Using diffusion MRI data acquired with ultra-high gradient strength to improve tractography in routine-quality data.

The development of scanners with ultra-high gradient strength, spearheaded by the Human Connectome Project, has led to dramatic improvements in the spatial, angular, and diffusion resolution that is feasible for in vivo diffusion MRI acquisitions. The improved quality of the data can be exploited to achieve higher accuracy in the inference of both microstructural and macrostructural anatomy. However, such high-quality data can only be acquired on a handful of Connectom MRI scanners worldwide, while remaining prohibitive in clinical settings because of the constraints imposed by hardware and scanning time. In this study, we first update the classical protocols for tractography-based, manual annotation of major white-matter pathways, to adapt them to the much greater volume and variability of the streamlines that can be produced from today's state-of-the-art diffusion MRI data. We then use these protocols to annotate 42 major pathways manually in data from a Connectom scanner. Finally, we show that, when we use these manually annotated pathways as training data for global probabilistic tractography with anatomical neighborhood priors, we can perform highly accurate, automated reconstruction of the same pathways in much lower-quality, more widely available diffusion MRI data. The outcomes of this work include both a new, comprehensive atlas of WM pathways from Connectom data, and an updated version of our tractography toolbox, TRActs Constrained by UnderLying Anatomy (TRACULA), which is trained on data from this atlas. Both the atlas and TRACULA are distributed publicly as part of FreeSurfer. We present the first comprehensive comparison of TRACULA to the more conventional, multi-region-of-interest approach to automated tractography, and the first demonstration of training TRACULA on high-quality, Connectom data to benefit studies that use more modest acquisition protocols.

Brain function and clinical characterization in the Boston adolescent neuroimaging of depression and anxiety study.

We present a Human Connectome Project study tailored toward adolescent anxiety and depression. This study is one of the first studies of the Connectomes Related to Human Diseases initiative and is collecting structural, functional, and diffusion-weighted brain imaging data from up to 225 adolescents (ages 14-17 years), 150 of whom are expected to have a current diagnosis of an anxiety and/or depressive disorder. Comprehensive clinical and neuropsychological evaluations and longitudinal clinical data are also being collected. This article provides an overview of task functional magnetic resonance imaging (fMRI) protocols and preliminary findings (N = 140), as well as clinical and neuropsychological characterization of adolescents. Data collection is ongoing for an additional 85 adolescents, most of whom are expected to have a diagnosis of an anxiety and/or depressive disorder. Data from the first 140 adolescents are projected for public release through the National Institutes of Health Data Archive (NDA) with the timing of this manuscript. All other data will be made publicly-available through the NDA at regularly scheduled intervals. This article is intended to serve as an introduction to this project as well as a reference for those seeking to clinical, neurocognitive, and task fMRI data from this public resource.

From State-to-Trait Meditation: Reconfiguration of Central Executive and Default Mode Networks.

While brain default mode network (DMN) activation in human subjects has been associated with mind wandering, meditation practice has been found to suppress it and to increase psychological well-being. In addition to DMN activity reduction, experienced meditators (EMs) during meditation practice show an increased connectivity between the DMN and the central executive network (CEN). However, the gradual change between DMN and CEN configuration from pre-meditation, during meditation, and post-meditation is unknown. Here, we investigated the change in DMN and CEN configuration by means of brain activity and functional connectivity (FC) analyses in EMs across three back-to-back functional magnetic resonance imaging (fMRI) scans: pre-meditation baseline (trait), meditation (state), and post-meditation (state-to-trait). Pre-meditation baseline group comparison was also performed between EMs and healthy controls (HCs). Meditation trait was characterized by a significant reduction in activity and FC within DMN and increased anticorrelations between DMN and CEN. Conversely, meditation state and meditation state-to-trait periods showed increased activity and FC within the DMN and between DMN and CEN. However, the latter anticorrelations were only present in EMs with limited practice. The interactions between networks during these states by means of positive diametric activity (PDA) of the fractional amplitude of low-frequency fluctuations (fALFFs) defined as [Formula: see text] revealed no trait differences but significant increases during meditation state that persisted in meditation state-to-trait. The gradual reconfiguration in DMN and CEN suggest a neural mechanism by which the CEN negatively regulates the DMN and is probably responsible for the long-term trait changes seen in meditators and reported psychological well-being.

