Addiction beyond pharmacological effects: The role of environment complexity and bounded rationality

Several decision-making vulnerabilities have been identified as underlying causes for addictive behaviours, or the repeated execution of stereotyped actions despite their adverse consequences. These vulnerabilities are mostly associated with brain alterations caused by the consumption of substances of abuse. However, addiction can also happen in the absence of a pharmacological component, such as seen in pathological gambling and videogaming. We use a new reinforcement learning model to highlight a previously neglected vulnerability that we suggest interacts with those already identified, whilst playing a prominent role in non-pharmacological forms of addiction. Specifically, we show that a dual-learning system (i.e. combining model-based and model-free) can be vulnerable to highly rewarding, but suboptimal actions, that are followed by a complex ramification of stochastic adverse effects. This phenomenon is caused by the overload of the capabilities of an agent, as time and cognitive resources required for exploration, deliberation, situation recognition, and habit formation, all increase as a function of the depth and richness of detail of an environment. Furthermore, the cognitive overload can be aggravated due to alterations (e.g. caused by stress) in the bounded rationality, i.e. the limited amount of resources available for the model-based component, in turn increasing the agent’s chances to develop or maintain addictive behaviours. Our study demonstrates that, independent of drug consumption, addictive behaviours can arise in the interaction between the environmental complexity and the biologically finite resources available to explore and represent it

A Multilevel Computational Characterization of Endophenotypes in Addiction

Addiction is characterized by a profound intersubject (phenotypic) variability in the expression of addictive symptomatology and propensity to relapse following treatment. However, laboratory investigations have primarily focused on common neural substrates in addiction and have not yet been able to identify mechanisms that can account for the multifaceted phenotypic behaviors reported in the literature. To fill this knowledge gap theoretically, here we simulated phenotypic variations in addiction symptomology and responses to putative treatments, using both a neural model, based on cortico-striatal circuit dynamics, and an algorithmic model of reinforcement learning (RL). These simulations rely on the widely accepted assumption that both the ventral, model-based, goal-directed system and the dorsal, model-free, habitual system are vulnerable to extra-physiologic dopamine reinforcements triggered by addictive rewards. We found that endophenotypic differences in the balance between the two circuit or control systems resulted in an inverted-U shape in optimal choice behavior. Specifically, greater unbalance led to a higher likelihood of developing addiction and more severe drug-taking behaviors. Furthermore, endophenotypes with opposite asymmetrical biases among cortico-striatal circuits expressed similar addiction behaviors, but responded differently to simulated treatments, suggesting personalized treatment development could rely on endophenotypic rather than phenotypic differentiations. We propose our simulated results, confirmed across neural and algorithmic levels of analysis, inform on a fundamental and, to date, neglected quantitative method to characterize clinical heterogeneity in addiction

Belief about Nicotine Selectively Modulates Value and Reward Prediction Error Signals in Smokers

Little is known about how prior beliefs impact biophysically described processes in the presence of neuroactive drugs, which presents a profound challenge to the understanding of the mechanisms and treatments of addiction. We engineered smokers\u27 prior beliefs about the presence of nicotine in a cigarette smoked before a functional magnetic resonance imaging session where subjects carried out a sequential choice task. Using a model-based approach, we show that smokers\u27 beliefs about nicotine specifically modulated learning signals (value and reward prediction error) defined by a computational model of mesolimbic dopamine systems. Belief of no nicotine in cigarette (compared with nicotine in cigarette ) strongly diminished neural responses in the striatum to value and reward prediction errors and reduced the impact of both on smokers\u27 choices. These effects of belief could not be explained by global changes in visual attention and were specific to value and reward prediction errors. Thus, by modulating the expression of computationally explicit signals important for valuation and choice, beliefs can override the physical presence of a potent neuroactive compound like nicotine. These selective effects of belief demonstrate that belief can modulate model-based parameters important for learning. The implications of these findings may be far ranging because belief-dependent effects on learning signals could impact a host of other behaviors in addiction as well as in other mental health problems

Autonomic and Brain Responses Associated with Empathy Deficits in Autism Spectrum Disorder

Accumulating evidence suggests that autonomic signals and their cortical representations are closely linked to emotional processes, and that related abnormalities could lead to social deficits. Although socio-emotional impairments are a defining feature of autism spectrum disorder (ASD), empirical evidence directly supporting the link between autonomic, cortical, and socio-emotional abnormalities in ASD is still lacking. In this study, we examined autonomic arousal indexed by skin conductance responses (SCR), concurrent cortical responses measured by functional magnetic resonance imaging, and effective brain connectivity estimated by dynamic causal modeling in seventeen unmedicated high-functioning adults with ASD and seventeen matched controls while they performed an empathy-for-pain task. Compared to controls, adults with ASD showed enhanced SCR related to empathetic pain, along with increased neural activity in the anterior insular cortex, although their behavioral empathetic pain discriminability was reduced and overall SCR was decreased. ASD individuals also showed enhanced correlation between SCR and neural activities in the anterior insular cortex.Importantly, significant group differences in effective brain connectivity were limited to greater reduction in the negative intrinsic connectivity of the anterior insular cortex in the ASD group, indicating a failure in attenuating anterior insular responses to empathetic pain. These results suggest that aberrant interoceptive precision, as indexed by abnormalities in autonomic activity and its central representations, may underlie empathy deficits in AS

Autonomic and Brain Responses Associated with Empathy Deficits in Autism Spectrum Disorder

