Journal Article

Generalized models for quantifying laterality using functional transcranial Doppler ultrasound

Thompson, Paul A., Bishop, Dorothy V. M., Watkins, Kate E., Woodhead, Zoe V. J.

2023

Overview

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. Transcranial functional Doppler Ultrasound has been used to assess brain lateralization, but the methods used to extract a laterality index (LI) have involved simple averaging over a period of interest. Here, we compare results from that method with results from a generalized linear models (GLM) approach similar to that used in functional magnetic resonance imaging (fMRI), as well as generalized additive models (GAM) to estimate the cerebral blood flow response. All methods give similar estimates for the mean LI, but error of measurement is much reduced with GAM.

• Publisher: John Wiley & Sons, Inc
• Subject: Brain - diagnostic imaging / Brain - physiology / Brain mapping / Brain research / Design / Doppler effect / Error analysis / Flow velocity / fMRI / fTCD / Functional Laterality - physiology / Functional magnetic resonance imaging / generalized additive model (GAM) / generalized linear model (GLM) / Generalized linear models / Hemispheric laterality / Hemodynamic responses / Humans / Language / laterality / Localization / Magnetic Resonance Imaging / Neuroimaging / Response functions / Statistical methods / Statistical models / Task complexity / Ultrasonic imaging / Ultrasonography, Doppler, Transcranial - methods / Ultrasound / Veins & arteries