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

Abstract

OverviewSignificancefNIRS is an increasingly popular tool in auditory research, but the range of analysis procedures employed across studies complicates interpretation of data.AimTo assess the impact of different analysis procedures on the morphology, detection, and lateralization of auditory responses in fNIRS. Specifically, whether averaging or GLM-based analyses generate 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.Approach17 listeners were exposed to three commonly employed auditory stimuli: noise, speech, and silence. A block design was employed, comprising sounds of 5-s duration, and 10–20 s silent intervals.ResultsBoth analysis procedures generated similar response morphologies and amplitude estimates, and both also indicated responses to speech to be significantly greater than to noise and 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.ConclusionsConsistent 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.

Wearable, high-density fNIRS and diffuse optical tomography technologies: a perspective

“…The user is then directed to where to enter that meta-data. Then, (3) a data quality report is generated using MNE NIRS 109 . In the future, researchers will be encouraged to also provide their processing and configuration files (e.g., Homer3 proc streams) with the datasets.…”

“…Then, (3) a data quality report is generated using MNE NIRS. 109 In the future, researchers will be encouraged to also provide their processing and configuration files (e.g., Homer3 proc streams) with the datasets. These data repositories can then be shared with the community for download.…”