Heterogeneity Analysis on Multi-state Brain Functional Connectivity and Adolescent Neurocognition.

Brain functional connectivity or connectome, a unique measure for brain functional organization, provides a great potential to explain the neurobiological underpinning of behavioral profiles. Existing connectome-based analyses highly concentrate on brain activities under a single cognitive state, and fail to consider heterogeneity when attempting to characterize brain-to-behavior relationships. In this work, we study the complex impact of multi-state functional connectivity on behaviors by analyzing the data from a recent landmark brain development and child health study. We propose a nonparametric, Bayesian supervised heterogeneity analysis to uncover neurodevelopmental subtypes with distinct effect mechanisms. We impose stochastic block structures to identify network-based functional phenotypes and develop a variational expectation-maximization algorithm to facilitate an efficient posterior computation. Through integrating resting-state and task-related functional connectomes, we dissect heterogeneous effect mechanisms on children's fluid intelligence from the functional network phenotypes including Fronto-parietal Network and Default Mode Network under different cognitive states. Based on extensive simulations, we further confirm the superior performance of our method on uncovering brain-to-behavior relationships.

Comprehension of English for-adverbials: The Nature of Lexical Meanings and the Neurocognitive Architecture of Language.

What is the nature of lexical meanings such that they can both compose with others and also appear boundless? We investigate this question by examining the compositional properties of for-time adverbial as in "Ana jumped for an hour." At issue is the source of the associated iterative reading which lacks overt morphophonological support, yet, the iteration is not disconnected from the lexical meanings in the sentence. This suggests an analysis whereby the iterative reading is the result of the interaction between lexical meanings under a specific compositional configuration. We test the predictions of two competing accounts: Mismatch-and-Repair and Partition-Measure. They differ in their assumptions about lexical meanings: assumptions that have implications for the possible compositional mechanisms that each can invoke. Mismatch-and-Repair assumes that lexical meaning representations are discrete, separate from the conceptual system from which they originally emerged and brought into sentence meaning through syntactic composition. Partition-Measure assumes that lexical meanings are contextually salient conceptual structures substantially indistinguishable from the conceptual system that they inhabit. During comprehension, lexical meanings construe a conceptual representation, in parallel, morphosyntactic and morphophonological composition as determined by the lexical items involved in the sentence. Whereas both hypotheses capture the observed cost in the punctual predicate plus for-time adverbial composition (e.g., jump (vs. swim) for an hour), their predictions differ regarding iteration with durative predicates; for example, swim for a year (vs. for an hour). Mismatch-and-Repair predicts contrasting processing profiles and nonoverlapping activation patterns along punctuality differences. Partition-Measure predicts overlapping processing and cortical distribution profiles, along the presence of iterativity. Results from a self-paced reading and an functional Magnetic Resonance Imaging (fMRI) studies bear out the predictions of the Partition-Measure account, supporting a view of linguistic meaning composition in line with an architecture of language whereby combinatoriality and generativity are distributed, carried out in parallel across linguistic and nonlinguistic subsystems.

Conditional Functional Graphical Models.

Graphical modeling of multivariate functional data is becoming increasingly important in a wide variety of applications. The changes of graph structure can often be attributed to external variables, such as the diagnosis status or time, the latter of which gives rise to the problem of dynamic graphical modeling. Most existing methods focus on estimating the graph by aggregating samples, but largely ignore the subject-level heterogeneity due to the external variables. In this article, we introduce a conditional graphical model for multivariate random functions, where we treat the external variables as conditioning set, and allow the graph structure to vary with the external variables. Our method is built on two new linear operators, the conditional precision operator and the conditional partial correlation operator, which extend the precision matrix and the partial correlation matrix to both the conditional and functional settings. We show that their nonzero elements can be used to characterize the conditional graphs, and develop the corresponding estimators. We establish the uniform convergence of the proposed estimators and the consistency of the estimated graph, while allowing the graph size to grow with the sample size, and accommodating both completely and partially observed data. We demonstrate the efficacy of the method through both simulations and a study of brain functional connectivity network.

