Differential expression of Arc in the mesocorticolimbic system is involved in drug and natural rewarding behavior in rats

Abstract

Aim:To investigate the different effects of heroin and milk in activating the corticostriatal system that plays a critical role in reward reinforcement learning. Methods: Male SD rats were trained daily for 15 d to self-administer heroin or milk tablets in a classic runway drug self-administration model. Immunohistochemical assay was used to quantify Arc protein expression in the medial prefrontal cortex (mPFC), the nucleus accumbens (NAc), the dorsomedial striatum (DMS) and the ventrolateral striatum (VLS) in response to chronic self-administration of heroin or milk tablets. NMDA receptor antagonist MK801 (0.1 mg/kg) or dopamine D1 receptor antagonist SCH23390 (0.03 mg/kg) were intravenously injected at the same time as heroin was infused intravenously. Results: Runway training with heroin resulted in robust enhancement of Arc expression in the mPFC, the NAc and the DMS on d 1, 7, and 15, and in the VLS on d 1 and d 7. However, runway training with milk led to increased Arc expression in the mPFC, the NAc and the DMS only on d 7 and/or d 15 but not on d 1. Moreover, runway training with milk failed to induce increased Arc protein in the VLS. Both heroin-seeking behavior and Arc protein expression were blocked by MK801 or SCH23390 administration. Conclusion: The VLS is likely to be critically involved in drug-seeking behavior. The NMDA-and D1 receptor-dependent Arc expression is important in drug-seeking behavior.

Effect of pharmacological manipulations on Arc function

“…Runway training with heroin, in which rats are trained to run to a goal area to self-administer the drug, significantly increases Arc in the mPFC, the nucleus accumbens (NAc) and the striatum, with differences in the temporal expression of Arc between the dorsomedial and ventrolateral striatum, suggesting the involvement of Arc in goal-directed behavior in the ventrolateral striatum. SCH2 3390 and MK-801 abolish this increase and suppress drug seeking behavior ( Li et al., 2013 ).…”

“…Changes in Arc expression in the prelimbic, infralimbic, anterior cingulate, prefrontal cortex, and amygdala have also been shown to play a role in mood regulation ( Li et al., 2015 ). Arc regulation in the mesocorticolimbic system, including the nucleus accumbens (NAc), medial prefrontal cortex (mPFC), and dorsomedial striatum modulates the reward and reinforcement system and affects drug-seeking behaviors ( Li et al., 2013 ). Modulation of Arc has further been implicated in several neurological disorders including Alzheimer's disease (AD), schizophrenia, depression, autism, Angelman syndrome, and Fragile X syndrome ( Gallo et al., 2018 ; Wilkerson et al., 2018 ).…”

Histone 3 lysine 9 acetylation of BRG1 in the medial prefrontal cortex is associated with heroin self‑administration in rats

“…The PFC has long been suspected to be involved in cognitive control; the ability to orchestrate thought and action in accordance with internal states or intentions (51), and other aspects of the addiction phenotype (52). Activity in the dorsal mPFC is thought to initiate drug-seeking behavior and is crucial for cue-induced nicotine or morphine relapse (15,53), whilst lesions in the mPFC may lead to insensitivity to changes in compulsive behavior (17) and marked inability to make choices (52).…”

“…The PFC exerts a strong influence on relapse to opiate seeking behavior during periods of drug abstinence, especially the ventral and medial parts of the PFC (11,12), with the medial PFC (mPFC) contributing to drug-, stress-and cue-induced drug seeking (13)(14)(15)(16). The nac serves an important role in drug self-administration through mediating Pavlovian influences on instrumental seeking behavior (17).…”

The Applicability of Reinforcement Learning Methods in the Development of Industry 4.0 Applications

“…Discussions of specific parts of RL solution design problems occur in smaller number of cases, but these kinds of publication demonstrate the fact that constructing an appropriate RL application is not always trivial. We can highlight state space design [12,25,33,107,144,179,193,208,217,220,222,224,227,266,267] and action space design [109,220,246,268], reward construction [14,76,110,199,220,226,246,[269][270][271][272][273], and exploration strategy planning [86,274] which can be determinants from the whole application point of view. [11,13,17,20,21,24,38,43,61,62,66,69,82,89,…”