Neural - hormonal responses to negative affective stimuli: Impact of dysphoric mood and sex.

BACKGROUND: Maladaptive responses to negative affective stimuli are pervasive, including clinically ill and healthy people, and men and women respond differently at neural and hormonal levels. Inspired by the Research Domain Criteria initiative, we used a transdiagnostic approach to investigate the impact of sex and dysphoric mood on neural-hormonal responses to negative affective stimuli. METHODS: Participants included 99 individuals with major depressive disorder, psychosis and healthy controls. Functional magnetic resonance imaging (fMRI) was complemented with real-time acquisition of hypothalamo-pituitary-adrenal (HPA) and -gonadal (HPG) hormones. fMRI data were analyzed in SPM8 and task-related connectivity was assessed using generalized psychophysiological interaction. RESULTS: Across all participants, elevated cortisol response predicted lower brain activity in orbitofrontal cortex and hypothalamus-amygdala connectivity. In those with worse dysphoric mood, elevated cortisol response predicted lower activity in hypothalamus and hippocampus. In women, elevated cortisol response was associated with lower activity in medial prefrontal cortex and low hypothalamo-hippocampal connectivity. In women with high dysphoric mood, elevated cortisol response was associated with low hypothalamo-hippocampal connectivity. There were no interactions with diagnosis or medication. LIMITATIONS: There was limited power to correct for multiple comparisons across total number of ROIs and connectivity targets; cortisol responses were relatively low. CONCLUSIONS: We conclude that the pathophysiology in neural-hormonal responses to negative affective stimuli is shared across healthy and clinical populations and varies as a function of sex and dysphoric mood. Our findings may contribute to the development of hormonal adjunctive therapeutics that are sex-dependent, underscoring the importance of one's sex to precision medicine.

Predictive analytics in mental health: applications, guidelines, challenges and perspectives.

The emerging field of 'predictive analytics in mental health' has recently generated tremendous interest with the bold promise to revolutionize clinical practice in psychiatry paralleling similar developments in personalized and precision medicine. Here, we provide an overview of the key questions and challenges in the field, aiming to (1) propose general guidelines for predictive analytics projects in psychiatry, (2) provide a conceptual introduction to core aspects of predictive modeling technology, and (3) foster a broad and informed discussion involving all stakeholders including researchers, clinicians, patients, funding bodies and policymakers.

Brain connectomics predict response to treatment in social anxiety disorder.

We asked whether brain connectomics can predict response to treatment for a neuropsychiatric disorder better than conventional clinical measures. Pre-treatment resting-state brain functional connectivity and diffusion-weighted structural connectivity were measured in 38 patients with social anxiety disorder (SAD) to predict subsequent treatment response to cognitive behavioral therapy (CBT). We used a priori bilateral anatomical amygdala seed-driven resting connectivity and probabilistic tractography of the right inferior longitudinal fasciculus together with a data-driven multivoxel pattern analysis of whole-brain resting-state connectivity before treatment to predict improvement in social anxiety after CBT. Each connectomic measure improved the prediction of individuals' treatment outcomes significantly better than a clinical measure of initial severity, and combining the multimodal connectomics yielded a fivefold improvement in predicting treatment response. Generalization of the findings was supported by leave-one-out cross-validation. After dividing patients into better or worse responders, logistic regression of connectomic predictors and initial severity combined with leave-one-out cross-validation yielded a categorical prediction of clinical improvement with 81% accuracy, 84% sensitivity and 78% specificity. Connectomics of the human brain, measured by widely available imaging methods, may provide brain-based biomarkers (neuromarkers) supporting precision medicine that better guide patients with neuropsychiatric diseases to optimal available treatments, and thus translate basic neuroimaging into medical practice.

Optimizing real time fMRI neurofeedback for therapeutic discovery and development.