Blunted neural reward response to alcohol and greater alcohol motivation in binge drinkers in a randomized clinical experiment.

BACKGROUND: Alcohol stimulates cerebral blood flow (CBF) in brain reward regions. However, neural processes that support sustained alcohol motivation after the first drink are not well understood. METHODS: Using a novel placebo-controlled, randomized, crossover experiment, 27 individuals who binge drink (BD; 15 M, 12 F) and 25 social drinkers (SD; 15 M, 10 F) underwent a behavioral test of self-motivated alcohol consumption using an Alcohol Taste Test (ATT) involving alcoholic and nonalcoholic beer on separate days. The test was followed immediately by perfusion functional magnetic resonance imaging (fMRI). On both days, participants then engaged in a post-scan ATT with placebo beer to assess sustained alcohol self-motivation without active alcohol effects. Linear mixed effects models were used to examine the effects of drinking group on the placebo-controlled effect of initial alcohol motivation on brain perfusion (whole brain corrected p < 0.001, cluster corrected p < 0.025) and on the relationship between placebo-controlled brain perfusion and sustained alcohol motivation. RESULTS: Initial alcohol self-motivation in the alcohol relative to placebo session led to markedly decreased activation in the medial orbitofrontal cortex (OFC) and the ventral striatum in BD relative to SD, indicative of neural reward tolerance. The BD group also showed an enhanced neural response in behavioral intention regions of the supplementary motor area (SMA) and inferior frontal gyrus (IFG) regions. Moreover, there was greater sustained alcohol motivation in BD than SD in the post-scan ATT in the alcohol relative to placebo session. Correspondingly, only in BD and only in the alcohol session, lower alcohol-induced OFC response correlated with concurrent sensitized SMA response, and each predicted the subsequent sustained higher alcohol motivation in the post-scan ATT. CONCLUSIONS: Alcohol-related OFC tolerance may play an important role in sustained alcohol motivation. Furthermore, both specific alcohol-related neural reward tolerance and premotor sensitization responses may contribute to escalating alcohol motivation to drive excessive alcohol intake, even in individuals without alcohol use disorder.

Sex differences in default mode network connectivity in healthy aging adults.

Women show an increased lifetime risk of Alzheimer's disease (AD) compared with men. Characteristic brain connectivity changes, particularly within the default mode network (DMN), have been associated with both symptomatic and preclinical AD, but the impact of sex on DMN function throughout aging is poorly understood. We investigated sex differences in DMN connectivity over the lifespan in 595 cognitively healthy participants from the Human Connectome Project-Aging cohort. We used the intrinsic connectivity distribution (a robust voxel-based metric of functional connectivity) and a seed connectivity approach to determine sex differences within the DMN and between the DMN and whole brain. Compared with men, women demonstrated higher connectivity with age in posterior DMN nodes and lower connectivity in the medial prefrontal cortex. Differences were most prominent in the decades surrounding menopause. Seed-based analysis revealed higher connectivity in women from the posterior cingulate to angular gyrus, which correlated with neuropsychological measures of declarative memory, and hippocampus. Taken together, we show significant sex differences in DMN subnetworks over the lifespan, including patterns in aging women that resemble changes previously seen in preclinical AD. These findings highlight the importance of considering sex in neuroimaging studies of aging and neurodegeneration.

Stress-level glucocorticoids increase fasting hunger and decrease cerebral blood flow in regions regulating eating.

