| dc.description.abstract | Functional MRI is a non-invasive imaging modality that allows a researcher or clinician to quantify the activity in the brain that is associated with particular functions and behaviors based on region-specific blood-oxygen variations. Yet, as participants are in the MRI scanner, it has been found that many lose wakefulness within the first few minutes of the scan. The impact that naturally fluctuating levels of wakefulness (vigilance) have on fMRI data and on the outcomes of fMRI analyses have only recently gained attention in the field. Understanding how vigilance manifests in fMRI data may be essential since fatigue and disturbed sleep can be linked to disorders such as Epilepsy, Alzheimer’s Disease, mood disorders, traumatic brain injury, and more.
In this work, we aim to advance current knowledge of how vigilance fluctuations are expressed in fMRI data and build tools for modeling these state changes. In one avenue of work, we investigated a method that allows a measure of vigilance to be derived from previously collected fMRI datasets, so that future analyses can incorporate potential effects of (and information within) these state changes. The generalization of this tool was then evaluated across patient populations, data acquisition parameters, and processing methods, and was validated across several gold-standard vigilance measures.
The need to understand how effects of vigilance may relate to variability in fMRI data analyses has become increasingly important, particularly as the field has moved toward using functional MRI to characterize individuals rather than only population averages. Characterizing the role of vigilance could be key for developing neural biomarkers, as well as improving surgical outcomes, medication administration, or overall treatment in many different clinical populations. | |
