterization. A recently introduced method, the response clamp, extends the voltage clamp rationale to the functional, phenomenological level. The method consists of on-line estimation of a response variable of interest (e.g., the probability of response or its latency) and a simple feedback control mechanism designed to tightly converge this variable toward a desired trajectory. In the present contribution I offer a perspective on this novel method and its applications in the broader context of system identification and characterization. First, I demonstrate how internal state variables are exposed using the method, and how the use of several controllers may allow for a detailed, multi-variable characterization of the system. Second, I discuss three different categories of applications of the method: (1) exploration of intrinsically generated dynamics, (2) exploration of extrinsically generated dynamics, and (3) generation of input-output trajectories. The relation of these categories to similar uses in the voltage clamp and other techniques is also discussed. Finally, I discuss the method's limitations, as well as its possible synthesis with existing complementary approaches.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 6%
Belgium 2 4%
Israel 1 2%
Spain 1 2%
Unknown 46 87%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 25%
Researcher 10 19%
Student > Master 8 15%
Professor 4 8%
Student > Doctoral Student 3 6%
Other 9 17%
Unknown 6 11%
Readers by discipline Count As %
Engineering 14 26%
Agricultural and Biological Sciences 12 23%
Medicine and Dentistry 4 8%
Neuroscience 4 8%
Physics and Astronomy 4 8%
Other 9 17%
Unknown 6 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 January 2013.
All research outputs
#23,112,190
of 25,759,158 outputs
Outputs from Frontiers in Neural Circuits
#1,103
of 1,302 outputs
Outputs of similar age
#260,627
of 291,038 outputs
Outputs of similar age from Frontiers in Neural Circuits
#135
of 169 outputs
Altmetric has tracked 25,759,158 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,302 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.7. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 169 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.