Brain connectomes in youth at risk for serious mental illness: a longitudinal perspective.

Identifying biomarkers for serious mental illnesses (SMI) has significant implications for prevention and early intervention. In the current study, changes in whole brain structural and functional connectomes were investigated in youth at transdiagnostic risk over a one-year period. Based on clinical assessments, participants were assigned to one of 5 groups: healthy controls (HC; n = 33), familial risk for serious mental illness (stage 0; n = 31), mild symptoms (stage 1a; n = 37), attenuated syndromes (stage 1b; n = 61), or discrete disorder (transition; n = 9).

tDCS for the treatment of negative symptoms in youth at clinical-high-risk for psychosis: A feasibility study.

Negative symptoms are often found in youth at clinical high risk (CHR) for psychosis. The present study explored the feasibility of using tDCS in conjunction with CBT in the treatment of negative symptoms in 5 youths at CHR. We sought to determine whether the protocol was feasible given the requirement for repeated visits over a three-week period, and to determine if measures of neurobiological change could be included, both acutely and following three weeks of stimulation.

Brain connectomes in youth at risk for serious mental illness: an exploratory analysis.

Background: Identifying early biomarkers of serious mental illness (SMI)-such as changes in brain structure and function-can aid in early diagnosis and treatment. Whole brain structural and functional connectomes were investigated in youth at risk for SMI.

Methods: Participants were classified as healthy controls (HC; n = 33), familial risk for serious mental illness (stage 0; n = 31), mild symptoms (stage 1a; n = 37), attenuated syndromes (stage 1b; n = 61), or discrete disorder (transition; n = 9) based on clinical assessments.

Cerebello-limbic functional connectivity patterns in youth at clinical high risk for psychosis.

Youth at clinical high risk (CHR) for psychosis can present not only with characteristic attenuated psychotic symptoms but also may have other comorbid conditions, including anxiety and depression. These undifferentiated mood symptoms can overlap with the clinical presentation of youth with Distress syndromes. Increased resting-state functional connectivity within cerebello-thalamo-cortical (CTC) pathways has been proposed as a trait-specific biomarker for CHR.

Social functioning and brain imaging in individuals at clinical high-risk for psychosis: A systematic review.

Impairments in social functioning are a core impairment in psychosis and are associated with poor outcomes. These deficits are found in those at clinical high-risk (CHR) for psychosis, and can persist even in the absence of transition. However, the neurobiological underpinnings of social functioning remain unclear, therefore we conducted a systematic review of brain metrics that have been associated with social functioning in youth at CHR for psychosis.

White matter microstructure in youth at risk for serious mental illness: A comparative analysis.

Identifying biomarkers of serious mental illness, such as altered white matter microstructure, can aid in early diagnosis and treatment. White matter microstructure was assessed using constrained spherical deconvolution of diffusion imaging data in a sample of 219 youth (age 12-25 years, 64.84% female) across 8 sites.

Functional imaging in youth at risk for transdiagnostic serious mental illness: Initial results from the PROCAN study.

Background: In their early stages, serious mental illnesses (SMIs) are often indistinguishable from one another, suggesting that studying alterations in brain activity in a transdiagnostic fashion could help to understand the neurophysiological origins of different SMI. The purpose of this study was to examine brain activity in youth at varying stages of risk for SMI using functional magnetic resonance imaging tasks (fMRI) that engage brain systems believed to be affected.

Methods: Two hundred and forty three participants at different stages of risk for SMI were recruited to the Canadian Psychiatric Risk and Outcome (PROCAN) study, however only 179 were scanned.

Brain changes associated with negative symptoms in clinical high risk for psychosis: A systematic review.

The negative symptoms of schizophrenia are linked to poorer functional outcomes and decreases in quality of life, and are often the first to develop in individuals who are at clinical high risk (CHR) for psychosis. However, the accompanying neurobiological changes are poorly understood. Therefore, we conducted a systematic review of the studies that have examined the brain metrics associated with negative symptoms in those at CHR.

White Matter Connectivity in Youth at Risk for Serious Mental Illness: A Longitudinal Analysis.

Longitudinal changes in white matter connectivity were assessed in a sample of youth at-risk for serious mental illness (n=183; age 12-25). Diffusion tensor imaging (DTI) was acquired at baseline and 12 months from youth recruited across two sites and classified as healthy controls (n=36), familial risk (n=30), mild-symptoms (n=41), attenuated syndromes (n=70), or transition (n=9) based on clinical assessments. Fractional anisotropy (FA) and mean diffusivity (MD) values were derived for the whole brain white matter, forceps minor, anterior cingulate, anterior thalamic radiations, inferior fronto-occipital fasciculus, superior longitudinal fasciculus, and uncinate fasciculus.

Stress impacts sensory variability through cortical sensory activity motifs.

Medically unexplained symptoms in depression are common. These individual-specific complaints are often considered an 'idiom of distress', yet animal studies suggest that cortical sensory representations are flexible and influenced by spontaneous cortical activity. We hypothesized that stress would reveal activity dynamics in somatosensory cortex resulting in greater sensory-evoked response variability.

Aberrant limbic brain structures in young individuals at risk for mental illness.

Aim: Alterations in limbic structures may be present before the onset of serious mental illness, but whether subfield-specific limbic brain changes parallel stages in clinical risk is unknown. To address this gap, we compared the hippocampus, amygdala, and thalamus subfield-specific volumes in adolescents at various stages of risk for mental illness.

Methods: MRI scans were obtained from 182 participants (aged 12-25 years) from the Canadian Psychiatric Risk and Outcome study.

Functional brain networks involved in lexical decision.

