This Viewpoint supports adoption of the Research Domain Criteria (RDoC) initiative to replace categorical with dimensional diagnoses.
This placebo trial examines the neurochemical mechanisms underlying the formation of placebo effects in patients with major depressive disorder.
This case-control study used whole-brain thalamic functional connectivity maps to examine the association of thalamic dysconnectivity and conversion to psychosis in youth and young adults at elevated clinical risk.
This neuroimaging study demonstrates characteristic signatures of altered intracortical relationships in patients with deficit schizophrenia compared with those with nondeficit schizophrenia, patients with bipolar I disorder, and healthy individuals.
This meta-analysis identified a concordance across psychiatric diagnoses in terms of integrity of an anterior insula/dorsal anterior cingulate–based network, which may relate to executive function deficits observed across diagnoses.
This observational study finds reduced effective connectivity in resting-state functional magnetic resonance imaging between key networks involved in attention and interoception in melancholia.
Van Dam et al identify structural neural characteristics independently associated with childhood maltreatment, comparing a sample with substance use disorders with a demographically comparable control sample, and they examine the relationship between childhood maltreatment–related structural brain changes and subsequent relapse.
This cohort study examines whether quantified neural function in social perception circuits can serve as an individual-level marker of autism spectrum disorder in children and adolescents.
This fMRI study determines differences in brain responses, habituation, and connectivity during exposure to mildly aversive sensory stimuli in youth with autism spectrum disorders (ASDs) and sensory overresponsivity (SOR) compared with youth with ASDs without SOR and control subjects.
Goh and colleagues assess brain lactate in individuals with autism spectrum disorder and typically developing controls using high-resolution, multiplanar spectroscopic imaging, and map the distribution of lactate in the brains of individuals with autism spectrum disorder, assessing correlations of elevated brain lactate with age, autism subtype, and intellectual ability.
Although psychiatric disorders are, to date, diagnosed on the basis of behavioral symptoms and course of illness, the interest in neurobiological markers of psychiatric disorders has grown substantially in recent years. However, current classification approaches are mainly based on data from a single biomarker, making it difficult to predict disorders characterized by complex patterns of symptoms.
To integrate neuroimaging data associated with multiple symptom-related neural processes and demonstrate their utility in the context of depression by deriving a predictive model of brain activation.
Two groups of participants underwent functional magnetic resonance imaging during 3 tasks probing neural processes relevant to depression.
Participants were recruited from the local population by use of advertisements; participants with depression were inpatients from the Department of Psychiatry, Psychosomatics, and Psychotherapy at the University of Wuerzburg, Wuerzburg, Germany.
We matched a sample of 30 medicated, unselected patients with depression by age, sex, smoking status, and handedness with 30 healthy volunteers.
Accuracy of single-subject classification based on whole-brain patterns of neural responses from all 3 tasks.
Integrating data associated with emotional and affective processing substantially increases classification accuracy compared with single classifiers. The predictive model identifies a combination of neural responses to neutral faces, large rewards, and safety cues as nonredundant predictors of depression. Regions of the brain associated with overall classification comprise a complex pattern of areas involved in emotional processing and the analysis of stimulus features.
Our method of integrating neuroimaging data associated with multiple, symptom-related neural processes can provide a highly accurate algorithm for classification. The integrated biomarker model shows that data associated with both emotional and reward processing are essential for a highly accurate classification of depression. In the future, large-scale studies will need to be conducted to determine the practical applicability of our algorithm as a biomarker-based diagnostic aid.
Watanabe et al directly examine whether oxytocin has beneficial effects on the sociocommunicational deficits of autism spectrum disorders using both behavioral and neural measures.