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Optimal phase control of biological oscillators using augmented phase reduction

Overview of attention for article published in Biological Cybernetics, June 2018
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Title
Optimal phase control of biological oscillators using augmented phase reduction
Published in
Biological Cybernetics, June 2018
DOI 10.1007/s00422-018-0764-z
Pubmed ID
Authors

Bharat Monga, Jeff Moehlis

Abstract

We develop a novel optimal control algorithm to change the phase of an oscillator using a minimum energy input, which also minimizes the oscillator's transversal distance to the uncontrolled periodic orbit. Our algorithm uses a two-dimensional reduction technique based on both isochrons and isostables. We develop a novel method to eliminate cardiac alternans by connecting our control algorithm with the underlying physiological problem. We also describe how the devised algorithm can be used for spike timing control which can potentially help with motor symptoms of essential and parkinsonian tremor, and aid in treating jet lag. To demonstrate the advantages of this algorithm, we compare it with a previously proposed optimal control algorithm based on standard phase reduction for the Hopf bifurcation normal form, and models for cardiac pacemaker cells, thalamic neurons, and circadian gene regulation cycle in the suprachiasmatic nucleus. We show that our control algorithm is effective even when a large phase change is required or when the nontrivial Floquet multiplier is close to unity; in such cases, the previously proposed control algorithm fails.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 23%
Researcher 5 17%
Student > Doctoral Student 2 7%
Other 2 7%
Student > Postgraduate 2 7%
Other 4 13%
Unknown 8 27%
Readers by discipline Count As %
Engineering 9 30%
Mathematics 2 7%
Agricultural and Biological Sciences 2 7%
Neuroscience 2 7%
Social Sciences 1 3%
Other 3 10%
Unknown 11 37%
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 01 July 2018.
All research outputs
#20,523,725
of 23,092,602 outputs
Outputs from Biological Cybernetics
#639
of 679 outputs
Outputs of similar age
#288,669
of 329,246 outputs
Outputs of similar age from Biological Cybernetics
#4
of 5 outputs
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So far Altmetric has tracked 679 research outputs from this source. They receive a mean Attention Score of 4.2. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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