Search

Objectives The spinal cord injury (SCI) patient population is overwhelmingly affected by neuropathic pain (NP), a secondary condition for which therapeutic options are limited and have a low degree of efficacy. The objective of this study was to identify novel deep brain stimulation (DBS) targets that may theoretically benefit those with NP in the SCI patient population. We hypothesize that localized changes in white matter identified in SCI subjects with NP compared to those without NP could be used to develop an evidence-based approach to DBS target identification. Materials and methods To classify localized neurostructural changes associated with NP in the SCI population, we compared white matter fiber density (FD) and cross-section (FC) between SCI subjects with NP (N = 17) and SCI subjects without NP (N = 15) using diffusion-weighted magnetic resonance imaging (MRI). We then identified theoretical target locations for DBS using fiber bundles connected to significantly altered regions of white matter. Finally, we used computational models of DBS to determine if our theoretical target locations could be used to feasibly activate our fiber bundles of interest. Results We identified significant increases in FC in the splenium of the corpus callosum in pain subjects when compared to controls. We then isolated five fiber bundles that were directly connected to the affected region of white matter. Our models were able to predict that our fiber bundles of interest can be feasibly activated with DBS at reasonable stimulation amplitudes and with clinically relevant implantation approaches. Conclusions Altogether, we identified neuroarchitectural changes associated with NP in the SCI cohort and implemented a novel, evidence-driven target selection approach for DBS to guide future research in neuromodulation treatment of NP after SCI.

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 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.

OBJECTIVE: To evaluate the relationship between degree of cognitive impairment and gray-matter density changes in the auditory cortex. STUDY DESIGN: Retrospective case-control. PATIENTS: Six hundred sixty-three patients of a tertiary referral center cognitive disorders clinic. INTERVENTION: Magnetic resonance imaging. MAIN OUTCOME MEASURES: Ratios of gray matter density of the primary auditory cortex (A1) to whole brain and auditory association cortex (AAC) to whole brain in patients with Alzheimer's disease (AD) compared with mild cognitive impairment (MCI) and patients with a mini-mental state exam (MMSE) scores ≤25 versus >25. RESULTS: After multivariate analysis, a statistically significant difference between AAC to brain ratios for patients with a MMSE ≤25 (n = 325) compared with >25 (n = 269) was found, with values -0.03 (95% CI -0.04 to -0.02, p 

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.

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.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,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.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.

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.

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.

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.

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.

Objective Individual differences in aesthetic engagement—the propensity to be moved by art, nature, and beauty—are associated with positive health outcomes, as well as stress resilience. The purpose of the current study was to identify potential neural substrate mechanisms underlying individual differences in aesthetic engagement and reported proneness to aesthetic chill. Methods Data from the Human Connectome Project (HCP) 1200 Subjects Release were utilized. Resting-state fMRI connectivity was extracted for 361 regions in the brain including cortical, subcortical and cerebellar regions for each participant, using participant-specific segmentation and parcellation of subcortical gray matter nuclei and a network-based statistics analytical approach. The Aesthetic Interests subcluster of the Openness to Experience scale (NEO-Five Factor Inventory; NEO-FFI) was used to characterize individual differences in aesthetic engagement and chill. Results Participants reporting higher aesthetic engagement, particularly proneness to aesthetic chill responses, exhibited significantly higher connectivity between the default network and sensory and motor cortices, higher connectivity between the ventral default and salience networks, and decreased connectivity between the cerebellum and somatomotor cortex. Conclusions Current findings suggest that greater integration of the default mode network, involving processing of internal narrative, with neural representations of sensory perception and salience detection may be a mechanism underlying individual differences in aesthetic engagement. Thus, these individual differences may reflect general integration of environmental perception with internal emotional experience, which in turn may facilitate comfort with novelty, self-regulation, and positive adaptation to potentially stressful experiences.