While reducing the burden of brain disorders remains a top priority of organizations like the World Health Organization and National Institutes of Health, the development of novel, safe and effective treatments for brain disorders has been slow. In this paper, we describe the state of the science for an emerging technology, real time functional magnetic resonance imaging (rtfMRI) neurofeedback, in clinical neurotherapeutics. We review the scientific potential of rtfMRI and outline research strategies to optimize the development and application of rtfMRI neurofeedback as a next generation therapeutic tool. We propose that rtfMRI can be used to address a broad range of clinical problems by improving our understanding of brain-behavior relationships in order to develop more specific and effective interventions for individuals with brain disorders. We focus on the use of rtfMRI neurofeedback as a clinical neurotherapeutic tool to drive plasticity in brain function, cognition, and behavior. Our overall goal is for rtfMRI to advance personalized assessment and intervention approaches to enhance resilience and reduce morbidity by correcting maladaptive patterns of brain function in those with brain disorders.

Altered language network activity in young people at familial high-risk for schizophrenia.

BACKGROUND: Abnormalities in language and language neural circuitry are observed in schizophrenia (SZ). Similar, but less pronounced language deficits are also seen in young first-degree relatives of people with SZ, who are at higher familial risk (FHR) for the disorder than the general population. The neural underpinnings of these deficits in people with FHR are unclear. METHODS: Participants were 43 people with FHR and 32 comparable controls. fMRI scans were collected while participants viewed associated and unrelated word pairs, and performed a lexical decision task. fMRI analyses conducted in SPM8 examined group differences in the modulation of hemodynamic activity by semantic association. RESULTS: There were no group differences in demographics, IQ or behavioral semantic priming, but FHR participants had more schizotypal traits than controls. Controls exhibited the expected suppression of hemodynamic activity to associated versus unrelated word pairs. Compared to controls, FHR participants showed an opposite pattern of hemodynamic modulation to associated versus unrelated word pairs, in the left inferior frontal gyrus (IFG), right superior and middle temporal gyrus (STG) and the left cerebellum. Group differences in activation were significant, FWE-corrected for multiple comparisons (p<0.05). Activity within the IFG during the unrelated condition predicted schizotypal symptoms in FHR participants. CONCLUSIONS: FHR for SZ is associated with abnormally increased neural activity to semantic associates within an inferior frontal/temporal network. This might increase the risk of developing unusual ideas, perceptions and disorganized language that characterize schizotypal traits, potentially predicting which individuals are at greater risk to develop a psychotic disorder.

A review of neuroimaging studies of young relatives of individuals with schizophrenia: a developmental perspective from schizotaxia to schizophrenia.

In an effort to identify the developing abnormalities preceding psychosis, Dr. Ming T. Tsuang and colleagues at Harvard expanded Meehl's concept of "schizotaxia," and examined brain structure and function in families affected by schizophrenia (SZ). Here, we systematically review genetic (familial) high-risk (HR) studies of SZ using magnetic resonance imaging (MRI), examine how findings inform models of SZ etiology, and suggest directions for future research. Neuroimaging studies of youth at HR for SZ through the age of 30 were identified through a MEDLINE (PubMed) search. There is substantial evidence of gray matter volume abnormalities in youth at HR compared to controls, with an accelerated volume reduction over time in association with symptoms and cognitive deficits. In structural neuroimaging studies, prefrontal cortex (PFC) alterations were the most consistently reported finding in HR. There was also consistent evidence of smaller hippocampal volume. In functional studies, hyperactivity of the right PFC during performance of diverse tasks with common executive demands was consistently reported. The only longitudinal fMRI study to date revealed increasing left middle temporal activity in association with the emergence of psychotic symptoms. There was preliminary evidence of cerebellar and default mode network alterations in association with symptoms. Brain abnormalities in structure, function and neurochemistry are observed in the premorbid period in youth at HR for SZ. Future research should focus on the genetic and environmental contributions to these alterations, determine how early they emerge, and determine whether they can be partially or fully remediated by innovative treatments.

HPA-axis hormone modulation of stress response circuitry activity in women with remitted major depression.

