ArticlePhysical review. E, Statistical, nonlinear, and soft matter physics2012
Phase response theory extended to nonoscillatory network components.
Article in Physical review. E, Statistical, nonlinear, and soft matter physics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Feedback control of variability in the cycle period of a central pattern generator.Journal of neurophysiology · 2015Article
- Differential effects of conductances on the phase resetting curve of a bursting neuronal oscillator.Journal of computational neuroscience · 2015Article
- Effects of synaptic plasticity on phase and period locking in a network of two oscillatory neurons.Journal of mathematical neuroscience · 2014Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
New tools for analysis of oscillatory networks using phase response theory (PRT) under the assumption of pulsatile coupling have been developed steadily since the 1980s, but none have yet allowed for analysis of mixed systems containing nonoscillatory elements. This caveat has excluded the application of PRT to most real systems, which are often mixed. We show that a recently developed tool, the functional phase resetting curve (fPRC), provides a serendipitous benefit: it allows incorporation of nonoscillatory elements into systems of oscillators where PRT can be applied. We validate this method in a model system of neural oscillators and a biological system, the pyloric network of crustacean decapods.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.