Brain imaging is an emerging neuroscientific tool that has become central to characterizing the pathophysiology of drug addiction. Structural and functional brain imaging studies have contributed to an understanding of the component neural systems and cognitive processes that mediate maladaptive drugseeking, risky choice, and avoidant behaviors, including those related to learning and memory. Due to the rapid pace of imaging research, the cost of the studies, the need to increase statistical power, and the complexity of the data collected, it is vital to share existing neuroimaging data sets with other researchers to facilitate scientific discovery into the causes and consequences of drug-related behaviors. This proposal is a one-year administrative supplement to a NIDA-funded R01 grant to establish a public data repository on brain imaging studies related to motivated learning and memory (LAM). Structural and functional imaging data collected as part of the parent grant will be shared and linked to another public repository of resting state data in addictive disorders (RAD). Some unique features of the data to be shared include the focus on LAM processes, high-resolution functional imaging of medial temporal, striatal, and frontal regions involved in drug addiction, and a core set of reward and punishment-related tasks and manipulations suitable for meta-analysis. Intellectual property rights and other regulations for data access and publication will be developed, and database linking structures will be created. While early attempts to establish large, monolithic brain imaging data repositories failed due to problems of scale and maintenance, we envision an alternate approach of linked ?niche? databases whose organization is inspired by brain architecture and social networks.

Public Health Relevance

In drug addiction, learning and memory systems become sensitized to reward and punishment cues in the environment. As a result, reward-seeking and avoidant behaviors become reinforced that culminate in maladaptive health consequences. Brain imaging studies provide a tool to link these behaviors to specific neural systems and can provide insight into novel treatments. Because these data sets are complex to assemble and expensive to conduct, it is important to share data that has been collected with other researchers. The proposed research activities will impact public health by providing a resource to the scientific community -- a publically-available brain imaging database -- that can speed discovery of the role of learning and memory systems in drug addiction and related disorders.

National Institute of Health (NIH)
National Institute on Drug Abuse (NIDA)
Research Project (R01)
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Special Emphasis Panel (ZDA1 (07))
Program Officer
Grant, Steven J
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Duke University
Other Basic Sciences
Schools of Arts and Sciences
United States
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Dunsmoor, Joseph E; Ahs, Fredrik; Zielinski, David J et al. (2014) Extinction in multiple virtual reality contexts diminishes fear reinstatement in humans. Neurobiol Learn Mem 113:157-64
Green, Steven R; Kragel, Philip A; Fecteau, Matthew E et al. (2014) Development and validation of an unsupervised scoring system (Autonomate) for skin conductance response analysis. Int J Psychophysiol 91:186-93
Dunsmoor, Joseph E; Kragel, Philip A; Martin, Alex et al. (2014) Aversive learning modulates cortical representations of object categories. Cereb Cortex 24:2859-72
Dunsmoor, Joseph E; LaBar, Kevin S (2013) Effects of discrimination training on fear generalization gradients and perceptual classification in humans. Behav Neurosci 127:350-6
Kragel, Philip A; Labar, Kevin S (2013) Multivariate pattern classification reveals autonomic and experiential representations of discrete emotions. Emotion 13:681-90
Murty, Vishnu P; Ballard, Ian C; Macduffie, Katherine E et al. (2013) Hippocampal networks habituate as novelty accumulates. Learn Mem 20:229-35
Dunsmoor, Joseph E; LaBar, Kevin S (2012) Brain activity associated with omission of an aversive event reveals the effects of fear learning and generalization. Neurobiol Learn Mem 97:301-12
Prince, Steven E; Thomas, Laura A; Kragel, Philip A et al. (2012) Fear-relevant outcomes modulate the neural correlates of probabilistic classification learning. Neuroimage 59:695-707
Dunsmoor, Joseph E; Martin, Alex; LaBar, Kevin S (2012) Role of conceptual knowledge in learning and retention of conditioned fear. Biol Psychol 89:300-5
Whitford, T J; Mathalon, D H; Shenton, M E et al. (2011) Electrophysiological and diffusion tensor imaging evidence of delayed corollary discharges in patients with schizophrenia. Psychol Med 41:959-69

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