CONTEXT: The neural regulation of appetite and energy homeostasis significantly overlaps with the neurobiology of stress. Frequent exposure to repeated acute stressors may cause increased allostatic load and subsequent dysregulation of the cortico-limbic striatal system leading to inefficient integration of postprandial homeostatic and hedonic signals. It is therefore important to understand the neural mechanisms by which stress generates alterations in appetite that may drive weight gain. OBJECTIVE: To determine glucocorticoid effects on metabolic, neural and behavioral factors that may underlie the association between glucocorticoids, appetite and obesity risk. METHODS: A randomized double-blind cross-over design of overnight infusion of hydrocortisone or saline followed by a fasting morning perfusion magnetic resonance imaging to assess regional cerebral blood flow (CBF) was completed. Visual Analog Scale (VAS) hunger, cortisol and metabolic hormones were also measured. RESULTS: Hydrocortisone relative to saline significantly decreased whole brain voxel based CBF responses in the hypothalamus and related cortico-striatal-limbic regions. Hydrocortisone significantly increased hunger VAS pre-scan, insulin, glucose and leptin, but not other metabolic hormones versus saline CBF groups. Hydrocortisone related increases in hunger were predicted by less reduction of CBF (hydrocortisone minus saline) in the medial OFC, medial brainstem and thalamus, left primary sensory cortex and right superior and medial temporal gyrus. Hunger ratings were also positively associated with plasma insulin on hydrocortisone but not saline day. CONCLUSIONS: Increased glucocorticoids at levels akin to those experienced during psychological stress, result in increased fasting hunger and decreased regional cerebral blood flow in a distinct brain network of prefrontal, emotional, reward, motivation, sensory and homeostatic regions that underlie control of food intake.

Age-dependent white matter microstructural disintegrity in autism spectrum disorder.

There has been increasing evidence of White Matter (WM) microstructural disintegrity and connectome disruption in Autism Spectrum Disorder (ASD). We evaluated the effects of age on WM microstructure by examining Diffusion Tensor Imaging (DTI) metrics and connectome Edge Density (ED) in a large dataset of ASD and control patients from different age cohorts. N = 583 subjects from four studies from the National Database of Autism Research were included, representing four different age groups: (1) A Longitudinal MRI Study of Infants at Risk of Autism [infants, median age: 7 (interquartile range 1) months, n = 155], (2) Biomarkers of Autism at 12 months [toddlers, 32 (11)m, n = 102], (3) Multimodal Developmental Neurogenetics of Females with ASD [adolescents, 13.1 (5.3) years, n = 230], (4) Atypical Late Neurodevelopment in Autism [young adults, 19.1 (10.7)y, n = 96]. For each subject, we created Fractional Anisotropy (FA), Mean- (MD), Radial- (RD), and Axial Diffusivity (AD) maps as well as ED maps. We performed voxel-wise and tract-based analyses to assess the effects of age, ASD diagnosis and sex on DTI metrics and connectome ED. We also optimized, trained, tested, and validated different combinations of machine learning classifiers and dimensionality reduction algorithms for prediction of ASD diagnoses based on tract-based DTI and ED metrics. There is an age-dependent increase in FA and a decline in MD and RD across WM tracts in all four age cohorts, as well as an ED increase in toddlers and adolescents. After correction for age and sex, we found an ASD-related decrease in FA and ED only in adolescents and young adults, but not in infants or toddlers. While DTI abnormalities were mostly limited to the corpus callosum, connectomes showed a more widespread ASD-related decrease in ED. Finally, the best performing machine-leaning classification model achieved an area under the receiver operating curve of 0.70 in an independent validation cohort. Our results suggest that ASD-related WM microstructural disintegrity becomes evident in adolescents and young adults-but not in infants and toddlers. The ASD-related decrease in ED demonstrates a more widespread involvement of the connectome than DTI metrics, with the most striking differences being localized in the corpus callosum.

Feasibility Analysis of Phenotype Quantification from Unstructured Clinical Interactions.

We conducted a feasibility analysis to determine the quality of data that could be collected ambiently during routine clinical conversations. We used inexpensive, consumer-grade hardware to record unstructured dialogue and open-source software tools to quantify and model face, voice (acoustic and language) and movement features. We used an external validation set to perform proof-of-concept predictive analyses and show that clinically relevant measures can be produced without a restrictive protocol.

