TY - JOUR
T1 - Noninvasive inference methods for interaction and noise intensities of coupled oscillators using only spike time data
AU - Mori, Fumito
AU - Kori, Hiroshi
N1 - Funding Information:
ACKNOWLEDGMENTS. We thank Hiroshi Ito for providing helpful comments. This work was supported by Japan Society for the Promotion of Science KAKENHI Grants JP11J11148, JP19K03663, and JP21K12056.
Publisher Copyright:
© This article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).
PY - 2022/2/8
Y1 - 2022/2/8
N2 - Measurements of interaction intensity are generally achieved by observing responses to perturbations. In biological and chemical systems, external stimuli tend to deteriorate their inherent nature, and thus, it is necessary to develop noninvasive inference methods. In this paper, we propose theoretical methods to infer coupling strength and noise intensity simultaneously in two well-synchronized noisy oscillators through observations of spontaneously fluctuating events such as neural spikes. A phase oscillator model is applied to derive formulae relating each of the parameters to spike time statistics. Using these formulae, each parameter is inferred from a specific set of statistics. We verify these methods using the FitzHugh-Nagumo model as well as the phase model. Our methods do not require external perturbations and thus can be applied to various experimental systems.
AB - Measurements of interaction intensity are generally achieved by observing responses to perturbations. In biological and chemical systems, external stimuli tend to deteriorate their inherent nature, and thus, it is necessary to develop noninvasive inference methods. In this paper, we propose theoretical methods to infer coupling strength and noise intensity simultaneously in two well-synchronized noisy oscillators through observations of spontaneously fluctuating events such as neural spikes. A phase oscillator model is applied to derive formulae relating each of the parameters to spike time statistics. Using these formulae, each parameter is inferred from a specific set of statistics. We verify these methods using the FitzHugh-Nagumo model as well as the phase model. Our methods do not require external perturbations and thus can be applied to various experimental systems.
UR - http://www.scopus.com/inward/record.url?scp=85124059063&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85124059063&partnerID=8YFLogxK
U2 - 10.1073/pnas.2113620119
DO - 10.1073/pnas.2113620119
M3 - Article
C2 - 35110405
AN - SCOPUS:85124059063
SN - 0027-8424
VL - 119
JO - Proceedings of the National Academy of Sciences of the United States of America
JF - Proceedings of the National Academy of Sciences of the United States of America
IS - 6
M1 - e2113620119
ER -