Neurite outgrowth deficits caused by rare PLXNB1 mutation in pediatric bipolar disorder

Pediatric bipolar disorder (PBD) is a severe mood dysregulation condition that affects 0.5-1% of children and teens in the United States. It is associated with recurrent episodes of mania and depression and an increased risk of suicidality. However, the genetics and neuropathology of PBD are largely unknown. Here, we used a combinatorial family-based approach to characterize cellular, molecular, genetic, and network-level deficits associated with PBD. We recruited a PBD patient and three unaffected family members from a family with a history of psychiatric illnesses. Using resting-state functional magnetic resonance imaging (rs-fMRI), we detected altered resting-state functional connectivity in the patient as compared to an unaffected sibling. Using transcriptomic profiling of patient and control induced pluripotent stem cell (iPSC)-derived telencephalic organoids, we found aberrant signaling in the molecular pathways related to neurite outgrowth. We corroborated the presence of neurite outgrowth deficits in patient iPSC-derived cortical neurons and identified a rare homozygous loss-of-function PLXNB1 variant (c.1360C>C; p.Ser454Arg) responsible for the deficits in the patient. Expression of wild-type PLXNB1, but not the variant, rescued neurite outgrowth in patient neurons, and expression of the variant caused the neurite outgrowth deficits in cortical neurons from PlxnB1 knockout mice. These results indicate that dysregulated PLXNB1 signaling may contribute to an increased risk of PBD and other mood dysregulation-related disorders by disrupting neurite outgrowth and functional brain connectivity. Overall, this study established and validated a novel family-based combinatorial approach for studying cellular and molecular deficits in psychiatric disorders and identified dysfunctional PLXNB1 signaling and neurite outgrowth as potential risk factors for PBD.

"Fully automated segmentation of the corticospinal tract using the TractSeg algorithm in patients with brain tumors"

OBJECTIVE

Tractography has been used to define the presurgical location of white matter tracts, but this is subjective and time-intensive, making incorporation to imaging workflow at scale problematic. The objective is to validate a fully automated pipeline using the TractSeg algorithm (Wasserthal et al. NeuroImage 2018;183:239-253) to segment the corticospinal tract in patients with brain tumors adjacent to the corticospinal tract.

METHODS

The process of importing a structural MPRAGE sequence and raw diffusion weighted images from PACS, executing the TractSeg algorithm, overlaying the resulting bilateral corticospinal tracts on the MPRAGE image, and exporting this composite image to PACS was automated. This procedure was used to segment the corticospinal tract in 28 patients with brain masses adjacent to or displacing the corticospinal tract. These segmentations were compared with both manual deterministic tractography performed with DSI Studio using seeds placed in the pons and an automated tractography method in DSI Studio.

RESULTS

The automated algorithm was able to segment the bilateral corticospinal tracts in all 28 patients whereas the manual reference method and DSI Studio based automated tractography were unsuccessful in 2 and 1 patients, respectively. In all cases, the TractSeg segmentations very closely matched the manual segmentations. Also, TractSeg appeared to include larger portions of the lateral corticospinal tract fibers than the other 2 methods.

CONCLUSION

The TractSeg algorithm demonstrated robust performance in segmenting the corticospinal tract in patients with brain tumors adjacent to this tract. The algorithm is fast to perform and has great potential for optimizing and streamlining neurosurgical planning.

Predicting biomarkers in intact older adults and those with amnestic Mild Cognitive Impairment, and mild Alzheimer's Disease using the Repeatable Battery for the Assessment of Neuropsychological Status

INTRODUCTION

The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) has been associated, to varying degrees, with commonly used biomarkers of Alzheimer's disease (AD). Given the ease of RBANS administration as a screening tool for clinical trials and other applications, a better understanding of how RBANS performance is associated with presence of APOE ε4 allele[s], cerebral amyloid burden, and hippocampal volume is warranted.

METHOD

One hundred twenty-one older adults who were classified as intact, amnestic Mild Cognitive Impairment, or mild AD underwent cognitive assessment with the RBANS, genetic analysis, and quantitative brain imaging. APOE ε4 carrier status, 18F-Flutemetamol composite standardized uptake value ratio (SUVR), and hippocampal volume were each regressed on demographic variables and RBANS Total Scale score, Index scores, and subtest scores.

RESULTS

Lower RBANS Total Scale score or Delayed Memory Index (DMI) predicted the presence of APOE ε4 allele[s], higher cerebral amyloid burden, and lower hippocampal volumes. DMI was a slightly better predictor than Total Scale score for most AD biomarkers. No demographic variables consistently contributed to these models.

CONCLUSIONS

The RBANS - DMI in particular - is sensitive to AD pathology. As such, it could be used as a predictive tool, particularly in clinical drug trials to enrich samples prior to less accessible AD biomarker investigation.

Understanding heterosexual women's erotic flexibility: the role of attention in sexual evaluations and neural responses to sexual stimuli

Many women experience desires, arousal and behavior that run counter to their sexual orientation (orientation inconsistent, 'OI'). Are such OI sexual experiences cognitively and neurobiologically distinct from those that are consistent with one's sexual orientation (orientation consistent, 'OC')? To address this question, we employed a mindful attention intervention-aimed at reducing judgment and enhancing somatosensory attention-to examine the underlying attentional and neurobiological processes of OC and OI sexual stimuli among predominantly heterosexual women. Women exhibited greater neural activity in response to OC, compared to OI, sexual stimuli in regions associated with implicit visual processing, volitional appraisal and attention. In contrast, women exhibited greater neural activity to OI, relative to OC, sexual stimuli in regions associated with complex visual processing and attentional shifting. Mindfully attending to OC sexual stimuli reduced distraction, amplified women's evaluations of OC stimuli as sexually arousing and deactivated the superior cerebellum. In contrast, mindfully attending to OI sexual stimuli amplified distraction, decreased women's evaluations of OI stimuli as sexually arousing and augmented parietal and temporo-occipital activity. Results of the current study constrain hypotheses of female erotic flexibility, suggesting that sexual orientation may be maintained by differences in attentional processing that cannot be voluntarily altered.

Beery VMI and Brain Volumetric Relations in Autism Spectrum Disorder

Although diminished proficiency on tasks that require visual-motor integration (VMI) has been reported in individuals with autism spectrum disorder (ASD), very few studies have examined the association between VMI performance and neuroanatomical regions of interest (ROI) involved in motor and perceptual functioning. To address these issues, the current study included an all-male sample of 41 ASD (ages 3-23 years) and 27 typically developing (TD) participants (ages 5-26 years) who completed the Beery-Buktenica Developmental Test of Visual-Motor Integration (Beery VMI) as part of a comprehensive neuropsychological battery. All participants underwent 3.0 T magnetic resonance imaging (MRI) with image quantification (FreeSurfer software v5.3). The groups were statistically matched on age, handedness, and intracranial volume (ICV). ASD participants performed significantly lower on VMI and IQ measures compared with the TD group. VMI performance was significantly correlated with FSIQ and PIQ in the TD group only. No pre-defined neuroanatomical ROIs were significantly different between groups. Significant correlations were observed in the TD group between VMI and total precentral gyrus gray matter volume (r = .51, p = .006) and total frontal lobe gray matter volume (r = .46, p = .017). There were no significant ROI correlations with Beery VMI performance in ASD participants. At the group level, despite ASD participants exhibiting reduced visuomotor abilities, no systematic relation with motor or sensory-perceptual ROIs was observed. In the TD group, results were consistent with the putative role of the precentral gyrus in motor control along with frontal involvement in planning, organization, and execution monitoring, all essential for VMI performance. Given that similar associations between VMI and ROIs were not observed in those with ASD, neurodevelopment in ASD group participants may not follow homogenous patterns making correlations in these brain regions unlikely to be observed.

Left Ear Hearing Predicts Functional Activity in the Brains of Patients with Alzheimer's Disease Dementia

OBJECTIVES

To determine whether central speech processing ability, as measured by hearing in noise, differs between right and left ears in adults with Alzheimer's disease related dementia (AD) as well as whether differences in central speech processing ability correlate with an fMRI-based measurement of global functional brain connectivity.