The thalamus is a key sensorimotor relay area that is implicated in autism spectrum disorder (ASD). However, it is unknown how the thalamus and white-matter structures that contain thalamo-cortical fiber connections (e.g., the internal capsule) develop from childhood into adulthood and whether this microstructure relates to basic motor challenges in ASD. We used diffusion weighted imaging in a cohort-sequential design to assess longitudinal development of the thalamus, and posterior- and anterior-limbs of the internal capsule (PLIC and ALIC, respectively) in 89 males with ASD and 56 males with typical development (3-41 years; all verbal). Our results showed that the group with ASD exhibited different developmental trajectories of microstructure in all regions, demonstrating childhood group differences that appeared to approach and, in some cases, surpass the typically developing group in adolescence and adulthood. The PLIC (but not ALIC nor thalamus) mediated the relation between age and finger-tapping speed in both groups. Yet, the gap in finger-tapping speed appeared to widen at the same time that the between-group gap in the PLIC appeared to narrow. Overall, these results suggest that childhood group differences in microstructure of the thalamus and PLIC become less robust in adolescence and adulthood. Further, finger-tapping speed appears to be mediated by the PLIC in both groups, but group differences in motor speed that widen during adolescence and adulthood suggest that factors beyond the microstructure of the thalamus and internal capsule may contribute to atypical motor profiles in ASD. Autism Res 2018, 11: 450-462. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. Lay summary Microstructure of the thalamus, a key sensory and motor brain area, appears to develop differently in individuals with autism spectrum disorder (ASD). Microstructure is important because it informs us of the density and organization of different brain tissues. During childhood, thalamic microstructure was distinct in the ASD group compared to the typically developing group. However, these group differences appeared to narrow with age, suggesting that the thalamus continues to dynamically change in ASD into adulthood.

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.

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.

Introduction: Derangement of the cerebrovascular unit (CVU) following ischemia-reperfusion from cardiac arrest contributes to overall brain injury. MRI can detect perfusion changes, but imaging timing and severity of injury vary in the clinical population. Hypothesis: We hypothesized that a large-animal model with fixed periods of global ischemia followed by standardized reperfusion and time to image acquisition would demonstrate a reliable gradient of perfusion changes. Such a model would allow neuroprotective strategies to be tested using early imaging biomarkers to quantify effects on cerebral perfusion. Methods: 10 healthy swine were placed under isoflurane anesthesia and underwent control MRI with dynamic susceptibility contrast (DSC) perfusion. Following imaging, animals were randomized to sham, 10, 15, 20, and 30-minute arrest groups, after which extracorporeal membrane oxygenation (ECMO) catheters were placed in the distal aorta and right atrium. Ventricular fibrillation was then induced by a bipolar pacing catheter for the fixed period of ischemia, after which animals were reperfused at 2.8-3.5 L/min with unblended oxygenated blood. After 4 minutes they were defibrillated. Over the next 2 hours they were weaned from pump and decannulated with epinephrine and fluid boluses given for hemodynamic support. Animals were then re-imaged within 2 hours post-resuscitation using the same pre-arrest protocol. DSC post-processing was performed and regions of interest were drawn in the bilateral frontal lobes to quantify perfusion parameters. Results: Baseline hemodynamic parameters, including BP, Heart Rate, ETCO2, and SpO2 were similar between animals. When comparing pre- to post-arrest MRI, there was a linear correlation of increasing Cerebral Blood Volume (CBV) with ischemic duration (r=0.69, p=0.028), and downward trend of Cerebral Blood Flow (CBF) with duration (r=-0.48, p=0.164). Conclusion: MRI DSC perfusion abnormalities were observed early in the post arrest period following fixed periods of ischemia with CBV correlated with ischemia duration consistent with dysfunctional vasodilation and uncoupling of the CVU. CBF showed a downward trend with injury severity. The effect of vasopressors and fluids on these findings is unclear.