Decades of clinical and basic research indicate significant links between altered hypothalamic-pituitary-adrenal (HPA)-axis hormone dynamics and major depressive disorder (MDD). Recent neuroimaging studies of MDD highlight abnormalities in stress response circuitry regions which play a role in the regulation of the HPA-axes. However, there is a dearth of research examining these systems in parallel, especially as related to potential trait characteristics. The current study addresses this gap by investigating neural responses to a mild visual stress challenge with real-time assessment of adrenal hormones in women with MDD in remission and controls. Fifteen women with recurrent MDD in remission (rMDD) and 15 healthy control women were scanned on a 3T Siemens MR scanner while viewing neutral and negative (stress-evoking) stimuli. Blood samples were obtained before, during, and after scanning for the measurement of HPA-axis hormone levels. Compared to controls, rMDD women demonstrated higher anxiety ratings, increased cortisol levels, and hyperactivation in the amygdala and hippocampus, p<0.05, family-wise error (FWE)-corrected in response to the stress challenge. Among rMDD women, amygdala activation was negatively related to cortisol changes and positively associated with the duration of remission. Findings presented here provide evidence for differential effects of altered HPA-axis hormone dynamics on hyperactivity in stress response circuitry regions elicited by a well-validated stress paradigm in women with recurrent MDD in remission.

Age-associated reduction of asymmetry in prefrontal function and preservation of conceptual repetition priming.

Older adults often show bilateral brain activation, compared to unilateral activation in younger adults, when performing tasks in domains of age-associated cognitive impairment, such as episodic and working memory. Less is known about activation associated with performance in cognitive domains that are typically unaffected by healthy aging. We used event-related functional magnetic resonance imaging to examine age-related patterns in brain activation associated with a form of implicit memory, repetition priming, which is typically preserved in healthy aging. Sixteen younger adults and 15 nondemented older adults performed semantic judgments (abstract/concrete) on single words in a study phase. In a test phase, identical judgments were made for repeated and new words. Younger and older adults showed similar response-time benefits (repetition priming) from repeated semantic classification. Repetition priming was associated with repetition-related reductions of prefrontal activation in both groups, but the patterns of activation differed between groups. Both groups showed similar activation reductions in dorsal left inferior prefrontal cortex (LIPFC), but older adults showed less reduction than younger adults in ventral and anterior LIPFC. Activation reductions were exclusively left-lateralized for younger adults, whereas older adults showed additional reductions in multiple regions of right frontal cortices. Right prefrontal activation reductions in older adults correlated with better repetition priming and better performance on independent tests of semantic processing. Thus, reduced asymmetry of prefrontal activation reductions in healthy aging was related to conceptual repetition priming, a form of learning that is spared in aging, and with the sparing of semantic memory.

Prediction of Successful Memory Encoding from fMRI Data.

In this work, we explore the use of classification algorithms in predicting mental states from functional neuroimaging data. We train a linear support vector machine classifier to characterize spatial fMRI activation patterns. We employ a general linear model based feature extraction method and use the t-test for feature selection. We evaluate our method on a memory encoding task, using participants' subjective prediction about learning as a benchmark for our classifier. We show that the classifier achieves better than random predictions and the average accuracy is close to subject's own prediction performance. In addition, we validate our tool on a simple motor task where we demonstrate an average prediction accuracy of over 90%. Our experiments demonstrate that the classifier performance depends significantly on the complexity of the experimental design and the mental process of interest.

Differential development of high-level visual cortex correlates with category-specific recognition memory.

High-level visual cortex in humans includes functionally defined regions that preferentially respond to objects, faces and places. It is unknown how these regions develop and whether their development relates to recognition memory. We used functional magnetic resonance imaging to examine the development of several functionally defined regions including object (lateral occipital complex, LOC)-, face ('fusiform face area', FFA; superior temporal sulcus, STS)- and place ('parahippocampal place area', PPA)-selective cortices in children (ages 7-11), adolescents (12-16) and adults. Right FFA and left PPA volumes were substantially larger in adults than in children. This development occurred by expansion of FFA and PPA into surrounding cortex and was correlated with improved recognition memory for faces and places, respectively. In contrast, LOC and STS volumes and object-recognition memory remained constant across ages. Thus, the ventral stream undergoes a prolonged maturation that varies temporally across functional regions, is determined by brain region rather than stimulus category, and is correlated with the development of category-specific recognition memory.