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.

Speech token detection and discrimination in individual infants using functional near-infrared spectroscopy

“…The correlation-based signal improvement (CBSI) method 35 was applied to limit the systemic component of the fNIRS response; a consequence was that the HbO and Hbr data were now perfectly correlated, and thus only the HbO data were used for all analyses. Data were then band-pass filtered between 0.01 and 0.25 Hz (8th order Butterworth filters) to remove remaining physiological noise while preserving task-related responses 36 . Data were epoched from three seconds before stimulus onset to eleven seconds after stimulus onset, resulting in epochs 14 s in length.…”

Characterization of Mayer-wave oscillations in functional near-infrared spectroscopy using a physiologically informed model of the neural power spectra

“…All data were stored in BIDS data format. 19 Data were processed with MNE-Python, 20,21 MNE-NIRS, 18 and Nilearn. 22,23…”

“…To demonstrate the practical utility of measuring the parameters of Mayer waves, a single, publicly available dataset of 17 participants was analyzed. 18 Participants were exposed to stimuli in a block design protocol but were not asked to actively respond to any stimulus. Each speech stimulus was 5.25 s in duration, blocks were separated by a random interstimulus interval that was randomly selected from a uniform distribution in the range of 10 to 20 s, a complete protocol description is provided with the source of the openly available dataset by Luke et al 18 The presence of an evoked response to auditory-speech stimuli was quantified at an individual level to determine whether data from participants with larger Mayer waves benefited from correction of systemic components in their hemodynamic responses.…”

“…The data were analyzed as described in Ref. 18. Briefly, the raw data were first converted to optical density and then to hemoglobin concentration using the modified Beer-Lambert Law with a differential pathlength factor of 0.1.…”

“…[13][14][15][16][17] The mitigation effect of using short-separation channel regression for reducing contamination of hemodynamic responses by Mayer waves is evaluated on over 200 fNIRS recordings. In addition, the impact of Mayer waves on the detection of auditory-evoked hemodynamic responses, which typically comprise small responses and poor signal-to-noise ratios, 18 is evaluated in a subgroup of recordings from 17 participants.…”