1. Neural circuitry underlying compulsive drug use behavior in rat model We recently demonstrated, in a human study, that the imbalance between a go circuit (the ventral striatum- anterior prefrontal pathway) and a stop circuit (the ventral striatum-dorsal anterior cingulate pathway) predicts compulsive cocaine using behaviors (Hu et al., 2015 JAMA Psychiatry). Compulsive drug seeking and taking behaviors, the defining features of drug addiction, are seen in both human and animal individuals addicted to drugs. While human studies are limited by the incapability of tracking the development of the disease, animal models allow us to monitor addiction processes from the initial drug use to the final compulsive stage as well as changes of underlying neural substrates. Causal relationships between drug intake, neural circuitry changes and compulsive behavior perseveration can be established by controlling experimental settings such as parameterization of drug does delivery, longitudinal monitoring of neural activity using fMRI, and in vivo modulation of specific neural circuits using optogenetics. Based on our previous work, we proposed these go and stop circuits as potential treatment targets. We now extend this work by transferring this go-stop model back to animals. We hypothesize that the restoration of go-stop imbalance will suppress compulsive drug seeking and taking behaviors. To test this hypothesis, we apply state-of-art MRI techniques, optical imaging, and optogenetic stimulation to a well-established compulsive drug seeking and taking animal model. Specifically, we use longitudinal resting state fMRI, structural MRI and MRS to identify the go and stop circuits in rats, and use dual optogenetic stimulation to suppress the go circuit and enhance the stop circuit at the same time, consequentially restoring the balance between them more effectively than targeting only one side of the pair. Data collection for the first phase aiming to identify neural circuits using fMRI will be completed in the end of September. Optical imaging and optogenetic experiments are under preparation. 2. Effects of nicotine exposure and withdrawal on dynamic functional connectivity of the brain in adult rats Dynamics of resting-state functional connectivity are assessed in adult rats exposed to nicotine for two weeks following a withdrawal of two weeks. Using a moving-window technique, dynamic functional connectivity in the whole brain was computed. A K-mean clustering was then used to identify states of functional connectivity in the dynamics. Among four states identified in our data, the occurrences of two states were found highly related to the nicotine dependence as measured by somatic signs based on previous literature. Notably, transitions between the two states were also significant related to the nicotine dependence. These results provide initial evidence that nicotine addiction is related to specific dynamic patterns of communication between brain regions. (Manuscript in preparation) 3. Effects of nicotine exposure on adolescent rats This project seeks to describe and understand adolescent and adult nicotine withdrawal behavior. The first phase of the project examined dose-dependent changes in the somatic and affective signs of withdrawal in adolescents and adults exposed to nicotine. Adolescents began treatment at three different developmental stages, early, mid and late adolescence, to further understand the effects of age of nicotine exposure on withdrawal behaviors. Preliminary results from this experiment were presented at an internal poster session at NIDA. The final results of this behavioral experiment will be presented at the Society for Neuroscience conference in November 2016 and are currently undergoing analysis for eventual publication submission. Preliminary analyses indicate that adolescent and adult rats display different withdrawal behaviors, and adolescents do not consistently display the affective signs of withdrawal. The second phase of the experiment will examine changes in resting state functional connectivity, anatomical connections as well as levels of inhibitory and excitatory neurotransmitters in adolescents and adults exposed to nicotine. The second phase will build on the results of the first phase, with the addition of neuroimaging to the previous experimental paradigm. This experiment is currently ongoing, and data continue to be collected. 4. Functional connectivity with the retrosplenial cortex predicts cognitive aging in rats Changes in the functional connectivity of large scale brain networks are a prominent feature of brain aging, but defining their relationship to variability along the continuum of normal and pathological cognitive outcomes has proved challenging. Here we took advantage of a well-characterized rat model that displays substantial individual differences in hippocampal memory during aging, uncontaminated by slowly progressive, spontaneous neurodegenerative disease. By this approach, we aimed to interrogate the underlying neural network substrates that mediate aging as a uniquely permissive condition and the primary risk for neurodegeneration. Using resting state BOLD fMRI and a restrosplenial/posterior cingulate cortex seed, aged rats demonstrated a large-scale network that had a spatial distribution similar to the default mode network (DMN) in humans, consistent with earlier findings in younger animals. Between-group whole brain contrasts revealed that aged subjects with documented deficits in memory (aged-impaired; AI) displayed widespread reductions in cortical functional connectivity, prominently including many areas outside the DMN, relative to both young adults (Y) and aged rats with preserved memory (aged-unimpaired; AU). Whereas functional connectivity was relatively preserved in AU rats, they exhibited a qualitatively distinct network signature, comprising the loss of an anti-correlated network observed in Y adults. Together the findings demonstrate that changes in resting state functional connectivity are specifically coupled to variability in the cognitive outcome of aging, and that successful neurocognitive aging is associated with adaptive remodeling, not simply the persistence of youthful network dynamics. (Submitted for publication)
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