Normative Magnetic Resonance Imaging Data Increase the Sensitivity to Brain Volume Abnormalities in the Classification of Fetal Alcohol Spectrum Disorder

OBJECTIVE

To evaluate the use of a large magnetic resonance imaging (MRI) normative dataset to quantify structural brain anomalies that may improve diagnostic sensitivity for atypical brain volume in youth with fetal alcohol spectrum disorder (FASD).

STUDY DESIGN

Participants included 48 children with prenatal alcohol exposure (PAE) and 43 controls, ages 8-17 years, from the longitudinal Collaborative Initiative on FASD s. Recently published lifespan brain charts were used to quantify participants' (per)centile for brain volumes (cortical and subcortical gray matter and cortical white matter), providing an index of (dis)similarity to typically developing individuals of the same age and sex.

RESULTS

Participants with PAE demonstrated lower mean centile scores compared with controls. Participants with PAE and scores ≤ 10th centile on at least 1 brain volume metric demonstrated significantly lower performance on measures of intellectual function and aspects of executive functioning compared with participants with PAE and "typical" volumes (>10th centile). Brain volume centiles explained a greater amount of variance in IQ and improved sensitivity to brain volume anomalies in FASD compared with the most commonly used diagnostic criterion of occipitofrontal circumference (OFC) ≤ 10th.

CONCLUSION

Age- and sex-adjusted brain volumes based on a large normative dataset may be useful predictors of functional outcomes and may identify a greater number of individuals with FASD than the currently used criterion of OFC.

Optimizing the measurement of sample entropy in resting-state fMRI data

Introduction

The complexity of brain signals may hold clues to understand brain-based disorders. Sample entropy, an index that captures the predictability of a signal, is a promising tool to measure signal complexity. However, measurement of sample entropy from fMRI signals has its challenges, and numerous questions regarding preprocessing and parameter selection require research to advance the potential impact of this method. For one example, entropy may be highly sensitive to the effects of motion, yet standard approaches to addressing motion (e.g., scrubbing) may be unsuitable for entropy measurement. For another, the parameters used to calculate entropy need to be defined by the properties of data being analyzed, an issue that has frequently been ignored in fMRI research. The current work sought to rigorously address these issues and to create methods that could be used to advance this field.

Methods

We developed and tested a novel windowing approach to select and concatenate (ignoring connecting volumes) low-motion windows in fMRI data to reduce the impact of motion on sample entropy estimates. We created utilities (implementing autoregressive models and a grid search function) to facilitate selection of the matching length m parameter and the error tolerance r parameter. We developed an approach to apply these methods at every grayordinate of the brain, creating a whole-brain dense entropy map. These methods and tools have been integrated into a publicly available R package ("powseR"). We demonstrate these methods using data from the ABCD study. After applying the windowing procedure to allow sample entropy calculation on the lowest-motion windows from runs 1 and 2 (combined) and those from runs 3 and 4 (combined), we identified the optimal m and r parameters for these data. To confirm the impact of the windowing procedure, we compared entropy values and their relationship with motion when entropy was calculated using the full set of data vs. those calculated using the windowing procedure. We then assessed reproducibility of sample entropy calculations using the windowed procedure by calculating the intraclass correlation between the earlier and later entropy measurements at every grayordinate.

Results

When applying these optimized methods to the ABCD data (from the subset of individuals who had enough windows of continuous "usable" volumes), we found that the novel windowing procedure successfully mitigated the large inverse correlation between entropy values and head motion seen when using a standard approach. Furthermore, using the windowed approach, entropy values calculated early in the scan (runs 1 and 2) are largely reproducible when measured later in the scan (runs 3 and 4), although there is some regional variability in reproducibility.

Discussion

We developed an optimized approach to measuring sample entropy that addresses concerns about motion and that can be applied across datasets through user-identified adaptations that allow the method to be tailored to the dataset at hand. We offer preliminary results regarding reproducibility. We also include recommendations for fMRI data acquisition to optimize sample entropy measurement and considerations for the field.

Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures

Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predictive power of the existing algorithms has been limited by small sample sizes, lack of representativeness, data leakage, and/or overfitting. Here, we overcome these limitations with the largest multi-site sample size to date (N = 5365) to provide a generalizable ML classification benchmark of major depressive disorder (MDD) using shallow linear and non-linear models. Leveraging brain measures from standardized ENIGMA analysis pipelines in FreeSurfer, we were able to classify MDD versus healthy controls (HC) with a balanced accuracy of around 62%. But after harmonizing the data, e.g., using ComBat, the balanced accuracy dropped to approximately 52%. Accuracy results close to random chance levels were also observed in stratified groups according to age of onset, antidepressant use, number of episodes and sex. Future studies incorporating higher dimensional brain imaging/phenotype features, and/or using more advanced machine and deep learning methods may yield more encouraging prospects.

Patterns of experience, expression, and physiology of stress relate to depressive symptoms and self-injurious thoughts and behaviors in adolescents: a person-centered approach

BACKGROUND

Preliminary evidence shows that discordance in stress experience, expression, and physiology (EEP) in adolescents is linked to depression, suicidal ideation (SI), non-suicidal self-injury (NSSI), and brain functioning. This study employs person-centered analysis to probe the relationship between stress responses, psychopathology, and neural patterns in female adolescents who are oversampled for engagement in NSSI.

METHODS

Adolescent females (N = 109, ages 12-17) underwent a social stress test from which self-report measures of stress experience, observer ratings of stress expression, and physiological metrics of stress (via salivary cortisol) were obtained. Multi-trajectory modeling was employed to identify concordant and discordant stress EEP groups. Depressive symptoms, SI and attempt, NSSI engagement, frontal and limbic activation to emotional stimuli, and resting state fronto-limbic connectivity were examined in the EEP groups derived from the multi-trajectory models.

RESULTS

Four groups were identified, three of which demonstrated relatively concordant EEP and one which demonstrated discordant EEP (High Experience-High Expression-Low Physiology). Further, replicating past research, the High Experience-High Expression-Low Physiology discordant group exhibited higher depressive symptoms, SI, suicide attempt, and NSSI episodes (only for sensitivity analyses based on past year) relative to other EEP groups. No significant group differences in brain functioning emerged.

CONCLUSION

Results indicate that within-person, multi-level patterns in stress responding capture risk for dysfunction including depression and self-injurious thoughts and behaviors. Further interrogating of system-level stress functioning may better inform assessment and intervention efforts.

Mitochondrial health, NLRP3 inflammasome activation, and white matter integrity in adolescent mood disorders: A pilot study

Adolescence is a particularly important period for brain development and is also when mood disorders typically emerge. Several psychiatric illnesses exhibit mitochondrial dysfunction, elevated inflammation, and impaired white matter integrity. This study explored the intersection of mitochondrial health, NLRP3 inflammasome activation, and white matter integrity in a small cohort of 29 adolescent patients with mood disorders (bipolar disorder (BD): n = 11, major depressive disorder (MDD): n = 19) and 19 healthy controls. In this sample, adolescents with mood disorders showed lower fractional anisotropy of the ventral cingulum bundle than healthy controls. Across all adolescents, we demonstrated a significant relationship between mitochondrial electron transport chain gene expression, and NLRP3 inflammasome gene expression and activation. Furthermore, circulating cell free mitochondrial DNA was associated with lower white matter integrity in the anterior thalamic radiation. Exploratory subgroup analyses revealed that adolescents with bipolar disorder exhibited lower levels of mitochondrial gene expression and volume, along with increased sensitivity to NLRP3 inflammasome activation compared to adolescents with unipolar depression. Overall, our results reveal relationships between peripherally-measured endpoints of mitochondrial health and NLRP3 inflammasome activation, and centrally measured endpoints of white matter integrity in adolescents. Together with subtle patterns of aberrant neural and biological structure and function in association with mood disorder diagnoses, these results may shed light on the pathophysiology of disease in this early phase of illness.

Locoregional Control Benefit of a Tumor Bed Boost for Ductal Carcinoma In Situ (DCIS)

PURPOSE/OBJECTIVE(S)

Radiotherapy (RT) following breast conserving surgery (BCS) for ductal carcinoma in situ (DCIS) reduces invasive and in situ recurrences. Whereas landmark studies suggest that a tumor bed boost improves local control for invasive breast cancer, the benefit in DCIS remains less certain. We evaluated outcomes of DCIS patients treated with or without a boost and hypothesized that a tumor bed boost would improve locoregional control rates.

MATERIALS/METHODS

The study cohort comprised patients with DCIS who underwent BCS at our institution from 2004-2018. Clinicopathologic features, treatment parameters and outcomes were ascertained from medical records. Patient and tumor characteristics were evaluated relative to outcomes using univariable and multivariable Cox models. Recurrence-free survival (RFS) estimates were generated using the Kaplan Meier method.

RESULTS

We identified 1675 patients who underwent BCS for DCIS (median age 56 [interquartile range (IQR) 49, 64]). Boost RT was employed in 68% of cases (n = 1146) and endocrine therapy in 32% (n = 536). At a median follow-up of 4.2 years (IQR 1.4, 7.0), we observed 61 locoregional recurrence events (56 local, 5 regional) and 21 deaths. Univariable logistic regression demonstrated that boost RT was more common among younger patients (p<0.001) with positive/close margins (p<0.001), and with larger tumors (p<0.001) of higher grade (p = 0.025). The 10-year RFS rate was 88.8% among those receiving a boost and 84.3% among those without a boost (p = 0.3), and neither univariable nor multivariable analyses revealed an association between boost RT and locoregional recurrence.