METHODS

This prospective study was carried out at a tertiary referral center. Patients with an AD diagnosis and pure tone averages 40 dB HL or better were included. They were examined using resting-state fMRI and underwent central audiometric testing using the Dichotic Sentence Identification Test (DSI), the Dichotic Digits Test (DD), and the Synthetic Sentence Identification Test (SS), which test hearing in noise. DSI scores were correlated with resting-state fMRI connectivity between 361 distinct gray matter brain regions of interest (ROIs). Average global connectivity was calculated as mean functional connectivity between an ROI and the other 360 regions, a quantitative marker representing overall functional connectivity in the brain.

RESULTS

Sixteen subjects had adequate fMRI and hearing data. The average age was 71.5 years old (±6.0). The average DSI score for the left ear was 40% (±34%) compared to 90% (±10%) in the right ear (P < .001). No difference between ears was noted on the DD. SS does not differentiate between ears, but worsening scores were noted with increasing background noise. Of the fMRI ROIs, 269 of the 361 had multiple comparison corrected significant correlations between global connectivity and DSI of the left ear (P = .004, r = .673), and all 269 showed higher functional connectivity for individuals with higher left DSI score. No correlations between DSI of the right ear and functional connectivity were found.

CONCLUSIONS

Correlation was noted between left sided DSI and functional connectivity in patients with AD. Auditory input from the left ear was more susceptible to impairment, suggesting that side-specific auditory input may influence central auditory processing.

Increased Functional Connectivity After Listening to Favored Music in Adults With Alzheimer Dementia

BACKGROUND

Personalized music programs have been proposed as an adjunct therapy for patients with Alzheimer disease related dementia, and multicenter trials have now demonstrated improvements in agitation, anxiety, and behavioral symptoms. Underlying neurophysiological mechanisms for these effects remain unclear.

METHODS

We examined 17 individuals with a clinical diagnosis of Alzheimer disease related dementia using functional MRI following a training period in a personalized music listening program.

RESULTS

We find that participants listening to preferred music show specific activation of the supplementary motor area, a region that has been associated with memory for familiar music that is typically spared in early Alzheimer disease. We also find widespread increases in functional connectivity in corticocortical and corticocerebellar networks following presentation of preferred musical stimuli, suggesting a transient effect on brain function.

CONCLUSIONS

Findings support a mechanism whereby attentional network activation in the brain's salience network may lead to improvements in brain network synchronization.

Autism Classification Using Topological Features and Deep Learning: A Cautionary Tale

The identification of autistic individuals using resting state functional connectivity networks can provide an objective diagnostic method for autism spectrum disorder (ASD). The present state-of-the-art machine learning model using deep learning has a classification accuracy of 70.2% on the ABIDE (Autism Brain Imaging Data Exchange) data set. In this paper, we explore the utility of topological features in the classification of ASD versus typically developing control subjects. These topological features have been shown to provide a complementary source of discriminative information in applications such as 2D object classification and social network analysis. We evaluate the performance of three different representations of topological features - persistence diagrams, persistence images, and persistence landscapes - for autism classification using neural networks, support vector machines and random forests. We also propose a hybrid approach of augmenting topological features with functional correlations, which typically outperforms the models that use functional correlations alone. With this approach, even with a simple 3-layer neural network, we are able to achieve a classification accuracy of 69.2% on the ABIDE data set. However, our experiments also show that the improvement due to topological features is not always statistically significant. Therefore, we offer a cautionary tale to the practitioners regarding the limited discriminative power of topological features derived from fMRI data for the classification of autism.

Surface-Based Spatial Pyramid Matching of Cortical Regions for Analysis of Cognitive Performance

We propose a method to analyze the relationship between the shape of functional regions of the cortex and cognitive measures, such as reading ability and vocabulary knowledge. Functional regions on the cortical surface can vary not only in size and shape but also in topology and position relative to neighboring regions. Standard diffeomorphism-based shape analysis tools do not work well here because diffeomorphisms are unable to capture these topological differences, which include region splitting and merging across subjects. State-of-the-art cortical surface shape analyses compute derived regional properties (scalars), such as regional volume, cortical thickness, curvature, and gyrification index. However, these methods cannot compare the full extent of topological or shape differences in cortical regions. We propose icosahedral spatial pyramid matching (ISPM) of region borders computed on the surface of a sphere to capture this variation in regional topology, position, and shape. We then analyze how this variation corresponds to measures of cognitive performance. We compare our method to other approaches and find that it is indeed informative to consider aspects of shape beyond the standard approaches. Analysis is performed using a subset of 27 test/retest subjects from the Human Connectome Project in order to understand both the effectiveness and reproducibility of this method.

Functional connectivity of emotional well-being: Overconnectivity between default and attentional networks is associated with attitudes of anger and aggression

Functional MRI connectivity has identified neurophysiology relevant to cognition and personality, motivating a search for relationships between brain architecture and emotional health and well-being. Two approaches were used to asses functional connectivity correlates of emotional health and well-being. The first approach used principal component analysis to evaluate resting-state functional magnetic resonance imaging data from the Human Connectome Project 1200 Subjects Data Release. Pairwise functional connectivity measurements were obtained from a 5 mm resolution parcellation of brain gray matter. Principal components were calculated for each individual and for group mean connectivity data and compared to obtain an estimate of typicality of functional connectivity for each component in each subject. Typicality scores were compared to reported emotional health metrics using a general linear model. The second approach calculated functional connectivity between each pair of networks from a 17-resting-state network cortical parcellation. Typicality of connectivity showed significant correlation across the population to emotional metrics corresponding to attitudes of anger and aggression in 3 of 10 principal components. Additionally, functional connectivity between the default and attentional networks was positively correlated with scores of attitudes of anger and aggression. These findings are consistent with a mechanism of impaired effortful control and decreased response inhibition of impulsivity.

Objective cognitive functioning in self-reported habitual short sleepers not reporting daytime dysfunction: examination of impulsivity via delay discounting

Study Objectives

(1) Examine performance on an objective measure of reward-related cognitive impulsivity (delay discounting) among self-reported habitual short sleepers and medium (i.e. recommended 7-9 hours) length sleepers either reporting or not reporting daytime dysfunction; (2) Inform the debate regarding what type and duration of short sleep (e.g. 21 to 24 hours of total sleep deprivation, self-reported habitual short sleep duration) meaningfully influences cognitive impulsivity; (3) Compare the predictive utility of sleep duration and perceived dysfunction to other factors previously shown to influence cognitive impulsivity via delay discounting performance (age, income, education, and fluid intelligence).

Methods

We analyzed data from 1190 adults from the Human Connectome Project database. Participants were grouped on whether they reported habitual short (≤6 hours) vs. medium length (7-9 hours) sleep duration and whether they perceived daytime dysfunction using the Pittsburgh Sleep Quality Index.

Results

All short sleepers exhibited increased delay discounting compared to all medium length sleepers, regardless of perceived dysfunction. Of the variables examined, self-reported sleep duration was the strongest predictor of delay discounting behavior between groups and across all 1190 participants.

Conclusions

Individuals who report habitual short sleep are likely to exhibit increased reward-related cognitive impulsivity regardless of perceived sleep-related daytime impairment. Therefore, there is a reason to suspect that these individuals exhibit more daytime dysfunction, in the form of reward-related cognitive impulsivity, than they may assume. Current findings suggest that assessment of sleep duration over the prior month has meaningful predictive utility for human reward-related impulsivity.

Neural reward processing in self-reported short sleepers: examination of gambling task brain activation in the Human Connectome Project database

STUDY OBJECTIVES

Much of what we assume about the effects of short sleep duration on neural reward processing derives from total sleep deprivation studies. Although total sleep deprivation appears rare, habitual short sleep is common: 30% of working US adults report habitually sleeping ≤ 6 hours/night. It remains largely unknown whether habitual short sleepers exhibit similar reward processing brain activation patterns to those observed following total sleep deprivation in prior studies. Therefore, our aim was to test objectively reward processing brain activation patterns associated with self-reported habitual short sleep duration in a large sample.

METHODS

Nine hundred and fifty-two adult participants from the Human Connectome Project database were grouped on reported habitual short (≤6 hours) vs. medium-length (7-9 hours) sleep duration using the Pittsburgh Sleep Quality Index (PSQI). Reward processing brain activation was examined using a gambling task during functional magnetic resonance imaging (fMRI). Subject-level covariates for age, sex, continuous sleep duration, daytime dysfunction, and PSQI total score are provided as supplemental analyses.

