Lin Li

Graduation Semester and Year




Document Type


Degree Name

Doctor of Philosophy in Biomedical Engineering



First Advisor

Hanli Liu


To better understand the age effect on neural correlates under risk decision-making stimulations, studies using advanced neuroimaging with a sufficient statistical power are desired. Diffuse optical tomography (DOT) of human brain functions is an emerging non-invasive neuroimaging technology. Compared to magnetic resonance imaging (MRI), DOT is more cost-effective, more portable, and easier to conduct studies targeting on different age groups. However, current DOT is limited by its low spatial resolution and depth accuracy. It is thus imperative to develop a technique that can improve imaging quality of DOT and be used to investigate age-dependent human brain functions under risk decision making. My doctoral study targets the needed development with three specific aims. The first aim is to develop human brain atlas-guided diffuse optical tomography (atlas-DOT) integrated with a 3D forward modeling technique and depth compensation algorithm, which greatly improves the image quality and depth accuracy in DOT. In my second aim, I utilize statistical modeling to implement a general linear model (GLM) with atlas-DOT to obtain more accurate identification of brain activation regions under a risk decision-making protocol. A total of 100 subjects (40 young adults; 60 older adults) have participated in my functional DOT measurements under the Balloon Analogue Risk Task (BART), a conventional risk decision-making stimulation protocol. The results indicate that age differences exist in cortical activation patterns, brain activation amplitudes, and behavior-brain function correlations. In particular, larger cortical activation with reduced amplitudes in the prefrontal cortex (PFC) are observed in older adults, not in young adults, when they face the same decision-making task. Behavior-brain function correlations indicate that young adults are more “risk-taking” while older adults tend to be more “risk-averse”. In the third aim, graph theory analysis (GTA) has been implemented with atlas-DOT to further quantify the resting-state functional brain connectivity between two age groups. Age-related differences are found in resting-state brain network metrics: Older adults show reduced global efficiency and hub numbers in prefrontal regions. My dissertation is the first study using the fDOT technique to investigate the aging and gender effect on brain responses under risk decision making, and it is also the first time to combine GTA with atlas-DOT to investigate brain network changes in young and older adults. Overall, my dissertation demonstrates the high feasibility of atlas-DOT to be used for assessment of age-related brain activations in both resting-state and under risk decision making.


Biomedical Engineering and Bioengineering | Engineering


Degree granted by The University of Texas at Arlington