CONCLUSION

Among patients with DCIS who underwent BCS, use of a tumor bed boost was not associated with locoregional recurrence or RFS. Despite a preponderance of adverse features among the boost cohort, outcomes were similar to those not receiving a boost, suggesting that a boost may mitigate risk of recurrence among patients with high-risk features. Ongoing studies will elucidate the extent to which a tumor bed boost influences disease control rates.

A Multilevel Examination of Cognitive Control in Adolescents With Nonsuicidal Self-injury

Background

Nonsuicidal self-injury (NSSI), a transdiagnostic behavior, often emerges during adolescence. This study used the Research Domain Criteria approach to examine cognitive control (CC) with a focus on response inhibition and urgency relative to NSSI severity in adolescents.

Methods

One hundred thirty-eight adolescents, assigned female sex at birth, with a continuum of NSSI severity completed negative and positive urgency measurements (self-report), an emotional Go/NoGo task within negative and positive contexts (behavioral), and structural and functional imaging during resting state and task (brain metrics). Cortical thickness, subcortical volume, resting-state functional connectivity, and task activation focused on an a priori-defined CC network. Eighty-four participants had all these main measures. Correlations and stepwise model selection followed by multiple regression were used to examine the association between NSSI severity and multiunit CC measurements.

Results

Higher NSSI severity correlated with higher negative urgency and lower accuracy during positive no-inhibition (Go). Brain NSSI severity correlates varied across modalities and valence. For right medial prefrontal cortex and right caudate, higher NSSI severity correlated with greater negative but lower positive inhibition (NoGo) activation. The opposite pattern was observed for the right dorsolateral prefrontal cortex. Higher NSSI severity correlated with lower left dorsal anterior cingulate cortex (ACC) negative inhibition activation and thicker left dorsal ACC, yet it was correlated with higher right rostral ACC positive inhibition activation and thinner right rostral ACC, as well as lower CC network resting-state functional connectivity.

Conclusions

Findings revealed multifaceted signatures of NSSI severity across CC units of analysis, confirming the relevance of this domain in adolescent NSSI and illustrating how multimodal approaches can shed light on psychopathology.

Auditory oddball hypoactivation in schizophrenia

Individuals with schizophrenia (SZ) show aberrant activations, assessed via functional magnetic resonance imaging (fMRI), during auditory oddball tasks. However, associations with cognitive performance and genetic contributions remain unknown. This study compares individuals with SZ to healthy volunteers (HVs) using two cross-sectional data sets from multi-center brain imaging studies. It examines brain activation to auditory oddball targets, and their associations with cognitive domain performance, schizophrenia polygenic risk scores (PRS), and genetic variation (loci). Both sample 1 (137 SZ vs. 147 HV) and sample 2 (91 SZ vs. 98 HV), showed hypoactivation in SZ in the left-frontal pole, and right frontal orbital, frontal pole, paracingulate, intracalcarine, precuneus, supramarginal and hippocampal cortices, and right thalamus. In SZ, precuneus activity was positively related to cognitive performance. Schizophrenia PRS showed a negative correlation with brain activity in the right-supramarginal cortex. GWA analyses revealed significant single-nucleotide polymorphisms associated with right-supramarginal gyrus activity. RPL36 also predicted right-supramarginal gyrus activity. In addition to replicating hypoactivation for oddball targets in SZ, this study identifies novel relationships between regional activity, cognitive performance, and genetic loci that warrant replication, emphasizing the need for continued data sharing and collaborative efforts.

Risk of Radiation-Associated Secondary Malignancies among Patients with Breast Cancer Harboring TP53 Germline Variants

PURPOSE/OBJECTIVE(S)

Radiation-associated malignancies are rare and poorly understood. TP53 encodes a multifunctional protein that maintains genome integrity and is the most common somatically mutated gene in cancer. Germline pathogenic variants of TP53 predispose carriers to several cancers comprising the Li-Fraumeni syndrome. It is hypothesized that carriers are also at increased risk of radiotherapy (RT)-associated secondary malignancies; however, reports are mixed. We evaluated the risk of secondary malignancies after breast RT among patients with Li-Fraumeni syndrome.

MATERIALS/METHODS

This multi-institutional cohort study included carriers of TP53 germline variants who underwent surgical treatment for breast cancer between 1980 and 2020. Patients were stratified based on germline TP53 classification (pathogenic variants [PV] vs variants of uncertain significance [VUS]). The primary outcome of interest was the cumulative incidence risk of developing an in-field secondary cancer after radiotherapy for primary breast carcinoma.

RESULTS

Ninety-one patients (57 PV and 34 VUS) were evaluated with a median age of 36 years (interquartile range [IQR] 31, 42) and a median follow up of 7.9 years (IQR 4.7, 14.4). Among those with PV who received RT (n = 22), 4 secondary non-breast cancers developed in the radiation field (15-year cumulative incidence 19% [95% CI: 4-43%]), whereas, among those with PV who did not receive RT (n = 35), 0 secondary non-breast cancers were observed in the treated breast (15-year cumulative incidence 0%; p = 0.043). We observed 3 radiation-associated sarcomas among patients with PV who received RT (15-year risk 12% [95% CI 2-33%]) compared with 0 among those who did not receive RT (p = 0.08). No RT-associated sarcomas were observed among 18 patients with TP53 VUS who received RT. RT was not associated with overall survival, despite higher T and N breast cancer stage among those receiving RT (p = 0.33). As expected, patients with PV were more likely than those with VUS to develop any secondary cancer following breast cancer treatment (15-year risk: 54% [95% CI: 33-72%] vs. 14% [95% CI: 3-36%]).

CONCLUSION

Carriers of pathogenic variants of TP53 are at elevated risk of developing secondary malignancies after breast cancer treatment. This population is at particular risk of developing in-field secondary cancers following RT. This iatrogenic risk must be weighed against the anticipated therapeutic benefit of tumor control. Shared decision making is crucial in the radiotherapeutic management of breast cancer patients harboring the Li-Fraumeni syndrome.

Accelerated Partial Breast Irradiation (APBI) For HER2+ Early-Stage Breast Cancer

PURPOSE/OBJECTIVE(S)

Historically, HER2+ breast cancer exhibited poor outcomes and, hence, has not been well-studied among trials of accelerated partial breast irradiation (APBI). We hypothesized that in contemporary practice with effective HER2-targeted agents, patients with HER2+ breast cancer now have excellent disease control and survival outcomes when treated with adjuvant APBI.

MATERIALS/METHODS

Using a prospectively-maintained institutional database, we identified all HER2+ breast cancer patients treated with breast conserving surgery (BCS) and adjuvant APBI from 2000 - 2022. Salient clinicopathologic parameters were collected, as were receipt of systemic and endocrine therapies. All patients received external beam APBI to a total dose of 40Gy in 10 daily fractions over 2 weeks. We analyzed outcomes including local recurrence (LR), regional recurrence, distant recurrence, and death. Cumulative incidence functions were calculated to estimate the incidence of LR with the competing risk of death. All statistical analyses were performed in R version 4.2.2.

RESULTS

The study cohort comprised 52 patients with HER2+ breast cancer (median age 64 years; range 44-87). Nearly all had T1 tumors (98%; median size 15 mm; range 1 - 21 mm). Approximately 10% had multifocal disease, with one exhibiting suspicion for lymphovascular invasion. Most patients had ER+ disease (88%). All patients had negative final surgical margins. Nearly all underwent sentinel node biopsy (94%), with the remainder undergoing no surgical axillary evaluation. 42 (81%) received chemotherapy, 40 (77%) endocrine therapy, and 42 (81%) HER2-directed therapy, most commonly trastuzumab. At 143.8 person-years of follow-up (range 7 - 226 months for each patient), we observed two LR events, at 14 and 26 months, yielding a 2-year LR rate of 3.8%. No regional or distant recurrences were observed, nor were any contralateral invasive breast cancer events or breast-specific mortality events. Two deaths were noted in the cohort, both without evidence of disease.

CONCLUSION

Among a cohort of HER2+ early-stage breast cancer patients managed with BCS and APBI, we observed a 2-year LR rate of 3.8% with no regional or distant recurrences, and excellent overall survival. These findings merit longer term follow-up among larger cohorts, although are thus far consistent with the results of contemporary randomized trials of APBI unselected for HER2-status.

Relating white matter microstructure in theoretically defined addiction networks to relapse in alcohol use disorder

Theoretical models group maladaptive behaviors in addiction into neurocognitive domains such as incentive salience (IS), negative emotionality (NE), and executive functioning (EF). Alterations in these domains lead to relapse in alcohol use disorder (AUD). We examine whether microstructural measures in the white matter pathways supporting these domains are associated with relapse in AUD. Diffusion kurtosis imaging data were collected from 53 individuals with AUD during early abstinence. We used probabilistic tractography to delineate the fornix (IS), uncinate fasciculus (NE), and anterior thalamic radiation (EF) in each participant and extracted mean fractional anisotropy (FA) and kurtosis fractional anisotropy (KFA) within each tract. Binary (abstained vs. relapsed) and continuous (number of days abstinent) relapse measures were collected over a 4-month period. Across tracts, anisotropy measures were typically (i) lower in those that relapsed during the follow-up period and (ii) positively associated with the duration of sustained abstinence during the follow-up period. However, only KFA in the right fornix reached significance in our sample. The association between microstructural measures in these fiber tracts and treatment outcome in a small sample highlights the potential utility of the three-factor model of addiction and the role of white matter alterations in AUD.

