Reward salience and risk aversion underlie differential ACC activity in substance dependence

Abnormal resting-state functional connectivity of the right anterior cingulate cortex in chronic ketamine users and its correlation with cognitive impairments

BACKGROUND

Chronic ketamine use leads to cognitive impairments, however, the neural mechanisms underpinning these impairments are still unclear.

AIMS

Many studies showed Anterior cingulate cortex (ACC)is strongly involved in cognition and drug addiction, as supported by our previous studies. The objective of this study was to assess the variations in resting-state functional connectivity (FC) changes in the right anterior cingulate cortex (ACC) of chronic ketamine users (CKUs) and their relationship with cognitive performance.

METHODS

The study enrolled 28 chronic ketamine users (CKUs) and 30 healthy controls (HCs). Resting-state functional magnetic resonance imaging (fMRI) data were gathered from both groups. Cognitive functions were evaluated using the MATRICS Consensus Cognitive Battery (MCCB).

RESULTS

CKUs demonstrated significantly poorer cognitive performance than HCs in various cognitive domains, including Visual Learning, Speed of Processing, Working Memory, and the composite score of MCCB. Group-level comparisons revealed that CKUs exhibited enhanced functional connectivity between the right ACC and the right postcentral gyrus (PCG) compared to HCs. There was a positive relationship between the connectivity of right ACC-PCG and reasoning and problem-solving score, but there was no significant association with the characteristics of ketamine use.

CONCLUSION

CKUs showed enhanced connectivity between the right ACC and the right PCG. This enhanced functional connectivity may indicate functional compensation for cognitive deficits in CKUs, especially for reasoning and problem-solving impairments in CKUs.

Appetitive conditioning with pornographic stimuli elicits stronger activation in reward regions than monetary and gaming-related stimuli

Appetitive conditioning plays an important role in the development and maintenance of pornography-use and gaming disorders. It is assumed that primary and secondary reinforcers are involved in these processes. Despite the common use of pornography and gaming in the general population appetitive conditioning processes in this context are still not well studied. This study aims to compare appetitive conditioning processes using primary (pornographic) and secondary (monetary and gaming-related) rewards as unconditioned stimuli (UCS) in the general population. Additionally, it investigates the conditioning processes with gaming-related stimuli as this type of UCS was not used in previous studies. Thirty-one subjects participated in a differential conditioning procedure in which four geometric symbols were paired with either pornographic, monetary, or gaming-related rewards or with nothing to become conditioned stimuli (CS + porn, CS + game, CS + money, and CS-) in an functional magnetic resonance imaging study. We observed elevated arousal and valence ratings as well as skin conductance responses for each CS+ condition compared to the CS-. On the neural level, we found activations during the presentation of the CS + porn in the bilateral nucleus accumbens, right medial orbitofrontal cortex, and the right ventral anterior cingulate cortex compared to the CS-, but no significant activations during CS + money and CS + game compared to the CS-. These results indicate that different processes emerge depending on whether primary and secondary rewards are presented separately or together in the same experimental paradigm. Additionally, monetary and gaming-related stimuli seem to have a lower appetitive value than pornographic rewards.

Neural Differences in Relation to Risk Preferences during Reward Processing: An Event-Related Potential Study

Inter-individual variability in risk preferences can be reflected in reward processing differences, making people risk-seekers or risk-averse. However, the neural correlates of reward processing in individuals with risk preferences remain unknown. Consequently, this event-related potential (ERP) study examined and compared electrophysiological correlates associated with different stages of reward processing in risk-seeking and risk-averse groups. Individuals scoring in the bottom and top 20% on the Balloon Analogue Risk Task (BART) were deemed risk-averse and risk-seeking, respectively. Participants engaged in a gambling task while their electroencephalogram (EEG) was recorded. Risk-seekers tended to choose high-risk options significantly more frequently than low-risk options, whereas risk-averse individuals chose low-risk options significantly more frequently than high-risk ones. All participants selected the low-risk alternative more slowly than the high-risk option. During the anticipation stage, the low-risk option elicited a relatively attenuated stimulus-preceding negativity (SPN) response from risk-seekers compared to risk-averse participants. During the outcome stage, feedback-related negativity (FRN) increased in risk-seekers responding to greater losses but not in risk-averse participants. These results indicate that ERP components can detect differences in reward processing during risky situations. In addition, these results suggest that motivation and cognitive control, along with their associated neural processes, may play a central role in differences in reward-based behavior between the two groups.

