Schizophrenia Bulletin最新文献

Subtle distortions of the experience of lived space have long been associated with schizophrenia. Although a body-centric transformation of space is considered an essential component of anomalous subjective experience in schizophrenia, its impact on the 2 major body-centric spatial constructs, that is, personal space (PS) and peripersonal space (PPS), is still not clear. This systematic review and meta-analysis have been set up to: (1) summarize the evidence on putative extensional differences of PS and PPS in schizophrenia as compared with controls, and (2) evaluate the quality and the limitations of available studies on the topic. Four electronic literature databases (MEDLINE, EMBASE, PsychINFO, and CINAHL) were searched with the keywords "Personal space OR Interpersonal distance AND Schizophrenia," "Peripersonal space AND Schizophrenia" from inception until December 31, 2023, resulting in 15 studies on PS and 5 studies on PPS included in this systematic review. The 12 studies on PS included in the meta-analysis revealed that individuals with a diagnosis of schizophrenia place a larger interpersonal distance from the stimuli than controls, with a moderate effect size in both the fixed-effect model (Hedges' g = 0.558 [95% confidence interval, CI: 0.445-0.671]; z = 9.67; P < 0.0001) and the random effects model (0.547 [0.294-0.799]; z = 4.77; P = 0.0006). The 5 studies included in the meta-analysis on PPS showed that individuals with a diagnosis of schizophrenia exhibit a narrower PPS than the controls at the fixed-effect (Hedges' g = 1.043 [95%CI: .739-1.348]; z = 6.72; P < .0001), but not at the random effects model (1.318 [-0.721 to 3.359]; z = 1.79; P = .147). Heterogeneity was substantial in both meta-analyses. Overall, the findings indicate that both body-centered space constructs (PS and PPS) are affected in schizophrenia, with an enlargement PS and a reduction PPS, thereby supporting the distinction of these constructs. These modifications cohere with the subjective transformation of the lived space (aka espace vécu) reported in classical psychopathology and may be promising, neurodevelopmentally grounded, biomarkers of vulnerability to schizophrenia and its spectrum conditions.

Objective: Motivational deficits in schizophrenia are proposed to be attributable in part to abnormal effort-cost computations, calculations weighing the costs vs. the benefits of actions. Several reports have shown that people with schizophrenia display a reduced willingness to exert effort for monetary rewards when compared to controls. The primary goal of the current study was to further characterize reduced willingness to exert effort in schizophrenia by determining whether reduced willingness reflects (1) reduced sensitivity to reward, (2) increased sensitivity to effort, or (3) a combination of both.

Design: We assessed effort-cost decision-making in 30 controls and 30 people with schizophrenia, using 2 separate experimental tasks. Critically, one paradigm allowed for independent estimation of effects of reward and effort sensitivity on choice behavior. The other task isolated effort sensitivity by measuring effort in the absence of reward. Clinical interviews and self-report questionnaires were administered to people with schizophrenia to determine negative symptom severity.

Results: Across both tasks, we found evidence for reduced willingness to exert effort in people with schizophrenia compared to controls. Further, in both paradigms reduced willingness to exert effort was driven by increased sensitivity to effort in people with schizophrenia compared to controls. In contrast, measures of reward sensitivity did not significantly differ between groups. Surprisingly, we did not find correlations between task variables and measures of negative symptom severity.

Conclusions and relevance: These findings further specify prior work by identifying a specific contributory role for increased effort sensitivity in effort-cost decision-making deficits in schizophrenia.

Background and hypothesis: Current treatments for schizophrenia are only partially effective, and there are no medications for negative symptoms or cognitive impairment. Neuromodulation, such as repetitive transcranial magnetic stimulation (rTMS), has potential as a novel intervention for schizophrenia. Prior to clinical use, rTMS should have demonstrated safety in a large schizophrenia population. However, the safety profile of rTMS in schizophrenia is not well characterized, and regulatory agencies have expressed concern about safety in this population.

