Identification of treatment-specific predictors of drug therapies for bipolar disorder (BD) is important because only about half of individuals respond to any specific medication. However, medication response in pediatric BD is variable and not well predicted by clinical characteristics.

A total of 121 youth with early course BD (acute manic/mixed episode) were prospectively recruited and randomized to 6 weeks of double-blind treatment with quetiapine (n = 71) or lithium (n = 50). Participants completed structural magnetic resonance imaging (MRI) at baseline before treatment and 1 week after treatment initiation, and brain morphometric features were extracted for each individual based on MRI scans. Positive antimanic treatment response at week 6 was defined as an over 50% reduction of Young Mania Rating Scale scores from baseline. Two-stage deep learning prediction model was established to distinguish responders and non-responders based on different feature sets.

Pre-treatment morphometry and morphometric changes occurring during the first week can both independently predict treatment outcome of quetiapine and lithium with balanced accuracy over 75% (all p < 0.05). Combining brain morphometry at baseline and week 1 allows prediction with the highest balanced accuracy (quetiapine: 83.2% and lithium: 83.5%). Predictions in the quetiapine and lithium group were found to be driven by different morphometric patterns.

These findings demonstrate that pre-treatment morphometric measures and acute brain morphometric changes can serve as medication response predictors in pediatric BD. Brain morphometric features may provide promising biomarkers for developing biologically-informed treatment outcome prediction and patient stratification tools for BD treatment development.

Childhood maltreatment is associated with altered neural reactivity during autobiographical memory (ABM) recall and a pattern of overgeneral memory (OGM). Altered ABM and OGM have been linked with psychopathology and poorer social functioning. The present study investigated the association between altered ABM and subsequent socio-emotional functioning (measured two years later) in a sample of adolescents with (N = 20; maltreatment group, MT) and without (N = 17; non-MT group) documented childhood maltreatment histories.

At baseline, adolescents (aged 12.6 ± 1.45 years) were administered the Autobiographical Memory Test to measure OGM. Participants also recalled specific ABMs in response to emotionally valenced cue words during functional MRI. Adolescents in both groups underwent assessments measuring depressive symptoms and prosocial behavior at both timepoints. Regression analyses were carried out to predict outcome measures at follow-up controlling for baseline levels.

In the MT group, greater OGM at baseline significantly predicted reduced prosocial behavior at follow-up and showed a trend level association with elevated depressive symptoms. Patterns of altered ABM-related brain activity did not significantly predict future psycho-social functioning.

The current findings highlight the potential value of OGM as a cognitive mechanism that could be targeted to reduce risk of depression in adolescents with prior histories of maltreatment.

Neuroanatomical abnormalities in first-episode psychosis (FEP) tend to be subtle and widespread. The vast majority of previous studies have used small samples, and therefore may have been underpowered. In addition, most studies have examined participants at a single research site, and therefore the results may be specific to the local sample investigated. Consequently, the findings reported in the existing literature are highly heterogeneous. This study aimed to overcome these issues by testing for neuroanatomical abnormalities in individuals with FEP that are expressed consistently across several independent samples.

Structural Magnetic Resonance Imaging data were acquired from a total of 572 FEP and 502 age and gender comparable healthy controls at five sites. Voxel-based morphometry was used to investigate differences in grey matter volume (GMV) between the two groups. Statistical inferences were made at p < 0.05 after family-wise error correction for multiple comparisons.

FEP showed a widespread pattern of decreased GMV in fronto-temporal, insular and occipital regions bilaterally; these decreases were not dependent on anti-psychotic medication. The region with the most pronounced decrease – gyrus rectus – was negatively correlated with the severity of positive and negative symptoms.

This study identified a consistent pattern of fronto-temporal, insular and occipital abnormalities in five independent FEP samples; furthermore, the extent of these alterations is dependent on the severity of symptoms and duration of illness. This provides evidence for reliable neuroanatomical alternations in FEP, expressed above and beyond site-related differences in anti-psychotic medication, scanning parameters and recruitment criteria.

