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Over the past decade, transdiagnostic indicators in relation to neurobiological processes have provided extensive insight into youth’s risk for psychopathology. During development, exposure to childhood trauma and dysregulation (i.e., so-called AAA symptomology: anxiety, aggression, and attention problems) puts individuals at a disproportionate risk for developing psychopathology and altered network-level neural functioning. Evidence for the latter has emerged from resting-state fMRI studies linking mental health symptoms and aberrations in functional networks (e.g., cognitive control (CCN), default mode networks (DMN)) in youth, although few of these investigations have used longitudinal designs. Herein, we leveraged a three-year longitudinal study to identify whether traumatic exposures and concomitant dysregulation trigger changes in the developmental trajectories of resting-state functional networks involved in cognitive control (N = 190; 91 females; time 1 Mage = 11.81). Findings from latent growth curve analyses revealed that greater trauma exposure predicted increasing connectivity between the CCN and DMN across time. Greater levels of dysregulation predicted reductions in within-network connectivity in the CCN. These findings presented in typically developing youth corroborate connectivity patterns reported in clinical populations, suggesting there is predictive utility in using transdiagnostic indicators to forecast alterations in resting-state networks implicated in psychopathology.
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.
Objectives: Apathy is a debilitating symptom of Huntington’s disease (HD) and manifests before motor diagnosis, making it an excellent therapeutic target in the preclinical phase of Huntington’s disease (prHD). HD is a neurological genetic disorder characterized by cognitive and motor impairment, and psychiatric abnormalities. Apathy is not well characterized within the prHD. In previous literature, damage to the caudate and putamen has been correlated with increased apathy in other neurodegenerative and movement disorders. The objective of this study was to determine whether apathy severity in individuals with prHD is related to striatum volumes and cognitive control. We hypothesized that, within prHD individuals, striatum volumes and cognitive control scores would be related to apathy. Methods: We constructed linear mixed models to analyze striatum volumes and cognitive control, a composite measure that includes tasks assessing with apathy scores from 797 prHD participants. The outcome variable for each model was apathy, and the independent variables for the four separate models were caudate volume, putamen volume, cognitive control score, and motor symptom score. We also included depression as a covariate to ensure that our results were not solely related to mood. Results: Caudate and putamen volumes, as well as measures of cognitive control, were significantly related to apathy scores even after controlling for depression. Conclusions: The behavioral apathy expressed by these individuals was related to regions of the brain commonly associated with isolated apathy, and not a direct result of mood symptoms. (JINS, 2019, 25, 462–469)
Objectives: Huntington’s disease (HD) is a debilitating genetic disorder characterized by motor, cognitive and psychiatric abnormalities associated with neuropathological decline. HD pathology is the result of an extended chain of CAG (cytosine, adenine, guanine) trinucleotide repetitions in the HTT gene. Clinical diagnosis of HD requires the presence of an otherwise unexplained extrapyramidal movement disorder in a participant at risk for HD. Over the past 15 years, evidence has shown that cognitive, psychiatric, and subtle motor dysfunction is evident decades before traditional motor diagnosis. This study examines the relationships among subcortical brain volumes and measures of emerging disease phenotype in prodromal HD, before clinical diagnosis. Methods: The dataset includes 34 cognitive, motor, psychiatric, and functional variables and five subcortical brain volumes from 984 prodromal HD individuals enrolled in the PREDICT HD study. Using cluster analyses, seven distinct clusters encompassing cognitive, motor, psychiatric, and functional domains were identified. Individual cluster scores were then regressed against the subcortical brain volumetric measurements. Results: Accounting for site and genetic burden (the interaction of age and CAG repeat length) smaller caudate and putamen volumes were related to clusters reflecting motor symptom severity, cognitive control, and verbal learning. Conclusions: Variable reduction of the HD phenotype using cluster analysis revealed biologically related domains of HD and are suitable for future research with this population. Our cognitive control cluster scores show sensitivity to changes in basal ganglia both within and outside the striatum that may not be captured by examining only motor scores. (JINS, 2017, 23, 159–170)
Objectives: Connectionist theories of brain function took hold with the seminal contributions of Norman Geschwind a half century ago. Modern neuroimaging techniques have expanded the scientific interest in the study of brain connectivity to include the intact as well as disordered brain. Methods: In this review, we describe the most common techniques used to measure functional and structural connectivity, including resting state functional MRI, diffusion MRI, and electroencephalography and magnetoencephalography coherence. We also review the most common analytical approaches used for examining brain interconnectivity associated with these various imaging methods. Results: This review presents a critical analysis of the assumptions, as well as methodological limitations, of each imaging and analysis approach. Conclusions: The overall goal of this review is to provide the reader with an introduction to evaluating the scientific methods underlying investigations that probe the human connectome. (JINS, 2016, 22, 105–119)
