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“Cocaine generates drug-seeking behavior by creating long-lasting changes in the reward pathway. The role of the growth factor, brain-derived neurotrophic factor (BDNF) in facilitating these changes was investigated in the present report with a genetic rat model. Using conditioned place preference, the current study investigated the hypothesis that a partial knockout of the BDNF gene in rats (BDNF+/-) would attenuate the rewarding effects of cocaine. Wildtype rats exposed to cocaine exhibited normal cocaine-seeking responses one day after www.selleckchem.com/products/azd6738.html conditioning and cocaine-seeking behavior was reinstated with drug priming following

drug abstinence. In contrast, BDNF+/- rats did not show cocaine-seeking behavior one day after conditioning, nor did they respond to drug priming. A median split of rats based on BDNF levels in sera collected prior to behavioral procedures revealed that wildtype rats with high BDNF levels showed stronger conditioned place preference and reinstatement to cocaine. Together, the results support the hypothesis that a partial knockout of the BDNF gene attenuates the rewarding properties of cocaine. Additionally, individual

differences in BDNF levels may predict future cocaine-seeking behavior. An underlying mechanism of these effects may be a reduction of the amount of synaptic changes made in the reward pathway. (c) 2013 Elsevier Ireland Ltd. All see more rights reserved.”
“Certain studies of associative learning show that attention

is more substantial to cues that have GDC-0994 purchase a history of being predictive of an outcome than to cues that are irrelevant. At the same time, other studies show that attention is more substantial to cues whose outcomes are uncertain than to cues whose outcomes are predictable. This has led to the suggestion of there being two kinds of attention in associative learning: one based upon a mechanism that allocates attention to a cue on the basis of its predictiveness, the other based upon a mechanism that allocates attention to a cue on the basis of its prediction error (e.g., Le Pelley, Quarterly Journal of Experimental Psychology, 57B, 193-243, 2004). As an alternative, it has been demonstrated that the effects of both predictiveness and uncertainty can be accounted for with only one kind of attention: one that emphasizes the role of prediction (Esber & Haselgrove, Proceedings of the Royal Society B, 278, 2553-2561, 2011). Here, we consider the alternative: whether the effects of predictiveness and uncertainty can be reconciled with a model of learning that emphasizes the role of prediction error (Pearce, Kaye, & Hall, 1982). Simulations of this model reveal that, in many cases, it too is able to account for the influence of predictiveness and uncertainty in associative learning.