Previous studies using resting-state functional neuroimaging have revealed alterations in whole-brain images, connectome-wide functional connectivity and graph-based metrics in groups of patients with schizophrenia relative to groups of healthy controls. However, it is unclear which of these measures best captures the neural correlates of this disorder at the level of the individual patient.

Here we investigated the relative diagnostic value of these measures. A total of 295 patients with schizophrenia and 452 healthy controls were investigated using resting-state functional Magnetic Resonance Imaging at five research centres. Connectome-wide functional networks were constructed by thresholding correlation matrices of 90 brain regions, and their topological properties were analyzed using graph theory-based methods. Single-subject classification was performed using three machine learning (ML) approaches associated with varying degrees of complexity and abstraction, namely logistic regression, support vector machine and deep learning technology.

Connectome-wide functional connectivity allowed single-subject classification of patients and controls with higher accuracy (average: 81%) than both whole-brain images (average: 53%) and graph-based metrics (average: 69%). Classification based on connectome-wide functional connectivity was driven by a distributed bilateral network including the thalamus and temporal regions.

These results were replicated across the three employed ML approaches. Connectome-wide functional connectivity permits differentiation of patients with schizophrenia from healthy controls at single-subject level with greater accuracy; this pattern of results is consistent with the ‘dysconnectivity hypothesis’ of schizophrenia, which states that the neural basis of the disorder is best understood in terms of system-level functional connectivity alterations.

Altered autobiographical memory (ABM) functioning has been implicated in the pathogenesis of depression and posttraumatic stress disorder and may represent one mechanism by which childhood maltreatment elevates psychiatric risk.

To investigate the impact of childhood maltreatment on ABM functioning.

Thirty-four children with documented maltreatment and 33 matched controls recalled specific ABMs in response to emotionally valenced cue words during functional magnetic resonance imaging.

Children with maltreatment experience showed reduced hippocampal and increased middle temporal and parahippocampal activation during positive ABM recall compared with peers. During negative ABM recall they exhibited increased amygdala activation, and greater amygdala connectivity with the salience network.

Childhood maltreatment is associated with altered ABM functioning, specifically reduced activation in areas encoding specification of positive memories, and greater activation of the salience network for negative memories. This pattern may confer latent vulnerability to future depression and posttraumatic stress disorder.

It is unclear to what extent the traditional distinction between neurological and psychiatric disorders reflects biological differences.

To examine neuroimaging evidence for the distinction between neurological and psychiatric disorders.

We performed an activation likelihood estimation meta-analysis on voxel-based morphometry studies reporting decreased grey matter in 14 neurological and 10 psychiatric disorders, and compared the regional and network-level alterations for these two classes of disease. In addition, we estimated neuroanatomical heterogeneity within and between the two classes.

Basal ganglia, insula, sensorimotor and temporal cortex showed greater impairment in neurological disorders; whereas cingulate, medial frontal, superior frontal and occipital cortex showed greater impairment in psychiatric disorders. The two classes of disorders affected distinct functional networks. Similarity within classes was higher than between classes; furthermore, similarity within class was higher for neurological than psychiatric disorders.

From a neuroimaging perspective, neurological and psychiatric disorders represent two distinct classes of disorders.

Childhood adversity is associated with significantly increased risk of psychiatric disorder. To date, functional magnetic resonance imaging (fMRI) studies of children have mainly focused on institutionalisation and investigated conscious processing of affect.

To investigate neural response to pre-attentively presented affect cues in a community sample of children with documented experiences of maltreatment in the home.

A masked dot-probe paradigm involving pre-attentive presentation of angry, happy and neutral facial expressions was employed. Eighteen maltreated children were compared with 23 carefully matched non-maltreated peers.

Increased neural response was observed in the right amygdala for pre-attentively presented angry and happy faces in maltreated v. non-maltreated children. Level of amygdala activation was negatively associated with age at onset for several abuse subtypes.

Maltreatment is associated with heightened neural response to positive and negative facial affect, even to stimuli outside awareness. This may represent a latent neural risk factor for future psychiatric disorder.