Predicting the entrainment of reentrant cardiac waves using phase resetting curves

2002 ◽  
Vol 65 (2) ◽  
Author(s):  
Leon Glass ◽  
Yoshihiko Nagai ◽  
Kevin Hall ◽  
Mario Talajic ◽  
Stanley Nattel
Keyword(s):  
Phase Resetting ◽  
Phase Resetting Curves

scholarly journals Phase Resetting Curves and Oscillatory Stability in Interneurons of Rat Somatosensory Cortex

2007 ◽  
Vol 92 (2) ◽  
pp. 683-695 ◽  
Author(s):  
T. Tateno ◽  
H.P.C. Robinson
Keyword(s):  
Somatosensory Cortex ◽  
Phase Resetting ◽  
Rat Somatosensory Cortex ◽  
Phase Resetting Curves

Macroscopic phase-resetting curves for spiking neural networks

2017 ◽  
Vol 96 (4) ◽  
Author(s):  
Grégory Dumont ◽  
G. Bard Ermentrout ◽  
Boris Gutkin
Keyword(s):  
Neural Networks ◽  
Spiking Neural Networks ◽  
Phase Resetting ◽  
Phase Resetting Curves

scholarly journals Why are all phase resetting curves bimodal?

2013 ◽  
Vol 14 (S1) ◽  
Author(s):  
Sorinel A Oprisan ◽  
Davy Vanderweyen ◽  
Patrick Lynn ◽  
Derek Russell Tuck
Keyword(s):  
Phase Resetting ◽  
Phase Resetting Curves

scholarly journals All Phase Resetting Curves Are Bimodal, but Some Are More Bimodal Than Others

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Sorinel A. Oprisan
Keyword(s):  
Hopf Bifurcation ◽  
Oscillatory Behavior ◽  
Positive Phase ◽  
Neural Oscillator ◽  
Phase Resetting ◽  
Invariant Circle ◽  
Neural Oscillators ◽  
External Stimuli ◽  
Firing Period ◽  
Phase Resetting Curves

Phase resetting curves (PRCs) are phenomenological and quantitative tools that tabulate the transient changes in the firing period of endogenous neural oscillators as a result of external stimuli, for example, presynaptic inputs. A brief current perturbation can produce either a delay (positive phase resetting) or an advance (negative phase resetting) of the subsequent spike, depending on the timing of the stimulus. We showed that any planar neural oscillator has two remarkable points, which we called neutral points, where brief current perturbations produce no phase resetting and where the PRC flips its sign. Since there are only two neutral points, all PRCs of planar neural oscillators are bimodal. The degree of bimodality of a PRC, that is, the ratio between the amplitudes of the delay and advance lobes of a PRC, can be smoothly adjusted when the bifurcation scenario leading to stable oscillatory behavior combines a saddle node of invariant circle (SNIC) and an Andronov-Hopf bifurcation (HB).

scholarly journals High dimensional phase resetting curves and their use in predicting network dynamics

2011 ◽  
Vol 12 (S1) ◽  
Author(s):  
Sorinel A Oprisan ◽  
Robert Raidt ◽  
Andrew Smith
Keyword(s):  
Network Dynamics ◽  
High Dimensional ◽  
Phase Resetting ◽  
Phase Resetting Curves

scholarly journals A Continuation Approach to Computing Phase Resetting Curves

2020 ◽  
pp. 3-30
Author(s):  
Peter Langfield ◽  
Bernd Krauskopf ◽  
Hinke M. Osinga
Keyword(s):  
Phase Resetting ◽  
Phase Resetting Curves

ANALYSIS OF CIRCUITS CONTAINING BURSTING NEURONS USING PHASE RESETTING CURVES

Bursting ◽  
2005 ◽  
pp. 175-200 ◽  
Author(s):  
Carmen Canavier
Keyword(s):  
Phase Resetting ◽  
Bursting Neurons ◽  
Phase Resetting Curves

scholarly journals Phase Resetting Curves Allow for Simple and Accurate Prediction of Robust N:1 Phase Locking for Strongly Coupled Neural Oscillators

2009 ◽  
Vol 97 (1) ◽  
pp. 59-73 ◽  
Author(s):  
Carmen C. Canavier ◽  
Fatma Gurel Kazanci ◽  
Astrid A. Prinz
Keyword(s):  
Phase Locking ◽  
Accurate Prediction ◽  
Phase Resetting ◽  
Neural Oscillators ◽  
Strongly Coupled ◽  
Phase Resetting Curves
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