Stress is present in everyday life in various forms and situations. Two stressors frequently investigated are physiological and psychosocial stress. Besides similar subjective and hormonal responses, it has been suggested that they also share common neural substrates. The current study used activation-likelihood-estimation meta-analysis to test this assumption by integrating results of previous neuroimaging studies on stress processing. Reported results are cluster-level FWE corrected. The inferior frontal gyrus (IFG) and the anterior insula (AI) were the only regions that demonstrated overlapping activation for both stressors. Analysis of physiological stress showed consistent activation of cognitive and affective components of pain processing such as the insula, striatum, or the middle cingulate cortex. Contrarily, analysis across psychosocial stress revealed consistent activation of the right superior temporal gyrus and deactivation of the striatum. Notably, parts of the striatum appeared to be functionally specified: the dorsal striatum was activated in physiological stress, whereas the ventral striatum was deactivated in psychosocial stress. Additional functional connectivity and decoding analyses further characterized this functional heterogeneity and revealed higher associations of the dorsal striatum with motor regions and of the ventral striatum with reward processing. Based on our meta-analytic approach, activation of the IFG and the AI seems to indicate a global neural stress reaction. While physiological stress activates a motoric fight-or-flight reaction, during psychosocial stress attention is shifted towards emotion regulation and goal-directed behavior, and reward processing is reduced. Our results show the significance of differentiating physiological and psychosocial stress in neural engagement. Furthermore, the assessment of deactivations in addition to activations in stress research is highly recommended.

Although cognitive regulation of emotion has been extensively examined, there is a lack of studies assessing cognitive regulation in stressful achievement situations. This study used functional magnetic resonance imaging in 23 females and 20 males to investigate cognitive downregulation of negative, stressful sensations during a frequently used psychosocial stress task. Additionally, subjective responses, cognitive regulation strategies, salivary cortisol, and skin conductance response were assessed. Subjective response supported the experimental manipulation by showing higher anger and negative affect ratings after stress regulation than after the mere exposure to stress. On a neural level, right middle frontal gyrus (MFG) and right superior temporal gyrus (STG) were more strongly activated during regulation than nonregulation, whereas the hippocampus was less activated during regulation. Sex differences were evident: after regulation females expressed higher subjective stress ratings than males, and these ratings were associated with right hippocampal activation. In the nonregulation block, females showed greater activation of the left amygdala and the right STG during stress than males while males recruited the putamen more robustly in this condition. Thus, cognitive regulation of stressful achievement situations seems to induce additional stress, to recruit regions implicated in attention integration and working memory and to deactivate memory retrieval. Stress itself is associated with greater activation of limbic as well as attention areas in females than males. Additionally, activation of the memory system during cognitive regulation of stress is associated with greater perceived stress in females. Sex differences in cognitive regulation strategies merit further investigation that can guide sex sensitive interventions for stress-associated disorders.

BACKGROUND: Disentangling psychopathological heterogeneity in schizophrenia is challenging, and previous results remain inconclusive. We employed advanced machine learning to identify a stable and generalizable factorization of the Positive and Negative Syndrome Scale and used it to identify psychopathological subtypes as well as their neurobiological differentiations. METHODS: Positive and Negative Syndrome Scale data from the Pharmacotherapy Monitoring and Outcome Survey cohort (1545 patients; 586 followed up after 1.35 6 0.70 years) were used for learning the factor structure by an orthonormal projective non-negative factorization. An international sample, pooled from 9 medical centers across Europe, the United States, and Asia (490 patients), was used for validation. Patients were clustered into psychopathological subtypes based on the identified factor structure, and the neurobiological divergence between the subtypes was assessed by classification analysis on functional magnetic resonance imaging connectivity patterns. RESULTS: A 4-factor structure representing negative, positive, affective, and cognitive symptoms was identified as the most stable and generalizable representation of psychopathology. It showed higher internal consistency than the original Positive and Negative Syndrome Scale subscales and previously proposed factor models. Based on this representation, the positive-negative dichotomy was confirmed as the (only) robust psychopathological subtypes, and these subtypes were longitudinally stable in about 80% of the repeatedly assessed patients. Finally, the individual subtype could be predicted with good accuracy from functional connectivity profiles of the ventromedial frontal cortex, temporoparietal junction, and precuneus. CONCLUSIONS: Machine learning applied to multisite data with cross-validation yielded a factorization generalizable across populations and medical systems. Together with subtyping and the demonstrated ability to predict subtype membership from neuroimaging data, this work further disentangles the heterogeneity in schizophrenia.

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