Adolescent and young adult survivors of pediatric brain tumors often live with long-term neuropsychological deficits, which have been found to be related to functional and structural brain changes related to the presence of the tumor itself as well as treatments such as radiation therapy. The importance of brain networks has become a central focus of research over recent decades across neurological populations. Graph theory is one way of analyzing network properties that can describe the integration, segregation, and other aspects of network organization. The existing literature using graph theory with survivors of brain tumor is small and inconsistent; therefore, more work is needed, particularly in survivors of pediatric brain tumors. The present study used graph theory to determine whether functional network properties in this population differ from healthy controls; whether graph metrics relate to core cognitive skills: attention, working memory, and processing speed; and whether they relate to a cumulative measure of neurological risk.

31 survivors and 31 matched controls completed neuropsychological testing including measures of attention, working memory, and processing speed. They also underwent resting state functional magnetic resonance imaging. Resting state data were preprocessed and spatially constrained independent component analysis was completed to construct connectivity matrices. Finally, graph metrics were calculated utilizing an area under the curve method, including global efficiency, clustering coefficient, betweenness centrality, and small-worldness. Group differences and associations between graph metrics, cognitive outcomes, and neurological risk were analyzed using SPSS version 28.0.

Results revealed a significant difference such that brain tumor survivors exhibited less small-world properties in their functional brain networks. This was found to be related to working memory, such that less smallworldness in the network was related to poorer performance. There were no significant relationships with neurological risk, but there were nonsignificant correlations of small-moderate effect size such that lower global efficiency and clustering coefficient were associated with greater neurological risk. Comparisons to structural network analysis from a similar sample and additional post-hoc analyses are also discussed.

These findings reveal that survivors of pediatric brain tumor indeed display significant differences in functional brain networks that are quantifiable by graph theory. It is also possible that, with further work, we might better understand how metrics such as smallworldness can be used to predict long-term cognitive outcomes and functional independence in adulthood.

The aim of the present study is to investigate the brain circuits or networks that underpin diagnostically specific tasks by means of group independent component analysis for FMRI toolbox (GIFT). We hypothesised that there will be neural network patterns of activation and deactivation, which correspond to real-time performance on clinical self-evaluation scales.

In total, 20 healthy controls (HC) and 22 patients with major depressive episode have been included. All subjects were scanned with functional magnetic resonance imaging (fMRI) with paradigm composed of diagnostic clinical self-assessment depression scale contrasted to neutral scale. The data were processed with group independent component analysis for functional MRI toolbox and statistical parametric mapping.

The results have demonstrated that there exist positively or negatively modulated brain networks during processing of diagnostic specific task questions for depressive disorder. There have also been confirmed differences in the networks processing diagnostic versus off blocks between patients and controls in anterior cingulate cortex and middle frontal gyrus. Diagnostic conditions (depression scale) when contrasted to neutral conditions demonstrate differential activity of right superior frontal gyrus and right middle cingulate cortex in the comparison of patients with HC.

Potential neuroimaging of state-dependent biomarkers has been directly linked with clinical assessment self-evaluation scale, administered as stimuli simultaneously with the fMRI acquisition. It may be regarded as further evidence in support of the convergent capacity of both methods to distinguish groups by means of incremental translational cross-validation.

Trait dissociation has not been examined from a structural human brain mapping perspective in healthy adults or children. Non-pathological dissociation shares some features with daydreaming and mind-wandering, but also involves subtle disruptions in affect and autobiographical memory.

To identify neurostructural biomarkers of trait dissociation in healthy children.

Typically developing 9- to 15-year-olds (n = 180) without psychological or behavioural disorders were enrolled in the Developmental Chronnecto-Genomics (DevCoG) study of healthy brain development and completed psychological assessments of trauma exposure and dissociation, along with a structural T1-weighted magnetic resonance imaging. We conducted univariate ANCOVA generalised linear models for each region of the default mode network examining the effects of trait dissociation, including scanner site, age, gender and trauma as covariates and correcting for multiple comparison.

