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- aging (5)
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Rationale: Advances in neurocomputational modeling suggest that valuation systems for goal-directed (deliberative) on one side, and habitual (automatic) decision-making on the other side may rely on distinct computational strategies for reinforcement learning, namely model-free vs. model-based learning. As a key theoretical difference, the model-based system strongly demands cognitive functions to plan actions prospectively based on an internal cognitive model of the environment, whereas valuation in the model-free system relies on rather simple learning rules from operant conditioning to retrospectively associate actions with their outcomes and is thus cognitively less demanding. Acute stress reactivity is known to impair model-based but not model-free choice behavior, with higher working memory capacity protecting the model-based system from acute stress. However, it is not clear which impact accumulated real life stress has on model-free and model-based decision systems and how this influence interacts with cognitive abilities. Methods: We used a sequential decision-making task distinguishing relative contributions of both learning strategies to choice behavior, the Social Readjustment Rating Scale questionnaire to assess accumulated real life stress, and the Digit Symbol Substitution Test to test cognitive speed in 95 healthy subjects. Results: Individuals reporting high stress exposure who had low cognitive speed showed reduced model-based but increased model-free behavioral control. In contrast, subjects exposed to accumulated real life stress with high cognitive speed displayed increased model-based performance but reduced model-free control. Conclusion: These findings suggest that accumulated real life stress exposure can enhance reliance on cognitive speed for model-based computations, which may ultimately protect the model-based system from the detrimental influences of accumulated real life stress. The combination of accumulated real life stress exposure and slower information processing capacities, however, might favor model-free strategies. Thus, the valence and preference of either system strongly depends on stressful experiences and individual cognitive capacities.
No association of goal-directed and habitual control with alcohol consumption in young adults
(2017)
Alcohol dependence is a mental disorder that has been associated with an imbalance in behavioral control favoring model-free habitual over model-based goal-directed strategies. It is as yet unknown, however, whether such an imbalance reflects a predisposing vulnerability or results as a consequence of repeated and/or excessive alcohol exposure. We, therefore, examined the association of alcohol consumption with model-based goal-directed and model-free habitual control in 188 18-year-old social drinkers in a two-step sequential decision-making task while undergoing functional magnetic resonance imaging before prolonged alcohol misuse could have led to severe neurobiological adaptations. Behaviorally, participants showed a mixture of model-free and model-based decision-making as observed previously. Measures of impulsivity were positively related to alcohol consumption. In contrast, neither model-free nor model-based decision weights nor the trade-off between them were associated with alcohol consumption. There were also no significant associations between alcohol consumption and neural correlates of model-free or model-based decision quantities in either ventral striatum or ventromedial prefrontal cortex. Exploratory whole-brain functional magnetic resonance imaging analyses with a lenient threshold revealed early onset of drinking to be associated with an enhanced representation of model-free reward prediction errors in the posterior putamen. These results suggest that an imbalance between model-based goal-directed and model-free habitual control might rather not be a trait marker of alcohol intake per se.
BACKGROUND: Addiction is supposedly characterized by a shift from goal-directed to habitual decision making, thus facilitating automatic drug intake. The two-step task allows distinguishing between these mechanisms by computationally modeling goal-directed and habitual behavior as model-based and model-free control. In addicted patients, decision making may also strongly depend upon drug-associated expectations. Therefore, we investigated model-based versus model-free decision making and its neural correlates as well as alcohol expectancies in alcohol-dependent patients and healthy controls and assessed treatment outcome in patients. METHODS: Ninety detoxified, medication-free, alcohol-dependent patients and 96 age-and gender-matched control subjects underwent functional magnetic resonance imaging during the two-step task. Alcohol expectancies were measured with the Alcohol Expectancy Questionnaire. Over a follow-up period of 48 weeks, 37 patients remained abstinent and 53 patients relapsed as indicated by the Alcohol Timeline Followback method. RESULTS: Patients who relapsed displayed reduced medial prefrontal cortex activation during model-based decision making. Furthermore, high alcohol expectancies were associated with low model-based control in relapsers, while the opposite was observed in abstainers and healthy control subjects. However, reduced model-based control per se was not associated with subsequent relapse. CONCLUSIONS: These findings suggest that poor treatment outcome in alcohol dependence does not simply result from a shift from model-based to model-free control but is instead dependent on the interaction between high drug expectancies and low model-based decision making. Reduced model-based medial prefrontal cortex signatures in those who relapse point to a neural correlate of relapse risk. These observations suggest that therapeutic interventions should target subjective alcohol expectancies.
The goal of this study was to determine the prevalence of depression and its risk factors in patients with late-onset rheumatoid arthritis (RA) treated in German primary care practices. Longitudinal data from general practices (n=1072) throughout Germany were analyzed. Individuals initially diagnosed with RA (2009-2013) were identified, and 7301 patients were included and matched (1:1) to 7301 controls. The primary outcome measure was the initial diagnosis of depression within 5 years after the index date in patients with and without RA. Cox proportional hazards models were used to adjust for confounders. The mean age was 72.2 years (SD: 7.6 years). A total of 34.9 % of patients were men. Depression diagnoses were present in 22.0 % of the RA group and 14.3 % of the control group after a 5-year follow-up period (p < 0.001). In the multivariate regression model, RA was a strong risk factor for the development of depression (HR: 1.55, p < 0.001). There was significant interaction of RA and diagnosed inflammatory polyarthropathies (IP) (RA*IP interaction: p < 0.001). Furthermore, dementia, cancer, osteoporosis, hypertension, and diabetes were associated with a higher risk of developing depression (p values < 0.001). The risk of depression is significantly higher in patients with late-onset RA than in patients without RA for subjects treated in primary care practices in Germany. RA patients should be screened routinely for depression in order to ensure improved treatment and management.