Functional Connectivity during Encoding Predicts Individual Differences in Long-Term Memory.

What is the neural basis of individual differences in the ability to hold information in long-term memory (LTM)? Here, we first characterize two whole-brain functional connectivity networks based on fMRI data acquired during an n-back task that robustly predict individual differences in two important forms of LTM, recognition and recollection. We then focus on the recognition memory model and contrast it with a working memory model. Although functional connectivity during the n-back task also predicts working memory performance and the two networks have some shared components, they are also largely distinct from each other: The recognition memory model performance remains robust when we control for working memory, and vice versa. Functional connectivity only within regions traditionally associated with LTM formation, such as the medial temporal lobe and those that show univariate subsequent memory effect, have little predictive power for both forms of LTM. Interestingly, the interactions between these regions and other brain regions play a more substantial role in predicting recollection memory than recognition memory. These results demonstrate that individual differences in LTM are dependent on the configuration of a whole-brain functional network including but not limited to regions associated with LTM during encoding and that such a network is separable from what supports the retention of information in working memory.

Functional Network Development in Sagittal Craniosynostosis Treated With Whole Vault Cranioplasty.

INTRODUCTION: In this study, the authors seek to clarify the neurological changes before and after whole vault cranioplasty (WVC) in patients born with sagittal craniosynostosis. METHODS: A case control study design was performed that included thirty functional MRI scans, from 25 individual patients. Functional MRI and diffusion tension imaging data were analyzed with BioImageSuite (Yale University, USA). 9 functional brain networks were analyzed, with appropriate correlated functional regions of the brain and utilized for analysis. RESULTS: Comparing functional MRI the infants after WVC versus infants before WVC group, the after WVC group demonstrated an increased connectivity in the left frontoparietal, secondary (V2), and third (V3) visual networks (P < 0.001). The right frontoparietal (RFPN) had decreased connectivity (P < 0.001). There is also a decrease and increase in anisotropy in the cingulum and precuneus despite surgery, respectively (P < 0.05). Adolescents treated with WVC compared to controls, demonstrated an increased connectivity in the salience and decreased connectivity in the RFPN relative to adolescent controls. CONCLUSIONS: Patients born with sagittal craniosynostosis have different connections in infancy in most of the defined cerebral networks compared to controls. After surgery, there are specific connectivity changes that occur in the RFPN, left frontoparietal, V2, and V3 networks, which are areas associated with executive function and emotional control. Changes identified in white matter tract microstructure connections could be influential in changes in functional connectivity. Although, as a child with sagittal craniosynostosis develops, much of the abnormal network connections, seen in infancy preoperatively, corrects to some degree after surgery. However, some aberrancies in the salience and RFPN networks remain potentially affecting executive functioning.

Loss of nucleus accumbens low-frequency fluctuations is a signature of chronic pain.

Chronic pain is a highly prevalent disease with poorly understood pathophysiology. In particular, the brain mechanisms mediating the transition from acute to chronic pain remain largely unknown. Here, we identify a subcortical signature of back pain. Specifically, subacute back pain patients who are at risk for developing chronic pain exhibit a smaller nucleus accumbens volume, which persists in the chronic phase, compared to healthy controls. The smaller accumbens volume was also observed in a separate cohort of chronic low-back pain patients and was associated with dynamic changes in functional connectivity. At baseline, subacute back pain patients showed altered local nucleus accumbens connectivity between putative shell and core, irrespective of the risk of transition to chronic pain. At follow-up, connectivity changes were observed between nucleus accumbens and rostral anterior cingulate cortex in the patients with persistent pain. Analysis of the power spectral density of nucleus accumbens resting-state activity in the subacute and chronic back pain patients revealed loss of power in the slow-5 frequency band (0.01 to 0.027 Hz) which developed only in the chronic phase of pain. This loss of power was reproducible across two cohorts of chronic low-back pain patients obtained from different sites and accurately classified chronic low-back pain patients in two additional independent datasets. Our results provide evidence that lower nucleus accumbens volume confers risk for developing chronic pain and altered nucleus accumbens activity is a signature of the state of chronic pain.

