Dyadic adjustment, family coping, body image, quality of life and psychological morbidity in patients with psoriasis and their partners

Background Psoriasis is an incurable and chronic disease that includes unpredictable periods of remission and relapse requiring long-term therapy. Purpose This paper focuses on the relationship among family coping, psychological morbidity, body image, dyadic adjustment and quality of life in psoriatic patients and their partners. Method One hundred and one patients with psoriasis and 78 partners comprised the sample. They were regular users of the Dermatology Service of a Central Northern hospital in Portugal and a private dermatology clinic. Patients with psoriasis were assessed on anxiety, depression, body image, quality of life, dyadic adjustment and family coping. Partners were assessed on the same measures except body image and quality of life. Results A positive relationship among dyadic adjustment, psychological morbidity and family coping in patients and their partners was found. Also, patients with lower levels of quality of life had partners with higher levels of depressive and anxious symptoms. Better dyadic adjustment predicted family coping in the psoriatic patient. High levels of dyadic adjustment in patients and low partners’ trait anxiety predicted better dyadic adjustment in partners. Conclusion The results highlight the importance of incorporating family variables in psychological interventions in psoriasis’ care, particularly family coping and dyadic adjustment as well as the need for psychological intervention to focus both on patients and partners

Spatiotemporal neural characterization of prediction error valence and surprise during reward learning in humans

Reward learning depends on accurate reward associations with potential choices. These associations can be attained with reinforcement learning mechanisms using a reward prediction error (RPE) signal (the difference between actual and expected rewards) for updating future reward expectations. Despite an extensive body of literature on the influence of RPE on learning, little has been done to investigate the potentially separate contributions of RPE valence (positive or negative) and surprise (absolute degree of deviation from expectations). Here, we coupled single-trial electroencephalography with simultaneously acquired fMRI, during a probabilistic reversal-learning task, to offer evidence of temporally overlapping but largely distinct spatial representations of RPE valence and surprise. Electrophysiological variability in RPE valence correlated with activity in regions of the human reward network promoting approach or avoidance learning. Electrophysiological variability in RPE surprise correlated primarily with activity in regions of the human attentional network controlling the speed of learning. Crucially, despite the largely separate spatial extend of these representations our EEG-informed fMRI approach uniquely revealed a linear superposition of the two RPE components in a smaller network encompassing visuo mnemonic and reward areas. Activity in this network was further predictive of stimulus value updating indicating a comparable contribution of both signals to reward learning

Neural processes mediating contextual influences on human choice behaviour

Contextual influences on choice are ubiquitous in ecological settings. Current evidence suggests that subjective values are normalized with respect to the distribution of potentially available rewards. However, how this context-sensitivity is realised in the brain remains unknown. To address this, here we examine functional magnetic resonance imaging (fMRI) data during performance of a gambling task where blocks comprise values drawn from one of two different, but partially overlapping, reward distributions or contexts. At the beginning of each block (when information about context is provided), hippocampus is activated and this response is enhanced when contextual influence on choice increases. In addition, response to value in ventral tegmental area/substantia nigra (VTA/SN) shows context-sensitivity, an effect enhanced with an increased contextual influence on choice. Finally, greater response in hippocampus at block start is associated with enhanced context sensitivity in VTA/SN. These findings suggest that context-sensitive choice is driven by a brain circuit involving hippocampus and dopaminergic midbrain

Mapping anhedonia onto reinforcement learning: A behavioural meta-analysis

BACKGROUND: Depression is characterised partly by blunted reactions to reward. However, tasks probing this deficiency have not distinguished insensitivity to reward from insensitivity to the prediction errors for reward that determine learning and are putatively reported by the phasic activity of dopamine neurons. We attempted to disentangle these factors with respect to anhedonia in the context of stress, Major Depressive Disorder (MDD), Bipolar Disorder (BPD) and a dopaminergic challenge. METHODS: Six behavioural datasets involving 392 experimental sessions were subjected to a model-based, Bayesian meta-analysis. Participants across all six studies performed a probabilistic reward task that used an asymmetric reinforcement schedule to assess reward learning. Healthy controls were tested under baseline conditions, stress or after receiving the dopamine D2 agonist pramipexole. In addition, participants with current or past MDD or BPD were evaluated. Reinforcement learning models isolated the contributions of variation in reward sensitivity and learning rate. RESULTS: MDD and anhedonia reduced reward sensitivity more than they affected the learning rate, while a low dose of the dopamine D2 agonist pramipexole showed the opposite pattern. Stress led to a pattern consistent with a mixed effect on reward sensitivity and learning rate. CONCLUSION: Reward-related learning reflected at least two partially separable contributions. The first related to phasic prediction error signalling, and was preferentially modulated by a low dose of the dopamine agonist pramipexole. The second related directly to reward sensitivity, and was preferentially reduced in MDD and anhedonia. Stress altered both components. Collectively, these findings highlight the contribution of model-based reinforcement learning meta-analysis for dissecting anhedonic behavior