RESULTS

Brain activation patterns revealed expected reward processing-related activation for age and sex. However, activation for sleep duration, dysfunction, and PSQI score did not correspond to those evident in previous total sleep deprivation studies.

CONCLUSIONS

Self-reported short sleep duration, perceived sleep-related dysfunction, and sleep quality via PSQI do not appear to be meaningfully associated with activation in well-described regions of the human neurobiological reward circuit. As these findings are counter to prior results using experimental sleep deprivation, future work focused on more direct comparisons between self-reported sleep variables and experimental sleep deprivation appears warranted.

Generalizability and reproducibility of functional connectivity in autism

Background

Autism is hypothesized to represent a disorder of brain connectivity, yet patterns of atypical functional connectivity show marked heterogeneity across individuals.

Methods

We used a large multi-site dataset comprised of a heterogeneous population of individuals with autism and typically developing individuals to compare a number of resting-state functional connectivity features of autism. These features were also tested in a single site sample that utilized a high-temporal resolution, long-duration resting-state acquisition technique.

Results

No one method of analysis provided reproducible results across research sites, combined samples, and the high-resolution dataset. Distinct categories of functional connectivity features that differed in autism such as homotopic, default network, salience network, long-range connections, and corticostriatal connectivity, did not align with differences in clinical and behavioral traits in individuals with autism. One method, lag-based functional connectivity, was not correlated to other methods in describing patterns of resting-state functional connectivity and their relationship to autism traits.

Conclusion

Overall, functional connectivity features predictive of autism demonstrated limited generalizability across sites, with consistent results only for large samples. Different types of functional connectivity features do not consistently predict different symptoms of autism. Rather, specific features that predict autism symptoms are distributed across feature types.

Electronic supplementary material

The online version of this article (10.1186/s13229-019-0273-5) contains supplementary material, which is available to authorized users.

Neuroimaging in Psychiatry and Neurodevelopment: why the emperor has no clothes

Neuroimaging has been a dominant force in guiding research into psychiatric and neurodevelopmental disorders for decades, yet researchers have been unable to formulate sensitive or specific imaging tests for these conditions. The search for neuroimaging biomarkers has been constrained by limited reproducibility of imaging techniques, limited tools for evaluating neurochemistry, heterogeneity of patient populations not defined by brain-based phenotypes, limited exploration of temporal components of brain function, and relatively few studies evaluating developmental and longitudinal trajectories of brain function. Opportunities for development of clinically impactful imaging metrics include longer duration functional imaging data sets, new engineering approaches to mitigate suboptimal spatiotemporal resolution, improvements in image post-processing and analysis strategies, big data approaches combined with data sharing of multisite imaging samples, and new techniques that allow dynamical exploration of brain function across multiple timescales. Despite narrow clinical impact of neuroimaging methods, there is reason for optimism that imaging will contribute to diagnosis, prognosis, and treatment monitoring for psychiatric and neurodevelopmental disorders in the near future.

Social Responsiveness Scale (SRS) in Relation to Longitudinal Cortical Thickness Changes in Autism Spectrum Disorder

The relationship between brain development and clinical heterogeneity in autism (ASD) is unknown. This study examines the Social Responsiveness Scale (SRS) in relation to the longitudinal development of cortical thickness. Participants (N = 91 ASD, N = 56 TDC; 3-39 years at first scan) were scanned up to three times over a 7-year period. Mixed-effects models examined cortical thickness in relation to SRS score. ASD participants with higher SRS scores showed regionally increased age-related cortical thinning. Regional thickness differences and reduced age-related cortical thinning were found in predominantly right lateralized regions in ASD with decreasing SRS scores over time. Our findings emphasize the importance of examining clinical phenotypes in brain-based studies of ASD.

High-Order Visual Processing, Visual Symptoms, and Visual Hallucinations: A Possible Symptomatic Progression of Parkinson's Disease

Objective: To determine whether Parkinson disease (PD) patients with (VH) have different clinical characteristics and gray-matter volume than those with visual misperceptions (VM) or other visual symptoms (OvS). Background: The spectrum of visual complaints in PD is broad and complex. Methods: We conducted a retrospective chart review of 525 PD patients to identify the frequency of visual symptoms and the association with clinical and radiological features. Brain volumetric MRI data was analyzed using multivariate logistic regression to differentiate cases with and without visual symptoms. Results: Among 525 PD cases, visual complaints were documented in 177 (33.7%). Among these, 83 (46.9%) had VH, 31 (17.5%) had VM, and 63 (35.6%) had OvS (diplopia, blurry vision, photophobia, dry eyes, and eye pain or soreness). When compared to OvS, patients with VH had significantly higher age, duration of disease, rate of REM sleep behavior disorder, and cognitive impairment. Visual hallucinations patients had decreased age-adjusted volumetric averages in 28/30 gray-matter regions when compared to PD without visual symptoms and 30/30 gray-matter regions when compared to VM patients. Conclusions: Visual symptoms in PD may represent a spectrum from OvS to VM to VH, with progression of the latter associated with older age, duration of disease, presence of REM sleep behavior disorder, cognitive impairment, and decreased gray-matter volume.

Evaluation of Differences in Temporal Synchrony Between Brain Regions in Individuals With Autism and Typical Development

IMPORTANCE

Despite reports of widespread but heterogeneous atypicality of functional connectivity in individuals with autism, little is known regarding the temporal dynamics of functional brain connections and how they relate to autistic traits.

OBJECTIVE

To investigate differences in temporal synchrony between brain regions in individuals with autism and those with typical development.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study, conducted at the University of Utah, included 90 adolescent and adult male participants. A larger sample from the multisite Autism Brain Imaging Data Exchange (ABIDE) was also used as a replication sample. The study includes data acquired between December 2016 and April 2018. Aggregate data included in the replication sample were released to the public in August 2012 (ABIDE I) and June 2016 (ABIDE II). Data analysis were conducted between January 2018 and April 2018.

EXPOSURES

Male individuals diagnosed as having autism (n = 52) and typically developing male individuals (n = 38).

MAIN OUTCOMES AND MEASURES

Long duration (30 minutes/individual) of multiband, multiecho functional magnetic resonance imaging was acquired to estimate functional connectivity between brain regions. Sustained connectivity, a measure of functional connectivity duration, as well as lagged temporal dynamics related to functional connectivity, were compared between groups for 361 gray matter regions of interest and a 17-network parcellation. Lagged findings were replicated in the larger ABIDE sample (n = 1402). Sustained connectivity findings were also associated with behavioral and cognitive variables.

RESULTS

In 52 males with autism (mean [SD] age, 27.73 [8.66] years) and 38 control males with typical development (mean [SD] age, 27.09 [7.49] years), increases in both sustained and functional connectivity at several lags were found in individuals with autism compared with the control group. Group differences in functional connectivity were replicated in the larger ABIDE data set at a 6-second lag. Measures of symptom severity in individuals with autism were positively associated with sustained connectivity values. In the control group, sustained connectivity was negatively associated with cognitive processing. A replication sample (n = 1402) composed of 579 individuals with autism (80 female and 499 male; mean [SD] age, 15.08 [6.89] years) and 823 in the control group (211 female and 612 male; mean [SD] age, 15.06 [6.79] years) from the ABIDE data set was also analyzed.

CONCLUSIONS AND RELEVANCE

Whereas the magnitude of functional connectivity in autism is variable across brain regions, participant samples, and development, prolonged temporal synchrony of functional connections is reproducibly observed in autism, suggesting a potential mechanism for core symptoms.

Riemannian Regression and Classification Models of Brain Networks Applied to Autism

Functional connectivity from resting-state functional MRI (rsfMRI) is typically represented as a symmetric positive definite (SPD) matrix. Analysis methods that exploit the Riemannian geometry of SPD matrices appropriately adhere to the positive definite constraint, unlike Euclidean methods. Recently proposed approaches for rsfMRI analysis have achieved high accuracy on public datasets, but are computationally intensive and difficult to interpret. In this paper, we show that we can get comparable results using connectivity matrices under the log-Euclidean and affine-invariant Riemannian metrics with relatively simple and interpretable models. On ABIDE Preprocessed dataset, our methods classify autism versus control subjects with 71.1% accuracy. We also show that Riemannian methods beat baseline in regressing connectome features to subject autism severity scores.