Functional magnetic resonance imaging (fMRI) studies on lexical decision (LD) attempting to isolate the brain network underlying access to lexical representations can be confounded by attentional and response processes. However, manipulating the "wordlikeness" of the LD stimuli can facilitate functional interpretation of each emerging brain network, providing principles for separation of attentional demand from linguistic processing. This is because activation of difficult-to-access lexical representations (for obscure real words), and avoidance of interfering word properties (for wordlike non-words), are both generally attentionally demanding.

Hippocampal tail volume as a predictive biomarker of antidepressant treatment outcomes in patients with major depressive disorder: a CAN-BIND report.

Finding a clinically useful neuroimaging biomarker that can predict treatment response in patients with major depressive disorder (MDD) is challenging, in part because of poor reproducibility and generalizability of findings across studies. Previous work has suggested that posterior hippocampal volumes in depressed patients may be associated with antidepressant treatment outcomes. The primary purpose of this investigation was to examine further whether posterior hippocampal volumes predict remission following antidepressant treatment.

Testing a deep convolutional neural network for automated hippocampus segmentation in a longitudinal sample of healthy participants.

Subtle changes in hippocampal volumes may occur during both physiological and pathophysiological processes in the human brain. Assessing hippocampal volumes manually is a time-consuming procedure, however, creating a need for automated segmentation methods that are both fast and reliable over time. Segmentation algorithms that employ deep convolutional neural networks (CNN) have emerged as a promising solution for large longitudinal neuroimaging studies.

Reduced functional connectivity during controlled semantic integration in schizophrenia: A multivariate approach.

Impairment in controlled semantic association is a central feature of schizophrenia, and the goal of the current functional magnetic resonance imaging study was to identify the neural correlates of this impairment. Thirty people with schizophrenia and 30 healthy age- and gender-matched control subjects performed a task requiring participants to match word pairs that varied in semantic distance (distant vs. close).

Functional brain networks involved in reality monitoring.

Source monitoring refers to the recollection of variables that specify the context and conditions in which a memory episode was encoded. This process involves using the qualitative and quantitative features of a memory trace to distinguish its source. One specific class of source monitoring is reality monitoring, which involves distinguishing internally generated from externally generated information, that is, memories of imagined events from real events.

Compensatory motor network connectivity is associated with motor sequence learning after subcortical stroke.

Following stroke, functional networks reorganize and the brain demonstrates widespread alterations in cortical activity. Implicit motor learning is preserved after stroke. However the manner in which brain reorganization occurs, and how it supports behavior within the damaged brain remains unclear.

Functional brain networks underlying detection and integration of disconfirmatory evidence.

Processing evidence that disconfirms a prior interpretation is a fundamental aspect of belief revision, and has clear social and clinical relevance. This complex cognitive process requires (at minimum) an alerting stage and an integration stage, and in the current functional magnetic resonance imaging (fMRI) study, we used multivariate analysis methodology on two datasets in an attempt to separate these sequentially-activated cognitive stages and link them to distinct functional brain networks. Thirty-nine healthy participants completed one of two versions of an evidence integration experiment involving rating two consecutive animal images, both of which consisted of two intact images of animal faces morphed together at different ratios (e.

Left-dominant temporal-frontal hypercoupling in schizophrenia patients with hallucinations during speech perception.

Background: Task-based functional neuroimaging studies of schizophrenia have not yet replicated the increased coordinated hyperactivity in speech-related brain regions that is reported with symptom-capture and resting-state studies of hallucinations. This may be due to suboptimal selection of cognitive tasks.

Methods: In the current study, we used a task that allowed experimental manipulation of control over verbal material and compared brain activity between 23 schizophrenia patients (10 hallucinators, 13 nonhallucinators), 22 psychiatric (bipolar), and 27 healthy controls.

Functional connectivity in a frontoparietal network involving the dorsal anterior cingulate cortex underlies decisions to accept a hypothesis.

Optimally interpreting our situations and experiences frequently requires comparing the evidence supporting conflicting hypotheses and deciding which to accept. This decision is comparable to an "Aha!" moment reached during insightful problem solving. We used a probabilistic reasoning task to investigate the neural activity underlying these processes.

Epoch-specific functional networks involved in working memory.

Working memory (WM) is not a unitary construct. There are distinct processes involved in encoding information, maintaining it on-line, and using it to guide responses. The anatomical configurations of these processes are more accurately analyzed as functionally connected networks than collections of individual regions.

Hyperintensity of functional networks involving voice-selective cortical regions during silent thought in schizophrenia.

An important aspect of schizophrenia symptomatology is inner-outer confusion, or blurring of ego boundaries, which is linked to symptoms such as hallucinations and Schneiderian delusions. Dysfunction in the cognitive processes involved in the generation of private thoughts may contribute to blurring of the ego boundaries through increased activation in functional networks including speech- and voice-selective cortical regions. In the present study, the neural underpinnings of silent verbal thought generation and speech perception were investigated using functional magnetic resonance imaging (fMRI).

The bivalency effect in task switching: event-related potentials.

During task switching, if we occasionally encounter stimuli that cue more than one task (i.e., bivalent stimuli), response slowing is observed on all univalent trials within that block, even when no features overlap with the bivalent stimuli.

Decreased efficiency of task-positive and task-negative networks during working memory in schizophrenia.

Working memory (WM) is one of the most impaired cognitive processes in schizophrenia. Functional magnetic resonance imaging (fMRI) studies in this area have typically found a reduction in information processing efficiency but have focused on the dorsolateral prefrontal cortex. In the current study using the Sternberg Item Recognition Test, we consider networks of regions supporting WM and measure the activation of functionally connected neural networks over different WM load conditions.