Analysis methods for measuring passive auditory fNIRS responses generated by a block-design paradigm

Robert Luke; Eric Larson; Maureen J. Shader; Hamish Innes-Brown; Lindsey Van Yper; Adrian K. C. Lee; Paul F. Sowman; David McAlpine

doi:10.1101/2020.12.22.423886

Analysis methods for measuring passive auditory fNIRS responses generated by a block-design paradigm

Robert Luke^*, Eric Larson, Maureen J. Shader, Hamish Innes-Brown, Lindsey Van Yper, Adrian K. C. Lee, Paul F. Sowman, David McAlpine

^*Corresponding author for this work

Department of Linguistics

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

114 Citations (Scopus)

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Abstract

Significance: Functional near-infrared spectroscopy (fNIRS) is an increasingly popular tool in auditory research, but the range of analysis procedures employed across studies may complicate the interpretation of data.

Aim: We aim to assess the impact of different analysis procedures on the morphology, detection, and lateralization of auditory responses in fNIRS. Specifically, we determine whether averaging or generalized linear model (GLM)-based analysis generates different experimental conclusions when applied to a block-protocol design. The impact of parameter selection of GLMs on detecting auditory-evoked responses was also quantified. Approach: 17 listeners were exposed to three commonly employed auditory stimuli: noise, speech, and silence. A block design, comprising sounds of 5 s duration and 10 to 20 s silent intervals, was employed.

Results: Both analysis procedures generated similar response morphologies and amplitude estimates, and both indicated that responses to speech were significantly greater than to noise or silence. Neither approach indicated a significant effect of brain hemisphere on responses to speech. Methods to correct for systemic hemodynamic responses using short channels improved detection at the individual level.

Conclusions: Consistent with theoretical considerations, simulations, and other experimental domains, GLM and averaging analyses generate the same group-level experimental conclusions. We release this dataset publicly for use in future development and optimization of algorithms.

Original language	English
Article number	025008
Pages (from-to)	025008-1- 025008-18
Number of pages	18
Journal	Neurophotonics
Volume	8
Issue number	2
DOIs	https://doi.org/10.1101/2020.12.22.423886 https://doi.org/10.1117/1.NPh.8.2.025008
Publication status	Published - 22 May 2021

Bibliographical note

Copyright the Author(s) 2021. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

auditory responses
block-design paradigm
analysis methods
speech
passive task

Access to Document

10.1101/2020.12.22.423886
10.1117/1.NPh.8.2.025008Licence: CC BY

Publisher version (open access)Final published version, 1.75 MBLicence: CC BY

Cite this

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title = "Analysis methods for measuring passive auditory fNIRS responses generated by a block-design paradigm",

abstract = "Significance: Functional near-infrared spectroscopy (fNIRS) is an increasingly popular tool in auditory research, but the range of analysis procedures employed across studies may complicate the interpretation of data. Aim: We aim to assess the impact of different analysis procedures on the morphology, detection, and lateralization of auditory responses in fNIRS. Specifically, we determine whether averaging or generalized linear model (GLM)-based analysis generates different experimental conclusions when applied to a block-protocol design. The impact of parameter selection of GLMs on detecting auditory-evoked responses was also quantified. Approach: 17 listeners were exposed to three commonly employed auditory stimuli: noise, speech, and silence. A block design, comprising sounds of 5 s duration and 10 to 20 s silent intervals, was employed. Results: Both analysis procedures generated similar response morphologies and amplitude estimates, and both indicated that responses to speech were significantly greater than to noise or silence. Neither approach indicated a significant effect of brain hemisphere on responses to speech. Methods to correct for systemic hemodynamic responses using short channels improved detection at the individual level. Conclusions: Consistent with theoretical considerations, simulations, and other experimental domains, GLM and averaging analyses generate the same group-level experimental conclusions. We release this dataset publicly for use in future development and optimization of algorithms.",

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author = "Robert Luke and Eric Larson and Shader, \{Maureen J.\} and Hamish Innes-Brown and \{Van Yper\}, Lindsey and Lee, \{Adrian K. C.\} and Sowman, \{Paul F.\} and David McAlpine",

note = "Copyright the Author(s) 2021. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.",

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doi = "10.1101/2020.12.22.423886",

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AU - Luke, Robert

AU - Larson, Eric

AU - Shader, Maureen J.

AU - Innes-Brown, Hamish

AU - Van Yper, Lindsey

AU - Lee, Adrian K. C.

AU - Sowman, Paul F.

AU - McAlpine, David

N1 - Copyright the Author(s) 2021. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

PY - 2021/5/22

Y1 - 2021/5/22

N2 - Significance: Functional near-infrared spectroscopy (fNIRS) is an increasingly popular tool in auditory research, but the range of analysis procedures employed across studies may complicate the interpretation of data. Aim: We aim to assess the impact of different analysis procedures on the morphology, detection, and lateralization of auditory responses in fNIRS. Specifically, we determine whether averaging or generalized linear model (GLM)-based analysis generates different experimental conclusions when applied to a block-protocol design. The impact of parameter selection of GLMs on detecting auditory-evoked responses was also quantified. Approach: 17 listeners were exposed to three commonly employed auditory stimuli: noise, speech, and silence. A block design, comprising sounds of 5 s duration and 10 to 20 s silent intervals, was employed. Results: Both analysis procedures generated similar response morphologies and amplitude estimates, and both indicated that responses to speech were significantly greater than to noise or silence. Neither approach indicated a significant effect of brain hemisphere on responses to speech. Methods to correct for systemic hemodynamic responses using short channels improved detection at the individual level. Conclusions: Consistent with theoretical considerations, simulations, and other experimental domains, GLM and averaging analyses generate the same group-level experimental conclusions. We release this dataset publicly for use in future development and optimization of algorithms.

AB - Significance: Functional near-infrared spectroscopy (fNIRS) is an increasingly popular tool in auditory research, but the range of analysis procedures employed across studies may complicate the interpretation of data. Aim: We aim to assess the impact of different analysis procedures on the morphology, detection, and lateralization of auditory responses in fNIRS. Specifically, we determine whether averaging or generalized linear model (GLM)-based analysis generates different experimental conclusions when applied to a block-protocol design. The impact of parameter selection of GLMs on detecting auditory-evoked responses was also quantified. Approach: 17 listeners were exposed to three commonly employed auditory stimuli: noise, speech, and silence. A block design, comprising sounds of 5 s duration and 10 to 20 s silent intervals, was employed. Results: Both analysis procedures generated similar response morphologies and amplitude estimates, and both indicated that responses to speech were significantly greater than to noise or silence. Neither approach indicated a significant effect of brain hemisphere on responses to speech. Methods to correct for systemic hemodynamic responses using short channels improved detection at the individual level. Conclusions: Consistent with theoretical considerations, simulations, and other experimental domains, GLM and averaging analyses generate the same group-level experimental conclusions. We release this dataset publicly for use in future development and optimization of algorithms.

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KW - analysis methods

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Analysis methods for measuring passive auditory fNIRS responses generated by a block-design paradigm

Abstract

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How the brain creates a sense of auditory space

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Analysis methods for measuring passive auditory fNIRS responses generated by a block-design paradigm

Abstract

Bibliographical note

Keywords

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How the brain creates a sense of auditory space

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