scholarly journals Logistic Regression Algorithm Differentiates Gulf War Illness (GWI) Functional Magnetic Resonance Imaging (fMRI) Data from a Sedentary Control

2020 ◽  
Vol 10 (5) ◽  
pp. 319
Author(s):  
Destie Provenzano ◽  
Stuart D. Washington ◽  
Yuan J. Rao ◽  
Murray Loew ◽  
James N. Baraniuk

Gulf War Illness (GWI) is a debilitating condition characterized by dysfunction of cognition, pain, fatigue, sleep, and diverse somatic symptoms with no known underlying pathology. As such, uncovering objective biomarkers such as differential regions of activity within a Functional Magnetic Resonance Imaging (fMRI) scan is important to enhance validity of the criteria for diagnosis. Symptoms are exacerbated by mild activity, and exertional exhaustion is a key complaint amongst sufferers. We modeled this exertional exhaustion by having GWI (n = 80) and sedentary control (n = 31) subjects perform submaximal exercise stress tests on two consecutive days. Cognitive differences were assessed by comparing fMRI scans performed during 2-Back working memory tasks before and after the exercise. Machine learning algorithms were used to identify differences in brain activation patterns between the two groups on Day 1 (before exercise) and Day 2 (after exercise). The numbers of voxels with t > 3.17 (corresponding to p < 0.001 uncorrected) were determined for brain regions defined by the Automated Anatomical Labeling (AAL) atlas. Data were divided 70:30 into training and test sets. Recursive feature selection identified twenty-nine regions of interest (ROIs) that significantly distinguished GWI from control on Day 1 and 28 ROIs on Day 2. Ten regions were present in both models between the two days, including right anterior insula, orbital frontal cortex, thalamus, bilateral temporal poles, and left supramarginal gyrus and cerebellar Crus 1. The models had 70% accuracy before exercise on Day 1 and 85% accuracy after exercise on Day 2, indicating the logistic regression model significantly differentiated subjects with GWI from the sedentary control group. Exercise caused changes in these patterns that may indicate the cognitive differences caused by exertional exhaustion. A second set of predictive models was able to classify previously identified GWI exercise subgroups START, STOPP, and POTS for both Days 1 and Days 2 with 67% and 69% accuracy respectively. This study was the first of its kind to differentiate GWI and the three sub-phenotypes START, STOPP, and POTS from a sedentary control using a logistic regression estimation method.

1998 ◽  
Vol 41 (3) ◽  
pp. 538-548 ◽  
Author(s):  
Sean C. Huckins ◽  
Christopher W. Turner ◽  
Karen A. Doherty ◽  
Michael M. Fonte ◽  
Nikolaus M. Szeverenyi

Functional Magnetic Resonance Imaging (fMRI) holds exciting potential as a research and clinical tool for exploring the human auditory system. This noninvasive technique allows the measurement of discrete changes in cerebral cortical blood flow in response to sensory stimuli, allowing determination of precise neuroanatomical locations of the underlying brain parenchymal activity. Application of fMRI in auditory research, however, has been limited. One problem is that fMRI utilizing echo-planar imaging technology (EPI) generates intense noise that could potentially affect the results of auditory experiments. Also, issues relating to the reliability of fMRI for listeners with normal hearing need to be resolved before this technique can be used to study listeners with hearing loss. This preliminary study examines the feasibility of using fMRI in auditory research by performing a simple set of experiments to test the reliability of scanning parameters that use a high resolution and high signal-to-noise ratio unlike that presently reported in the literature. We used consonant-vowel (CV) speech stimuli to investigate whether or not we could observe reproducible and consistent changes in cortical blood flow in listeners during a single scanning session, across more than one scanning session, and in more than one listener. In addition, we wanted to determine if there were differences between CV speech and nonspeech complex stimuli across listeners. Our study shows reproducibility within and across listeners for CV speech stimuli. Results were reproducible for CV speech stimuli within fMRI scanning sessions for 5 out of 9 listeners and were reproducible for 6 out of 8 listeners across fMRI scanning sessions. Results of nonspeech complex stimuli across listeners showed activity in 4 out of 9 individuals tested.


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