We found that the precuneus was significantly larger in children with higher levels of trait dissociation but this was not related to trauma exposure. The inferior parietal volume was smaller in children with higher levels of trauma but was not related to dissociation. No other regions of interest, including frontal and limbic structures, were significantly related to trait dissociation even before multiple comparison correction.

Trait dissociation reflects subtle cognitive disruptions worthy of study in healthy people and warrants study as a potential risk factor for psychopathology. This neurostructural study of trait dissociation in healthy children identified the precuneus as an essential brain region to consider in future dissociation research.

The Cognitive Battery of the National Institutes of Health Toolbox (NIH-TB) is a collection of assessments that have been adapted and normed for administration across the lifespan and is increasingly used in large-scale population-level research. However, despite increasing adoption in longitudinal investigations of neurocognitive development, and growing recommendations that the Toolbox be used in clinical applications, little is known about the long-term temporal stability of the NIH-TB, particularly in youth.

The present study examined the long-term temporal reliability of the NIH-TB in a large cohort of youth (9–15 years-old) recruited across two data collection sites. Participants were invited to complete testing annually for 3 years.

Reliability was generally low-to-moderate, with intraclass correlation coefficients ranging between 0.31 and 0.76 for the full sample. There were multiple significant differences between sites, with one site generally exhibiting stronger temporal stability than the other.

Reliability of the NIH-TB Cognitive Battery was lower than expected given early work examining shorter test-retest intervals. Moreover, there were very few instances of tests meeting stability requirements for use in research; none of the tests exhibited adequate reliability for use in clinical applications. Reliability is paramount to establishing the validity of the tool, thus the constructs assessed by the NIH-TB may vary over time in youth. We recommend further refinement of the NIH-TB Cognitive Battery and its norming procedures for children before further adoption as a neuropsychological assessment. We also urge researchers who have already employed the NIH-TB in their studies to interpret their results with caution.

Adolescent subthreshold emotional symptoms arise from impaired self-referential information-processing and approach–avoidance behaviour network integration, which compromises goal evaluation and pursuit strategies.

We investigated whether impairment of negative emotion (goal) reappraisal strategies (self-focussing and self-distancing) generates emotional symptoms (emotional disorders precursors).

Using functional magnetic resonance imaging and a triple-network model (default mode, executive control and salience), functional connectivity differences within and between networks, and their modulation by task and relationships with emotional symptoms were determined in healthy adolescent girls (N = 202) grouped by presence or absence of emotional symptoms.

The groups differed in spectral power distribution and in dorsal default mode network and right executive control network modulation when self-focussing and self-distancing, respectively. Girls without emotional symptoms had greater spectral power and less network modulation. Greater spectral power was associated with reduced emotional symptoms and less dorsal default mode network modulation when self-focussing.

The early phases of anxiety and depressive disorders in adolescence are marked by emotional symptoms that usually emerge in the context of negative life events. To contend with the negative effect of such events, a typical reappraisal strategy is to distance oneself and switch the focus of one's thinking. This brain-imaging study in adolescent girls prone to the development of emotional disorders has found functional changes in key neural networks that are involved in reappraisal and shown that this process is impaired. This is important because it provides an early indication of these common disorders and a potential target for psychological interventions.

Positive symptoms are a useful predictor of aggression in schizophrenia. Although a similar pattern of abnormal brain structures related to both positive symptoms and aggression has been reported, this observation has not yet been confirmed in a single sample.

To study the association between positive symptoms and aggression in schizophrenia on a neurobiological level, a prospective meta-analytic approach was employed to analyze harmonized structural neuroimaging data from 10 research centers worldwide. We analyzed brain MRI scans from 902 individuals with a primary diagnosis of schizophrenia and 952 healthy controls.

The result identified a widespread cortical thickness reduction in schizophrenia compared to their controls. Two separate meta-regression analyses revealed that a common pattern of reduced cortical gray matter thickness within the left lateral temporal lobe and right midcingulate cortex was significantly associated with both positive symptoms and aggression.

These findings suggested that positive symptoms such as formal thought disorder and auditory misperception, combined with cognitive impairments reflecting difficulties in deploying an adaptive control toward perceived threats, could escalate the likelihood of aggression in schizophrenia.

