The role of the opioid system in decision making and cognitive control: A review

Abstract

The opioid system regulates affective processing, including pain, pleasure, and reward. Restricting the role of this system to hedonic modulation may be an underestimation, however. Opioid receptors are distributed widely in the human brain, including the more "cognitive" regions in the frontal and parietal lobes. Nonhuman animal research points to opioid modulation of cognitive and decision-making processes. We review emerging evidence on whether acute opioid drug modulation in healthy humans can influence cognitive function, such as how we choose between actions of different values and how we control our behavior in the face of distracting information. Specifically, we review studies employing opioid agonists or antagonists together with experimental paradigms of reward-based decision making, impulsivity, executive functioning, attention, inhibition, and effort. Although this field is still in its infancy, the emerging picture suggests that the mu-opioid system can influence higher-level cognitive function via modulation of valuation, motivation, and control circuits dense in mu-opioid receptors, including orbitofrontal cortex, basal ganglia, amygdalae, anterior cingulate cortex, and prefrontal cortex. The framework that we put forward proposes that opioids influence decision making and cognitive control by increasing the subjective value of reward and reducing aversive arousal. We highlight potential mechanisms that might underlie the effects of mu-opioid signaling on decision making and cognitive control and provide directions for future research.

Keywords: Affect; Cognitive control; Decision making; Drugs; Executive function; Hedonic states; Mood; Morphine; Mu-opioid receptors; Opioid system; Reward; Value-based choice.

Fig. 1

Neural circuits involved in decision making (A) and cognitive control (B) based on meta analyses (analysis date 24 May 2018), showing forward inference maps of statistically significant (false discovery rate, p < 0.01) activations in Neurosynth (Yarkoni, Poldrack, Nichols, Van Essen, & Wager, 2011). (C) Density of mu-opioid receptor expression as revealed by [11C]-carfentanil PET (mean nondisplaceable binding potential (BPND) image of 89 PET scans from healthy volunteers; courtesy of Dr. Lauri Nummenmaa). The circuits involved in decision making and cognitive control show particular high density of mu-opioid receptors in the limbic system (including thalamus, basal ganglia, and cingulate cortex) and a moderate density of mu-opioid receptors in cortical regions, such as insular and lateral-prefrontal cortex. Note that mu-opioid receptors regulate many functions. As shown above, receptors are expressed throughout the brain, including in regions less commonly associated with cognition, such as the midbrain (periaqueductal gray), hypothalamus, and cerebellum. These maps and their conjunctions are available at Neurovault (Gorgolewski et al., 2015): https://neurovault.org/collections/4841/

Fig. 2

Left panel: Drugs can affect the opioid system via different receptor subtypes. The opioid system is made up of four different opioid receptor types, the mu-, delta, kappa-, and the nociceptin receptors (Corbett, 2009). Several types of endogenous ligands, such as endorphins, enkephalins, dynorphins, endomorphins, and nociceptin activate these (Calo, Guerrini, Rizzi, Salvadori, & Regoli, ; Fichna, Janecka, Costentin, & Do Rego, 2007). Drugs, such as morphine and heroin, are considered mu-opioid agonists, i.e., they act primarily on the mu-opioid receptor (Pasternak, 2001). The drugs that block endogenous opioid signaling (antagonists, such as naloxone or naltrexone) in humans typically inhibit activity at both mu- and kappa-receptors. To date, the mechanism of action of the mu-opioid receptor is best understood. Both the analgesic and the euphoric effects of opioid drugs are thought to be mediated by this receptor type (Fields & Margolis, 2015). Although mu-opioid receptors are widely distributed in the brain (and in other parts of the body as well), they are in particular highly expressed in limbic brain areas, such as the basal ganglia, thalamus, and anterior cingulate. They also are expressed to a moderate extent in cortical areas, such as lateral prefrontal and insular regions (Henriksen & Willoch, 2008). Right panel: Mu-opioid receptors are activated by a large number of different drugs, and they are commonly compared in terms of their efficacy to relieve pain at a particular dose and administration method. Opioid drugs are often given as pills (per oral; PO) but also intravenously (IV), transnasally (TN), subcutaneously (SC), and intramuscularly (IM). We have calculated a rough estimate of “morphine equivalence” on the basis of available evidence of analgesic effects. This conversion was primarily based on the values provided in earlier work (Knotkova, Fine, & Portenoy, ; Zacny, 1995). It is important to emphasize that dosages with similar analgesic properties can have different effects on cognitive function, and a simple conversion does not capture the different pharmacokinetics of different drugs. To emphasize that the conversion is coarse for the present purposes, we do not report the exact equianalgesic doses of morphine. Instead, we have categorized the dose as a low, medium, or high dose, using 4 mg and 7 mg IV of morphine as the minimal cutoff values for the medium and high dose, respectively. As for the opioid antagonists, these were categorized on the basis of available PET evidence about the proportion of mu-opioid receptors blocked by a given drug dose (Mayberg & Frost, 1990). Doses covering 90-100% of receptors are considered full antagonists (Weerts et al., 2013). Where doses administered were much higher or lower than this range, this is specified in the text. In addition to drugs acting primarily as agonists or antagonist to opioid receptors, the literature also contains several reports from “mixed agonists,” i.e., drugs that act simultaneously as agonists and antagonists at different opioid receptors (Jacob, Michaud, & Tremblay, 1979). This category also covers drugs that act as partial agonists and antagonists, such as buprenorphine, which binds strongly to mu-opioid receptors, but causes less activation of the receptor than the endogenous ligand. Buprenorphine is also a kappa-opioid antagonist. These drugs were also categorized on the basis of their analgesic effects at the doses used in the literature. Figures were produced with graphics from Servier Medical Art (smart.servier.com) under Creative Commons BY 3.0 license.

Fig. 3

The number of times opioid agonist drug has shown a significant impairment on coding task (DSST) performance and logical reasoning for all type of drugs used in the studies (antagonist drug effects not included, see details in Tables 1 and 2). Dose refers to the minimal dose needed to produce a significant effect; if no effect was observed, we used the maximum dose used in the study.

Fig. 4

Subjective value as a function of reward and punishment. The gray line plots a typical value function for reward and punishment according to prospect theory (Kahneman & Tversky, 1979). Opioid drugs might modulate decision making by shifting this value function, such that opioid agonists increase (white line) and opioid antagonists decrease (black line) subjective value for rewards. Similar modulation specifically of high-salience stimuli may occur for punishments (dotted lines), although the available evidence is equivocal and future research is warranted (see Discussion in main text).

Fig. 5

U-shaped relationship between aversive arousal and cognitive control. Opioids agonist might reduce aversive arousal (white), whereas opioid antagonist might increase it (black). According to this hypothesis, drug effects on cognition depend on the baseline level of aversive arousal, such that an opioid agonist might improve performance in high stress contexts, yet impair performance under low stress.