Topological Data Analysis of Functional MRI Connectivity in Time and Space Domains

The functional architecture of the brain can be described as a dynamical system where components interact in flexible ways, constrained by physical connections between regions. Using correlation, either in time or in space, as an abstraction of functional connectivity, we analyzed resting state fMRI data from 1003 subjects. We compared several data preprocessing strategies and found that independent component-based nuisance regression outperformed other strategies, with the poorest reproducibility in strategies that include global signal regression. We also found that temporal vs. spatial functional connectivity can encode different aspects of cognition and personality. Topological analyses using persistent homology show that persistence barcodes are significantly correlated to individual differences in cognition and personality, with high reproducibility. Topological data analyses, including approaches to model connectivity in the time domain, are promising tools for representing high-level aspects of cognition, development, and neuropathology.

Short-term repeat cognitive testing and its relationship to hippocampal volumes in older adults

BACKGROUND

Practice effects are improvements in cognitive test scores due to repeated exposure to testing materials. If practice effects provide information about Alzheimer's disease pathology, then they could be useful for clinical trials enrichment. The current study sought to add to the limited literature on short-term practice effects on cognitive tests and their relationship to neuroimaging biomarkers.

METHODS

Twenty-five, non-demented older adults (8 cognitively intact, 17 with mild cognitive impairment) received magnetic resonance imaging and two testing sessions across one week to determine practice effects on seven neuropsychological test scores. A series of correlations examined if hippocampal volume was associated with baseline, one-week, or practice effects scores on these tests. Next, a series of stepwise multiple regression models examined which of the three test scores best predicted hippocampal volumes RESULTS: In the correlation analysis, baseline scores on 5 of the 7 tests were significantly associated with hippocampal volumes, one week scores were significantly related for 7 of the 7 tests, and practice effects scores were significantly correlated for 4 of the 7 tests. In the stepwise regression models, 5 of the 7 tests indicated that one-week scores best predicted hippocampal volumes. For the other models, baseline score and practice effects score each best predicted hippocampal volume.

CONCLUSIONS

These results add to the growing body of evidence suggesting that diminished practice effects on short-term repeat testing is related to neuroimaging biomarkers of Alzheimer's disease and may serve as a screening tool for clinical practice and to enrich samples for research trials.

Sustained versus instantaneous connectivity differentiates cognitive functions of processing speed and episodic memory

Synchrony of brain activity over time describes the functional connectivity between brain regions but does not address the temporal component of this relationship. We propose a complementary method of analysis by introducing the width of cross-correlation curves between functional MRI (fMRI) time series as a metric of the relative duration of synchronous activity between brain regions, or "sustained connectivity". Using resting-state fMRI, cognitive, and demographics data from 1,003 subjects included in the Human Connectome Project, we find that sustained connectivity is a reproducible trait in individuals, heritable, more transient in females, and shows changes with age in early adulthood. Sustained connectivity in sensory brain regions is specifically associated with differences in processing speed across subjects, particularly in men. In contrast, traditional functional connectivity was correlated with a measure of episodic memory, but not with processing speed. Individual differences in hemodynamic response function (HRF) are closely approximated by sustained connectivity and width of the HRF is also correlated with processing speed across individuals, suggesting that variability in hemodynamic response may be influenced by transient versus sustained neural activity rather than simply differences in vascularity and signal transduction. Sustained connectivity may provide new opportunities to study brain dynamics in clinical populations.

Decreased anterior cingulate activation in a motor task in youths with bipolar disorder

BACKGROUND

Bipolar disorder (BP) is characterized by abnormal shifts in mood between episodes of mania and severe depression, both of which have been linked with psychomotor disturbances. This study compares brain activation patterns in motor networks between euthymic youths with BP and healthy controls (HC) during the completion of a simple motor task.

METHODS

Thirty-five youths with BP and 35 HC (aged 10-19) completed a self-paced sequential bilateral finger-tapping task, consisting of a 4-minute scan block with alternating 20-second periods of either the tapping task (six blocks) or rest (six blocks), while undergoing functional magnetic resonance imaging. Clinical and behavioral symptoms were assessed using the Child Behavior Checklist (CBCL). A between-group whole-brain analysis compared activation pattern differences while controlling for effects of age and sex. Clusters meeting whole-brain false discovery rate (FDR) correction (qFDR < .05) were considered statistically significant. Post hoc analyses evaluating comorbid attention-deficit/hyperactivity disorder (ADHD) in the BP group were also conducted.

RESULTS

Significantly decreased activation was found in the anterior cingulate cortex (ACC) in youths with BP compared to HC. Furthermore, ACC activation was negatively correlated with CBCL mood dysregulation profile scores in the BP group. No significant differences in functional activation patterns were found between youths with BP and comorbid ADHD and those with only BP.

CONCLUSIONS

These findings suggest a potential common mechanism of impaired ACC modulation between emotion dysregulation and motor processing in youths with BP.

Low b-value diffusion weighted imaging is promising in the diagnosis of brain death and hypoxic-ischemic injury secondary to cardiopulmonary arrest

Background

Cardiorespiratory arrest can result in a spectrum of hypoxic ischemic brain injury leading to global hypoperfusion and brain death (BD). Because up to 40% of patients with BD are viable organ donors, avoiding delayed diagnosis of this condition is critical. High b-value diffusion weighted imaging (DWI) measures primarily molecular self-diffusion; however, low b-values are sensitive to perfusion. We investigated the feasibility of low b-value DWI in discriminating the global hypoperfusion of BD and hypoxic ischemic encephalopathy (HIE).

Methods

We retrospectively reviewed cardiorespiratory arrest subjects with a diagnosis of HIE or BD. Inclusion criteria included brain DWI acquired at both low (50 s/mm²) and high (1000–2000 s/mm²) b-values. Automated segmentation was used to determine mean b50 apparent diffusion coefficient (ADC) values in gray and white matter regions. Normal subjects with DWI at both values were used as age- and sex-matched controls.

Results

We evaluated 64 patients (45 with cardiorespiratory arrest and 19 normal). Cardiorespiratory arrest patients with BD had markedly lower mean b50 ADC in gray matter regions compared with HIE (0.70 ± 0.18 vs. 1.95 ± 0.25 × 10⁻³ mm²/s, p < 0.001) and normal subjects (vs. 1.79 ± 0.12 × 10⁻³ mm²/s, p < 0.001). HIE had higher mean b50 ADC compared with normal (1.95 ± 0.25 vs. 1.79 ± 0.12 × 10⁻³ mm²/s, p = 0.016). There was wide separation of gray matter ADC values in BD subjects compared with age matched normal and HIE subjects. White matter values were also markedly decreased in the BD population, although they were less predictive than gray matter.

Conclusion

Low b-value DWI is promising for the discrimination of HIE with maintained perfusion and brain death in cardiorespiratory arrest.

External validation of change formulae in neuropsychology with neuroimaging biomarkers: A methodological recommendation and preliminary clinical data

OBJECTIVE

Within neuropsychology, a number of mathematical formulae (e.g. reliable change index, standardized regression based) have been used to determine if change across time has reliably occurred. When these formulae have been compared, they often produce different results, but 'different' results do not necessarily indicate which formulae are 'best.' The current study sought to further our understanding of change formulae by comparing them to clinically relevant external criteria (amyloid deposition and hippocampal volume).

METHOD

In a sample of 25 older adults with varying levels of cognitive intactness, participants were tested twice across one week with a brief cognitive battery. Seven different change scores were calculated for each participant. An amyloid PET scan (to get a composite of amyloid deposition) and an MRI (to get hippocampal volume) were also obtained.

RESULTS

Deviation-based change formulae (e.g. simple discrepancy score, reliable change index with or without correction for practice effects) were all identical in their relationship to the two neuroimaging biomarkers, and all were non-significant. Conversely, regression-based change formulae (e.g. simple and complex indices) showed stronger relationships to amyloid deposition and hippocampal volume.

CONCLUSIONS

These results highlight the need for external validation of the various change formulae used by neuropsychologists in clinical settings and research projects. The findings also preliminarily suggest that regression-based change formulae may be more relevant than deviation-based change formulae in this context.

High-throughput synthesis and characterization of nanocrystalline porphyrinic zirconium metal-organic frameworks

We describe and employ a high-throughput screening method to accelerate the synthesis and identification of pure-phase, nanocrystalline metal-organic frameworks (MOFs). We demonstrate the efficacy of this method through its application to a series of porphyrinic zirconium MOFs, resulting in the isolation of MOF-525, MOF-545, and PCN-223 on the nanoscale.

