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Hello! My name is Vishal Easwar. I am a junior from Greensboro, North Carolina pursuing a B.S. in psychology and neuroscience as well as a creative writing minor in the fiction concentration. My passions have evolved since childhood, becoming more refined in high school and finally emerging in college, but two remained constant: psychology and working with children. I realized how much I liked psychology when I took AP Psychology in tenth grade, amazed at the breadth of topics and how applied they were. I was finally beginning to get answers to the questions of “why” and “how” I had about human behavior. Through conducting science fairs and completing the AP Capstone program in high school, I also began to realize that I enjoyed research and the process of inquiry. Thanks to my experiences with the AP Capstone program, Dr. Brenna Maddox’s Foundation of Hope study, and the Behavior Consultation and Psychological Services (BCPS) clinic in Clemmons, North Carolina, I was able to identify the precise research interests I am delving into with my internship in the current cohort and hopefully beyond.

As a research assistant with Dr. Maddox, I helped collect biomarkers of suicide risk in female autistic adolescents, and as a behavior technician at BCPS, I had the opportunity to implement ABA therapy to help autistic children learn new skills. These experiences reinforced my desire to help children, and specifically learning and bringing the best out of their individuality; being able to understand these children on a personal level and how to best help them, as a friend and as a professional, is something I hope to carry forward throughout my career. I have fostered an interest in applying this motivation to the fields of cognitive and educational psychology through my independent research projects. In high school, I surveyed students about their perceptions of intelligence; having observed firsthand the effects of poor student self-concept, I wanted to better understand and convey their importance. Building on this study and the research skills I gained, I am currently extending the survey to both students and teachers as a function of school socioeconomic status.

Throughout this process, I have developed a passion for developing research to build an equitable learning environment and equip students with the beliefs and skills they need to succeed. By understanding the content of student and teacher beliefs from an educational psychology perspective, I hope to then address them from a cognitive psychology and neuroscience perspective. For instance, in the future, I plan to study emotion regulation during learning to help students cope with failure during learning and identify at-risk students by illuminating a possible biological basis of emotion regulation using neuroimaging. To gain an understanding of neuroimaging, I applied for the Gil Internship and am currently interning at the Neuro Image Research and Analysis Laboratories (NIRAL) under Dr. Martin A. Styner.

At NIRAL, Dr. Styner uses computer science to develop statistical models for analyzing neuroimaging as applied to different disorders, such as Alzheimer’s disease. The project I am working on focuses on autism spectrum disorder, and specifically a biomarker of autism that has recently illuminated by novel research at UNC: cerebrospinal fluid (CSF), the fluid around and within the brain that cushions it from injury, provides it nutrients, and removes toxic waste. Specifically, increased levels during early development of the local extra-axial CSF (EA-CSF), which is the CSF around the brain in cavities called ventricles, has been associated with not only diagnosis of autism, but also heightened severity of symptoms.

My responsibilities at NIRAL include performing quality control and data analysis. First, I used software programs called ShapePopulationViewer and ITK-SNAP to parse through the MRI data of infant participants. This MRI data was overlaid with a statistical model developed by Dr. Styner and his research team to assess the likelihood of there being EA-CSF in different parts of the brain. This likelihood is based on other parts of the participant’s brain, such as how much white and gray matter they have. Looking at the coronal, sagittal, and horizontal (i.e., 3D) views of the brain, I used ShapePopulationViewer to identify cases where the MRI and subsequent EA-CSF data appeared to be inaccurate to improve the quality of our data. For instance, if an individual did not show developmentally appropriate changes in predicted EA-CSF over time, their case was marked for further investigation. Thereafter, using ITK-SNAP, I looked at each of these suspicious cases to see if their MRI scans came out well. If they did not come out well, then those cases were disregarded for data analysis.

Currently, I am studying trends in the cases that did come out well, both across the entire sample of MRI data as well as within individuals that we were able to get multiple MRI scans of, so that we can see how the levels of predicted EA-CSF in those individuals changed over time. This analysis involves dividing the brain into sections that we can separately analyze for EA-CSF trends. This work builds on past research at NIRAL of developing and applying a statistical model to compute EA-CSF in infants; now, we are applying an even more accurate model and using a larger participant sample (ranging from 1-month-olds to even 72-month-olds)! With these improved tools, we hope to elevate our understanding of the developmental changes of EA-CSF to better use it as potential biomarker of EA-CSF in autism. Being able to use EA-CSF as a biomarker would allow clinicians to identify at-risk infants and thus accordingly plan for interventions that can improve their developmental outcomes – urgent work considering the current lack of concrete biological means to accurately anticipate and diagnose autism.

My research experience at NIRAL has been incredible so far! Not only have I broadened my knowledge of neuroimaging and its merging with statistics – from the different ways one can divide the brain for data analysis, to even the simpler considerations of having to keep toddlers still during scanning – but I also better understand the dynamics of a research lab. NIRAL, for instance, involves the coordination of psychologists, neuroscientists, data analysts/statisticians, and computer scientists! I am extremely grateful for the guidance of Dr. Styner, Dr. Buzinski, Emily Dolegowski, and all those who have made this journey possible. Looking ahead, I feel that my internship experience has given me the foundational skills and vision to succeed as a researcher in the next steps of my career path.










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