Absence of negative associations of insular and medial frontal gray matter volume with dissociative symptoms in schizophrenia

Decreased resting-state neural signal in the left angular gyrus as a potential neuroimaging biomarker of schizophrenia: An amplitude of low-frequency fluctuation and support vector machine analysis

Objective

Schizophrenia (SCH) is primarily diagnosed based on specific clinical symptoms, with the lack of any objective SCH-related biomarkers often resulting in patient misdiagnosis and the underdiagnosis of this condition. This study was developed to assess the utility of amplitude of low-frequency fluctuation (ALFF) values analyzed via support vector machine (SVM) methods as a means of diagnosing SCH.

Methods

In total, 131 SCH patients and 128 age- and gender-matched healthy control (HC) individuals underwent resting-state functional magnetic resonance imaging (rs-fMRI), with the resultant data then being analyzed using ALFF values and SVM methods.

Results

Relative to HC individuals, patients with SCH exhibited ALFF reductions in the left angular gyrus (AG), fusiform gyrus, anterior cingulate cortex (ACC), right cerebellum, bilateral middle temporal gyrus (MTG), and precuneus (PCu) regions. No SCH patient brain regions exhibited significant increases in ALFF relative to HC individuals. SVM results indicated that reductions in ALFF values in the bilateral PCu can be used to effectively differentiate between SCH patients and HCs with respective accuracy, sensitivity, and specificity values of 73.36, 91.60, and 54.69%.

Conclusion

These data indicate that SCH patients may exhibit characteristic reductions in regional brain activity, with decreased ALFF values of the bilateral PCu potentially offering value as a candidate biomarker capable of distinguishing between SCH patients and HCs.

Dissociation and Dissociative Disorders Reconsidered: Beyond Sociocognitive and Trauma Models Toward a Transtheoretical Framework

For more than 30 years, the posttraumatic model (PTM) and the sociocognitive model (SCM) of dissociation have vied for attention and empirical support. We contend that neither perspective provides a satisfactory account and that dissociation and dissociative disorders (e.g., depersonalization/derealization disorder, dissociative identity disorder) can be understood as failures of normally adaptive systems and functions. We argue for a more encompassing transdiagnostic and transtheoretical perspective that considers potentially interactive variables including sleep disturbances; impaired self-regulation and inhibition of negative cognitions and affects; hyperassociation and set shifts; and deficits in reality testing, source attributions, and metacognition. We present an overview of the field of dissociation, delineate uncontested and converging claims across perspectives, summarize key multivariable studies in support of our framework, and identify empirical pathways for future research to advance our understanding of dissociation, including studies of highly adverse events and dissociation. Expected final online publication date for the Annual Review of Clinical Psychology, Volume 18 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.