Accumulating evidence suggests that autonomic signals and their cortical representations are closely linked to emotional processes, and that related abnormalities could lead to social deficits. Although socio-emotional impairments are a defining feature of autism spectrum disorder (ASD), empirical evidence directly supporting the link between autonomic, cortical, and socio-emotional abnormalities in ASD is still lacking. In this study, we examined autonomic arousal indexed by skin conductance responses (SCR), concurrent cortical responses measured by functional magnetic resonance imaging, and effective brain connectivity estimated by dynamic causal modeling in seventeen unmedicated high-functioning adults with ASD and seventeen matched controls while they performed an empathy-for-pain task. Compared to controls, adults with ASD showed enhanced SCR related to empathetic pain, along with increased neural activity in the anterior insular cortex, although their behavioral empathetic pain discriminability was reduced and overall SCR was decreased. ASD individuals also showed enhanced correlation between SCR and neural activities in the anterior insular cortex.Importantly, significant group differences in effective brain connectivity were limited to greater reduction in the negative intrinsic connectivity of the anterior insular cortex in the ASD group, indicating a failure in attenuating anterior insular responses to empathetic pain. These results suggest that aberrant interoceptive precision, as indexed by abnormalities in autonomic activity and its central representations, may underlie empathy deficits in AS

Functional Neural Correlates of Attentional Deficits in Amnestic Mild Cognitive Impairment

Although amnestic mild cognitive impairment (aMCI; often considered a prodromal phase of Alzheimer’s disease, AD) is most recognized by its implications for decline in memory function, research suggests that deficits in attention are present early in aMCI and may be predictive of progression to AD. The present study used functional magnetic resonance imaging to examine differences in the brain during the attention network test between 8 individuals with aMCI and 8 neurologically healthy, demographically matched controls. While there were no significant behavioral differences between groups for the alerting and orienting functions, patients with aMCI showed more activity in neural regions typically associated with the networks subserving these functions (e.g., temporoparietal junction and posterior parietal regions, respectively). More importantly, there were both behavioral (i.e., greater conflict effect) and corresponding neural deficits in executive control (e.g., less activation in the prefrontal and anterior cingulate cortices). Although based on a small number of patients, our findings suggest that deficits of attention, especially the executive control of attention, may significantly contribute to the behavioral and cognitive deficits of aMCI

Somatic and Vicarious Pain are Represented by Dissociable Multivariate Brain Patterns

Understanding how humans represent others’ pain is critical for understanding pro-social behavior. ‘Shared experience’ theories propose common brain representations for somatic and vicarious pain, but other evidence suggests that specialized circuits are required to experience others’ suffering. Combining functional neuroimaging with multivariate pattern analyses, we identified dissociable patterns that predicted somatic (high versus low: 100%) and vicarious (high versus low: 100%) pain intensity in out-of-sample individuals. Critically, each pattern was at chance in predicting the other experience, demonstrating separate modifiability of both patterns. Somatotopy (upper versus lower limb: 93% accuracy for both conditions) was also distinct, located in somatosensory versus mentalizing-related circuits for somatic and vicarious pain, respectively. Two additional studies demonstrated the generalizability of the somatic pain pattern (which was originally developed on thermal pain) to mechanical and electrical pain, and also demonstrated the replicability of the somatic/vicarious dissociation. These findings suggest possible mechanisms underlying limitations in feeling others’ pain, and present new, more specific, brain targets for studying pain empathy

Nonpolitical Images Evoke Neural Predictors of Political Ideology

Political ideologies summarize dimensions of life that define how a person organizes their public and private behavior, including their attitudes associated with sex, family, education, and personal autonomy [1, 2]. Despite the abstract nature of such sensibilities, fundamental features of political ideology have been found to be deeply connected to basic biological mechanisms [3–7] that may serve to defend against environmental challenges like contamination and physical threat [8–12]. These results invite the provocative claim that neural responses to nonpolitical stimuli (like contaminated food or physical threats) should be highly predictive of abstract political opinions (like attitudes toward gun control and abortion) [13]. We applied a machinelearning method to fMRI data to test the hypotheses that brain responses to emotionally evocative images predict individual scores on a standard political ideology assay. Disgusting images, especially those related to animalreminder disgust (e.g., mutilated body), generate neural responses that are highly predictive of political orientation even though these neural predictors do not agree with participants’ conscious rating of the stimuli. Images from other affective categories do not support such predictions. Remarkably, brain responses to a single disgusting stimulus were sufficient to make accurate predictions about an individual subject’s political ideology. These results provide strong support for the idea that fundamental neural processing differences that emerge under the challenge of emotionally evocative stimuli may serve to structure political beliefs in ways formerly unappreciated

Venlafaxine treatment reduces the deficit of executive control of attention in patients with major depressive disorder

Attention plays an essential role in supporting other cognitive functions and behavior, and disturbance of attention is one of the most common symptoms in major depressive disorder (MDD). Although treatment with venlafaxine for MDD symptoms has been shown to reduce deficits in cognition and emotion regulation, it remains unclear whether venlafaxine improves specific attentional functions. We used the Attention Network Test to measure the attentional functions of alerting, orienting, and executive control before and after treatment with venlafaxine in patients with MDD compared to untreated healthy controls. Before treatment, the MDD group showed a selective impairment in alerting and executive control of attention, while there were no significant group differences in the orienting function. The interaction between group and session was significant for executive control, and after treatment with venlafaxine, the performance of the MDD group on executive control of attention was not significantly different from that of controls. Reported symptoms of MDD were also significantly reduced after treatment with venlafaxine. These results demonstrate that treatment with venlafaxine selectively normalizes the executive control function of attention in addition to improving clinical symptoms in MDD