Auditory attention in autism spectrum disorder: An exploration of volumetric magnetic resonance imaging findings

Studies have shown that individuals with autism spectrum disorder (ASD) tend to perform significantly below typically developing individuals on standardized measures of attention, even when controlling for IQ. The current study sought to examine within ASD whether anatomical correlates of attention performance differed between those with average to above-average IQ (AIQ group) and those with low-average to borderline ability (LIQ group) as well as in comparison to typically developing controls (TDC). Using automated volumetric analyses, we examined regional volume of classic attention areas including the superior frontal gyrus, anterior cingulate cortex, and precuneus in ASD AIQ (n = 38) and LIQ (n = 18) individuals along with 30 TDC. Auditory attention performance was assessed using subtests of the Test of Memory and Learning (TOMAL) compared among the groups and then correlated with regional brain volumes. Analyses revealed group differences in attention. The three groups did not differ significantly on any auditory attention-related brain volumes; however, trends toward significant size-attention function interactions were observed. Negative correlations were found between the volume of the precuneus and auditory attention performance for the AIQ ASD group, indicating larger volume related to poorer performance. Implications for general attention functioning and dysfunctional neural connectivity in ASD are discussed.

Fluid and flexible minds: Intelligence reflects synchrony in the brain's intrinsic network architecture

Human intelligence has been conceptualized as a complex system of dissociable cognitive processes, yet studies investigating the neural basis of intelligence have typically emphasized the contributions of discrete brain regions or, more recently, of specific networks of functionally connected regions. Here we take a broader, systems perspective in order to investigate whether intelligence is an emergent property of synchrony within the brain’s intrinsic network architecture. Using a large sample of resting-state fMRI and cognitive data (n = 830), we report that the synchrony of functional interactions within and across distributed brain networks reliably predicts fluid and flexible intellectual functioning. By adopting a whole-brain, systems-level approach, we were able to reliably predict individual differences in human intelligence by characterizing features of the brain’s intrinsic network architecture. These findings hold promise for the eventual development of neural markers to predict changes in intellectual function that are associated with neurodevelopment, normal aging, and brain disease.

In our study, we aimed to understand how individual differences in intellectual functioning are reflected in the intrinsic network architecture of the human brain. We applied statistical methods, known as spectral decompositions, in order to identify individual differences in the synchronous patterns of spontaneous brain activity that reliably predict core aspects of human intelligence. The synchrony of brain activity at rest across multiple discrete neural networks demonstrated positive relationships with fluid intelligence. In contrast, global synchrony within the brain’s network architecture reliably, and inversely, predicted mental flexibility, a core facet of intellectual functioning. The multinetwork systems approach described here represents a methodological and conceptual extension of earlier efforts that related differences in intellectual ability to variations in specific brain regions, networks, or their interactions. Our findings suggest that the neural basis of complex, integrative cognitive functions can be most completely understood from the perspective of network neuroscience.

Brain connectivity and psychiatric comorbidity in adolescents with Internet gaming disorder

Prolonged Internet video game play may have multiple and complex effects on human cognition and brain development in both negative and positive ways. There is not currently a consensus on the principle effects of video game play neither on brain development nor on the relationship to psychiatric comorbidity. In this study, 78 adolescents with Internet gaming disorder (IGD) and 73 comparison subjects without IGD, including subgroups with no other psychiatric comorbid disease, with major depressive disorder and with attention deficit hyperactivity disorder (ADHD), were included in a 3 T resting state functional magnetic resonance imaging analysis. The severity of Internet gaming disorder, depression, anxiety and ADHD symptoms were assessed with the Young Internet Addiction Scale, the Beck Depression Inventory, the Beck Anxiety Inventory and the Korean ADHD rating scales, respectively. Patients with IGD showed an increased functional correlation between seven pairs of regions, all satisfying q < 0.05 False discovery rates in light of multiple statistical tests: left frontal eye field to dorsal anterior cingulate, left frontal eye field to right anterior insula, left dorsolateral prefrontal cortex (DLPFC) to left temporoparietal junction (TPJ), right DLPFC to right TPJ, right auditory cortex to right motor cortex, right auditory cortex to supplementary motor area and right auditory cortex to dorsal anterior cingulate. These findings may represent a training effect of extended game play and suggest a risk or predisposition in game players for over-connectivity of the default mode and executive control networks that may relate to psychiatric comorbidity.

Multivariate characterization of white matter heterogeneity in autism spectrum disorder

The complexity and heterogeneity of neuroimaging findings in individuals with autism spectrum disorder has suggested that many of the underlying alterations are subtle and involve many brain regions and networks. The ability to account for multivariate brain features and identify neuroimaging measures that can be used to characterize individual variation have thus become increasingly important for interpreting and understanding the neurobiological mechanisms of autism. In the present study, we utilize the Mahalanobis distance, a multidimensional counterpart of the Euclidean distance, as an informative index to characterize individual brain variation and deviation in autism. Longitudinal diffusion tensor imaging data from 149 participants (92 diagnosed with autism spectrum disorder and 57 typically developing controls) between 3.1 and 36.83 years of age were acquired over a roughly 10-year period and used to construct the Mahalanobis distance from regional measures of white matter microstructure. Mahalanobis distances were significantly greater and more variable in the autistic individuals as compared to control participants, demonstrating increased atypicalities and variation in the group of individuals diagnosed with autism spectrum disorder. Distributions of multivariate measures were also found to provide greater discrimination and more sensitive delineation between autistic and typically developing individuals than conventional univariate measures, while also being significantly associated with observed traits of the autism group. These results help substantiate autism as a truly heterogeneous neurodevelopmental disorder, while also suggesting that collectively considering neuroimaging measures from multiple brain regions provides improved insight into the diversity of brain measures in autism that is not observed when considering the same regions separately. Distinguishing multidimensional brain relationships may thus be informative for identifying neuroimaging-based phenotypes, as well as help elucidate underlying neural mechanisms of brain variation in autism spectrum disorders.

Sleep duration and resting fMRI functional connectivity: examination of short sleepers with and without perceived daytime dysfunction

BACKGROUND

Approximately 30% of the U.S. population reports recurrent short sleep; however, perceived sleep need varies widely among individuals. Some "habitual short sleepers" routinely sleep 4-6 hr/night without self-reported adverse consequences. Identifying neural mechanisms underlying individual differences in perceived sleep-related dysfunction has important implications for understanding associations between sleep duration and health.

METHOD

This study utilized data from 839 subjects of the Human Connectome Project to examine resting functional connectivity associations with self-reported short sleep duration, as well as differences between short sleepers with versus without reported dysfunction. Functional connectivity was analyzed using a parcellation covering the cortical, subcortical, and cerebellar gray matter at 5 mm resolution.

RESULTS

Self-reported sleep duration predicts one of the primary patterns of intersubject variance in resting functional connectivity. Compared to conventional sleepers, both short sleeper subtypes exhibited resting fMRI (R-fMRI) signatures consistent with diminished wakefulness, potentially indicating inaccurate perception of functionality among those denying dysfunction. Short sleepers denying dysfunction exhibited increased connectivity between sensory cortices and bilateral amygdala and hippocampus, suggesting that efficient sleep-related memory consolidation may partly explain individual differences in perceived daytime dysfunction.

CONCLUSIONS

Overall, current findings indicate that R-fMRI investigations should include assessment of average sleep duration during the prior month. Furthermore, short sleeper subtype findings provide a candidate neural mechanism underlying differences in perceived daytime impairment associated with short sleep duration.

Reward, salience, and attentional networks are activated by religious experience in devout Mormons

High-level cognitive and emotional experience arises from brain activity, but the specific brain substrates for religious and spiritual euphoria remain unclear. We demonstrate using functional magnetic resonance imaging scans in 19 devout Mormons that a recognizable feeling central to their devotional practice was reproducibly associated with activation in nucleus accumbens, ventromedial prefrontal cortex, and frontal attentional regions. Nucleus accumbens activation preceded peak spiritual feelings by 1–3 s and was replicated in four separate tasks. Attentional activation in the anterior cingulate and frontal eye fields was greater in the right hemisphere. The association of abstract ideas and brain reward circuitry may interact with frontal attentional and emotive salience processing, suggesting a mechanism whereby doctrinal concepts may come to be intrinsically rewarding and motivate behavior in religious individuals.

