Direct Photon-by-Photon Analysis of Time-Resolved Pulsed Excitation Data using Bayesian Nonparametrics

Meysam Tavakoli; Sina Jazani; Ioannis Sgouralis; Wooseok Heo; Kunihiko Ishii; Tahei Tahara; Steve Pressé

doi:10.1016/j.xcrp.2020.100234

Direct Photon-by-Photon Analysis of Time-Resolved Pulsed Excitation Data using Bayesian Nonparametrics

Meysam Tavakoli, Sina Jazani, Ioannis Sgouralis, Wooseok Heo, Kunihiko Ishii, Tahei Tahara, Steve Pressé

Physics

Research output: Contribution to journal › Article › peer-review

10 Scopus citations

Abstract

Lifetimes of chemical species are typically estimated by either fitting time-correlated single-photon counting (TCSPC) histograms or phasor analysis from time-resolved photon arrivals. While both methods yield lifetimes in a computationally efficient manner, their performance is limited by choices made on the number of distinct chemical species contributing photons. However, the number of species is encoded in the photon arrival times collected for each illuminated spot and need not be set by hand a priori. Here, we propose a direct photon-by-photon analysis of data drawn from pulsed excitation experiments to infer, simultaneously and self-consistently, the number of species and their associated lifetimes from a few thousand photons. We do so by leveraging new mathematical tools within the Bayesian nonparametric. We benchmark our method for both simulated and experimental data for 1–4 species.

Original language	English (US)
Article number	100234
Journal	Cell Reports Physical Science
Volume	1
Issue number	11
DOIs	https://doi.org/10.1016/j.xcrp.2020.100234
State	Published - Nov 18 2020

Keywords

Bayesian nonparametrics
Markov chain Monte Carlo
TCSPC
data analysis
fluorescence lifetime imaging
phasor plot

ASJC Scopus subject areas

Engineering(all)
Energy(all)
Physics and Astronomy(all)
Chemistry(all)
Materials Science(all)

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10.1016/j.xcrp.2020.100234

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title = "Direct Photon-by-Photon Analysis of Time-Resolved Pulsed Excitation Data using Bayesian Nonparametrics",

abstract = "Lifetimes of chemical species are typically estimated by either fitting time-correlated single-photon counting (TCSPC) histograms or phasor analysis from time-resolved photon arrivals. While both methods yield lifetimes in a computationally efficient manner, their performance is limited by choices made on the number of distinct chemical species contributing photons. However, the number of species is encoded in the photon arrival times collected for each illuminated spot and need not be set by hand a priori. Here, we propose a direct photon-by-photon analysis of data drawn from pulsed excitation experiments to infer, simultaneously and self-consistently, the number of species and their associated lifetimes from a few thousand photons. We do so by leveraging new mathematical tools within the Bayesian nonparametric. We benchmark our method for both simulated and experimental data for 1–4 species.",

keywords = "Bayesian nonparametrics, Markov chain Monte Carlo, TCSPC, data analysis, fluorescence lifetime imaging, phasor plot",

author = "Meysam Tavakoli and Sina Jazani and Ioannis Sgouralis and Wooseok Heo and Kunihiko Ishii and Tahei Tahara and Steve Press{\'e}",

note = "Funding Information: S.P. acknowledges support from NIH NIGMS grant no. R01GM134426 for the contributions and support of S.J. and grant no. R01GM130745 for the contributions and support of I.S. T.T. acknowledges support from JSPS KAKENHI grant no. JP19F19340 . Publisher Copyright: {\textcopyright} 2020 The Author(s)",

year = "2020",

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doi = "10.1016/j.xcrp.2020.100234",

language = "English (US)",

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AU - Tavakoli, Meysam

AU - Jazani, Sina

AU - Sgouralis, Ioannis

AU - Heo, Wooseok

AU - Ishii, Kunihiko

AU - Tahara, Tahei

AU - Pressé, Steve

N1 - Funding Information: S.P. acknowledges support from NIH NIGMS grant no. R01GM134426 for the contributions and support of S.J. and grant no. R01GM130745 for the contributions and support of I.S. T.T. acknowledges support from JSPS KAKENHI grant no. JP19F19340 . Publisher Copyright: © 2020 The Author(s)

PY - 2020/11/18

Y1 - 2020/11/18

N2 - Lifetimes of chemical species are typically estimated by either fitting time-correlated single-photon counting (TCSPC) histograms or phasor analysis from time-resolved photon arrivals. While both methods yield lifetimes in a computationally efficient manner, their performance is limited by choices made on the number of distinct chemical species contributing photons. However, the number of species is encoded in the photon arrival times collected for each illuminated spot and need not be set by hand a priori. Here, we propose a direct photon-by-photon analysis of data drawn from pulsed excitation experiments to infer, simultaneously and self-consistently, the number of species and their associated lifetimes from a few thousand photons. We do so by leveraging new mathematical tools within the Bayesian nonparametric. We benchmark our method for both simulated and experimental data for 1–4 species.

AB - Lifetimes of chemical species are typically estimated by either fitting time-correlated single-photon counting (TCSPC) histograms or phasor analysis from time-resolved photon arrivals. While both methods yield lifetimes in a computationally efficient manner, their performance is limited by choices made on the number of distinct chemical species contributing photons. However, the number of species is encoded in the photon arrival times collected for each illuminated spot and need not be set by hand a priori. Here, we propose a direct photon-by-photon analysis of data drawn from pulsed excitation experiments to infer, simultaneously and self-consistently, the number of species and their associated lifetimes from a few thousand photons. We do so by leveraging new mathematical tools within the Bayesian nonparametric. We benchmark our method for both simulated and experimental data for 1–4 species.

KW - Bayesian nonparametrics

KW - Markov chain Monte Carlo

KW - TCSPC

KW - data analysis

KW - fluorescence lifetime imaging

KW - phasor plot

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U2 - 10.1016/j.xcrp.2020.100234

DO - 10.1016/j.xcrp.2020.100234

M3 - Article

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SN - 2666-3864

VL - 1

JO - Cell Reports Physical Science

JF - Cell Reports Physical Science

IS - 11

M1 - 100234

ER -

Direct Photon-by-Photon Analysis of Time-Resolved Pulsed Excitation Data using Bayesian Nonparametrics

Abstract

Keywords

ASJC Scopus subject areas

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