Alterations in grey matter structure linked to frequency-specific cortico-subcortical connectivity in schizophrenia via multimodal data fusion

Schizophrenia (SZ) is a complex psychiatric disorder that is currently defined by symptomatic and behavioral, rather than biological, criteria. Neuroimaging is an appealing avenue for SZ biomarker development, as several neuroimaging-based studies comparing individuals with SZ to healthy controls (HC) have shown measurable group differences in brain structure, as well as functional brain alterations in both static and dynamic functional network connectivity (sFNC and dFNC, respectively). The recently proposed filter-banked connectivity (FBC) method extends the standard dFNC sliding-window approach to estimate FNC within an arbitrary number of distinct frequency bands. The initial implementation used a set of filters spanning the full connectivity spectral range, providing a unified approach to examine both sFNC and dFNC in a single analysis. Initial FBC results found that individuals with SZ spend more time in a less structured, more disconnected low-frequency (i.e., static) FNC state than HC, as well as preferential SZ occupancy in high-frequency connectivity states, suggesting a frequency-specific component underpinning the functional dysconnectivity observed in SZ. Building on these findings, we sought to link such frequency-specific patterns of FNC to covarying data-driven structural brain networks in the context of SZ. Specifically, we employ a multi-set canonical correlation analysis + joint independent components analysis (mCCA + jICA) data fusion framework to study the connection between grey matter volume (GMV) maps and FBC states across the full connectivity frequency spectrum. Our multimodal analysis identified two joint sources that captured co-varying patterns of frequency-specific functional connectivity and alterations in GMV with significant group differences in loading parameters between the SZ group and HC. The first joint source linked frequency-modulated connections between the subcortical and sensorimotor networks and GMV alterations in the frontal and temporal lobes, while the second joint source identified a relationship between low-frequency cerebellar-sensorimotor connectivity and structural changes in both the cerebellum and motor cortex. Together, these results show a strong connection between cortico-subcortical functional connectivity at both high and low frequencies and alterations in cortical GMV that may be relevant to the pathogenesis and pathophysiology of SZ.

Delayed cortical thinning in children and adolescents with prenatal alcohol exposure

BACKGROUND

Prenatal alcohol exposure (PAE) is associated with abnormalities in cortical structure and maturation, including cortical thickness (CT), cortical volume, and surface area. This study provides a longitudinal context for the developmental trajectory and timing of abnormal cortical maturation in PAE.

METHODS

We studied 35 children with PAE and 30 nonexposed typically developing children (Comparisons), aged 8-17 at enrollment, who were recruited from the University of Minnesota FASD Program. Participants were matched on age and sex. They underwent a formal evaluation of growth and dysmorphic facial features associated with PAE and completed cognitive testing. MRI data were collected on a Siemens Prisma 3T scanner. Two sessions, each including MRI scans and cognitive testing, were spaced approximately 15 months apart on average. Change in CT and performance on tests of executive function (EF) were examined.

RESULTS

Significant age-by-group (PAE vs. Comparison) linear interaction effects in CT were observed in the parietal, temporal, occipital, and insular cortices suggesting altered developmental trajectories in the PAE vs. Comparison groups. Results suggest a pattern of delayed cortical thinning in PAE, with the Comparison group showing more rapid thinning at younger ages and those with PAE showing accelerated thinning at older ages. Overall, children in the PAE group showed reduced cortical thinning across time relative to the Comparison participants. Symmetrized percent change (SPC) in CT in several regions was significantly correlated with EF performance at 15-month follow-up for the Comparison group but not the group with PAE.

CONCLUSIONS

Regional differences were seen longitudinally in the trajectory and timing of CT change in children with PAE, suggesting delayed cortical maturation and an atypical pattern of development compared with typically developing individuals. In addition, exploratory correlation analyses of SPC and EF performance suggest the presence of atypical brain-behavior relationships in PAE. The findings highlight the potential role of altered developmental timing of cortical maturation in contributing to long-term functional impairment in PAE.

Frontal tDCS reduces alcohol relapse rates by increasing connections from left dorsolateral prefrontal cortex to addiction networks

BACKGROUND

Brain-based interventions are needed to address persistent relapse in alcohol use disorder (AUD). Neuroimaging evidence suggests higher frontal connectivity as well as higher within-network connectivity of theoretically defined addiction networks are associated with reduced relapse rates and extended abstinence during follow-up periods.

OBJECTIVE

/Hypothesis: A longitudinal randomized double-blind sham-controlled clinical trial investigated whether a non-invasive neuromodulation intervention delivered during early abstinence can (i) modulate connectivity of addiction networks supporting abstinence and (ii) improve relapse rates.

HYPOTHESES

Active transcranial direct current stimulation (tDCS) will (i) increase connectivity of addiction networks known to support abstinence and (ii) reduce relapse rates.

METHODS

Short-term abstinent AUD participants (n = 60) were assigned to 5 days of either active tDCS or sham during cognitive training. Causal discovery analysis (CDA) examined the directional influence from left dorsolateral prefrontal cortex (LDLPFC, stimulation site) to addiction networks that support abstinence.

RESULTS

Active tDCS had an effect on the average strength of CDA-determined connectivity from LDLPFC to the incentive salience and negative emotionality addiction networks - increasing in the active tDCS group only. Active tDCS had an effect on relapse rates following the intervention, with lower probability of relapse in the active tDCS vs. sham. Active tDCS showed an unexpected sex-dependent effect on relapse rates.

CONCLUSION

Our results suggest that LDLPFC stimulation delivered during early abstinence has an effect on addiction networks supporting abstinence and on relapse rates. The unexpected sex-dependent neuromodulation effects need to be further examined in larger clinical trials.

Psychiatric Diagnoses and Treatment in Nine- to Ten-Year-Old Participants in the ABCD Study

Objective

Psychiatric disorders commonly emerge prior to adulthood. Identification and intervention may vary significantly across populations. We leveraged a large population-based study to estimate the prevalence of psychiatric disorders and treatments, and evaluate predictors of treatment, in children ages 9-10 in the United States.

Method

We analyzed cross-sectional data from the Adolescent Brain Cognitive Developmental (ABCD) Study. The Computerized Kiddie Schedule for Affective Disorders and Schizophrenia (KSADS-COMP) was used to estimate clinical diagnoses, and the Child Behavior Checklist (CBCL) was used to assess internalizing and externalizing psychopathology. Parents reported on prescription medications and other mental health interventions. Prevalence rates of KSADS diagnoses and treatments were calculated. Logistic regression analyses estimated associations between clinical and sociodemographic predictors (sex at birth, race, ethnicity, income, education, urbanicity) and treatments.

Results

The most common KSADS diagnoses were anxiety disorders, followed by attention deficit/hyperactivity disorder (ADHD) and oppositional defiant disorder. ADHD and depression diagnoses predicted stimulant and antidepressant medication use, respectively. Bipolar and ADHD diagnoses also predicted antidepressant medications, outpatient treatment and psychotherapy. The odds of reporting specific treatments varied by sex, ethnic and racial identities, urbanicity, and income.

Conclusion

Expected rates of KSADS-based psychiatric symptoms are present in the ABCD sample at ages 9-10, with treatment patterns broadly mapping onto psychopathology in expected ways. However, we observed important variations in reported treatment utilization across sociodemographic groups, likely reflecting societal and cultural influences. Findings are considered in the context of potential mental health disparities in U.S. children.

Multi-model order spatially constrained ICA reveals highly replicable group differences and consistent predictive results from resting data: A large N fMRI schizophrenia study

Brain functional networks identified from resting functional magnetic resonance imaging (fMRI) data have the potential to reveal biomarkers for brain disorders, but studies of complex mental illnesses such as schizophrenia (SZ) often yield mixed results across replication studies. This is likely due in part to the complexity of the disorder, the short data acquisition time, and the limited ability of the approaches for brain imaging data mining. Therefore, the use of analytic approaches which can both capture individual variability while offering comparability across analyses is highly preferred. Fully blind data-driven approaches such as independent component analysis (ICA) are hard to compare across studies, and approaches that use fixed atlas-based regions can have limited sensitivity to individual sensitivity. By contrast, spatially constrained ICA (scICA) provides a hybrid, fully automated solution that can incorporate spatial network priors while also adapting to new subjects. However, scICA has thus far only been used with a single spatial scale (ICA dimensionality, i.e., ICA model order). In this work, we present an approach using multi-objective optimization scICA with reference algorithm (MOO-ICAR) to extract subject-specific intrinsic connectivity networks (ICNs) from fMRI data at multiple spatial scales, which also enables us to study interactions across spatial scales. We evaluate this approach using a large N (N > 1,600) study of schizophrenia divided into separate validation and replication sets. A multi-scale ICN template was estimated and labeled, then used as input into scICA which was computed on an individual subject level. We then performed a subsequent analysis of multiscale functional network connectivity (msFNC) to evaluate the patient data, including group differences and classification. Results showed highly consistent group differences in msFNC in regions including cerebellum, thalamus, and motor/auditory networks. Importantly, multiple msFNC pairs linking different spatial scales were implicated. The classification model built on the msFNC features obtained up to 85% F1 score, 83% precision, and 88% recall, indicating the strength of the proposed framework in detecting group differences between schizophrenia and the control group. Finally, we evaluated the relationship of the identified patterns to positive symptoms and found consistent results across datasets. The results verified the robustness of our framework in evaluating brain functional connectivity of schizophrenia at multiple spatial scales, implicated consistent and replicable brain networks, and highlighted a promising approach for leveraging resting fMRI data for brain biomarker development.