The PRO model accounts for the anterior cingulate cortex role in risky decision-making and monitoring

The anterior cingulate cortex (ACC) has been implicated in a number of functions, including performance monitoring and decision-making involving effort. The prediction of responses and outcomes (PRO) model has provided a unified account of much human and monkey ACC data involving anatomy, neurophysiology, EEG, fMRI, and behavior. We explored the computational nature of ACC with the PRO model, extending it to account specifically for both human and macaque monkey decision-making under risk, including both behavioral and neural data. We show that the PRO model can account for a number of additional effects related to outcome prediction, decision-making under risk, gambling behavior. In particular, we show that the ACC represents the variance of uncertain outcomes, suggesting a link between ACC function and mean-variance theories of decision making. The PRO model provides a unified account of a large set of data regarding the ACC.

Neural bases of risky decisions involving nicotine vapor versus monetary reward

•

• Most studies of addiction with fMRI use only money reward.

•

• Little is known about the neural basis of real-time drug use decisions.

•

• Subjects gambled for either money or immediate nicotine vape reward in scanner.

•

• The neural response to immediate drug reward is different from monetary reward.

•

• Money reward has limitations as a proxy for studying addiction.

Substantial effort has gone into neuroimaging studies of neural mechanisms underlying addiction. Human studies of smoking typically either give monetary reward during an fMRI task or else allow subjects to smoke outside the scanner, after the session. This raises a fundamental issue of construct validity, as it is unclear whether the same neural mechanisms process decisions about nicotine that process decisions about money. To address this, we developed a novel MR-compatible nicotine vaping device, such that access to nicotine vapor could be controlled and monitored. We recruited heavy smokers (Money: 45 subjects, 13 females and 32 males; Nicotine: 21 subjects, 4 females and 17 males) to perform a gambling task with nicotine and monetary reward on separate days. We collected BOLD fMRI data while they performed the task inside the scanner and analyzed it using general linear modeling, with inference based on cluster-size correction. This allowed a direct comparison between the neural mechanisms of choosing and receiving immediate drug vs. monetary reward. We found substantial differences in the neural mechanisms that underlie risky choices about money vs. drug reward, including a reversal of the well-known error effects in the medial prefrontal cortex.

Is monetary reward processing altered in drug-naïve youth with a behavioral addiction? Findings from internet gaming disorder

Current models of addiction biology highlight altered neural responses to non-drug rewards as a central feature of addiction. However, given that drugs of abuse can directly impact reward-related dopamine circuitry, it is difficult to determine the extent to which reward processing alterations are a trait feature of individuals with addictions, or primarily a consequence of exogenous drug exposure. Examining individuals with behavioral addictions is one promising approach for disentangling neural features of addiction from the direct effects of substance exposure. The current fMRI study compared neural responses during monetary reward processing between drug naïve young adults with a behavioral addiction, internet gaming disorder (IGD; n = 22), and healthy controls (n = 27) using a monetary incentive delay task. Relative to controls, individuals with IGD exhibited blunted caudate activity associated with loss magnitude at the outcome stage, but did not differ from controls in neural activity at other stages. These findings suggest that decreased loss sensitivity might be a critical feature of IGD, whereas alterations in gain processing may be less characteristic of individuals with IGD, relative to those with substance use disorders. Therefore, classic theories of altered reward processing in substance use disorders should be translated to behavioral addictions with caution.

dACC response to presentation of negative feedback predicts stimulant dependence diagnosis and stimulant use severity

Error-monitoring abnormalities in stimulant-dependent individuals (SDIs) may be due to reduced awareness of committed errors, or to reduced sensitivity upon such awareness. The distinction between these alternatives remains largely undifferentiated, but may have substantial clinical relevance. We sought to better characterize the nature, and clinical relevance, of SDIs' error-monitoring processes by comparing carefully isolated neural responses during the presentation of negative feedback to a) stimulant dependence status and b) lifetime stimulant use. Forty-eight SDIs and twenty-three non-SDIs performed an fMRI-based time-estimation task specifically designed to isolate neural responses associated with the presentation (versus expectation) of contingent negative feedback. SDIs showed reduced dACC response compared to non-SDIs following the presentation of negative feedback, but only when error expectancies were controlled. Moreover, lifetime stimulant use correlated negatively with magnitude of expectancy-controlled dACC attenuation. While this finding was minimized after controlling for age, these results suggest that SDIs may be characterized by a core reduction in neural activity following error feedback, in the context of intact feedback expectancies. Correlations with lifetime stimulant use suggest that this neural attenuation may hold clinical significance.