Abnormal Functional Connectivity Between Default and Salience Networks in Pediatric Bipolar Disorder

BACKGROUND

Pediatric bipolar disorder (PBD) (occurring prior to 18 years of age) is a developmental brain disorder that is among the most severe and disabling psychiatric conditions affecting youth. Despite increasing evidence that brain connectivity is atypical in adults with bipolar disorder, it is not clear how brain connectivity may be altered in youths with PBD.

METHODS

This cross-sectional resting-state functional magnetic resonance imaging study included 80 participants recruited over 4 years: 32 youths with PBD, currently euthymic (13 males; 15.1 years old), and 48 healthy control (HC) subjects (27 males; 14.5 years old). Functional connectivity between eight major intrinsic connectivity networks, along with connectivity measurements between 333 brain regions, was compared between PBD and HC subjects. Additionally, connectivity differences were evaluated between PBD and HC samples in negatively correlated connections, as defined by 839 subjects of the Human Connectome Project dataset.

RESULTS

We found increased inter- but not intranetwork functional connectivity in PBD between the default mode and salience networks (p = .0017). Throughout the brain, atypical connections showed failure to develop anticorrelation with age during adolescence in PBD but not HC samples among connections that exhibit negative correlation in adulthood.

CONCLUSIONS

Youths with PBD demonstrate reduced anticorrelation between default mode and salience networks. Further evaluation of the interaction between these networks is needed in development and with other mood states such as depression and mania to clarify if this atypical connectivity is a PBD trait biomarker.

Assessment of white matter microstructure in stroke patients using NODDI

Diffusion weighted imaging (DWI) is widely used to study changes in white matter following stroke. In various studies employing diffusion tensor imaging (DTI) and high angular resolution diffusion imaging (HARDI) modalities, it has been shown that fractional anisotropy (FA), mean diffusivity (MD), and generalized FA (GFA) can be used as measures of white matter tract integrity in stroke patients. However, these measures may be non-specific, as they do not directly delineate changes in tissue microstructure. Multi-compartment models overcome this limitation by modeling DWI data using a set of indices that are directly related to white matter microstructure. One of these models which is gaining popularity, is neurite orientation dispersion and density imaging (NODDI). This model uses conventional single or multi-shell HARDI data to describe fiber orientation dispersion as well as densities of different tissue types in the imaging voxel. In this paper, we apply for the first time the NODDI model to 4-shell HARDI stroke data. By computing NODDI indices over the entire brain in two stroke patients, and comparing tissue regions in ipsilesional and contralesional hemispheres, we demonstrate that NODDI modeling provides specific information on tissue microstructural changes. We also introduce an information theoretic analysis framework to investigate the non-local effects of stroke in the white matter. Our initial results suggest that the NODDI indices might be more specific markers of white matter reorganization following stroke than other measures previously used in studies of stroke recovery.

Investigating the Microstructural Correlation of White Matter in Autism Spectrum Disorder

White matter microstructure forms a complex and dynamical system that is critical for efficient and synchronized brain function. Neuroimaging findings in children with autism spectrum disorder (ASD) suggest this condition is associated with altered white matter microstructure, which may lead to atypical macroscale brain connectivity. In this study, we used diffusion tensor imaging measures to examine the extent that white matter tracts are interrelated within ASD and typical development. We assessed the strength of inter-regional white matter correlations between typically developing and ASD diagnosed individuals. Using hierarchical clustering analysis, clustering patterns of the pairwise white matter correlations were constructed and revealed to be different between the two groups. Additionally, we explored the use of graph theory analysis to examine the characteristics of the patterns formed by inter-regional white matter correlations and compared these properties between ASD and typical development. We demonstrate that the ASD sample has significantly less coherence in white matter microstructure across the brain compared to that in the typical development sample. The ASD group also presented altered topological characteristics, which may implicate less efficient brain networking in ASD. These findings highlight the potential of graph theory based network characteristics to describe the underlying networks as measured by diffusion magnetic resonance imaging and furthermore indicates that ASD may be associated with altered brain network characteristics. Our findings are consistent with those of a growing number of studies and hypotheses that have suggested disrupted brain connectivity in ASD.

Reliability and reproducibility of individual differences in functional connectivity acquired during task and resting state

OBJECTIVES

Application of fMRI connectivity metrics as diagnostic biomarkers at the individual level will require reliability, sensitivity and specificity to longitudinal changes in development, aging, neurocognitive, and behavioral performance and pathologies. Such metrics have not been well characterized for recent advances in BOLD acquisition.

EXPERIMENTAL DESIGN

Analysis of multiband BOLD data from the HCP 500 Subjects Release was performed with FIX ICA and with WM, CSF and motion parameter regression. Analysis with ROIs covering the gray matter at 5 mm resolution was performed to assess functional connectivity. ROIs in key areas were used to demonstrate statistical differences between specific connections. Reproducibility of group-mean functional connectivity and for single connections for individuals was evaluated for both resting state and task acquisitions.

PRINCIPAL OBSERVATIONS

Systematic differences in group-mean connectivity were demonstrated during task and rest and during different tasks, although individual differences in connectivity were maintained. Reproducibility of a single connection for a subject and across subjects for resting and task acquisition was demonstrated to be a linear function of the square root of imaging time. Randomly removing up to 50% of time points had little effect on reliability, while truncating an acquisition was associated with decreased reliability. Reliability was highest within the cortex, and lowest for deep gray nuclei, gray-white junction, and near large sulci.

CONCLUSIONS

This study found systematic differences in group-mean connectivity acquired during task and rest acquitisions and preserved individual differences in connectivity due to intrinsic differences in an individual's brain activity and structural brain architecture. We also show that longer scan times are needed to acquire data on single subjects for information on connections between specific ROIs. Longer scans may be facilitated by acquisition during task paradigms, which will systematically affect functional connectivity but may preserve individual differences in connectivity on top of task modulations.

Mesial temporal lobe and memory function in autism spectrum disorder: an exploration of volumetric findings

Studies have shown that individuals with autism spectrum disorder (ASD) tend to perform significantly below typical developing individuals on standardized measures of memory, even when not significantly different on measures of IQ. The current study sought to examine within ASD whether anatomical correlates of memory performance differed between those with average-to-above-average IQ (AIQ group) and those with low-average to borderline ability (LIQ group) as well as in relations to typically developing comparisons (TDC). Using automated volumetric analyses, we examined regional volume of classic memory areas including the hippocampus, parahippocampal gyrus, entorhinal cortex, and amygdala in an all-male sample AIQ (n = 38) and LIQ (n = 18) individuals with ASD along with 30 typically developing comparisons (TDC). Memory performance was assessed using the Test of Memory and Learning (TOMAL) compared among the groups and then correlated with regional brain volumes. Analyses revealed group differences on almost all facets of memory and learning as assessed by the various subtests of the TOMAL. The three groups did not differ on any region of interest (ROI) memory-related brain volumes. However, significant size-memory function interactions were observed. Negative correlations were found between the volume of the amygdala and composite, verbal, and delayed memory indices for the LIQ ASD group, indicating larger volume related to poorer performance. Implications for general memory functioning and dysfunctional neural connectivity in ASD are discussed.

Beery VMI performance in autism spectrum disorder

Few studies have examined the visuomotor integration (VMI) abilities of individuals with autism spectrum disorder (ASD). An all-male sample consisting of 56 ASD participants (ages 3-23 years) and 36 typically developing (TD) participants (ages 4-26 years) completed the Beery-Buktenica Developmental Test of Visual-Motor Integration (Beery VMI) as part of a larger neuropsychological battery. Participants were also administered standardized measures of intellectual functioning and the Social Responsiveness Scale (SRS), which assesses autism and autism-like traits. The ASD group performed significantly lower on the Beery VMI and on all IQ measures compared to the TD group. VMI performance was significantly correlated with full scale IQ (FSIQ), performance IQ (PIQ), and verbal IQ (VIQ) in the TD group only. However, when FSIQ was taken into account, no significant Beery VMI differences between groups were observed. Only one TD participant scored 1.5 standard deviations (SDs) below the Beery VMI normative sample mean, in comparison to 21% of the ASD sample. As expected, the ASD group was rated as having significantly higher levels of social impairment on the SRS compared to the TD group across all major domains. However, level of functioning on the SRS was not associated with Berry VMI performance. These findings demonstrate that a substantial number of individuals with ASD experience difficulties compared to TD in performing VMI-related tasks, and that VMI is likely affected by general cognitive ability. The fact that lowered Beery VMI performance occurred only within a subset of individuals with ASD and did not correlate with SRS would indicate that visuomotor deficits are not a core feature of ASD, even though they present at a higher rate of impairment than observed in TD participants.

