The Neuroimaging Core functions as a resource for instrumentation, data acquisition, processing, and analysis in support of the experiments conducted in Projects 1 and 2. This core will provide cutting edge neuroimaging advances and computational tools, which are important to optimize data processing. The director of this core, Dr. Thomas Liu, is also the Director of the UCSD Center for Functional Magnetic Resonance Imaging (fMRI) and, therefore, brings to bear the significant existing infrastructure of the UCSD Center for fMRI for this proposal. Moreover, Dr. Liu's expertise in perfusion imaging will help provide analysis approaches to determine whether general differences in blood perfusion across groups account for BOLD fMRI differences during the interoception and cue reactivity tasks, and will ensure high quality neuroimaging data.
The specific aims of this core are: (1) To utilize neuroimaging procedures developed at the UCSD Center for fMRI to provide continued quality control of ongoing experiments.
This aim will help us to optimize our imaging analyses steps and to have explicit quality control implemented similar to that of other large-scale fMRI studies. (2) To provide a core computational infrastructure to standardize and optimize the neuroimaging pipeline. This will help us to compare images obtained for Project 1 with those of Project 2 to better delineate the degree of dysregulated interoception across the addiction cycle. (3) To provide basic and advanced training for all CIDIA associated investigators for neuroimaging acquisition and analysis.
This aim i s focused primarily on combine educational and training activities in the Neuroimaging Core so as to economize our ability to bring in new investigators, maintain high level of expertise among neuroimaging investigators, and incorporate new insights from the literature to optimize the image analysis pathway. By accomplishing these aims, the core will primarily support Projects 1 and 2, which will make it easier and more appropriate to compare data sets across projects. However, we also envision that this core will begin to explore the possibility for future animal neuroimaging, which could be done in a full center extension of this initial project.
Having a centralized core for neuroimaging data helps ensure that the data acquisition, processing, and analysis is done according to the latest standards in this quickly changing field of functional magnetic resonance imaging. Moreover, we hope this core will be a resource for new investigators that are interested in studying how the brain controls the urge to use drugs.
|Blair, Melanie A; Stewart, Jennifer L; May, April C et al. (2018) Blunted Frontostriatal Blood Oxygen Level-Dependent Signals Predict Stimulant and Marijuana Use. Biol Psychiatry Cogn Neurosci Neuroimaging 3:947-958|
|Huang, He; Thompson, Wesley; Paulus, Martin P (2017) Computational Dysfunctions in Anxiety: Failure to Differentiate Signal From Noise. Biol Psychiatry 82:440-446|
|Gowin, Joshua L; May, April C; Wittmann, Marc et al. (2017) Doubling down: increased risk-taking behavior following a loss by individuals with cocaine use disorder is associated with striatal and anterior cingulate dysfunction. Biol Psychiatry Cogn Neurosci Neuroimaging 2:94-103|
|Gowin, Joshua L; Ball, Tali M; Wittmann, Marc et al. (2017) Corrigendum to ""Individualized relapse prediction: Personality measures and striatal and insular activity during reward-processing robustly predict relapse"" [Drug and Alcohol Dependence 152 (2015) 93-101]. Drug Alcohol Depend 175:255|
|Squeglia, Lindsay M; Ball, Tali M; Jacobus, Joanna et al. (2017) Neural Predictors of Initiating Alcohol Use During Adolescence. Am J Psychiatry 174:172-185|
|Paulus, Martin P; Huys, Quentin J M; Maia, Tiago V (2016) A Roadmap for the Development of Applied Computational Psychiatry. Biol Psychiatry Cogn Neurosci Neuroimaging 1:386-392|
|Mackey, Scott; Olafsson, Valur; Aupperle, Robin L et al. (2016) Greater preference consistency during the Willingness-to-Pay task is related to higher resting state connectivity between the ventromedial prefrontal cortex and the ventral striatum. Brain Imaging Behav 10:730-8|
|Harlé, Katia M; Zhang, Shunan; Ma, Ning et al. (2016) Reduced Neural Recruitment for Bayesian Adjustment of Inhibitory Control in Methamphetamine Dependence. Biol Psychiatry Cogn Neurosci Neuroimaging 1:448-459|
|Gowin, Joshua L; Ball, Tali M; Wittmann, Marc et al. (2015) Individualized relapse prediction: Personality measures and striatal and insular activity during reward-processing robustly predict relapse. Drug Alcohol Depend 152:93-101|
|Oosterwijk, Suzanne; Mackey, Scott; Wilson-Mendenhall, Christine et al. (2015) Concepts in context: Processing mental state concepts with internal or external focus involves different neural systems. Soc Neurosci 10:294-307|
Showing the most recent 10 out of 31 publications