Schizophrenia is associated with robust hippocampal volume deficits but subregion volume deficits, their associations with cognition, and contributing genes remain to be determined.

Hippocampal formation (HF) subregion volumes were obtained using FreeSurfer 6.0 from individuals with schizophrenia (n = 176, mean age ± s.d. = 39.0 ± 11.5, 132 males) and healthy volunteers (n = 173, mean age ± s.d. = 37.6 ± 11.3, 123 males) with similar mean age, gender, handedness, and race distributions. Relationships between the HF subregion volume with the largest between group difference, neuropsychological performance, and single-nucleotide polymorphisms were assessed.

This study found a significant group by region interaction on hippocampal subregion volumes. Compared to healthy volunteers, individuals with schizophrenia had significantly smaller dentate gyrus (DG) (Cohen's d = −0.57), Cornu Ammonis (CA) 4, molecular layer of the hippocampus, hippocampal tail, and CA 1 volumes, when statistically controlling for intracranial volume; DG (d = −0.43) and CA 4 volumes remained significantly smaller when statistically controlling for mean hippocampal volume. DG volume showed the largest between group difference and significant positive associations with visual memory and speed of processing in the overall sample. Genome-wide association analysis with DG volume as the quantitative phenotype identified rs56055643 (β = 10.8, p < 5 × 10−8, 95% CI 7.0–14.5) on chromosome 3 in high linkage disequilibrium with MOBP. Gene-based analyses identified associations between SLC25A38 and RPSA and DG volume.

This study suggests that DG dysfunction is fundamentally involved in schizophrenia pathophysiology, that it may contribute to cognitive abnormalities in schizophrenia, and that underlying biological mechanisms may involve contributions from MOBP, SLC25A38, and RPSA.

Suicide is a serious and not uncommon consequence of mood disorders that occurs primarily when individuals are depressed. Understanding the neurobiology of suicidal activity (thoughts or behaviors) is likely to facilitate prevention.

Seventy-nine adult depressed mood disorder patients (MDP), of which 25 had attempted suicide at least once, and 66 healthy controls (HC) participated in this study. Resting-state functional MRI was used to identify neural activity differences between suicide attempters (SA) and non-attempters (NA). Specifically, differences were examined in functional connectivity both within and between four large cognitive networks [Executive Control (ECN), Default Mode (DMN), Salience (SN), and Basal Ganglia (BGN)] and their respective associations with suicidal activity.

Compared to HCs, patients had greater posterior DMN activity, but less activity in the BGN, and less low-frequency spectral power in the dorso-medial DMN. Furthermore, increased posterior DMN activity in SA was associated with recent suicidal activity, whereas NA had reduced BGN activity and less dorso-medial DMN spectral power, the latter being associated with lifelong suicidal thinking. SA also had greater activity in midline circuitry compared to both HC and NA, and the pattern of BGN and DMN co-activity differed between SA and NA.

DMN engagement raises the possibility that suicidal activity in mood disorder patients may be a consequence of impaired self-referential thought processing. Furthermore, differential BGN and DMN co-activation according to suicide attempt status suggests that attempting suicide perhaps alters cognitive flexibility. These insights are potentially useful for understanding the neural basis of suicide activity.

Subsyndromal emotional symptoms in adolescence may represent precursors for full-blown emotional disorders in early adulthood. Understanding the neurobiological mechanisms that drive this development is essential for prevention.

Self-referential processing and emotion regulation are remodelled substantively during adolescence, therefore this study examined integration of key neural networks involved in these processes.

At baseline, clinical and resting-state functional magnetic resonance imaging data were collected for 88 adolescent girls (mean age 15 years), and 71 of these girls underwent repeat clinical assessment after 2 years. These 71 girls were then partitioned into two groups depending on the presence (ES+) or absence (ES−) of emotional symptoms, and differences in dynamic functional network connectivity were determined and correlated with clinical variables.