Violence: heightened brain attentional network response is selectively muted in Down syndrome

BACKGROUND

The ability to recognize and respond appropriately to threat is critical to survival, and the neural substrates subserving attention to threat may be probed using depictions of media violence. Whether neural responses to potential threat differ in Down syndrome is not known.

METHODS

We performed functional MRI scans of 15 adolescent and adult Down syndrome and 14 typically developing individuals, group matched by age and gender, during 50 min of passive cartoon viewing. Brain activation to auditory and visual features, violence, and presence of the protagonist and antagonist were compared across cartoon segments. fMRI signal from the brain's dorsal attention network was compared to thematic and violent events within the cartoons between Down syndrome and control samples.

RESULTS

We found that in typical development, the brain's dorsal attention network was most active during violent scenes in the cartoons and that this was significantly and specifically reduced in Down syndrome. When the antagonist was on screen, there was significantly less activation in the left medial temporal lobe of individuals with Down syndrome. As scenes represented greater relative threat, the disparity between attentional brain activation in Down syndrome and control individuals increased. There was a reduction in the temporal autocorrelation of the dorsal attention network, consistent with a shortened attention span in Down syndrome. Individuals with Down syndrome exhibited significantly reduced activation in primary sensory cortices, and such perceptual impairments may constrain their ability to respond to more complex social cues such as violence.

CONCLUSIONS

These findings may indicate a relative deficit in emotive perception of violence in Down syndrome, possibly mediated by impaired sensory perception and hypoactivation of medial temporal structures in response to threats, with relative preservation of activity in pro-social brain regions. These findings indicate that specific genetic differences associated with Down syndrome can modulate the brain's response to violence and other complex emotive ideas.

Atypical development of white matter microstructure of the corpus callosum in males with autism: a longitudinal investigation

BACKGROUND

The corpus callosum is the largest white matter structure in the brain, and it is the most consistently reported to be atypical in diffusion tensor imaging studies of autism spectrum disorder. In individuals with typical development, the corpus callosum is known to undergo a protracted development from childhood through young adulthood. However, no study has longitudinally examined the developmental trajectory of corpus callosum in autism past early childhood.

METHODS

The present study used a cohort sequential design over 9 years to examine age-related changes of the corpus callosum in 100 males with autism and 56 age-matched males with typical development from early childhood (when autism can first be reliably diagnosed) to mid-adulthood (after development of the corpus callosum has been completed) (3 to 41 years of age).

RESULTS

The group with autism demonstrated a different developmental trajectory of white matter microstructure in the anterior corpus callosum's (genu and body) fractional anisotropy, which suggests atypical brain maturation in these regions in autism. When analyses were broken down by age group, atypical developmental trajectories were present only in the youngest participants (10 years of age and younger). Significant main effects for group were found in terms of decreased fractional anisotropy across all three subregions of the corpus callosum (genu, body, and splenium) and increased mean diffusivity, radial diffusivity, and axial diffusivity in the posterior corpus callosum.

CONCLUSIONS

These longitudinal results suggest atypical early childhood development of the corpus callosum microstructure in autism that transitions into sustained group differences in adolescence and adulthood. This pattern of results provides longitudinal evidence consistent with a growing number of published studies and hypotheses regarding abnormal brain connectivity across the life span in autism.

Longitudinal volumetric brain changes in autism spectrum disorder ages 6-35 years

Since the impairments associated with autism spectrum disorder (ASD) tend to persist or worsen from childhood into adulthood, it is of critical importance to examine how the brain develops over this growth epoch. We report initial findings on whole and regional longitudinal brain development in 100 male participants with ASD (226 high-quality magnetic resonance imaging [MRI] scans; mean inter-scan interval 2.7 years) compared to 56 typically developing controls (TDCs) (117 high-quality scans; mean inter-scan interval 2.6 years) from childhood into adulthood, for a total of 156 participants scanned over an 8-year period. This initial analysis includes between one and three high-quality scans per participant that have been processed and segmented to date, with 21% having one scan, 27% with two scans, and 52% with three scans in the ASD sample; corresponding percentages for the TDC sample are 30%, 30%, and 40%. The proportion of participants with multiple scans (79% of ASDs and 68% of TDCs) was high in comparison to that of large longitudinal neuroimaging studies of typical development. We provide volumetric growth curves for the entire brain, total gray matter (GM), frontal GM, temporal GM, parietal GM, occipital GM, total cortical white matter (WM), corpus callosum, caudate, thalamus, total cerebellum, and total ventricles. Mean volume of cortical WM was reduced significantly. Mean ventricular volume was increased in the ASD sample relative to the TDCs across the broad age range studied. Decreases in regional mean volumes in the ASD sample most often were due to decreases during late adolescence and adulthood. The growth curve of whole brain volume over time showed increased volumes in young children with autism, and subsequently decreased during adolescence to meet the TDC curve between 10 and 15 years of age. The volume of many structures continued to decline atypically into adulthood in the ASD sample. The data suggest that ASD is a dynamic disorder with complex changes in whole and regional brain volumes that change over time from childhood into adulthood.

A functional network estimation method of resting-state fMRI using a hierarchical Markov random field

We propose a hierarchical Markov random field model for estimating both group and subject functional networks simultaneously. The model takes into account the within-subject spatial coherence as well as the between-subject consistency of the network label maps. The statistical dependency between group and subject networks acts as a regularization, which helps the network estimation on both layers. We use Gibbs sampling to approximate the posterior density of the network labels and Monte Carlo expectation maximization to estimate the model parameters. We compare our method with two alternative segmentation methods based on K-Means and normalized cuts, using synthetic and real fMRI data. The experimental results show that our proposed model is able to identify both group and subject functional networks with higher accuracy on synthetic data, more robustness, and inter-session consistency on the real data.

Altered resting functional connectivity of expressive language regions after speed reading training

A goal of interventions designed to increase reading speed is to reduce the practice of articulating words in an individual's thoughts, or subvocalization. This practice may require redundant cognitive resources, slow reading speed, and detract from efficient transfer of written words to semantic understanding. It is unclear, however, whether exercises designed to promote faster reading speed generalize to cognitive function beyond the reading task itself. To investigate this possibility, we measured resting state functional connectivity in classical language regions before and after a course of cognitive exercise designed to increase reading speed in 9 healthy adolescent female volunteers. We found significantly decreased correlation between left Broca area and right Broca homologue and between right Broca homologue and right Wernicke homologue in the resting state after the training period compared to before training. Differences in functional connectivity after training to left Broca area showed a spatial distribution reflecting decreased correlation to memory-associated brain regions and increased correlation to auditory regions, which might be consistent with a hypothesis that such training may decrease subvocalization associated with semantic memory function during the resting state.

Longitudinal changes in cortical thickness in autism and typical development

The natural history of brain growth in autism spectrum disorders remains unclear. Cross-sectional studies have identified regional abnormalities in brain volume and cortical thickness in autism, although substantial discrepancies have been reported. Preliminary longitudinal studies using two time points and small samples have identified specific regional differences in cortical thickness in the disorder. To clarify age-related trajectories of cortical development, we examined longitudinal changes in cortical thickness within a large mixed cross-sectional and longitudinal sample of autistic subjects and age- and gender-matched typically developing controls. Three hundred and forty-five magnetic resonance imaging scans were examined from 97 males with autism (mean age = 16.8 years; range 3-36 years) and 60 males with typical development (mean age = 18 years; range 4-39 years), with an average interscan interval of 2.6 years. FreeSurfer image analysis software was used to parcellate the cortex into 34 regions of interest per hemisphere and to calculate mean cortical thickness for each region. Longitudinal linear mixed effects models were used to further characterize these findings and identify regions with between-group differences in longitudinal age-related trajectories. Using mean age at time of first scan as a reference (15 years), differences were observed in bilateral inferior frontal gyrus, pars opercularis and pars triangularis, right caudal middle frontal and left rostral middle frontal regions, and left frontal pole. However, group differences in cortical thickness varied by developmental stage, and were influenced by IQ. Differences in age-related trajectories emerged in bilateral parietal and occipital regions (postcentral gyrus, cuneus, lingual gyrus, pericalcarine cortex), left frontal regions (pars opercularis, rostral middle frontal and frontal pole), left supramarginal gyrus, and right transverse temporal gyrus, superior parietal lobule, and paracentral, lateral orbitofrontal, and lateral occipital regions. We suggest that abnormal cortical development in autism spectrum disorders undergoes three distinct phases: accelerated expansion in early childhood, accelerated thinning in later childhood and adolescence, and decelerated thinning in early adulthood. Moreover, cortical thickness abnormalities in autism spectrum disorders are region-specific, vary with age, and may remain dynamic well into adulthood.

