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When MRI data are observed at rest, signal fluctuations continue to appear in the time series. Independent Components Analysis offers a means for the neuroimaging data to effectively nominate their own self-organized spatio-temporal structure. Anderson has shown shown that when descriptors of the temporal dynamics are used as features in non-linear machine learning contexts, they can be used to perform high reliability classification of schizophrenics from normals – without reference to the actual spatial distribution of the signal changes. The latter mitigates much of the challenge of comparing brains across individuals, as the anatomical variance is suppressed. Dr. Anderson now has promising results as well using EEG data as inputs in a study of the pharmacologic efficacy of anti-depressive medications. |
Jennifer Bramen, Ph.D. |
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Pamela Douglas |
Michael Durnhofer |
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Dianna Han |
Catherine Hubbard, Ph.D.
Catherine Hubbard is a postdoctoral fellow at UCLA David Geffen School of Medicine, Division of Digestive Diseases and the Center for Neurobiology of Stress. Dr. Hubbard received her BS in Biological Psychology from The University of California, Davis and her MA in Psychology from California State University, Chico. In 2008, she obtained her doctorate in Neuroscience from The University of Wyoming and was also awarded an NIH Gastroenterology Training Grant (Kirschstein-NRSA). Dr. Hubbard takes a multidisciplinary and systems-level approach to her research and has a strong background in electrophysiological methods and basic neuroscience techniques using both human and animals models. Currently her work is focused broadly toward understanding the neurobiology underlying emotional modulation of pain and nociception. She is working on several research projects investigating the effects of endogenous pain modulation and enhanced limbic responsiveness to emotionally-salient and disease-relevant psychological stressors in patients with Irritable Bowel Syndrome (IBS) utilizing a combination of psychophysiological, behavioral, and neuroimaging techniques. |
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Wesley is an MSTP student interested in mathematical methods related to high dimensional systems and stochastic modeling. His past work includes applications of machine learning, psychometric function modeling, multidimensional scaling, m-sequences, knowledge based potentials, and network theory. He has primarily worked with applications in fMRI and has also worked with psychometrics, genetics and protein folding. Medically, he is interested in radiology and neurology. |
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Edward is an undergraduate student at UCLA pursuing a double major in Bioengineering and Computational & Systems Biology. About to begin his fifth year of study, he is interested in research that has the potential to improve human-machine interactions. Improving HMI starts with furthering our understanding of the neural mechanisms of cognition. Research leveraging multi-modal neuroimaging (EEG, fMRI) is one way to accomplish this. He was first introduced to the application of MRI for brain studies while volunteering at LONI at UCLA and EEG and brain-state classification while interning at NeuroSky. While looking forward to enrolling in a graduate program in the coming years, he stays busy exploring LA and staying active. |
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Attention is what determines the contents of our mind. Self-control is our ability to resist an automatic behavior and do "something else". My research aims to understand how - in terms of brain processes - attention mediates, modulates and interferes with self-control. I examine how external cues influence brain activity and behavior by eliciting in our mind a learned set of behaviors, both when this is desired (e.g., seeing a stop sign) and when it is not (e.g., approaching a cross-street that used to have a stop sign). My aim is to understand the dynamics (time and space) of the neural interactions that underlie these processes. To this end I combine multi-modal neuroimaging technology (e.g., EEG, fMRI) with multivariate analytical techniques. |
Wei Li
I am currently a first year Neuroscience IDP graduate student entering the Neuroimaging track. I graduated last year from Caltech with a B.S. in Computation and Neural Systems. I first conducted EEG experiments on visual processing in London at UCL. Most recently, I worked for Dr. Shimojo at Caltech for two years using EEG and motion tracking cameras to try to find neural correlates of implicit coordination in people interacting in a finger game. I am interested in:
- studying brain dynamics & behavior on a macroscopic scale using EEG, fMRI and othe tools,
- integrating the data from these different modalities to better inform analyses and
- specifically combining EEG with fMRI to explore the rapid brain dynamics underlying cognitive tasks.
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Malina coordinates lab activities, manages grants and interactions with the investigational review board, directs purchasing, prepares filings to funding bodies and facilitates all management activities in the group.
"I dig food. I sing into toilets. I love watching highly-choreographed musical numbers spontaneously occur while shopping at Target. I love fighting with the mattress monster in the mornings and dodging the body-snatcher in the kitchen. Also, it would appear that I'm "cute", but that's a biased opinion." |
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 PAST MEMBERS and STILL FRIENDS |
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