Enhanced Amygdala-Striatal Functional Connectivity during the Processing of Cocaine Cues in Male Cocaine Users with a History of Childhood Trauma

BACKGROUND AND AIMS

Childhood trauma is associated with increased levels of anxiety later in life, an increased risk for the development of substance use disorders, and neurodevelopmental abnormalities in the amygdala and frontostriatal circuitry. The aim of this study was to investigate the (neurobiological) link among childhood trauma, state anxiety, and amygdala-frontostriatal activity in response to cocaine cues in regular cocaine users.

METHODS

In this study, we included 59 non-treatment seeking regular cocaine users and 58 non-drug using controls. Blood oxygenation level-dependent responses were measured using functional magnetic resonance imaging while subjects performed a cue reactivity paradigm with cocaine and neutral cues. Psychophysiological interaction analyses were applied to assess functional connectivity between the amygdala and other regions in the brain. Self-report questionnaires were used to measure childhood trauma, state anxiety, drug use, drug use severity, and craving.

RESULTS

Neural activation was increased during the presentation of cocaine cues, in a widespread network including the frontostriatal circuit and amygdala in cocaine users but not in controls. Functional coupling between the amygdala and medial prefrontal cortex was reduced in response to cocaine cues, in both cocaine users and controls, which was further diminished with increasing state anxiety. Importantly, amygdala-striatal connectivity was positively associated with childhood trauma in regular cocaine users, while there was a negative association in controls. At the behavioral level, state anxiety was positively associated with cocaine use severity and craving related to negative reinforcement.

CONCLUSION

Childhood trauma is associated with enhanced amygdala-striatal connectivity during cocaine cue reactivity in regular cocaine users, which may contribute to increased habit behavior and poorer cognitive control. While we cannot draw conclusions on causality, this study provides novel information on how childhood trauma may contribute to the development and persistence of cocaine use disorder.

Neural correlates of appetitive extinction in humans

Appetitive extinction receives attention as an important model for the treatment of psychiatric disorders. However, in humans, its underlying neural correlates remain unknown. To close this gap, we investigated appetitive acquisition and extinction with fMRI in a 2-day monetary incentive delay paradigm. During appetitive conditioning, one stimulus (CS+) was paired with monetary reward, while another stimulus (CS−) was never rewarded. Twenty-four hours later, subjects underwent extinction, in which neither CS was reinforced. Appetitive conditioning elicited stronger skin conductance responses to the CS+ as compared with the CS−. Regarding subjective ratings, the CS+ was rated more pleasant and arousing than the CS− after conditioning. Furthermore, fMRI-results (CS+ − CS−) showed activation of the reward circuitry including amygdala, midbrain and striatal areas. During extinction, conditioned responses were successfully extinguished. In the early phase of extinction, we found a significant activation of the caudate, the hippocampus, the dorsal and ventral anterior cingulate cortex (dACC and vACC). In the late phase, we found significant activation of the nucleus accumbens (NAcc) and the amygdala. Correlational analyses with subjective ratings linked extinction success to the vACC and the NAcc, while associating the dACC with reduced extinction. The results reveal neural correlates of appetitive extinction in humans and extend assumptions from models for human extinction learning.

Foraging Value, Risk Avoidance, and Multiple Control Signals: How the Anterior Cingulate Cortex Controls Value-based Decision-making

Recent work on the role of the ACC in cognition has focused on choice difficulty, action value, risk avoidance, conflict resolution, and the value of exerting control among other factors. A main underlying question is what are the output signals of ACC, and relatedly, what is their effect on downstream cognitive processes? Here we propose a model of how ACC influences cognitive processing in other brain regions that choose actions. The model builds on the earlier Predicted Response Outcome model and suggests that ACC learns to represent specifically the states in which the potential costs or risks of an action are high, on both short and long timescales. It then uses those cost signals as a basis to bias decisions to minimize losses while maximizing gains. The model simulates both proactive and reactive control signals and accounts for a variety of empirical findings regarding value-based decision-making.

Predicting Motivation: Computational Models of PFC Can Explain Neural Coding of Motivation and Effort-based Decision-making in Health and Disease