Elucidating the nature and mechanism of tic improvement in tourette syndrome: a pilot study

Background

For unclear reasons, many Tourette syndrome (TS) children report near-complete tic remission by young adulthood. Immature maturation of brain networks, observed with resting-state functional MRI (rs-fc-MRI) in adolescents and adults with TS, might evolve to a mature pattern in adults who experience tic improvement or remission. We explored the feasibility of testing this hypothesis in our population of young adult TS males, each with prior clinical assessments completed during childhood as part of a separate TS Association Genetics Consortium study.

Methods

A total of 10 TS males (off tic suppressing drugs for at least 6 months) aged 19–32 years, mean follow-up interval 7.5 (2 to 13) years, and 11 neurologically normal controls were enrolled and underwent 3-Tesla structural and rs-fc-MRI sequences.

Results

The mean change in Yale Global Tic Severity Scale (YGTSS) was −31.5% (total) and −26.6% (YGTSS motor+vocal). Two subjects reported resolution of tic-related disability, with drops from mean 45 to 16.5 (YGTSS-total) and 25 to 11.5 (YGTSS motor+vocal.).

Rs-fc-MRI revealed significantly increased connectivity between the ipsilateral anterior and mid cingulate cortex and striatum, increased connectivity between local connections, and decreased connectivity between more distant connections; representing an immature connectivity pattern.

Discussion

Similar to previous reports, we found immature patterns of functional connectivity in adult TS subjects. Despite a lack of complete tic remission, two subjects exhibited dramatic drops in tic severity that correlated with tic-related disability improvement. More work is needed to elucidate the mechanism of such dramatic improvement in TS.

Abnormal lateralization of functional connectivity between language and default mode regions in autism

Background

Lateralization of brain structure and function occurs in typical development, and abnormal lateralization is present in various neuropsychiatric disorders. Autism is characterized by a lack of left lateralization in structure and function of regions involved in language, such as Broca and Wernicke areas.

Methods

Using functional connectivity magnetic resonance imaging from a large publicly available sample (n = 964), we tested whether abnormal functional lateralization in autism exists preferentially in language regions or in a more diffuse pattern across networks of lateralized brain regions.

Results

The autism group exhibited significantly reduced left lateralization in a few connections involving language regions and regions from the default mode network, but results were not significant throughout left- and right-lateralized networks. There is a trend that suggests the lack of left lateralization in a connection involving Wernicke area and the posterior cingulate cortex associates with more severe autism.

Conclusions

Abnormal language lateralization in autism may be due to abnormal language development rather than to a deficit in hemispheric specialization of the entire brain.

BOLD Granger causality reflects vascular anatomy

A number of studies have tried to exploit subtle phase differences in BOLD time series to resolve the order of sequential activation of brain regions, or more generally the ability of signal in one region to predict subsequent signal in another region. More recently, such lag-based measures have been applied to investigate directed functional connectivity, although this application has been controversial. We attempted to use large publicly available datasets (FCON 1000, ADHD 200, Human Connectome Project) to determine whether consistent spatial patterns of Granger Causality are observed in typical fMRI data. For BOLD datasets from 1,240 typically developing subjects ages 7–40, we measured Granger causality between time series for every pair of 7,266 spherical ROIs covering the gray matter and 264 seed ROIs at hubs of the brain’s functional network architecture. Granger causality estimates were strongly reproducible for connections in a test and replication sample (n=620 subjects for each group), as well as in data from a single subject scanned repeatedly, both during resting and passive video viewing. The same effect was even stronger in high temporal resolution fMRI data from the Human Connectome Project, and was observed independently in data collected during performance of 7 task paradigms. The spatial distribution of Granger causality reflected vascular anatomy with a progression from Granger causality sources, in Circle of Willis arterial inflow distributions, to sinks, near large venous vascular structures such as dural venous sinuses and at the periphery of the brain. Attempts to resolve BOLD phase differences with Granger causality should consider the possibility of reproducible vascular confounds, a problem that is independent of the known regional variability of the hemodynamic response.

Multisite functional connectivity MRI classification of autism: ABIDE results

Background: Systematic differences in functional connectivity MRI metrics have been consistently observed in autism, with predominantly decreased cortico-cortical connectivity. Previous attempts at single subject classification in high-functioning autism using whole brain point-to-point functional connectivity have yielded about 80% accurate classification of autism vs. control subjects across a wide age range. We attempted to replicate the method and results using the Autism Brain Imaging Data Exchange (ABIDE) including resting state fMRI data obtained from 964 subjects and 16 separate international sites.

Methods: For each of 964 subjects, we obtained pairwise functional connectivity measurements from a lattice of 7266 regions of interest covering the gray matter (26.4 million “connections”) after preprocessing that included motion and slice timing correction, coregistration to an anatomic image, normalization to standard space, and voxelwise removal by regression of motion parameters, soft tissue, CSF, and white matter signals. Connections were grouped into multiple bins, and a leave-one-out classifier was evaluated on connections comprising each set of bins. Age, age-squared, gender, handedness, and site were included as covariates for the classifier.

Results: Classification accuracy significantly outperformed chance but was much lower for multisite prediction than for previous single site results. As high as 60% accuracy was obtained for whole brain classification, with the best accuracy from connections involving regions of the default mode network, parahippocampaland fusiform gyri, insula, Wernicke Area, and intraparietal sulcus. The classifier score was related to symptom severity, social function, daily living skills, and verbal IQ. Classification accuracy was significantly higher for sites with longer BOLD imaging times.

Conclusions: Multisite functional connectivity classification of autism outperformed chance using a simple leave-one-out classifier, but exhibited poorer accuracy than for single site results. Attempts to use multisite classifiers will likely require improved classification algorithms, longer BOLD imaging times, and standardized acquisition parameters for possible future clinical utility.

An evaluation of the left-brain vs. right-brain hypothesis with resting state functional connectivity magnetic resonance imaging

Lateralized brain regions subserve functions such as language and visuospatial processing. It has been conjectured that individuals may be left-brain dominant or right-brain dominant based on personality and cognitive style, but neuroimaging data has not provided clear evidence whether such phenotypic differences in the strength of left-dominant or right-dominant networks exist. We evaluated whether strongly lateralized connections covaried within the same individuals. Data were analyzed from publicly available resting state scans for 1011 individuals between the ages of 7 and 29. For each subject, functional lateralization was measured for each pair of 7266 regions covering the gray matter at 5-mm resolution as a difference in correlation before and after inverting images across the midsagittal plane. The difference in gray matter density between homotopic coordinates was used as a regressor to reduce the effect of structural asymmetries on functional lateralization. Nine left- and 11 right-lateralized hubs were identified as peaks in the degree map from the graph of significantly lateralized connections. The left-lateralized hubs included regions from the default mode network (medial prefrontal cortex, posterior cingulate cortex, and temporoparietal junction) and language regions (e.g., Broca Area and Wernicke Area), whereas the right-lateralized hubs included regions from the attention control network (e.g., lateral intraparietal sulcus, anterior insula, area MT, and frontal eye fields). Left- and right-lateralized hubs formed two separable networks of mutually lateralized regions. Connections involving only left- or only right-lateralized hubs showed positive correlation across subjects, but only for connections sharing a node. Lateralization of brain connections appears to be a local rather than global property of brain networks, and our data are not consistent with a whole-brain phenotype of greater “left-brained” or greater “right-brained” network strength across individuals. Small increases in lateralization with age were seen, but no differences in gender were observed.