Atypical developmental trajectories of white matter microstructure in prenatal alcohol exposure: Preliminary evidence from neurite orientation dispersion and density imaging

Introduction

Fetal alcohol spectrum disorder (FASD), a life-long condition resulting from prenatal alcohol exposure (PAE), is associated with structural brain anomalies and neurobehavioral differences. Evidence from longitudinal neuroimaging suggest trajectories of white matter microstructure maturation are atypical in PAE. We aimed to further characterize longitudinal trajectories of developmental white matter microstructure change in children and adolescents with PAE compared to typically-developing Controls using diffusion-weighted Neurite Orientation Dispersion and Density Imaging (NODDI).

Materials and methods

Participants: Youth with PAE (n = 34) and typically-developing Controls (n = 31) ages 8-17 years at enrollment. Participants underwent formal evaluation of growth and facial dysmorphology. Participants also completed two study visits (17 months apart on average), both of which involved cognitive testing and an MRI scan (data collected on a Siemens Prisma 3 T scanner). Age-related changes in the orientation dispersion index (ODI) and the neurite density index (NDI) were examined across five corpus callosum (CC) regions defined by tractography.

Results

While linear trajectories suggested similar overall microstructural integrity in PAE and Controls, analyses of symmetrized percent change (SPC) indicated group differences in the timing and magnitude of age-related increases in ODI (indexing the bending and fanning of axons) in the central region of the CC, with PAE participants demonstrating atypically steep increases in dispersion with age compared to Controls. Participants with PAE also demonstrated greater increases in ODI in the mid posterior CC (trend-level group difference). In addition, SPC in ODI and NDI was differentially correlated with executive function performance for PAE participants and Controls, suggesting an atypical relationship between white matter microstructure maturation and cognitive function in PAE.

Discussion

Preliminary findings suggest subtle atypicality in the timing and magnitude of age-related white matter microstructure maturation in PAE compared to typically-developing Controls. These findings add to the existing literature on neurodevelopmental trajectories in PAE and suggest that advanced biophysical diffusion modeling (NODDI) may be sensitive to biologically-meaningful microstructural changes in the CC that are disrupted by PAE. Findings of atypical brain maturation-behavior relationships in PAE highlight the need for further study. Further longitudinal research aimed at characterizing white matter neurodevelopmental trajectories in PAE will be important.

Reliability and clinical utility of spatially constrained estimates of intrinsic functional networks from very short fMRI scans

Resting-state functional network connectivity (rsFNC) has shown utility for identifying characteristic functional brain patterns in individuals with psychiatric and mood disorders, providing a promising avenue for biomarker development. However, several factors have precluded widespread clinical adoption of rsFNC diagnostics, namely a lack of standardized approaches for capturing comparable and reproducible imaging markers across individuals, as well as the disagreement on the amount of data required to robustly detect intrinsic connectivity networks (ICNs) and diagnostically relevant patterns of rsFNC at the individual subject level. Recently, spatially constrained independent component analysis (scICA) has been proposed as an automated method for extracting ICNs standardized to a chosen network template while still preserving individual variation. Leveraging the scICA methodology, which solves the former challenge of standardized neuroimaging markers, we investigate the latter challenge of identifying a minimally sufficient data length for clinical applications of resting-state fMRI (rsfMRI). Using a dataset containing rsfMRI scans of individuals with schizophrenia and controls (M = 310) as well as simulated rsfMRI, we evaluated the robustness of ICN and rsFNC estimates at both the subject- and group-level, as well as the performance of diagnostic classification, with respect to the length of the rsfMRI time course. We found individual estimates of ICNs and rsFNC from the full-length (5 min) reference time course were sufficiently approximated with just 3-3.5 min of data (r = 0.85, 0.88, respectively), and significant differences in group-average rsFNC could be sufficiently approximated with even less data, just 2 min (r = 0.86). These results from the shorter clinical data were largely consistent with the results from validation experiments using longer time series from both simulated (30 min) and real-world (14 min) datasets, in which estimates of subject-level FNC were reliably estimated with 3-5 min of data. Moreover, in the real-world data we found rsFNC and ICN estimates generated across the full range of data lengths (0.5-14 min) more reliably matched those generated from the first 5 min of scan time than those generated from the last 5 min, suggesting increased influence of "late scan" noise factors such as fatigue or drowsiness may limit the reliability of FNC from data collected after 10+ min of scan time, further supporting the notion of shorter scans. Lastly, a diagnostic classification model trained on just 2 min of data retained 97%-98% classification accuracy relative to that of the full-length reference model. Our results suggest that, when decomposed with scICA, rsfMRI scans of just 2-5 min show good clinical utility without significant loss of individual FNC information of longer scan lengths.

Identifying body awareness-related brain network changes after Spring Forest Qigong™ practice or P.Volve low-intensity exercise in adults with chronic low back pain: a feasibility Phase I Randomized Clinical Trial

Background

Chronic low back pain (cLBP) affects the quality of life of 52 million Americans and leads to an enormous personal and economic burden. A multidisciplinary approach to cLBP management is recommended. Since medication has limited efficacy and there are mounting concerns about opioid addiction, the American College of Physicians and American Pain Society recommend non-pharmacological interventions, such as mind and body approaches (e.g., Qigong, yoga, Tai Chi) before prescribing medications. Of those, Qigong practice might be most accessible given its gentle movements and because it can be performed standing, sitting, or lying down. The three available Qigong studies in adults with cLBP showed that Qigong reduced pain more than waitlist and equally well than exercise. Yet, the duration and/or frequency of Qigong practice were low (<12 weeks or less than 3x/week). The objectives of this study were to investigate the feasibility of practicing Spring Forest Qigong™ or performing P.Volve low intensity exercises 3x/week for 12 weeks, feasibility of recruitment, data collection, delivery of the intervention as intended, as well as identify estimates of efficacy on brain function and behavioral outcomes after Qigong practice or exercise. To our knowledge, this is the first study investigating the feasibility of the potential effect of Qigong on brain function in adults with cLBP.

Methods

We conducted a feasibility Phase I Randomized Clinical Trial. Of the 36 adults with cLBP recruited between January 2020 and June 2021, 32 were enrolled and randomized to either 12 weeks of remote Spring Forest Qigong™ practice or remote P.Volve low-intensity exercises. Participants practiced at least 3x/week for 41min/session with online videos. Our main outcome measures were the Numeric Pain Rating Scale (highest, average, and lowest cLBP pain intensity levels in the prior week), assessed weekly and fMRI data (resting-state and task-based fMRI tasks: pain imagery, kinesthetic imagery of a Qigong movement, and robot-guided shape discrimination). We compared baseline resting-state connectivity and brain activation during fMRI tasks in adults with cLBP with data from a healthy control group (n=28) acquired in a prior study. Secondary outcomes included measures of function, disability, body awareness, kinesiophobia, balance, self-efficacy, core muscle strength, and ankle proprioceptive acuity with a custom-build device.

Results

Feasibility of the study design and methods was demonstrated with 30 participants completing the study (94% retention) and reporting high satisfaction with the programs; 96% adherence to P.Volve low-intensity exercises, and 128% of the required practice intensity for Spring Forest Qigong™ practice. Both groups saw promising reductions in low back pain (effect sizes Cohen's d =1.01-2.22) and in most other outcomes ( d =0.90-2.33). Markers of ankle proprioception were not significantly elevated in the cLBP group after the interventions. Brain imaging analysis showed weaker parietal operculum and insula network connectivity in adults with cLBP (n=26), compared to data from a healthy control group (n=28). The pain imagery task elicited lower brain activation of insula, parietal operculum, angular gyrus and supramarginal gyrus at baseline in adults with cLBP than in healthy adults. Adults with cLBP had lower precentral gyrus activation than healthy adults for the Qigong movement and robot task at baseline. Pre-post brain function changes showed individual variability: Six (out of 13) participants in the Qigong group showed increased activation in the parietal operculum, angular gyrus, supramarginal gyrus, and precentral gyrus during the Qigong fMRI task.

Interpretation

Our data indicate the feasibility and acceptability of using Spring Forest Qigong™ practice or P.Volve low-intensity exercises for cLBP relief showing promising results in terms of pain relief and associated symptoms. Our brain imaging results indicated brain function improvements after 12 weeks of Qigong practice in some participants, pointing to the need for further investigation in larger studies.

Trial registration number

ClinicalTrials.gov: NCT04164225 .

