Dataset Information

Functional near-infrared spectroscopy for speech protocols: characterization of motion artifacts and guidelines for improving data analysis.

ABSTRACT: Monitoring speech tasks with functional near-infrared spectroscopy (fNIRS) enables investigation of speech production mechanisms and informs treatment strategies for speech-related disorders such as stuttering. Unfortunately, due to movement of the temporalis muscle, speech production can induce relative movement between probe optodes and skin. These movements generate motion artifacts during speech tasks. In practice, spurious hemodynamic responses in functional activation signals arise from lack of information about the consequences of speech-related motion artifacts, as well as from lack of standardized processing procedures for fNIRS signals during speech tasks. To this end, we characterize the effects of speech production on fNIRS signals, and we introduce a systematic analysis to ameliorate motion artifacts. The study measured 50 healthy subjects performing jaw movement (JM) tasks and found that JM produces two different patterns of motion artifacts in fNIRS. To remove these unwanted contributions, we validate a hybrid motion-correction algorithm based sequentially on spline interpolation and then wavelet filtering. We compared performance of the hybrid algorithm with standard algorithms based on spline interpolation only and wavelet decomposition only. The hybrid algorithm corrected 94% of the artifacts produced by JM, and it did not lead to spurious responses in the data. We also validated the hybrid algorithm during a reading task performed under two different conditions: reading aloud and reading silently. For both conditions, we observed significant cortical activation in brain regions related to reading. Moreover, when comparing the two conditions, good agreement of spatial and temporal activation patterns was found only when data were analyzed using the hybrid approach. Overall, the study demonstrates a standardized processing scheme for fNIRS data during speech protocols. The scheme decreases spurious responses and intersubject variability due to motion artifacts.

SUBMITTER: Novi SL

PROVIDER: S-EPMC6953699 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Functional near-infrared spectroscopy for speech protocols: characterization of motion artifacts and guidelines for improving data analysis.

Novi Sergio L SL Roberts Erin E Spagnuolo Danielle D Spilsbury Brianna M BM Price D'manda C DC Imbalzano Cara A CA Forero Edwin E Yodh Arjun G AG Tellis Glen M GM Tellis Cari M CM Mesquita Rickson C RC

Neurophotonics 20200110 1

Monitoring speech tasks with functional near-infrared spectroscopy (fNIRS) enables investigation of speech production mechanisms and informs treatment strategies for speech-related disorders such as stuttering. Unfortunately, due to movement of the temporalis muscle, speech production can induce relative movement between probe optodes and skin. These movements generate motion artifacts during speech tasks. In practice, spurious hemodynamic responses in functional activation signals arise from la ...[more]

PMID: 31956662

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Project description:The present study aimed to investigate the effects of degraded speech perception and binaural unmasking using functional near-infrared spectroscopy (fNIRS). Normal hearing listeners were tested when attending to unprocessed or vocoded speech, presented to the left ear at two speech-to-noise ratios (SNRs). Additionally, by comparing monaural versus diotic masker noise, we measured binaural unmasking. Our primary research question was whether the prefrontal cortex and temporal cortex responded differently to varying listening configurations. Our a priori regions of interest (ROIs) were located at the left dorsolateral prefrontal cortex (DLPFC) and auditory cortex (AC). The left DLPFC has been reported to be involved in attentional processes when listening to degraded speech and in spatial hearing processing, while the AC has been reported to be sensitive to speech intelligibility. Comparisons of cortical activity between these two ROIs revealed significantly different fNIRS response patterns. Further, we showed a significant and positive correlation between self-reported task difficulty levels and fNIRS responses in the DLPFC, with a negative but non-significant correlation for the left AC, suggesting that the two ROIs played different roles in effortful speech perception. Our secondary question was whether activity within three sub-regions of the lateral PFC (LPFC) including the DLPFC was differentially affected by varying speech-noise configurations. We found significant effects of spectral degradation and SNR, and significant differences in fNIRS response amplitudes between the three regions, but no significant interaction between ROI and speech type, or between ROI and SNR. When attending to speech with monaural and diotic noises, participants reported the latter conditions being easier; however, no significant main effect of masker condition on cortical activity was observed. For cortical responses in the LPFC, a significant interaction between SNR and masker condition was observed. These findings suggest that binaural unmasking affects cortical activity through improving speech reception threshold in noise, rather than by reducing effort exerted.

Dataset Information

Functional near-infrared spectroscopy for speech protocols: characterization of motion artifacts and guidelines for improving data analysis.

Publications

Functional near-infrared spectroscopy for speech protocols: characterization of motion artifacts and guidelines for improving data analysis.

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