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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.
Addiction: smoking
Adolescent Brain Development
pubertal influences
sex differences in maturation
Adolescent Addiction
Technology Development
new methods of combining structural (s) and functional (f) MRI
Real Time analysis of fMRI data (identifying mental states while scanning)
New methods for combining EEG and fMRI (so they better inform one another) |
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Pamela Douglas, Ph.D.
As a biomedical engineer I seek to apply the most advanced concepts in modern engineering to the exceptionally challenging task of forming a better understanding of the human brain, perhaps the single most sophisticated information processing structure. To do this I have gained a broad knowledge in both engineering and neuroscience. My PhD work under the guidance of Mark S. Cohen and Joseph DiStefano, III focused on computational neuroscience and mathematical modeling of both sparse and data-rich functional neuroimaging data sets. Recently, I have become interested in understanding how these concepts can be applied towards understanding functional connectivity networks that are involved in attention. Specifically, I have recently developed a machine learning protocol towards classifying individuals as either typically developing or having an autism spectral disorder using resting state functional connectivity data. My current goal is to understand how hypnosis modulates functional brain networks involved in attention and stimuli saliency. |
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Arpana (Annie) Gupta
Research Interests: Racial/ethnic health disparities; with a focus on discrimination processes, cultural variables and the stereotypes associated with health outcomes and help seeking attitudes among various ethnic/racial groups in America. Additional interests include investigating how socio-cultural factors (e.g. immigration status, generation status, acculturation, religion, ethnic identity, etc.) can lead to health disparities among diverse ethnic and racial groups, with a focus on integrating behavioral, biomarkers, and imaging modalities. |
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Dianna Han
As a Ph.D candidate and a full-time engineer, Dianna is currently working on her dissertation in these areas:
- fMRI data analysis using temporal pattern modeling
- Real-time craving state classification for fMRI
- Fast and accurate cognitive state detection with multi-modal measurements (EEG and fMRI)
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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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Given that modern imaging approaches have proven remarkably powerful in exposing plastic changes from even short term behavioral interventions in a variety of presenting clinical problems, I am interested in further understanding the windows that neuroimaging can provide into behavioral disorders and illuminating the physiological effects of specific intermediations, so as to better guide and focus treatments. As a psychologist, my interests focus on developing empirically supported treatments for patients experiencing impulse control deficits (e.g., pathological gambling, hypersexual behavior) and other addictive behaviors. As part of this work, I am seeking to understand the neurobiological mechanisms associated with changes in the brain in response to Mindfulness Based Stress Reduction (MBSR) in patients seeking help for pathological gambling, hypersexual behavior, and chemical dependency
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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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Hongjing is a 3d year BME graduate student interested in:
- Integration of multimodal neuroimaging technology (eg., EEG, MRI)
- Real Time analysis and classification of MRI data
- Artifact Detection for MRI and EEG
- Fast MRI acquisition technique
- MRI Pulse Sequence Programming
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 PAST MEMBERS and STILL FRIENDS |
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