Five negative symptom domains are differentially associated with resting state amplitude of low frequency fluctuations in Schizophrenia

This study examined associations between resting-state amplitude of low frequency fluctuations (ALFF) and negative symptoms represented by total scores, second-order dimension (motivation and pleasure, expressivity), and first-order domain (anhedonia, avolition, asociality, alogia, blunted affect) factor scores in schizophrenia (n = 57). Total negative symptom scores showed positive associations with ALFF in temporal and frontal brain regions. Negative symptom domain scores showed predominantly stronger associations with regional ALFF compared to total scores, suggesting domain scores may better map to neural signatures than total scores. Improving our understanding of the neuropathology underlying negative symptoms may aid in addressing this unmet therapeutic need in schizophrenia.

Identifying Body Awareness-Related Brain Network Changes after Cognitive Multisensory Rehabilitation for Neuropathic Pain Relief in Adults with Spinal Cord Injury: Delayed Treatment arm Phase I Randomized Controlled Trial

Background

Neuropathic pain after spinal cord injury (SCI) is notoriously hard to treat. Mechanisms of neuropathic pain are unclear, which makes finding effective treatments challenging. Prior studies have shown that adults with SCI have body awareness deficits. Recent imaging studies, including ours, point to the parietal operculum and insula as key areas for both pain perception and body awareness. Cognitive multisensory rehabilitation (CMR) is a physical therapy approach that helps improve body awareness for pain reduction and sensorimotor recovery. Based on our prior brain imaging work in CMR in stroke, we hypothesized that improving body awareness through restoring parietal operculum network connectivity leads to neuropathic pain relief and improved sensorimotor and daily life function in adults with SCI. Thus, the objectives of this study were to (1) determine baseline differences in resting-state and task-based functional magnetic resonance imaging (fMRI) brain function in adults with SCI compared to healthy controls and (2) identify changes in brain function and behavioral pain and pain-associated outcomes in adults with SCI after CMR.

Methods

Healthy adults underwent a one-time MRI scan and completed questionnaires. We recruited community-dwelling adults with SCI-related neuropathic pain, with complete or incomplete SCI >3 months, and highest neuropathic pain intensity level of >3 on the Numeric Pain Rating Scale (NPRS). Participants with SCI were randomized into two groups, according to a delayed treatment arm phase I randomized controlled trial (RCT): Group A immediately received CMR intervention, 3x/week, 45 min/session, followed by a 6-week and 1-year follow-up. Group B started with a 6-week observation period, then 6 weeks of CMR, and a 1-year follow-up. Highest, average, and lowest neuropathic pain intensity levels were assessed weekly with the NPRS as primary outcome. Other primary outcomes (fMRI resting-state and functional tasks; sensory and motor function with the INSCI AIS exam), as well as secondary outcomes (mood, function, spasms, and other SCI secondary conditions), were assessed at baseline, after the first and second 6-week period. The INSCI AIS exam and questionnaires were repeated at the 1-year follow-up.

Findings

Thirty-six healthy adults and 28 adults with SCI were recruited between September 2020 and August 2021, and of those, 31 healthy adults and 26 adults with SCI were enrolled in the study. All 26 participants with SCI completed the intervention and pre-post assessments. There were no study-related adverse events. Participants were 52±15 years of age, and 1-56 years post-SCI. During the observation period, group B did not show any reductions in neuropathic pain and did not have any changes in sensation or motor function (INSCI ASIA exam). However, both groups experienced a significant reduction in neuropathic pain after the 6-week CMR intervention. Their highest level of neuropathic pain of 7.81±1.33 on the NPRS at baseline was reduced to 2.88±2.92 after 6 weeks of CMR. Their change scores were 4.92±2.92 (large effect size Cohen's d =1.68) for highest neuropathic pain, 4.12±2.23 ( d =1.85) for average neuropathic pain, and 2.31±2.07 ( d =1.00) for lowest neuropathic pain. Nine participants out of 26 were pain-free after the intervention (34.62%). The results of the INSCI AIS testing also showed significant improvements in sensation, muscle strength, and function after 6 weeks of CMR. Their INSCI AIS exam increased by 8.81±5.37 points ( d =1.64) for touch sensation, 7.50±4.89 points ( d =1.53) for pin prick sensation, and 3.87±2.81 ( d =1.38) for lower limb muscle strength. Functional improvements after the intervention included improvements in balance for 17 out of 18 participants with balance problems at baseline; improved transfers for all of them and a returned ability to stand upright with minimal assistance in 12 out of 20 participants who were unable to stand at baseline. Those improvements were maintained at the 1-year follow-up. With regard to brain imaging, we confirmed that the resting-state parietal operculum and insula networks had weaker connections in adults with SCI-related neuropathic pain (n=20) compared to healthy adults (n=28). After CMR, stronger resting-state parietal operculum network connectivity was found in adults with SCI. Also, at baseline, as expected, right toe sensory stimulation elicited less brain activation in adults with SCI (n=22) compared to healthy adults (n=26). However, after CMR, there was increased brain activation in relevant sensorimotor and parietal areas related to pain and mental body representations (i.e., body awareness and visuospatial body maps) during the toe stimulation fMRI task. These brain function improvements aligned with the AIS results of improved touch sensation, including in the feet.

Interpretation

Adults with chronic SCI had significant neuropathic pain relief and functional improvements, attributed to the recovery of sensation and movement after CMR. The results indicate the preliminary efficacy of CMR for restoring function in adults with chronic SCI. CMR is easily implementable in current physical therapy practice. These encouraging impressive results pave the way for larger randomized clinical trials aimed at testing the efficacy of CMR to alleviate neuropathic pain in adults with SCI.

Clinical Trial registration

ClinicalTrials.gov Identifier: NCT04706208.

Funding

AIRP2-IND-30: Academic Investment Research Program (AIRP) University of Minnesota School of Medicine. National Center for Advancing Translational Sciences of the National Institutes of Health Award Number UL1TR002494; the Biotechnology Research Center: P41EB015894, the National Institute of Neurological Disorders & Stroke Institutional Center Core Grants to Support Neuroscience Research: P30 NS076408; and theHigh-Performancee Connectome Upgrade for Human 3T MR Scanner: 1S10OD017974.

Sex and age variations in the impact of puberty on cortical thickness and associations with internalizing symptoms and suicidal ideation in early adolescence

PURPOSE

The childhood-to-adolescence transition is a notable period of change including pubertal development, neurodevelopment, and psychopathology onset, that occurs in divergent patterns between sexes. This study examined the effects of sex and puberty on cortical thickness (CT) in children and explored whether CT changes over time related to emergence of psychopathology in early adolescence.

METHODS

We used longitudinal data (baseline ages 9-10 and Year 2 [Y2] ages 11-12) from the ABCD Study (n = 9985). Linear and penalized function-on-function regressions modeled the impact of puberty, as it interacts with sex, on CT. Focusing on regions that showed sex differences, linear and logistic regressions modeled associations between change in CT and internalizing problems and suicide ideation.

RESULTS

We identified significant sex differences in the inverse relation between puberty and CT in fifteen primarily posterior brain regions. Nonlinear pubertal effects across age were identified in the fusiform, isthmus cingulate, paracentral, and precuneus. All effects were stronger for females relative to males during this developmental window. We did not identify associations between CT change and early adolescent clinical outcomes.

CONCLUSION

During this age range, puberty is most strongly associated with regional changes in CT in females, which may have implications for the later emergence of psychopathology.

A method for estimating and characterizing explicitly nonlinear dynamic functional network connectivity in resting-state fMRI data

The past 10 years have seen an explosion of approaches that focus on the study of time-resolved change in functional connectivity (FC). FC characterization among networks at a whole-brain level is frequently termed functional network connectivity (FNC). Time-resolved or dynamic functional network connectivity (dFNC) focuses on the estimation of transient, recurring, whole-brain patterns of FNC. While most approaches in this area have attempted to capture dynamic linear correlation, we are particularly interested in whether explicitly nonlinear relationships, above and beyond linear, are present and contain unique information. This study thus proposes an approach to assess explicitly nonlinear dynamic functional network connectivity (EN dFNC) derived from the relationship among independent component analysis time courses. Linear relationships were removed at each time point to evaluate, typically ignored, explicitly nonlinear dFNC using normalized mutual information (NMI). Simulations showed the proposed method estimated explicitly nonlinearity over time, even within relatively short windows of data. We then, applied our approach on 151 schizophrenia patients, and 163 healthy controls fMRI data and found three unique, highly structured, mostly long-range, functional states that also showed significant group differences. In particular, explicitly nonlinear relationships tend to be more widespread than linear ones. Results also highlighted a state with long range connections to the visual domain, which were significantly reduced in schizophrenia. Overall, this work suggests that quantifying EN dFNC may provide a complementary and potentially valuable tool for studying brain function by exposing relevant variation that is typically ignored.

Long-term follow-up of a randomized controlled trial of choline for neurodevelopment in fetal alcohol spectrum disorder: corpus callosum white matter microstructure and neurocognitive outcomes

BACKGROUND

Fetal alcohol spectrum disorder (FASD) is a lifelong condition. Early interventions targeting core neurocognitive deficits have the potential to confer long-term neurodevelopmental benefits. Time-targeted choline supplementation is one such intervention that has been shown to provide neurodevelopmental benefits that emerge with age during childhood. We present a long-term follow-up study evaluating the neurodevelopmental effects of early choline supplementation in children with FASD approximately 7 years on average after an initial efficacy trial.