Distributed Patterns of Functional Connectivity Predict Working Memory Performance in Novel Healthy and Memory-impaired Individuals.

Individual differences in working memory relate to performance differences in general cognitive ability. The neural bases of such individual differences, however, remain poorly understood. Here, using a data-driven technique known as connectome-based predictive modeling, we built models to predict individual working memory performance from whole-brain functional connectivity patterns. Using n-back or rest data from the Human Connectome Project, connectome-based predictive models significantly predicted novel individuals' 2-back accuracy. Model predictions also correlated with measures of fluid intelligence and, with less strength, sustained attention. Separate fluid intelligence models predicted working memory score, as did sustained attention models, again with less strength. Anatomical feature analysis revealed significant overlap between working memory and fluid intelligence models, particularly in utilization of prefrontal and parietal regions, and less overlap in predictive features between working memory and sustained attention models. Furthermore, showing the generality of these models, the working memory model developed from Human Connectome Project data generalized to predict memory in an independent data set of 157 older adults (mean age = 69 years; 48 healthy, 54 amnestic mild cognitive impairment, 55 Alzheimer disease). The present results demonstrate that distributed functional connectivity patterns predict individual variation in working memory capability across the adult life span, correlating with constructs including fluid intelligence and sustained attention.

What is the Functional Difference Between Sagittal With Metopic and Isolated Sagittal Craniosynotosis?

INTRODUCTION: The purpose of this study is to understand the neurological differences between patients born with combined sagittal and metopic craniosynostosis (SMc) and isolated sagittal craniosynostosis (ISc) by studying aberrations in functional brain connectivity and white matter microstructure, before surgery, utilizing functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI). METHODS: The authors collected DTI and resting-state (ie, no sedation and asleep) functional connectivity MRI data in 10 infant patients preoperatively: 5 in the SMc group (4.3 ±â€Š1 months) and 5 in the ISc group (4.8 ±â€Š1.1 months). Resting state fMRI imaging and DTI data were acquired using a 3-T Siemens Trio MRI system (Erlangen, Germany) while the infant patients slept. fMRI data were corrected for movement using SPM, underwent cerebrospinal fluid and white matter signal regression and further analyzed with BioImageSuite. For the DTI data, 3 diffusion runs were averaged, processed utilizing FMRIB Software Library, and analyzed statistically using BioImageSuite. RESULTS: Comparing the SMc versus ISc groups, SMc demonstrated that there was increased connectivity, statistically significant differences, in neural networks between children with sagittal synostosis alone versus those with sagittal with metopic synostosis, in the right BA 31 and BA 23 (corresponding to the posterior cingulate cortex (PCC) (P < 0.001). Analysis of the DTI revealed increased fractional anisotropy (normal maturation of white tracts) in the SMc group in the cingulum compared to the ISc group (P < 0.05). Differences in the functional networks include increased connectivity right frontoparietal network (RFPN) in ISc and increased connectivity in the primary visual network (V1) in SMc (P < 0.001). CONCLUSION: The SMc had increased connectivity as measured by fMR in the PCC, an area associated with attention deficit hyperactivity disorder. The DTI analysis demonstrated an increase in fractional anisotropy of the cingulum in the SMc group, a white matter tract projecting from the cingulate cortex; connections of the limbic (emotional regulation) system are instrumental. In SMc, increase of connectivity in the PCC correlates with an increase in maturation of the cingulum compared to ISc. There is increased connectivity of the RFPN network in the ISc and increased connectivity of the V1 network in the SMc patients. The SMc group has increased connectivity in the PCC, the original seed of the DMN network, and decreased connectivity to the RFPN network. The pattern of increased connectivity in the area of the DMN and decreased connectivity in the RFPN network is similar to the trend when comparing ADHD patients to normal controls. SMc has more similar functional network connectivity to ADHD as compared to ISc.

