Awarded PDF Collaborative Research Grants

We regard the brain as a scientist that formulates a hypothesis or prediction about how the world works, collects sensory data, estimates a prediction error, and updates the prediction. This scientist-like mechanism is broken down in schizophrenia, causing cognitive symptoms such as failures in response inhibition (e.g., braking a car when the traffic light turns red) and in temporal prediction (e.g., predicting the collision time in a rear-end collision). Accurate processing of dynamic visual information is crucial for successful performance in these two tasks. We suspect that this sort of processing is deficient in schizophrenia and that the responsible neural mechanism is located within a circuit comprised by the insular cortex and the visual cortex. This project investigates the role that eye movements might play in the (sketched) abnormal scientist-like mechanism in first episode psychosis when patients perform a response inhibition task combined with a temporal prediction task – predicting the collision time of two billiards balls. We expect that a combination of ultra-high field (7T) fMRI, eye tracking, and computational models of both behavioral and imaging data will shed lights on how abnormal processing in the insular-visual network relates to the cognitive symptoms of schizophrenia.

Studying the brain of NHP offers crucial insights into the mechanism of our own and various neurological conditions. With good spatial resolution, functional magnetic resonance imaging (fMRI) is a staple non-invasive technique to study neural functions, but the speed of imaging, or temporal resolution, is still restricted. Unfortunately, other standard non-invasive neuroimaging tools also fail to provide high spatial and temporal resolution simultaneously to accurately capture neural activations in detail. Recent developments in functional ultrasound (fUS) imaging has demonstrated great potential for neuroimaging with both superior spatial and temporal resolutions. Leveraging the Doppler effect, the technique can also measure blood volume changes due to neural activities, similar to fMRI. This project will establish fUS as a powerful non-invasive tool to study brain function for NHP, by comparing the performance of fUS with the gold-standard fMRI.

Parkinson's disease (PD) is a common and debilitating brain disease with characteristic motor symptoms like tremor, rigidity, and slowed movements. These symptoms are caused by a loss of dopamine-producing brain cells, and medications that increase levels of dopamine in the brain, like levodopa, provide patients with relief from the motor symptoms of PD. In addition to the motor symptoms, recent research has started to focus on understanding the cognitive symptoms that also occur with PD which can include impairments in attention and cognitive flexibility. Moreover, studies have shown that the medications that improve the motor symptoms of PD might make some of the cognitive symptoms worse. As a first step toward understanding how and why this happens, we are taking a translational approach to studying PD by examining the effects of both the disease and medication on cognitive functions in people with PD and a mouse model of PD. This study is unique because it utilizes touchscreen technology to deliver the exact same cognitive tasks to both people and mice, which will allow us to make direct comparisons. These comparisons will provide an important foundation for future studies of the mechanisms underlying the cognitive effects of PD.