Elena Rykhlevskaia, phd
Postdoctoral Fellow
I am interested in connectivity aspects of brain organization. I develop data mining algorithms for analysis and modeling of in vivo human brain imaging data to understand how different brain areas interact as part of a large-scale network. On the Stanford campus, I work with two brain imaging research groups: the Vision, Imaging Science and Technology Activities Lab, and the Cognitive and Systems Neuroscience Lab. To capture the structural back bone of brain networks, we use diffusion tensor imaging (DTI). To infer activity synchronization and information flow among the key network nodes (at rest, or when performing a task), we employ functional magnetic resonance imaging (fMRI). I am particularly fascinated with the changes in structural and functional aspects of brain network connectivity due to brain development and aging. Subject populations I am currently studying include healthy elderly adults, children with difficulties in learning math, and patients with Cushing's syndrome.
Research Interests:
- Structural and functional neuroimaging (optical imaging, functional magnetic resonance imaging, diffusion tensor imaging); multimodality integration of neuroimaging data
- Individual differences (aging, developmental) in anatomical, functional and effective connectivity in the brain
- Statistical inference and modeling; latent variable modeling; multivariate analysis
Educational Background:
| 2001-2006 | Ph.D. in Quantitative Psychology, University of Illinois at Urbana-Champaign. Dissertation: Anatomically informed models of functional connectivity in the brain. Research Advisor: Prof. Gabriele Gratton. Minors: Brain and Cognition, Statistics. |
| 2002-2004 | M.Sc. in Applied Statistics with specialization in Psychometrics and Behavioral Statistic, University of Illinois at Urbana-Champaign. |
| 1999-2001 | M.Sc. in Computer Science (as a joint degree), Lomonosov Moscow State University. |
| 1996-2001 | Diploma (with honors) in Industrial/Organizational Psychology, Lomonosov Moscow State University, Russia. Thesis: A method for scaling nonverbal stimuli on the Internet: technological problems and future prospects. |
Selected Publications:
- Gratton, G., Wee, E., Rykhlevskaia, E., Leaver, E., Fabiani, M. (2008). Does white matter matter? Spatiotemporal dynamics of task switching in aging. Journal of Cognitive Neuroscience.
- Gordon, B., Rykhlevskaia, E., Brumback, C., Lee, Y., Elavsky, S., Konopack, J., McAuley, E., Kramer, A., Colcombe, S., Gratton, G., Fabiani, M. (2008). Neuroanatomical correlates of aging, cardiopulmonary fitness level, and education. Psychophysiology.
- Ombao, H., Shao, X., Rykhlevskaia, E., Fabiani, M. and Gratton, G. (2008). Spatio-Spectral Analysis of Brain Signals. Statistica Sinica, 18 (4).
- Rykhlevskaia, E., Gratton, G., Fabiani, M. (2008). Combining structural and functional neuroimaging data for studying brain connectivity: A review. Psychophysiology, 45, 173-182.
- Regenwetter M., Rykhlevskaia, E. (2007). A general concept of scoring rules: General definitions, statistical inference, and empirical illustrations. Social Choice Welfare, 29: 211-228.
- Rykhlevskaia, E., Fabiani, M., Gratton, G. (2006). Lagged covariance structure models for studying functional connectivity in the brain. NeuroImage, 30: 1203-1218.
- Regenwetter, M., Rykhlevskaia, E. (2004). On the (numerical) ranking associated with any finite binary relation. Journal of Mathematical Psychology, 48: 239-246.