Understanding the Learning Disabilities Linked to Sagittal Craniosynostosis.

OBJECTIVE: The purpose of this study is to investigate further findings that corroborate similarities between corrected sagittal craniosynostosis and attention deficit hyperactivity disorder (ADHD). The aim is to further characterize the neurocognitive deficits seen in adolescents with corrected craniosynostosis by comparing it to established learning deficits such as ADHD. METHODS: A total of 30 functional magnetic resonance imaging (fMRI) of 10 sagittal nonsyndromic craniosynostosis (sNSC), 10 ADHD-combined, and 10 control adolescents were studied. The fMRI scans were analyzed utilizing Statistical Parametric Mapping (University College London, UK) and analyzed with BioImageSuite (Yale University, New Haven, CT). RESULTS: The ADHD has lower connectivity to Brodmann area (BA) 11 (Montreal Neurological Institution [MNI]: -12,26,-21), BA20 (MNI: 62,-24,-25), and BA21 (MNI: 62,-32,-23) compared to sNSC and controls (P < 0.001). The sNSC has a unique visuospatial defect, compared to ADHD, created by decreased connectivity to BA31 (MNI: -3,-68,37), BA7 (MNI: -4,-68,41), BA19 (MNI: 0,-83,31), visual association cortex (MNI: -4,-78,22), and primary visual cortex (MNI: 7,-74,21) (P < 0.001). CONCLUSION: Patients born with sNSC have different neural connections than children born with ADHD. Patients born with sNSC have decreased connections in areas of visual processing and increased connections in areas of attention and auditory processing than patients with ADHD. Therefore, children with sagittal craniosynsotosis may have learning difficulties that, similar, yet different from ADHD.

Humans with obesity have disordered brain responses to food images during physiological hyperglycemia.

Blood glucose levels influence brain regulation of food intake. This study assessed the effect of mild physiological hyperglycemia on brain response to food cues in individuals with obesity (OB) versus normal weight individuals (NW). Brain responses in 10 OB and 10 NW nondiabetic healthy adults [body mass index: 34 (3) vs. 23 (2) kg/m2, means (SD), P < 0.0001] were measured with functional MRI (blood oxygen level-dependent contrast) in combination with a two-step normoglycemic-hyperglycemic clamp. Participants were shown food and nonfood images during normoglycemia (~95 mg/dl) and hyperglycemia (~130 mg/dl). Plasma glucose levels were comparable in both groups during the two-step clamp ( P = not significant). Insulin and leptin levels were higher in the OB group compared with NW, whereas ghrelin levels were lower (all P < 0.05). During hyperglycemia, insula activity showed a group-by-glucose level effect. When compared with normoglycemia, hyperglycemia resulted in decreased activity in the hypothalamus and putamen in response to food images ( P < 0.001) in the NW group, whereas the OB group exhibited increased activity in insula, putamen, and anterior and dorsolateral prefrontal cortex (aPFC/dlPFC; P < 0.001). These data suggest that OB, compared with NW, appears to have disruption of brain responses to food cues during hyperglycemia, with reduced insula response in NW but increased insula response in OB, an area involved in food perception and interoception. In a post hoc analysis, brain activity in obesity appears to be associated with dysregulated motivation (striatum) and inappropriate self-control (aPFC/dlPFC) to food cues during hyperglycemia. Hyperstimulation for food and insensitivity to internal homeostatic signals may favor food consumption to possibly play a role in the pathogenesis of obesity.

Diffusion Tensor Imaging in Patients with Glioblastoma Multiforme Using the Supertoroidal Model.