Substance-dependent individuals often lack the ability to adjust decisions flexibly in response to the changes in reward contingencies. Prediction errors (PEs) are thought to mediate flexible decision-making by updating the reward values associated with available actions. In this study, we explored whether the neurobiological correlates of PEs are altered in alcohol dependence. Behavioral, and functional magnetic resonance imaging (fMRI) data were simultaneously acquired from 34 abstinent alcohol-dependent patients (ADP) and 26 healthy controls (HC) during a probabilistic reward-guided decision-making task with dynamically changing reinforcement contingencies. A hierarchical Bayesian inference method was used to fit and compare learning models with different assumptions about the amount of task-related information subjects may have inferred during the experiment. Here, we observed that the best-fitting model was a modified Rescorla-Wagner type model, the “double-update” model, which assumes that subjects infer the knowledge that reward contingencies are anti-correlated, and integrate both actual and hypothetical outcomes into their decisions. Moreover, comparison of the best-fitting model's parameters showed that ADP were less sensitive to punishments compared to HC. Hence, decisions of ADP after punishments were loosely coupled with the expected reward values assigned to them. A correlation analysis between the model-generated PEs and the fMRI data revealed a reduced association between these PEs and the BOLD activity in the dorsolateral prefrontal cortex (DLPFC) of ADP. A hemispheric asymmetry was observed in the DLPFC when positive and negative PE signals were analyzed separately. The right DLPFC activity in ADP showed a reduced correlation with positive PEs. On the other hand, ADP, particularly the patients with high dependence severity, recruited the left DLPFC to a lesser extent than HC for processing negative PE signals. These results suggest that the DLPFC, which has been linked to adaptive control of action selection, may play an important role in cognitive inflexibility observed in alcohol dependence when reinforcement contingencies change. Particularly, the left DLPFC may contribute to this impaired behavioral adaptation, possibly by impeding the extinction of the actions that no longer lead to a reward.
Background: The purpose of this study was to analyze the prevalence of long-term benzodiazepine use in older adults treated in general and neuropsychiatric practices in Germany. Methods: This study included 32,182 patients over the age of 65 years who received benzodiazepine prescriptions for the first time between January 2010 and December 2014 in general and neuropsychiatric practices in Germany. Follow up lasted until July 2016. The main outcome measure was the proportion of patients treated with benzodiazepines for >6 months. Results: The proportion of patients with benzodiazepine therapy for >6 months increased with age (65-70 years: 12.3%; 71-80 years: 15.5%; 81-90 years: 23.7%; >90 years: 31.6%) but did not differ significantly between men (15.5%) and women (17.1%). The proportion of patients who received benzodiazepines for >6 months was higher among those with sleep disorders (21.1%), depression (20.8%) and dementia (32.1%) than among those with anxiety (15.5%). By contrast, this proportion was lower among people diagnosed with adjustment disorders (7.7%) and back pain (3.8%). Conclusion: Overall, long-term use of benzodiazepines is common in older people, particularly in patients over the age of 80 and in those diagnosed with dementia, sleep disorders, or depression.
Cities and Mental Health
(2017)
Background: More than half of the global population currently lives in cities, with an increasing trend for further urbanization. Living in cities is associated with increased population density, traffic noise and pollution, but also with better access to health care and other commodities. Methods: This review is based on a selective literature search, providing an overview of the risk factors for mental illness in urban centers. Results: Studies have shown that the risk for serious mental illness is generally higher in cities compared to rural areas. Epidemiological studies have associated growing up and living in cities with a considerably higher risk for schizophrenia. However, correlation is not causation and living in poverty can both contribute to and result from impairments associated with poor mental health. Social isolation and discrimination as well as poverty in the neighborhood contribute to the mental health burden while little is known about specific inter actions between such factors and the built environment. Conclusion: Further insights on the interaction between spatial heterogeneity of neighborhood resources and socio-ecological factors is warranted and requires interdisciplinary research.
Background: The patterns of benzodiazepine prescriptions in older adults are of general and scientific interest as they are not yet well understood. The aim of this study was to compare the prescription patterns of benzodiazepines in elderly people in Germany to determine the share or proportion treated by general practitioners (GP) and neuropsychiatrists (NP). Methods: This study included 31,268 and 6,603 patients between the ages of 65 and 100 with at least one benzodiazepine prescription in 2014 from GP and NP, respectively. Demographic data included age, gender, and type of health insurance coverage. The share of elderly people with benzodiazepine prescriptions was estimated in different age and disease groups for both GP and NP patients. The share of the six most commonly prescribed drugs was also calculated for each type of practice. Results: The share of people taking benzodiazepines prescribed by GP increased from 3.2% in patients aged between 65 and 69 years to 8.6% in patients aged between 90 and 100 years, whereas this share increased from 5.4% to 7.1% in those seen by NP. Benzodiazepines were frequently used by patients suffering from sleep disorders (GP: 33.9%; NP: 5.5%), depression (GP: 17.9%; NP: 29.8%), and anxiety disorders (GP: 14.5%; NP: 22.8%). Lorazepam (30.3%), oxazepam (24.7%), and bromazepam (24.3%) were the three most commonly prescribed drugs for GP patients. In contrast, lorazepam (60.4%), diazepam (14.8%), and oxazepam (11.2%) were those more frequently prescribed to NP patients. Conclusion: Prescription patterns of benzodiazepine in the elderly varied widely between GP and NP.