METHODS

The initial study was a randomized, double-blind, placebo-controlled trial of choline vs. placebo in 2.5 to 5 year olds with FASD. Participants in this long-term follow-up study include 18 children (9 placebo; 9 choline) seen 7 years on average following initial trial completion. The mean age at follow-up was 11.0 years old. Diagnoses were 28% fetal alcohol syndrome (FAS), 28% partial FAS, and 44% alcohol-related neurodevelopmental disorder. The follow-up included measures of executive functioning and an MRI scan.

RESULTS

Children who received choline had better performance on several tasks of lower-order executive function (e.g., processing speed) and showed higher white matter microstructure organization (i.e., greater axon coherence) in the splenium of the corpus callosum compared to the placebo group.

CONCLUSIONS

These preliminary findings, although exploratory at this stage, highlight potential long-term benefits of choline as a neurodevelopmental intervention for FASD and suggest that choline may affect white matter development, representing a potential target of choline in this population.

TRIAL REGISTRATION

Prior to enrollment, this trial was registered with clinicaltrials.gov ( NCT01149538 ) on June 23, 2010.

Nonlinear functional network connectivity in resting functional magnetic resonance imaging data

In this work, we focus on explicitly nonlinear relationships in functional networks. We introduce a technique using normalized mutual information (NMI) that calculates the nonlinear relationship between different brain regions. We demonstrate our proposed approach using simulated data and then apply it to a dataset previously studied by Damaraju et al. This resting-state fMRI data included 151 schizophrenia patients and 163 age- and gender-matched healthy controls. We first decomposed these data using group independent component analysis (ICA) and yielded 47 functionally relevant intrinsic connectivity networks. Our analysis showed a modularized nonlinear relationship among brain functional networks that was particularly noticeable in the sensory and visual cortex. Interestingly, the modularity appears both meaningful and distinct from that revealed by the linear approach. Group analysis identified significant differences in explicitly nonlinear functional network connectivity (FNC) between schizophrenia patients and healthy controls, particularly in the visual cortex, with controls showing more nonlinearity (i.e., higher normalized mutual information between time courses with linear relationships removed) in most cases. Certain domains, including subcortical and auditory, showed relatively less nonlinear FNC (i.e., lower normalized mutual information), whereas links between the visual and other domains showed evidence of substantial nonlinear and modular properties. Overall, these results suggest that quantifying nonlinear dependencies of functional connectivity may provide a complementary and potentially important tool for studying brain function by exposing relevant variation that is typically ignored. Beyond this, we propose a method that captures both linear and nonlinear effects in a "boosted" approach. This method increases the sensitivity to group differences compared to the standard linear approach, at the cost of being unable to separate linear and nonlinear effects.

Multimodel Order Independent Component Analysis: A Data-Driven Method for Evaluating Brain Functional Network Connectivity Within and Between Multiple Spatial Scales

Background: While functional connectivity is widely studied, there has been little work studying functional connectivity at different spatial scales. Likewise, the relationship of functional connectivity between spatial scales is unknown. Methods: We proposed an independent component analysis (ICA)-based approach to capture information at multiple-model orders (component numbers), and to evaluate functional network connectivity (FNC) both within and between model orders. We evaluated the approach by studying group differences in the context of a study of resting-state functional magnetic resonance imaging (rsfMRI) data collected from schizophrenia (SZ) individuals and healthy controls (HC). The predictive ability of FNC at multiple spatial scales was assessed using support vector machine-based classification. Results: In addition to consistent predictive patterns at both multiple-model orders and single-model orders, unique predictive information was seen at multiple-model orders and in the interaction between model orders. We observed that the FNC between model orders 25 and 50 maintained the highest predictive information between HC and SZ. Results highlighted the predictive ability of the somatomotor and visual domains both within and between model orders compared with other functional domains. Also, subcortical-somatomotor, temporal-somatomotor, and temporal-subcortical FNCs had relatively high weights in predicting SZ. Conclusions: In sum, multimodel order ICA provides a more comprehensive way to study FNC, produces meaningful and interesting results, which are applicable to future studies. We shared the spatial templates from this work at different model orders to provide a reference for the community, which can be leveraged in regression-based or fully automated (spatially constrained) ICA approaches. Impact statement Multimodel order independent component analysis (ICA) provides a comprehensive way to study brain functional network connectivity within and between multiple spatial scales, highlighting findings that would have been ignored in single-model order analysis. This work expands upon and adds to the relatively new literature on resting functional magnetic resonance imaging-based classification and prediction. Results highlighted the differentiating power of specific intrinsic connectivity networks on classifying brain disorders of schizophrenia patients and healthy participants, at different spatial scales. The spatial templates from this work provide a reference for the community, which can be leveraged in regression-based or fully automated ICA approaches.

The resting-state causal human connectome is characterized by hub connectivity of executive and attentional networks

We demonstrate a data-driven approach for calculating a "causal connectome" of directed connectivity from resting-state fMRI data using a greedy adjacency search and pairwise non-Gaussian edge orientations. We used this approach to construct n = 442 causal connectomes. These connectomes were very sparse in comparison to typical Pearson correlation-based graphs (roughly 2.25% edge density) yet were fully connected in nearly all cases. Prominent highly connected hubs of the causal connectome were situated in attentional (dorsal attention) and executive (frontoparietal and cingulo-opercular) networks. These hub networks had distinctly different connectivity profiles: attentional networks shared incoming connections with sensory regions and outgoing connections with higher cognitive networks, while executive networks primarily connected to other higher cognitive networks and had a high degree of bidirected connectivity. Virtual lesion analyses accentuated these findings, demonstrating that attentional and executive hub networks are points of critical vulnerability in the human causal connectome. These data highlight the central role of attention and executive control networks in the human cortical connectome and set the stage for future applications of data-driven causal connectivity analysis in psychiatry.

Tralesinidase alfa enzyme replacement therapy prevents disease manifestations in a canine model of mucopolysaccharidosis type IIIB

Mucopolysaccharidosis type IIIB (MPS IIIB; Sanfilippo syndrome B; OMIM #252920) is a lethal, pediatric, neuropathic, autosomal recessive, and lysosomal storage disease with no approved therapy. Patients are deficient in the activity of N-acetyl-alpha-glucosaminidase (NAGLU; EC 3.2.150), necessary for normal lysosomal degradation of the glycosaminoglycan heparan sulfate (HS). Tralesinidase alfa (TA), a fusion protein comprised of recombinant human NAGLU and a modified human insulin-like growth factor 2, is in development as an enzyme replacement therapy that is administered via intracerebroventricular (ICV) infusion, thus circumventing the blood brain barrier. Previous studies have confirmed ICV infusion results in widespread distribution of TA throughout the brains of mice and nonhuman primates. We assessed the long-term tolerability, pharmacology, and clinical efficacy of TA in a canine model of MPS IIIB over a 20-month study. Long-term administration of TA was well tolerated as compared with administration of vehicle. TA was widely distributed across brain regions, which was confirmed in a follow-up 8-week pharmacokinetic/pharmacodynamic study. MPS IIIB dogs treated for up to 20 months had near-normal levels of HS and nonreducing ends of HS in cerebrospinal fluid and central nervous system (CNS) tissues. TA-treated MPS IIIB dogs performed better on cognitive tests and had improved CNS pathology and decreased cerebellar volume loss relative to vehicle-treated MPS IIIB dogs. These findings demonstrate the ability of TA to prevent or limit the biochemical, pathologic, and cognitive manifestations of canine MPS IIIB disease, thus providing support of its potential long-term tolerability and efficacy in MPS IIIB subjects.

Resting Hypoconnectivity of Theoretically Defined Addiction Networks during Early Abstinence Predicts Subsequent Relapse in Alcohol Use Disorder

Theoretical models of addiction suggest that alterations in addiction domains including incentive salience, negative emotionality, and executive control lead to relapse in alcohol use disorder (AUD). To determine whether the functional organization of neural networks underlying these domains predict subsequent relapse, we generated theoretically defined addiction networks. We collected resting functional magnetic resonance imaging data from 45 individuals with AUD during early abstinence (number of days abstinent M = 25.40, SD = 16.51) and calculated the degree of resting-state functional connectivity (RSFC) within these networks. Regression analyses determined whether the RSFC strength in domain-defined addiction networks measured during early abstinence predicted subsequent relapse (dichotomous or continuous relapse metrics). RSFC within each addiction network measured during early abstinence was significantly lower in those that relapsed (vs. abstained) and predicted subsequent time to relapse. Lower incentive salience RSFC during early abstinence increased the odds of relapsing. Neither RSFC in a control network nor clinical self-report measures predicted relapse. The association between low incentive salience RSFC and faster relapse highlights the need to design timely interventions that enhance RSFC in AUD individuals at risk of relapsing faster.

