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Networks Associated with Reward

  • Elise Lesage
  • Elliot A. Stein
Reference work entry

Abstract

This chapter describes brain networks related to reward processing. We will first consider the reward regions identified by decades of preclinical and more recently human research and the circuits that connect them. These will include the classical “reward centers” along with various cortical and subcortical structures that contribute to reward learning and reward-based decision-making. The second section explores how these nodes, identified and described primarily in nonhuman mammals, are identified in humans through the use of noninvasive imaging techniques like functional magnetic resonance imaging (fMRI) and positron emission tomography (PET). We next discuss reward processing from a network-level perspective, including the methods by which structural and functional connectivity can be identified in humans with MRI-based tools. The final section will discuss functional connectivity networks that center on reward-related circuitry, as well as networks that serve many behavioral purposes but are affected by reward. Dysregulation of these reward networks circuitry in neuropsychiatric disorders will be explored using addiction as an exemplar.

Keywords

Cue-reactivity paradigms Default mode network Delay discounting Dependence Diffusion tensor imaging (DTI) Dorsal anterior cingulate cortex Dorsal striatum Executive control network Functional MRI Habit formation Incentive salience Independent component analysis (ICA) Instrumental conditioning Mesocorticolimbic (MCL) system Monetary incentive delay (MID) task Neuropharmacological mapping studies Nucleus accumbens Orbitofrontal cortex (OFC) Pavlovian conditioning PET Reinforcement learning task Resting-state fMRI Resting-state functional connectivity Salience network Seed-based correlation analysis Substance use disorders Triple network model Value-based decision-making Ventral striatum Ventromedial prefrontal cortex Withdrawal syndrome 

Notes

Acknowledgments

This work was supported by the NIDA Intramural Research Program. The authors would like to thank Drs. V. Pariyadath, J.R. Fedota and J.L. Gowin for stimulating discussion.

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Copyright information

© Springer Science+Business Media New York (outside the USA) 2016

Authors and Affiliations

  1. 1.Neuroimaging Research Branch, Intramural Research ProgramNational Institute on Drug Abuse, National Institutes of HealthBaltimoreUSA

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