Shella Keilholz
Associate Professor
Dr. Keilholz has been working in preclinical imaging for more than twenty years, with the goal of using animal models to improve the analysis of human MRI imaging. Her research uses multimodal approaches to extract information about neural dynamics from functional neuroimaging studies.
404-727-2433
Office Location:
Emory, HSRB W230
University, College, and School/Department
Research Focus Areas:
- Neuroscience
Additional Research:
The goal of my research is to develop a method for mapping spontaneous activity throughout the whole brain with high spatial and temporal resolution, with the intention of using this technique to characterize alterations in dynamic neural activity linked to dysfunction and to identify potential targets for intervention. My primary expertise is in fMRI and functional connectivity mapping, and since my lab was established at Emory, we have focused on obtaining information about the dynamic activity of functional networks from the BOLD signal. Despite BOLD's indirect relationship to neural signals, evidence is growing that the BOLD fluctuations provide information about behaviorally relevant network activity. We take a two-pronged approach to the problem, combining MRI with direct neural measures like electrophysiology and optical imaging in the rodent, or with EEG and behavioral outputs in the human. Our effort to understand the relationship between BOLD and electrical or optical recordings (very different signals that cover very different spatial and temporal scales) has led us to develop new approaches to data analysis that include spectral, spatial, and temporal information. To better understand the large-scale dynamics of brain activity, we have become fluent in network modeling, nonlinear dynamics, and machine learning.
The goal of my research is to develop a method for mapping spontaneous activity throughout the whole brain with high spatial and temporal resolution, with the intention of using this technique to characterize alterations in dynamic neural activity linked to dysfunction and to identify potential targets for intervention. My primary expertise is in fMRI and functional connectivity mapping, and since my lab was established at Emory, we have focused on obtaining information about the dynamic activity of functional networks from the BOLD signal. Despite BOLD's indirect relationship to neural signals, evidence is growing that the BOLD fluctuations provide information about behaviorally relevant network activity. We take a two-pronged approach to the problem, combining MRI with direct neural measures like electrophysiology and optical imaging in the rodent, or with EEG and behavioral outputs in the human. Our effort to understand the relationship between BOLD and electrical or optical recordings (very different signals that cover very different spatial and temporal scales) has led us to develop new approaches to data analysis that include spectral, spatial, and temporal information. To better understand the large-scale dynamics of brain activity, we have become fluent in network modeling, nonlinear dynamics, and machine learning.
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