Multi-spatial-scale dynamic interactions between functional sources reveal sex-specific changes in schizophrenia

We introduce an extension of independent component analysis (ICA), called multiscale ICA, and design an approach to capture dynamic functional source interactions within and between multiple spatial scales. Multiscale ICA estimates functional sources at multiple spatial scales without imposing direct constraints on the size of functional sources, overcomes the limitation of using fixed anatomical locations, and eliminates the need for model-order selection in ICA analysis. We leveraged this approach to study sex-specific and sex-common connectivity patterns in schizophrenia. Results show dynamic reconfiguration and interaction within and between multi-spatial scales. Sex-specific differences occur (a) within the subcortical domain, (b) between the somatomotor and cerebellum domains, and (c) between the temporal domain and several others, including the subcortical, visual, and default mode domains. Most of the sex-specific differences belong to between-spatial-scale functional interactions and are associated with a dynamic state with strong functional interactions between the visual, somatomotor, and temporal domains and their anticorrelation patterns with the rest of the brain. We observed significant correlations between multi-spatial-scale functional interactions and symptom scores, highlighting the importance of multiscale analyses to identify potential biomarkers for schizophrenia. As such, we recommend such analyses as an important option for future functional connectivity studies.

Path Analysis: A Method to Estimate Altered Pathways in Time-varying Graphs of Neuroimaging Data

Graph-theoretical methods have been widely used to study human brain networks in psychiatric disorders. However, the focus has primarily been on global graphic metrics with little attention to the information contained in paths connecting brain regions. Details of disruption of these paths may be highly informative for understanding disease mechanisms. To detect the absence or addition of multistep paths in the patient group, we provide an algorithm estimating edges that contribute to these paths with reference to the control group. We next examine where pairs of nodes were connected through paths in both groups by using a covariance decomposition method. We apply our method to study resting-state fMRI data in schizophrenia versus controls. Results show several disconnectors in schizophrenia within and between functional domains, particularly within the default mode and cognitive control networks. Additionally, we identify new edges generating additional paths. Moreover, although paths exist in both groups, these paths take unique trajectories and have a significant contribution to the decomposition. The proposed path analysis provides a way to characterize individuals by evaluating changes in paths, rather than just focusing on the pairwise relationships. Our results show promise for identifying path-based metrics in neuroimaging data.

Differential extrinsic brain network connectivity and social cognitive task-specific demands in Autism Spectrum Disorder (ASD)

Few studies have used task-based functional connectivity (FC) magnetic resonance imaging to examine emotion-processing during the critical neurodevelopmental period of adolescence in Autism Spectrum Disorders (ASDs). Moreover, task designs with pervasive confounds (e.g., lack of appropriate controls) persist because they activate neural circuits of interest reliably. As an alternative approach to "subtracting" activity from putative control conditions, we propose examining FC across an entire task run. By pivoting our analysis and interpretation of existing paradigms, we may better understand neural response to non-focal instances of socially-relevant stimuli that approximate real-world experiences more closely. Hence, using two well-established affective tasks (face-viewing, face-matching) with diverging social-cognitive demands, we investigated extrinsic FC from amygdala (AMG) and fusiform gyrus (FG) seeds in typically-developing (TD; N = 17) and ASD (N = 17) male adolescents (10-18 yo) and clinical correlations (Social Communication Questionnaire; SCQ) of group FC differences. Participant data (4TD, 6ASD) with excessive head-motion were excluded from final analysis. Direct between-group comparisons revealed significant differences between groups for neural response but not task performance (accuracy, reaction time). During face-viewing, we found greater FC from AMG and FG seeds for ASD participants (ASD > TD) in regions involved in the Default Mode and Fronto-Parietal Task Control Networks. During face-matching, we found greater FC from AMG and FG seeds for TD participants (TD > ASD), in regions associated with the Salience, Dorsal Attention, and Somatosensory Networks. SCQ scores correlated positively with regions with group differences on the face-viewing task and negatively with regions identified for the face-matching task. Task-dependent group differences in FC despite comparable behavioral performance suggest that high-functioning ASD may wield compensatory strategies; clinically-correlated FC patterns may associate with differential task-demands, ecological validity, and context-dependent processing. Employing this novel approach may further the development of targeted therapeutic interventions informed by individual differences in the highly heterogeneous ASD population.

Quantitative brain MRI morphology in severe and attenuated forms of mucopolysaccharidosis type I

OBJECTIVE

To assess our hypothesis that brain macrostructure is different in individuals with mucopolysaccharidosis type I (MPS I) and healthy controls (HC), we conducted a comprehensive multicenter study using a uniform quantitative magnetic resonance imaging (qMRI) protocol, with analyses that account for the effects of disease phenotype, age, and cognition.

METHODS

Brain MRIs in 23 individuals with attenuated (MPS IA) and 38 with severe MPS I (MPS IH), aged 4-25 years, enrolled under the study protocol NCT01870375, were compared to 98 healthy controls.

RESULTS

Cortical and subcortical gray matter, white matter, corpus callosum, ventricular and choroid plexus volumes in MPS I significantly differed from HC. Thicker cortex, lower white matter and corpus callosum volumes were already present at the youngest MPS I participants aged 4-5 years. Age-related differences were observed in both MPS I groups, but most markedly in MPS IH, particularly in cortical gray matter metrics. IQ scores were inversely associated with ventricular volume in both MPS I groups and were positively associated with cortical thickness only in MPS IA.

CONCLUSIONS

Quantitatively-derived MRI measures distinguished MPS I participants from HC as well as severe from attenuated forms. Age-related neurodevelopmental trajectories in both MPS I forms differed from HC. The extent to which brain structure is altered by disease, potentially spared by treatment, and how it relates to neurocognitive dysfunction needs further exploration.

A meta-analysis of deep brain structural shape and asymmetry abnormalities in 2,833 individuals with schizophrenia compared with 3,929 healthy volunteers via the ENIGMA Consortium

Schizophrenia is associated with widespread alterations in subcortical brain structure. While analytic methods have enabled more detailed morphometric characterization, findings are often equivocal. In this meta-analysis, we employed the harmonized ENIGMA shape analysis protocols to collaboratively investigate subcortical brain structure shape differences between individuals with schizophrenia and healthy control participants. The study analyzed data from 2,833 individuals with schizophrenia and 3,929 healthy control participants contributed by 21 worldwide research groups participating in the ENIGMA Schizophrenia Working Group. Harmonized shape analysis protocols were applied to each site's data independently for bilateral hippocampus, amygdala, caudate, accumbens, putamen, pallidum, and thalamus obtained from T1-weighted structural MRI scans. Mass univariate meta-analyses revealed more-concave-than-convex shape differences in the hippocampus, amygdala, accumbens, and thalamus in individuals with schizophrenia compared with control participants, more-convex-than-concave shape differences in the putamen and pallidum, and both concave and convex shape differences in the caudate. Patterns of exaggerated asymmetry were observed across the hippocampus, amygdala, and thalamus in individuals with schizophrenia compared to control participants, while diminished asymmetry encompassed ventral striatum and ventral and dorsal thalamus. Our analyses also revealed that higher chlorpromazine dose equivalents and increased positive symptom levels were associated with patterns of contiguous convex shape differences across multiple subcortical structures. Findings from our shape meta-analysis suggest that common neurobiological mechanisms may contribute to gray matter reduction across multiple subcortical regions, thus enhancing our understanding of the nature of network disorganization in schizophrenia.

ENIGMA + COINSTAC: Improving Findability, Accessibility, Interoperability, and Re-usability

The FAIR principles, as applied to clinical and neuroimaging data, reflect the goal of making research products Findable, Accessible, Interoperable, and Reusable. The use of the Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymized Computation (COINSTAC) platform in the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium combines the technological approach of decentralized analyses with the sociological approach of sharing data. In addition, ENIGMA + COINSTAC provides a platform to facilitate the use of machine-actionable data objects. We first present how ENIGMA and COINSTAC support the FAIR principles, and then showcase their integration with a decentralized meta-analysis of sex differences in negative symptom severity in schizophrenia, and finally present ongoing activities and plans to advance FAIR principles in ENIGMA + COINSTAC. ENIGMA and COINSTAC currently represent efforts toward improved Access, Interoperability, and Reusability. We highlight additional improvements needed in these areas, as well as future connections to other resources for expanded Findability.

The psychosis human connectome project: An overview

Investigations within the Human Connectome Project have expanded to include studies focusing on brain disorders. This paper describes one of the investigations focused on psychotic psychopathology: The psychosis Human Connectome Project (P-HCP). The data collected as part of this project were multimodal and derived from clinical assessments of psychopathology, cognitive assessments, instrument-based motor assessments, blood specimens, and magnetic resonance imaging (MRI) data. The dataset will be made publicly available through the NIMH Data Archive. In this report we provide specific information on how the sample of participants was obtained and characterized and describe the experimental tasks and procedures used to probe neural functions involved in psychotic disorders that may also mark genetic liability for psychotic psychopathology. Our goal in this paper is to outline the data acquisition process so that researchers intending to use these publicly available data can plan their analyses. MRI data described in this paper are limited to data acquired at 3 Tesla. A companion paper describes the study's 7 Tesla image acquisition protocol in detail, which is focused on visual perceptual functions in psychotic psychopathology.

Reward Processing in Novelty Seekers: A Transdiagnostic Psychiatric Imaging Biomarker

BACKGROUND

Dysfunctional reward processing is implicated in multiple mental disorders. Novelty seeking (NS) assesses preference for seeking novel experiences, which is linked to sensitivity to reward environmental cues.