The two groups displayed a differential pattern of functional connectivity involving the left lateral prefrontal network (LPFN). Specifically, in the ES+ group this network displayed positive coupling with the right LPFN but negative coupling with the default mode network, and the inverse of this pattern was found in the ES− group. Furthermore, the coupling strengths between left and right LPFN at the irst time point predicted follow-up depression and state anxiety scores.

Our findings suggest that in adolescent girls, emotional symptoms may emerge as a result of impaired integration between networks involved in self-referential information processing and approach-avoidance behaviours. These impairments can compromise the pursuit of important goals and have an impact on emotion processing and finally may lead to the development of emotional disorders, such as anxiety and depression in adulthood.

None.

Studies have produced conflicting evidence regarding whether cognitive control deficits in patients with schizophrenia result from dysfunction within the cognitive control network (CCN; top-down) and/or unisensory cortex (bottom-up).

To investigate CCN and sensory cortex involvement during multisensory cognitive control in patients with schizophrenia.

Patients with schizophrenia and healthy controls underwent functional magnetic resonance imaging while performing a multisensory Stroop task involving auditory and visual distracters.

Patients with schizophrenia exhibited an overall pattern of response slowing, and these behavioural deficits were associated with a pattern of patient hyperactivation within auditory, sensorimotor and posterior parietal cortex. In contrast, there were no group differences in functional activation within prefrontal nodes of the CCN, with small effect sizes observed (incongruent–congruent trials). Patients with schizophrenia also failed to upregulate auditory cortex with concomitant increased attentional demands.

Results suggest a prominent role for dysfunction within auditory, sensorimotor and parietal areas relative to prefrontal CCN nodes during multisensory cognitive control.

Virtual reality in the form of simulated driving is a useful tool for studying the brain. Various clinical questions can be addressed, including both the role of alcohol as a modulator of brain function and regional brain activation related to elements of driving.

We reviewed a study of the neural correlates of alcohol intoxication through the use of a simulated-driving paradigm and wished to demonstrate the utility of recording continuous-driving behavior through a new study using a programmable driving simulator developed at our center.

Functional magnetic resonance imaging data was collected from subjects while operating a driving simulator. Independent component analysis (ICA) was used to analyze the data. Specific brain regions modulated by alcohol, and relationships between behavior, brain function, and alcohol blood levels were examined with aggregate behavioral measures. Fifteen driving epochs taken from two subjects while also recording continuously recorded driving variables were analyzed with ICA.

Preliminary findings reveal that four independent components correlate with various aspects of behavior. An increase in braking while driving was found to increase activation in motor areas, while cerebellar areas showed signal increases during steering maintenance, yet signal decreases during steering changes. Additional components and significant findings are further outlined.

In summary, continuous behavioral variables conjoined with ICA may offer new insight into the neural correlates of complex human behavior.

Aberrant electrophysiological and haemodynamic processing of auditory oddball stimuli is among the most robustly documented findings in patients with schizophrenia. However, no study to date has directly examined linked patterns of electrical and haemodynamic differences in patients and controls.

In a recent paper we demonstrated a data-driven approach, joint independent component analysis (jICA) to fuse together functional magnetic resonance imaging (fMRI) and event-related potential (ERP) data and elucidated the chronometry of auditory oddball target detection in healthy control subjects. In this paper we extend our fusion method to identify specific differences in the neuronal chronometry of target detection for chronic schizophrenia patients compared to healthy controls.

We found one linked source, consistent with the N2 response, known to be related to cognitive processing of deviant stimuli, spatially localized to bilateral fronto-temporal regions. This source showed significant between-group differences both in amplitude response and in the fMRI/ERP distribution pattern. These findings are consistent with previous work showing N2 amplitude and latency abnormalities in schizophrenia, and provide new information about the linkage between the two.

In summary, we use a novel approach to isolate and identify a linked fMRI/ERP component which shows marked differences in chronic schizophrenia patients. We also show that jointly using both fMRI and ERP measures provides a fully picture of the underlying haemodynamic and electrical changes which are present in patients. Our approach also has broad applicability to other diseases such as autism, Alzheimer's disease, or bipolar disorder.