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Activity Number:
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576
- Brain Connectivity Studies
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Type:
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Contributed
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Date/Time:
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Wednesday, July 31, 2019 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistics in Imaging
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Abstract #306629
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Title:
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A Spatial-Temporal Model for Detecting the Effect of Cocaine Dependence on Brain Connectivity
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Author(s):
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Jifang Zhao* and Montserrat Fuentes and Liangsuo Ma and Frederick Moeller and Qiong Zhang
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Companies:
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Virginia Commonwealth University and Virginia Commonwealth University and Virginia Commonwealth University and Virginia Commonwealth University and Clemson University
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Keywords:
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Functional connectivity;
drug abuse;
high dimensionality;
fMRI;
spatiotemporal models
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Abstract:
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Drug addiction can cause many health problems in both physics and psychology, which gives rise to a series of serious social problems. Researchers are interested in the association between long-term drug usage and brain functional connectivity abnormal. Brain connectivity obtained from resting state data promotes a variety of fundamental understandings in Neuroscience. Due to the complex correlation structure and large dimensionality, fMRI data are hard to analyze. We propose a spatial-temporal model for multi-subject Neuroimage data which could efficiently incorporate spatial-temporal dependence of brain measurements to improve the accuracy in statistical inference. Our method is used to (1) identify significant brain connectivities, and (2) detect the effect of cocaine dependence on brain connectivities between different brain regions. Our results show significant brain connectivities. We discover brain connectivities differences between cocaine-dependent and control groups.
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Authors who are presenting talks have a * after their name.