Study design: We conducted a systematic review with meta-analysis of rTMS studies in schizophrenia. We searched PubMed, the Cochrane Library, PsycINFO, and Science Citation Index Expanded for rTMS studies in schizophrenia that reported adverse effects. We extracted the number of participants who experienced an adverse effect and calculated the prevalence of each adverse effect for active or sham rTMS. We tested the difference between the prevalence of events in the active and sham conditions. We assessed risk of bias using the Cochrane Handbook.

Study results: The initial search identified 1472 studies. After screening, 261 full-text studies were assessed, and 126 met inclusion criteria (N = 4122 total subjects). The prevalence of headache or scalp pain, dizziness or syncope, facial twitching, and nausea was higher for active rTMS compared to sham (P < .05). The prevalence of all other adverse effects, including seizure, was not different between active and sham rTMS.

Conclusions: rTMS is safe and well tolerated for people with schizophrenia. Individuals with schizophrenia are not at increased risk for adverse effects, including seizure, compared to the general population.

Background and hypothesis: Individuals with schizophrenia (SZ) and bipolar disorder (BD) show disruptions in self-referential gaze perception-a social perceptual process related to symptoms and functioning. However, our current mechanistic understanding of these dysfunctions and relationships is imprecise.

Study design: The present study used mathematical modeling to uncover cognitive processes driving gaze perception abnormalities in SZ and BD, and how they relate to cognition, symptoms, and social functioning. We modeled the behavior of 28 SZ, 38 BD, and 34 controls (HC) in a self-referential gaze perception task using drift-diffusion models parameterized to index key cognitive components: drift rate (evidence accumulation efficiency), drift bias (perceptual bias), start point (expectation bias), threshold separation (response caution), and nondecision time (encoding/motor processes).

Study results: Results revealed that aberrant gaze perception in SZ and BD was driven by less efficient evidence accumulation, perceptual biases predisposing self-referential responses, and greater caution (SZ only). Across SZ and HC, poorer social functioning was related to greater expectation biases. Within SZ, perceptual and expectancy biases were associated with hallucination and delusion severity, respectively.

Conclusions: These findings indicate that diminished evidence accumulation and perceptual biases may underlie altered gaze perception in patients and that SZ may engage in compensatory cautiousness, sacrificing response speed to preserve accuracy. Moreover, biases at the belief and perceptual levels may relate to symptoms and functioning. Computational modeling can, therefore, be used to achieve a more nuanced, cognitive process-level understanding of the mechanisms of social cognitive difficulties, including gaze perception, in individuals with SZ and BD.

Background: Electroencephalography (EEG) is a noninvasive, cost-effective, and robust tool, which directly measures in vivo neuronal mass activity with high temporal resolution. Combined with state-of-the-art machine learning (ML) techniques, EEG recordings could potentially yield in silico biomarkers of severe mental disorders.

Hypothesis: Pathological and physiological aging processes influence the electrophysiological signatures of schizophrenia (SCZ) and major depressive disorder (MDD).

Study design: From a single-center cohort (N = 735, 51.6% male) comprising healthy control individuals (HC, N = 245) and inpatients suffering from SCZ (N = 250) or MDD (N = 240), we acquired resting-state 19 channel-EEG recordings. Using repeated nested cross-validation, support vector machine models were trained to (1) classify patients with SCZ or MDD and HC individuals and (2) predict age in HC individuals. The age model was applied to patient groups to calculate Electrophysiological Age Gap Estimation (EphysAGE) as the difference between predicted and chronological age. The links between EphysAGE, diagnosis, and medication were then further explored.

Study results: The classification models robustly discriminated SCZ from HC (balanced accuracy, BAC = 72.7%, P < .001), MDD from HC (BAC = 67.0%, P < .001), and SCZ from MDD individuals (BAC = 63.2%, P < .001). Notably, central alpha (8-11 Hz) power decrease was the most consistently predictive feature for SCZ and MDD. Higher EphysAGE was associated with an increased likelihood of being misclassified as SCZ in HC and MDD (ρHC = 0.23, P < .001; ρMDD = 0.17, P = .01).

Conclusions: ML models can extract electrophysiological signatures of MDD and SCZ for potential clinical use. However, the impact of aging processes on diagnostic separability calls for timely application of such models, possibly in early recognition settings.