PURPOSE: Diffusion Tensor Imaging (DTI) is a powerful imaging technique that has led to improvements in the diagnosis and prognosis of cerebral lesions and neurosurgical guidance for tumor resection. Traditional tensor modeling, however, has difficulties in differentiating tumor-infiltrated regions and peritumoral edema. Here, we describe the supertoroidal model, which incorporates an increase in surface genus and a continuum of toroidal shapes to improve upon the characterization of Glioblastoma multiforme (GBM). MATERIALS AND METHODS: DTI brain datasets of 18 individuals with GBM and 18 normal subjects were acquired using a 3T scanner. A supertoroidal model of the diffusion tensor and two new diffusion tensor invariants, one to evaluate diffusivity, the toroidal volume (TV), and one to evaluate anisotropy, the toroidal curvature (TC), were applied and evaluated in the characterization of GBM brain tumors. TV and TC were compared with the mean diffusivity (MD) and fractional anisotropy (FA) indices inside the tumor, surrounding edema, as well as contralateral to the lesions, in the white matter (WM) and gray matter (GM). RESULTS: The supertoroidal model enhanced the borders between tumors and surrounding structures, refined the boundaries between WM and GM, and revealed the heterogeneity inherent to tumor-infiltrated tissue. Both MD and TV demonstrated high intensities in the tumor, with lower values in the surrounding edema, which in turn were higher than those of unaffected brain parenchyma. Both TC and FA were effective in revealing the structural degradation of WM tracts. CONCLUSIONS: Our findings indicate that the supertoroidal model enables effective tensor visualization as well as quantitative scalar maps that improve the understanding of the underlying tissue structure properties. Hence, this approach has the potential to enhance diagnosis, preoperative planning, and intraoperative image guidance during surgical management of brain lesions.

Reliability of an fMRI paradigm for emotional processing in a multisite longitudinal study.

Multisite neuroimaging studies can facilitate the investigation of brain-related changes in many contexts, including patient groups that are relatively rare in the general population. Though multisite studies have characterized the reliability of brain activation during working memory and motor functional magnetic resonance imaging tasks, emotion processing tasks, pertinent to many clinical populations, remain less explored. A traveling participants study was conducted with eight healthy volunteers scanned twice on consecutive days at each of the eight North American Longitudinal Prodrome Study sites. Tests derived from generalizability theory showed excellent reliability in the amygdala ( Eρ2 = 0.82), inferior frontal gyrus (IFG; Eρ2 = 0.83), anterior cingulate cortex (ACC; Eρ2 = 0.76), insula ( Eρ2 = 0.85), and fusiform gyrus ( Eρ2 = 0.91) for maximum activation and fair to excellent reliability in the amygdala ( Eρ2 = 0.44), IFG ( Eρ2 = 0.48), ACC ( Eρ2 = 0.55), insula ( Eρ2 = 0.42), and fusiform gyrus ( Eρ2 = 0.83) for mean activation across sites and test days. For the amygdala, habituation ( Eρ2 = 0.71) was more stable than mean activation. In a second investigation, data from 111 healthy individuals across sites were aggregated in a voxelwise, quantitative meta-analysis. When compared with a mixed effects model controlling for site, both approaches identified robust activation in regions consistent with expected results based on prior single-site research. Overall, regions central to emotion processing showed strong reliability in the traveling participants study and robust activation in the aggregation study. These results support the reliability of blood oxygen level-dependent signal in emotion processing areas across different sites and scanners and may inform future efforts to increase efficiency and enhance knowledge of rare conditions in the population through multisite neuroimaging paradigms.

Ipsilateral synkinesia involves the supplementary motor area.

The supplementary motor area coordinates movements. Synkinesia is a rare disorder in which an involuntary movement occurs coordinated with a voluntary movement. Here, we test the hypothesis that the supplementary motor area is involved in involuntary coordination of movement. We collected functional magnetic resonance imaging (fMRI) data from two patients with ipsilateral hand-foot synkinesia and two control participants while they performed rhythmic tasks. In synkinesia patients, both the supplementary motor area and the foot motor cortex were significantly activated during the hand motor task. This pattern was not seen in controls. Our findings suggest that the supplementary motor area plays a central role in involuntary coordination observed in synkinesia, and provides insight into how the supplementary motor area orchestrates movements.

