A comparison of methods to determine neuronal phase-response curves

Ben Torben-Nielsen; Marylka Uusisaari; Klaus M. Stiefel

doi:10.3389/fninf.2010.00006

A comparison of methods to determine neuronal phase-response curves

Ben Torben-Nielsen, Marylka Uusisaari, Klaus M. Stiefel

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

17 Citations (Scopus)

35 Downloads (Pure)

Abstract

The phase-response curve (PRC) is an important tool to determine the excitability type of single neurons which reveals consequences for their synchronizing properties. We review five methods to compute the PRC from both model data and experimental data and compare the numerically obtained results from each method. The main difference between the methods lies in the reliability which is influenced by the fluctuations in the spiking data and the number of spikes available for analysis. We discuss the significance of our results and provide guidelines to choose the best method based on the available data

Original language	English
Article number	6
Number of pages	11
Journal	Frontiers in Neuroinformatics
Volume	4
DOIs	https://doi.org/10.3389/fninf.2010.00006
Publication status	Published - 2010

Access to Document

10.3389/fninf.2010.00006

907193
© 2010 Torben-Nielsen, Uusisaari and Stiefel. This is an open-access article subject to an exclusive license agreement between the authors and the Frontiers Research Foundation, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are credited
Final published version, 1.9 MB

Cite this

@article{a88ebb808d0d4bec91260c6fdc1e617c,

title = "A comparison of methods to determine neuronal phase-response curves",

abstract = "The phase-response curve (PRC) is an important tool to determine the excitability type of single neurons which reveals consequences for their synchronizing properties. We review five methods to compute the PRC from both model data and experimental data and compare the numerically obtained results from each method. The main difference between the methods lies in the reliability which is influenced by the fluctuations in the spiking data and the number of spikes available for analysis. We discuss the significance of our results and provide guidelines to choose the best method based on the available data",

author = "Ben Torben-Nielsen and Marylka Uusisaari and Stiefel, {Klaus M.}",

note = "{\textcopyright} 2010 Torben-Nielsen, Uusisaari and Stiefel. This is an open-access article subject to an exclusive license agreement between the authors and the Frontiers Research Foundation, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are credited",

year = "2010",

doi = "10.3389/fninf.2010.00006",

language = "English",

volume = "4",

journal = "Frontiers in Neuroinformatics",

publisher = "Frontiers Media S.A.",

}

TY - JOUR

T1 - A comparison of methods to determine neuronal phase-response curves

AU - Torben-Nielsen, Ben

AU - Uusisaari, Marylka

AU - Stiefel, Klaus M.

N1 - © 2010 Torben-Nielsen, Uusisaari and Stiefel. This is an open-access article subject to an exclusive license agreement between the authors and the Frontiers Research Foundation, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are credited

PY - 2010

Y1 - 2010

N2 - The phase-response curve (PRC) is an important tool to determine the excitability type of single neurons which reveals consequences for their synchronizing properties. We review five methods to compute the PRC from both model data and experimental data and compare the numerically obtained results from each method. The main difference between the methods lies in the reliability which is influenced by the fluctuations in the spiking data and the number of spikes available for analysis. We discuss the significance of our results and provide guidelines to choose the best method based on the available data

AB - The phase-response curve (PRC) is an important tool to determine the excitability type of single neurons which reveals consequences for their synchronizing properties. We review five methods to compute the PRC from both model data and experimental data and compare the numerically obtained results from each method. The main difference between the methods lies in the reliability which is influenced by the fluctuations in the spiking data and the number of spikes available for analysis. We discuss the significance of our results and provide guidelines to choose the best method based on the available data

U2 - 10.3389/fninf.2010.00006

DO - 10.3389/fninf.2010.00006

M3 - Article

C2 - 20431724

VL - 4

JO - Frontiers in Neuroinformatics

JF - Frontiers in Neuroinformatics

M1 - 6

ER -

A comparison of methods to determine neuronal phase-response curves

Abstract

Access to Document

Fingerprint

Cite this