Introduction: Reperfusion/ischemic brain injury following arrest is a major cause of death/disability among patients surviving to admission. Aside from targeted temperature management, no proven neuroprotective strategies exist. Melatonin (anti-epileptic/antioxidant) and ketamine (glutamate inhibitor), along with controlled reintroduction of oxygenated blood have been proposed to reduce secondary injury. Hypothesis: We hypothesized that a combination of above therapies would reduce the ischemic burden measured on MRI following cardiac arrest if administered upon initial reperfusion. Methods: 6 swine underwent isoflurane anesthesia and control MRI (DTI b2000/20 directions, DSC). Swine were randomized to fixed periods of cardiac arrest (2 swine to 20 min and 1 to 30 min in both control and treated groups), and ECMO catheters placed in the distal aorta and right atrium, then ventricular fibrillation induced by a bipolar pacing catheter. Following ischemia, swine were reperfused at 2.8-3.5 L/min with either unblended oxygenated blood in the control group, or 21% oxygenated blood increased to 30% after 4 minutes and then titrated to maintain PaO2 of 80-100 mm Hg, melatonin 5 mg/kg bolus then 5 mg/kg/hr and ketamine 4 mg/kg/hr for 2 hours in the treated group. After 4 min swine were defibrillated until return of heartbeat. Animals were weaned from pump, decannulated, and epinephrine and fluid boluses administered for hemodynamic support, then re-imaged within 2 hours post-resuscitation using same protocol. Whole brain ADC measurements were performed on gray and white matter. Frontal lobe regions of interest drawn for DSC perfusion parameters. Results: Baseline hemodynamic parameters: BP, Heart Rate, End-Tidal CO2, and SpO2 were similar between animals. There was no difference in percent change ADC in gray or white matter between treated and untreated swine (p=0.9), or difference in CBV (p=0.67). CBF showed an upward trend in treated animals (p=0.17). Conclusions: A multimodal neuroprotective strategy of melatonin, ketamine, and controlled reoxygenation failed to demonstrate measurable impact on MRI markers of ischemia-reperfusion injury in this pilot study. The translation of promising neuroprotectants might be triaged using the employed model.

Introduction: Hypoxic ischemic brain injury (HIBI) results from loss of oxygen or perfusion during cardiac arrest and is the most common cause of death/disability in patients surviving to admission. Diagnostic tests are crucial to identify irreversible injury thresholds for neuroprognostication. MRI DTI can detect cellular injury in response to HIBI, but imaging timing and severity of hypoxia vary widely. Hypothesis: We hypothesized that a model with fixed periods of ischemia followed by both standardized reperfusion and time to image acquisition would demonstrate a reliable gradient of injury. Such a model would allow neuroprotective strategies to be tested using early imaging biomarkers to quantify effects on cytoarchitecture. Methods: Eleven healthy swine (49 + 5 kg) under isoflurane anesthesia underwent control MRI with DTI at b2000/20 directions. Two animals each were then randomized to sham, 10, 15, 20, and one to 30-minutes of arrest. For reperfusion, extracorporeal membrane oxygenation (ECMO) catheters were placed in the distal aorta and right atrium, after which ventricular fibrillation was induced by a bipolar pacing catheter. Following the fixed period of ischemia, animals were reperfused at 2.8-3.5 L/min with unblended oxygenated blood. After 4 minutes they were defibrillated. Over two hours they were weaned from pump and decannulated with epinephrine and fluid boluses for hemodynamic support. Animals were re-imaged within two hours post-resuscitation using the same pre-arrest protocol. Whole brain ADC measurements were performed in the gray and white matter. Results: Baseline hemodynamic parameters: BP, Heart Rate, End-Tidal CO2, and SpO2 were similar between animals. When comparing pre- to post-arrest MRI, there was a strong linear correlation between percent gray matter ADC change (r=-0.87, p Conclusion: MRI DTI changes observed following fixed periods of ischemia with ADC in gray and white matter correlated well with ischemia duration in the first few hours post arrest. These findings support the feasibility of MRI for measuring severity of insult in HIBI and an animal model that might serve as translational endpoint for neuroprotectant strategies.

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.

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.

A large body of evidence relates autism with abnormal structural and functional brain connectivity. Structural covariance MRI (scMRI) is a technique that maps brain regions with covarying gray matter density across subjects. It provides a way to probe the anatomical structures underlying intrinsic connectivity networks (ICNs) through the analysis of the gray matter signal covariance. In this paper, we apply topological data analysis in conjunction with scMRI to explore network-specific differences in the gray matter structure in subjects with autism versus age-, gender- and IQ-matched controls. Specifically, we investigate topological differences in gray matter structures captured by structural covariance networks (SCNs) derived from three ICNs strongly implicated in autism, namely, the salience network (SN), the default mode network (DMN) and the executive control network (ECN). By combining topological data analysis with statistical inference, our results provide evidence of statistically significant network-specific structural abnormalities in autism, from SCNs derived from SN and ECN. These differences in brain architecture are consistent with direct structural analysis using scMRI (Zielinski et al. 2012).

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.

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., Highlights • Mahalanobis distance proposed to characterize brain differences from a multivariate set of neuroimaging measures. • Brain variation in autism is examined using Mahalanobis distance is sensitive to underlying microstructure. • Comparison of Mahalanobis distance with traditional univariate measures is examined. • Utility of multivariate brain relations with Mahalanobis distance and prospect of future studies are described.