The effects of protocol factors and participant characteristics on functional near-infrared spectroscopy data quality after stroke
Functional Near-Infrared Spectroscopy (fNIRS) is an emerging neurotechnology that has several advantages over fMRI, but questions remain about factors that affect data quality and activity in stroke survivors. We examined the effect of protocol factors (Aim 1) and participant characteristics (Aim 2)...
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Elsevier
2025-09-01
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| Series: | NeuroImage: Reports |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666956025000443 |
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| author | Erin L. Meier Lisa D. Bunker Hana Kim Alexandra Zezinka Durfee Victoria Tilton-Bolowsky Voss Neal Argye E. Hillis |
| author_facet | Erin L. Meier Lisa D. Bunker Hana Kim Alexandra Zezinka Durfee Victoria Tilton-Bolowsky Voss Neal Argye E. Hillis |
| author_sort | Erin L. Meier |
| collection | DOAJ |
| description | Functional Near-Infrared Spectroscopy (fNIRS) is an emerging neurotechnology that has several advantages over fMRI, but questions remain about factors that affect data quality and activity in stroke survivors. We examined the effect of protocol factors (Aim 1) and participant characteristics (Aim 2) on raw fNIRS signal quality and tested associations between quality control metrics and brain activity and connectivity (Aim 3) in a sample of 107 individuals with a history of left or right hemisphere stroke. Participants completed tasks that varied by cognitive and motor speech demands (from low to high): Resting State, Discourse Comprehension, and Picture Naming. Scalp-coupling indices, peak spectral power values, and number of bad channels from each task were extracted from the Quality Testing of Near Infrared Scans (QT-NIRS) toolbox (Montero-Hernandez and Pollonini, 2020) and used to index raw data quality. Data quality did not vary by session location or protocol experience, but all data quality metrics from Picture Naming were significantly lower than those from the other tasks. fNIRS signals were generally worse for Black women compared to Black men and White individuals regardless of gender. No significant associations between the raw fNIRS signal quality and Resting State functional connectivity were found. However, relative changes in Picture Naming hemoglobin concentrations were associated with scalp-coupling indices for certain channels. These results highlight the need for careful data preprocessing of already collected data and a systematic approach in future studies to mitigate inherent biases of optical instruments, thereby enhancing the inclusion of underrepresented groups in neuroscience research. |
| format | Article |
| id | doaj-art-46dea8a6d55e44b48a3d986dc3072c0d |
| institution | Matheson Library |
| issn | 2666-9560 |
| language | English |
| publishDate | 2025-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage: Reports |
| spelling | doaj-art-46dea8a6d55e44b48a3d986dc3072c0d2025-06-26T09:53:41ZengElsevierNeuroImage: Reports2666-95602025-09-0153100276The effects of protocol factors and participant characteristics on functional near-infrared spectroscopy data quality after strokeErin L. Meier0Lisa D. Bunker1Hana Kim2Alexandra Zezinka Durfee3Victoria Tilton-Bolowsky4Voss Neal5Argye E. Hillis6Department of Neurology, Johns Hopkins University, Baltimore, MD, 21287, USA; Corresponding author. Department of Communication Sciences and Disorders Bouvé College of Health Sciences, Northeastern University 360 Huntington Avenue, Forsyth room 228C, Boston, MA, 02115, USA.Department of Neurology, Johns Hopkins University, Baltimore, MD, 21287, USADepartment of Neurology, Johns Hopkins University, Baltimore, MD, 21287, USADepartment of Neurology, Johns Hopkins University, Baltimore, MD, 21287, USADepartment of Neurology, Johns Hopkins University, Baltimore, MD, 21287, USADepartment of Neurology, Johns Hopkins University, Baltimore, MD, 21287, USADepartment of Neurology, Johns Hopkins University, Baltimore, MD, 21287, USA; Department of Physical Medicine and Rehabilitation, Johns Hopkins University, Baltimore, MD, 21287, USA; Department of Cognitive Science, Johns Hopkins University, Baltimore, MD, 21287, USAFunctional Near-Infrared Spectroscopy (fNIRS) is an emerging neurotechnology that has several advantages over fMRI, but questions remain about factors that affect data quality and activity in stroke survivors. We examined the effect of protocol factors (Aim 1) and participant characteristics (Aim 2) on raw fNIRS signal quality and tested associations between quality control metrics and brain activity and connectivity (Aim 3) in a sample of 107 individuals with a history of left or right hemisphere stroke. Participants completed tasks that varied by cognitive and motor speech demands (from low to high): Resting State, Discourse Comprehension, and Picture Naming. Scalp-coupling indices, peak spectral power values, and number of bad channels from each task were extracted from the Quality Testing of Near Infrared Scans (QT-NIRS) toolbox (Montero-Hernandez and Pollonini, 2020) and used to index raw data quality. Data quality did not vary by session location or protocol experience, but all data quality metrics from Picture Naming were significantly lower than those from the other tasks. fNIRS signals were generally worse for Black women compared to Black men and White individuals regardless of gender. No significant associations between the raw fNIRS signal quality and Resting State functional connectivity were found. However, relative changes in Picture Naming hemoglobin concentrations were associated with scalp-coupling indices for certain channels. These results highlight the need for careful data preprocessing of already collected data and a systematic approach in future studies to mitigate inherent biases of optical instruments, thereby enhancing the inclusion of underrepresented groups in neuroscience research.http://www.sciencedirect.com/science/article/pii/S2666956025000443StrokeFunctional near-infrared spectroscopySignal qualityGenderRace |
| spellingShingle | Erin L. Meier Lisa D. Bunker Hana Kim Alexandra Zezinka Durfee Victoria Tilton-Bolowsky Voss Neal Argye E. Hillis The effects of protocol factors and participant characteristics on functional near-infrared spectroscopy data quality after stroke NeuroImage: Reports Stroke Functional near-infrared spectroscopy Signal quality Gender Race |
| title | The effects of protocol factors and participant characteristics on functional near-infrared spectroscopy data quality after stroke |
| title_full | The effects of protocol factors and participant characteristics on functional near-infrared spectroscopy data quality after stroke |
| title_fullStr | The effects of protocol factors and participant characteristics on functional near-infrared spectroscopy data quality after stroke |
| title_full_unstemmed | The effects of protocol factors and participant characteristics on functional near-infrared spectroscopy data quality after stroke |
| title_short | The effects of protocol factors and participant characteristics on functional near-infrared spectroscopy data quality after stroke |
| title_sort | effects of protocol factors and participant characteristics on functional near infrared spectroscopy data quality after stroke |
| topic | Stroke Functional near-infrared spectroscopy Signal quality Gender Race |
| url | http://www.sciencedirect.com/science/article/pii/S2666956025000443 |
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