Human behavior is strongly driven by the pursuit of rewards. In daily life, however, benefits mostly come at a cost, often requiring that effort be exerted to obtain potential benefits. Medial PFC (MPFC) and dorsolateral PFC (DLPFC) are frequently implicated in the expectation of effortful control, showing increased activity as a function of predicted task difficulty. Such activity partially overlaps with expectation of reward and has been observed both during decision-making and during task preparation. Recently, novel computational frameworks have been developed to explain activity in these regions during cognitive control, based on the principle of prediction and prediction error (predicted response-outcome [PRO] model [Alexander, W. H., & Brown, J. W. Medial prefrontal cortex as an action-outcome predictor. Nature Neuroscience, 14, 1338-1344, 2011], hierarchical error representation [HER] model [Alexander, W. H., & Brown, J. W. Hierarchical error representation: A computational model of anterior cingulate and dorsolateral prefrontal cortex. Neural Computation, 27, 2354-2410, 2015]). Despite the broad explanatory power of these models, it is not clear whether they can also accommodate effects related to the expectation of effort observed in MPFC and DLPFC. Here, we propose a translation of these computational frameworks to the domain of effort-based behavior. First, we discuss how the PRO model, based on prediction error, can explain effort-related activity in MPFC, by reframing effort-based behavior in a predictive context. We propose that MPFC activity reflects monitoring of motivationally relevant variables (such as effort and reward), by coding expectations and discrepancies from such expectations. Moreover, we derive behavioral and neural model-based predictions for healthy controls and clinical populations with impairments of motivation. Second, we illustrate the possible translation to effort-based behavior of the HER model, an extended version of PRO model based on hierarchical error prediction, developed to explain MPFC-DLPFC interactions. We derive behavioral predictions that describe how effort and reward information is coded in PFC and how changing the configuration of such environmental information might affect decision-making and task performance involving motivation.

Computational Models of Anterior Cingulate Cortex: At the Crossroads between Prediction and Effort

In the last two decades the anterior cingulate cortex (ACC) has become one of the most investigated areas of the brain. Extensive neuroimaging evidence suggests countless functions for this region, ranging from conflict and error coding, to social cognition, pain and effortful control. In response to this burgeoning amount of data, a proliferation of computational models has tried to characterize the neurocognitive architecture of ACC. Early seminal models provided a computational explanation for a relatively circumscribed set of empirical findings, mainly accounting for EEG and fMRI evidence. More recent models have focused on ACC's contribution to effortful control. In parallel to these developments, several proposals attempted to explain within a single computational framework a wider variety of empirical findings that span different cognitive processes and experimental modalities. Here we critically evaluate these modeling attempts, highlighting the continued need to reconcile the array of disparate ACC observations within a coherent, unifying framework.

Integrative Modeling of Prefrontal Cortex

pFC is generally regarded as a region critical for abstract reasoning and high-level cognitive behaviors. As such, it has become the focus of intense research involving a wide variety of subdisciplines of neuroscience and employing a diverse range of methods. However, even as the amount of data on pFC has increased exponentially, it appears that progress toward understanding the general function of the region across a broad array of contexts has not kept pace. Effects observed in pFC are legion, and their interpretations are generally informed by a particular perspective or methodology with little regard with how those effects may apply more broadly. Consequently, the number of specific roles and functions that have been identified makes the region a very crowded place indeed and one that appears unlikely to be explained by a single general principle. In this theoretical article, we describe how the function of large portions of pFC can be accommodated by a single explanatory framework based on the computation and manipulation of error signals and how this framework may be extended to account for additional parts of pFC.

A preliminary study of longitudinal neuroadaptation associated with recovery from addiction

BACKGROUND

Few studies have explored longitudinal change in event-related brain responses during early recovery from addiction. Moreover, existing findings yield evidence of both increased and decreased signaling within reward and control centers over time. The current study explored reward- and control-related signals in a risky decision-making task and specifically investigated parametric modulations of the BOLD signal, rather than signal magnitude alone. It was hypothesized that risk-related signals during decision-making and outcome evaluation would reflect recovery and that change in specific signals would correspond with improved treatment outcomes.

METHODS

Twenty-one substance dependent individuals were recruited upon enrollment in community-based substance use treatment programs, wherein they received treatment-as-usual. Participants completed functional neuroimaging assessments at baseline and 3-month follow-up while performing the Balloon Analogue Risk Task (BART). Risk- and reward-sensitive signals were identified using parametric modulators. Substance use was tracked throughout the 3-month study interval using the timeline follow-back procedure.

RESULTS

Longitudinal contrasts of parametric modulators suggested improved formation of risk-informed outcome expectations at follow-up. Specifically, a greater response to high risk (low-likelihood) positive feedback was identified in caudal anterior cingulate cortex (ACC) and a greater response to low risk (low-likelihood) negative feedback was identified in caudal ACC and inferior frontal gyrus. In addition, attenuation of a ventromedial prefrontal cortex (vmPFC) "reward-seeking" signal (i.e., increasing response with greater reward) during risky decisions at follow-up was associated with less substance use during the study interval.

CONCLUSIONS

Changes in risk- and reward-related signaling in ACC/vmPFC appear to reflect recovery and may support sobriety.