Real-time fMRI biofeedback targeting the orbitofrontal cortex for contamination anxiety.

We present a method for training subjects to control activity in a region of their orbitofrontal cortex associated with contamination anxiety using biofeedback of real-time functional magnetic resonance imaging (rt-fMRI) data. Increased activity of this region is seen in relationship with contamination anxiety both in control subjects and in individuals with obsessive-compulsive disorder (OCD), a relatively common and often debilitating psychiatric disorder involving contamination anxiety. Although many brain regions have been implicated in OCD, abnormality in the orbitofrontal cortex (OFC) is one of the most consistent findings. Furthermore, hyperactivity in the OFC has been found to correlate with OCD symptom severity and decreases in hyperactivity in this region have been reported to correlate with decreased symptom severity. Therefore, the ability to control this brain area may translate into clinical improvements in obsessive-compulsive symptoms including contamination anxiety. Biofeedback of rt-fMRI data is a new technique in which the temporal pattern of activity in a specific region (or associated with a specific distributed pattern of brain activity) in a subject's brain is provided as a feedback signal to the subject. Recent reports indicate that people are able to develop control over the activity of specific brain areas when provided with rt-fMRI biofeedback. In particular, several studies using this technique to target brain areas involved in emotion processing have reported success in training subjects to control these regions. In several cases, rt-fMRI biofeedback training has been reported to induce cognitive, emotional, or clinical changes in subjects. Here we illustrate this technique as applied to the treatment of contamination anxiety in healthy subjects. This biofeedback intervention will be a valuable basic research tool: it allows researchers to perturb brain function, measure the resulting changes in brain dynamics and relate those to changes in contamination anxiety or other behavioral measures. In addition, the establishment of this method serves as a first step towards the investigation of fMRI-based biofeedback as a therapeutic intervention for OCD. Given that approximately a quarter of patients with OCD receive little benefit from the currently available forms of treatment, and that those who do benefit rarely recover completely, new approaches for treating this population are urgently needed.

Altered age-related trajectories of amygdala-prefrontal circuitry in adolescents at clinical high risk for psychosis: a preliminary study.

Emotion processing deficits are prominent in schizophrenia and exist prior to the onset of overt psychosis. However, developmental trajectories of neural circuitry subserving emotion regulation and the role that they may play in illness onset have not yet been examined in patients at risk for psychosis. The present study employed a cross-sectional analysis to examine age-related functional activation in amygdala and prefrontal cortex, as well as functional connectivity between these regions, in adolescents at clinical high risk (CHR) for psychosis relative to typically developing adolescents. Participants (n=34) performed an emotion processing fMRI task, including emotion labeling, emotion matching, and non-emotional control conditions. Regression analyses were used to predict activation in the amygdala and ventrolateral prefrontal cortex (vlPFC) based on age, group, sex, and the interaction of age by group. CHR adolescents exhibited altered age-related variation in amygdala and vlPFC activation, relative to controls. Controls displayed decreased amygdala and increased vlPFC activation with age, while patients exhibited the opposite pattern (increased amygdala and decreased vlPFC activation), suggesting a failure of prefrontal cortex to regulate amygdala reactivity. Moreover, a psychophysiological interaction analysis revealed decreased amygdala-prefrontal functional connectivity among CHR adolescents, consistent with disrupted brain connectivity as a vulnerability factor in schizophrenia. These results suggest that the at-risk syndrome is marked by abnormal development and functional connectivity of neural systems subserving emotion regulation. Longitudinal data are needed to confirm aberrant developmental trajectories intra-individually and to examine whether these abnormalities are predictive of conversion to psychosis, and of later deficits in socioemotional functioning.