NUR 3.426
Cancer Neuroscience Lab Webpage
Biography
Dr. Kesler is a cognitive neuroscientist with specific expertise in neuroimaging, neuropsychology, biostatistics, machine learning, and computer programming. Her research program focuses on the neural mechanisms of cancer-related cognitive neurotoxicities including both clinical and preclinical studies that involve translational approaches for measuring the functional and structural connectome in both humans and rodents using neuroimaging. The overarching goals of her work concern the neurobiologic subtyping of chemotherapy-related cognitive impairments as well as neuroimaging-based prediction of cognitive-behavioral outcomes, survival and treatment response in patients with cancer across the lifespan.
Publications and Projects
Current Funding
- R01CA226080 (PI) "Predicting Long-Term Chemotherapy-Related Cognitive Impairment"
- R01CA172145(PI) "Very Long-Term Neurocognitive Outcomes in Breast Cancer Survivors"
- R01CA208371(Co-I) "Targeting Mitochondrial Damage and Neuroinflammation to Prevent Chemobrain
Research Resources and Data
Software
We have developed several software toolboxes for conducting connectome and machine learning analyses
https://github.com/srkesler/bnets
Predictive Models
We have developed preliminary models for predicting cancer-related cognitive outcomes
- Predicting cognitive impairment from baseline resting state fMRI (Kesler, SR, et al. 2017. Front Hum Neurosci, 11, pp. 555)
- Predicting probability of Alzheimer’s disease from T1 weighted MRI (Kesler, SR, et al. 2017. Alzheimers Dement (Amst), 9, pp. 67-75.)
Data
Transgenic 5XFAD and non-transgenic functional and structural connectome data from Kesler, SR, et al. 2018. Netw Neurosci, 2, pp. 241-258.