• Ann E Kelley.
• Department of Psychiatry and Neuroscience Program, University of Wisconsin-Madison Medical School, 6001 Research Park Boulevard, Madison, WI 53719, USA. aekelly@facstaff.wisc.edu
• Neurosci Biobehav Rev. 2004 Jan 1; 27 (8): 765-76.

AbstractThe nucleus accumbens is a brain region that participates in the control of behaviors related to natural reinforcers, such as ingestion, sexual behavior, incentive and instrumental learning, and that also plays a role in addictive processes. This paper comprises a review of work from our laboratory that focuses on two main research areas: (i). the role of the nucleus accumbens in food motivation, and (ii). its putative functions in cellular plasticity underlying appetitive learning. First, work within a number of different behavioral paradigms has shown that accumbens neurochemical systems play specific and dissociable roles in different aspects of food seeking and food intake, and part of this function depends on integration with the lateral hypothalamus and amygdala. We propose that the nucleus accumbens integrates information related to cognitive, sensory, and emotional processing with hypothalamic mechanisms mediating energy balance. This system as a whole enables complex hierarchical control of adaptive ingestive behavior. Regarding the second research area, our studies examining acquisition of lever-pressing for food in rats have shown that activation of glutamate N-methyl-d-aspartate (NMDA) receptors, within broadly distributed but interconnected regions (nucleus accumbens core, posterior striatum, prefrontal cortex, basolateral and central amygdala), is critical for such learning to occur. This receptor stimulation triggers intracellular cascades that involve protein phosphorylation and new protein synthesis. It is hypothesized that activity in this distributed network (including D1 receptor activity) computes coincident events and thus enhances the probability that temporally related actions and events (e.g. lever pressing and delivery of reward) become associated. Such basic mechanisms of plasticity within this reinforcement learning network also appear to be profoundly affected in addiction.

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