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Generalized models for quantifying laterality using functional transcranial Doppler ultrasound
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Thompson, Paul A., Watkins, Kate E., Woodhead, Zoe V. J. and Bishop, Dorothy V. M. (2023) Generalized models for quantifying laterality using functional transcranial Doppler ultrasound. Human Brain Mapping, 44 (1). pp. 35-48. doi:10.1002/hbm.26138 ISSN 1065-9471.
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WRAP-generalized-models-quantifying-laterality-using-functional-transcranial-Doppler-ultrasound-Thompson-2022.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution 4.0. Download (1305Kb) | Preview |
Official URL: https://doi.org/10.1002/hbm.26138
Abstract
We consider how analysis of brain lateralization using functional transcranial Doppler ultrasound (fTCD) data can be brought in line with modern statistical methods typically used in functional magnetic resonance imaging (fMRI). Conventionally, a laterality index is computed in fTCD from the difference between the averages of each hemisphere's signal within a period of interest (POI) over a series of trials. We demonstrate use of generalized linear models (GLMs) and generalized additive models (GAM) to analyze data from individual participants in three published studies (N = 154, 73 and 31), and compare this with results from the conventional POI averaging approach, and with laterality assessed using fMRI (N = 31). The GLM approach was based on classic fMRI analysis that includes a hemodynamic response function as a predictor; the GAM approach estimated the response function from the data, including a term for time relative to epoch start (simple GAM), plus a categorical index corresponding to individual epochs (complex GAM). Individual estimates of the fTCD laterality index are similar across all methods, but error of measurement is lowest using complex GAM. Reliable identification of cases of bilateral language appears to be more accurate with complex GAM. We also show that the GAM-based approach can be used to efficiently analyze more complex designs that incorporate interactions between tasks.
| Item Type: | Journal Article | ||||||||
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| Subjects: | B Philosophy. Psychology. Religion > BF Psychology Q Science > QA Mathematics R Medicine > RC Internal medicine |
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| Divisions: | Faculty of Social Sciences > Centre for Educational Development, Appraisal and Research (CEDAR) | ||||||||
| Library of Congress Subject Headings (LCSH): | Brain -- Magnetic resonance imaging, Transcranial Doppler ultrasonography, Laterality, Linear models (Statistics), Nonparametric statistics | ||||||||
| Journal or Publication Title: | Human Brain Mapping | ||||||||
| Publisher: | John Wiley and Sons | ||||||||
| ISSN: | 1065-9471 | ||||||||
| Official Date: | January 2023 | ||||||||
| Dates: |
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| Volume: | 44 | ||||||||
| Number: | 1 | ||||||||
| Page Range: | pp. 35-48 | ||||||||
| DOI: | 10.1002/hbm.26138 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Access rights to Published version: | Open Access (Creative Commons) | ||||||||
| Date of first compliant deposit: | 21 December 2022 | ||||||||
| Date of first compliant Open Access: | 21 December 2022 | ||||||||
| RIOXX Funder/Project Grant: |
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