Objectives: One of the most prominent features of schizophrenia is relatively lower general cognitive ability (GCA). An emerging approach to understanding the roots of variation in GCA relies on network properties of the brain. In this multi-center study, we determined global characteristics of brain networks using graph theory and related these to GCA in healthy controls and individuals with schizophrenia. Methods: Participants (N=116 controls, 80 patients with schizophrenia) were recruited from four sites. GCA was represented by the first principal component of a large battery of neurocognitive tests. Graph metrics were derived from diffusion-weighted imaging. Results: The global metrics of longer characteristic path length and reduced overall connectivity predicted lower GCA across groups, and group differences were noted for both variables. Measures of clustering, efficiency, and modularity did not differ across groups or predict GCA. Follow-up analyses investigated three topological types of connectivity—connections among high degree “rich club” nodes, “feeder” connections to these rich club nodes, and “local” connections not involving the rich club. Rich club and local connectivity predicted performance across groups. In a subsample (N=101 controls, 56 patients), a genetic measure reflecting mutation load, based on rare copy number deletions, was associated with longer characteristic path length. Conclusions: Results highlight the importance of characteristic path lengths and rich club connectivity for GCA and provide no evidence for group differences in the relationships between graph metrics and GCA. (JINS, 2016, 22, 240–249)
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
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.
Calhoun VD, Wu L, Kiehl KA, Eichele T, Pearlson GD. Aberrant processing of deviant stimuli in schizophrenia revealed by fusion of fMRI and EEG data.
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.
Structural brain measures are employed as endophenotypes in the search for schizophrenia susceptibility genes. We analyzed two independent structural imaging datasets with voxel-based morphometry and with source-based morphometry, a multivariate, independent components analysis, to determine the stability and heritability of regional gray matter concentration abnormalities in schizophrenia. The samples comprised 209 and 102 patients with schizophrenia and 208 and 96 healthy volunteers, respectively. The second sample additionally included non-ill siblings of participants with and without schizophrenia. A standard voxel-based analysis showed reproducible regional gray matter deficits in the affected participants compared with unrelated, unaffected controls in both datasets: patients showed significant gray matter concentration deficits in cortical frontal, temporal, and insular lobes. Source-based morphometry (SBM) was applied to the gray matter images of the entire sample to determine the effects of diagnosis on networks of covarying structures. The SBM analysis extracted 24 significant sets of covarying regions (components). Four of these components showed significantly lower gray matter concentrations in patients (p < .05). We determined the familiality of the observed SBM components based on 66 sibling pairs (25 discordant for schizophrenia). Two components, one including the medial frontal, insular, inferior frontal, and temporal lobes, and the other including the posterior occipital lobe, showed significant familiality (p < .05). We conclude that structural brain deficits in schizophrenia are replicable, and that SBM can extract unique familial and likely heritable components. SBM provides a useful data reduction technique that can provide measures that may serve as endophenotypes for schizophrenia.
Synaptic development and elimination are normal neurodevelopmental processes, which if altered could contribute to various neuropsychiatric disorders. 31P-1H magnetic resonance spectroscopic imaging (MRSI) and structural magnetic resonance imaging (MRI) exams were conducted on 105 healthy children ages 6–18 years old to identify neuromolecular indices of synaptic development and elimination. Over the age range studied, age-related changes in high-energy phosphate (phosphocreatine), membrane phospholipid metabolism (precursors and breakdown products), and percent gray matter volume were found. These neuromolecular and structural indices of synaptic development and elimination are associated with development of several cognitive domains. Monitoring of these molecular markers is essential for devising treatment strategies for neurodevelopmental disorders. (JINS, 2009, 15, 671–683.)
Formal thought disorder (FTD) is a debilitating symptom that affects 90 percent of schizophrenic patients and undermines a patient's capacity to communicate. This chapter reviews the clinical and cognitive symptoms related to (FTD), the evidence available that supports different aspects of semantic impairments in FTD, and recent data suggesting that a far-spreading activation theory within the semantic system is the core, underlying deficit resulting in FTD. The Thought, Language and Communication Scale (TLC) provided the first standardized tool that quantified positive FTD severity which in turn enhanced FTD research. An early neuroimaging study used positron emission tomography (PET) to evaluate the relationship between regional blood flow and symptomatology of 30 schizophrenia patients during a resting state. Based on the suggested role of semantic memory dysfunction in the pathophysiology of FTD, the chapter examines whether a specific semantic memory operation is more relevant to this symptomatology.