METHODS

A subset of 14-year-old adolescents (IMAGEN) with the top 20% ranked high-NS scores was used to identify high-NS-associated multimodal components by supervised fusion. These features were then used to longitudinally predict five different risk scales for the same and unseen subjects (an independent dataset of subjects at 19 years of age that was not used in predictive modeling training at 14 years of age) (within IMAGEN, n ≈1100) and even for the corresponding symptom scores of five types of patient cohorts (non-IMAGEN), including drinking (n = 313), smoking (n = 104), attention-deficit/hyperactivity disorder (n = 320), major depressive disorder (n = 81), and schizophrenia (n = 147), as well as to classify different patient groups with diagnostic labels.

RESULTS

Multimodal biomarkers, including the prefrontal cortex, striatum, amygdala, and hippocampus, associated with high NS in 14-year-old adolescents were identified. The prediction models built on these features are able to longitudinally predict five different risk scales, including alcohol drinking, smoking, hyperactivity, depression, and psychosis for the same and unseen 19-year-old adolescents and even predict the corresponding symptom scores of five types of patient cohorts. Furthermore, the identified reward-related multimodal features can classify among attention-deficit/hyperactivity disorder, major depressive disorder, and schizophrenia with an accuracy of 87.2%.

CONCLUSIONS

Adolescents with higher NS scores can be used to reveal brain alterations in the reward-related system, implicating potential higher risk for subsequent development of multiple disorders. The identified high-NS-associated multimodal reward-related signatures may serve as a transdiagnostic neuroimaging biomarker to predict disease risks or severity.

Effect of SSRIs on Resting-State Functional Brain Networks in Adolescents with Major Depressive Disorder

Investigation of brain changes in functional connectivity and functional network topology from receiving 8-week selective serotonin reuptake inhibitor (SSRI) treatments is conducted in 12 unmedicated adolescents with major depressive disorder (MDD) by using wavelet-filtered resting-state functional magnetic resonance imaging (fMRI). Changes are observed in frontal-limbic, temporal, and default mode networks. In particular, topological analysis shows, at the global scale and in the 0.12–0.25 Hz band, that the normalized clustering coefficient and smallworldness of brain networks decreased after treatment. Regional changes in clustering coefficient and efficiency were observed in the bilateral caudal middle frontal gyrus, rostral middle frontal gyrus, superior temporal gyrus, left pars triangularis, putamen, and right superior frontal gyrus. Furthermore, changes of nodal centrality and changes of connectivity associated with these frontal and temporal regions confirm the global topological alternations. Moreover, frequency dependence is observed from FDR-controlled subnetworks for the limbic-cortical connectivity change. In the high-frequency band, the altered connections involve mostly frontal regions, while the altered connections in the low-frequency bands spread to parietal and temporal areas. Due to the limitation of small sample sizes and lack of placebo control, these preliminary findings require confirmation with future work using larger samples. Confirmation of biomarkers associated with treatment could suggest potential avenues for clinical applications such as tracking treatment response and neurobiologically informed treatment optimization.

Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group

Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen's d = 0.14, 95% CI: 0.08-0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.

Identifying Biological Signatures of N-Acetylcysteine for Non-Suicidal Self-Injury in Adolescents and Young Adults

The prevalence of non-suicidal self-injury (NSSI) is high in adolescents and young adults. However, there is a paucity of evidence-based treatments to address this clinical problem. An open-label, pilot study in the target population showed that treatment with oral N-acetylcysteine (NAC), a widely available dietary supplement, was associated with reduction in NSSI frequency. In preparation for a biologically informed design of an efficacy trial, a critical preliminary step is to clarify NAC's biological signatures, or measures of the mechanisms underlying its clinical effects. Toward that end, we propose a 2-stage project to investigate NAC's biological signatures (changes in glutathione (GSH) and/or glutamate (Glu)) in women with NSSI. The first stage; a double-blind randomized placebo-controlled study will focus on identifying the optimal dose to achieve meaningful change in GSH and Glu during short-term (4 weeks) NAC treatment in 36 women aged 16-24 years with NSSI. Go/No-go criteria to determine if the study will progress to the second stage include pre-specified changes in brain and blood measures of GSH. Changes in the brain GSH are measured through magnetic resonance spectroscopy (MRS). The dose for the stage 2 will be selected based on the biological changes and the tolerability observed in the stage 1. The stage 2 will seek to replicate the biological signature findings in an 8-week trial in a new patient cohort, and examine the relationships among biological signatures, NAC pharmacokinetics and clinical response. This 2-stage project is unique as it unifies clinical psychiatric measurements, quantitative MRS and pharmacological approaches in the first placebo-controlled clinical trial of NAC in young women with NSSI.

TRIAL REGISTRATION

The stage 1 trial protocol has been registered on https://clinicaltrials.gov/ with ClinicalTrials.gov ID "NCT04005053" (Registered on 02 July 2019. Available from: https://clinicaltrials.gov/ct2/show/NCT04005053).

Accelerated maturation in functional connectivity following early life stress: Circuit specific or broadly distributed?

Psychosocial acceleration theory and other frameworks adapted from life history predict a link between early life stress and accelerated maturation in several physiological systems. Those findings led researchers to suggest that the emotion-regulatory brain circuits of previously-institutionalized (PI) youth are more mature than youth raised in their biological families (non-adopted, or NA, youth) during emotion tasks. Whether this accelerated maturation is evident during resting-state fMRI has not yet been established. Resting-state fMRI data from 83 early adolescents (Mage = 12.9 years, SD = 0.57 years) including 41 PI and 42 NA youth, were used to examine seed-based functional connectivity between the amygdala and ventromedial prefrontal cortex (vmPFC). Additional whole-brain analyses assessed group differences in functional connectivity and associations with cognitive performance and behavior. We found group differences in amygdala - vmPFC connectivity that may be consistent with accelerated maturation following early life stress. Further, whole-brain connectivity analyses revealed group differences associated with internalizing and externalizing symptoms. However, the majority of whole-brain results were not consistent with an accelerated maturation framework. Our results suggest early life stress in the form of institutional care is associated with circuit-specific alterations to a frontolimbic emotion-regulatory system, while revealing limited differences in more broadly distributed networks.

Resting State Hypoconnectivity of Reward Networks in Binge Eating Disorder

The clinical presentation of binge eating disorder (BED) and data emerging from task-based functional neuroimaging research suggests that this disorder may be associated with alterations in reward processing. However, there is a dearth of research investigating the functional organization of brain networks that mediate reward in BED. To address this gap, 27 adults with BED and 21 weight-matched healthy controls (WMC) completed a multimodel assessment consisting of a resting functional magnetic resonance imaging scan, behavioral tasks measuring reward-based decision-making (i.e., delay discounting and reversal learning), and self-report assessing clinical symptoms. A seed-based approach was employed to examine the resting state functional connectivity (rsFC) of the striatum (nucleus accumbens [NAcc] and ventral and dorsal caudate), a collection of regions implicated in reward processing. Compared with WMC, the BED group exhibited lower rsFC of striatal seeds, with frontal regions mediating executive functioning (e.g., superior frontal gyrus [SFG]) and posterior, parietal, and temporal regions implicated in emotional processing. Lower NAcc-SFG rsFC was associated with more difficulties with reversal learning and binge eating frequency in the BED group. Results suggest that hypoconnectivity of striatal networks that integrate self-regulation and reward processing may promote the clinical phenomenology of BED. Interventions for BED may benefit from targeting these circuit-based disturbances.

Coordination between frontolimbic resting state connectivity and hypothalamic-pituitary-adrenal axis functioning in adolescents with and without depression

Depression is associated with abnormalities in Hypothalamic-Pituitary-Adrenal (HPA) axis functioning and neural circuitry that underlie the stress response. Resting-state functional connectivity (RSFC) between frontolimbic brain regions captures intrinsic connections that may set the stage for the rallying and regulating of the HPA axis system. This study examined the association between cortisol stress response and frontolimbic (amygdala and ventral and dorsal medial prefrontal cortex [vmPFC and dmPFC respectively]) RSFC in 88 (Age: M = 15.95, SD = 2.04; 71.60% female) adolescents with (N = 55) and without (N = 33) major depressive disorder (MDD). We collected salivary cortisol in the context of a modified Trier Social Stress Test (TSST) paradigm. Key findings were that adolescents with depression and healthy controls showed different patterns of association between amygdala and vmPFC RSFC and HPA functioning: while healthy controls showed a positive relationship between frontolimbic connectivity and cortisol levels that may indicate coordination across neural and neuroendocrine systems, adolescents with depression showed a minimal or inverse relationship, suggesting poor coordination of these systems. Results were similar when examining non-suicidal self-injury subgroups within the MDD sample. These findings suggest that the intrinsic quality of this frontolimbic connection may be related to HPA axis functioning. In MDD, inverse associations may represent a compensatory response in one system in response to dysfunction in the other. Longitudinal multilevel research, however, is needed to disentangle how stress system coordination develops in normal and pathological contexts and how these systems recover with treatment.

Social behaviors and gray matter volumes of brain areas supporting social cognition in children and adolescents with prenatal alcohol exposure

The goal of this study was to examine: 1) differences in parent-reported prosocial and antisocial behaviors between children and adolescents with and without prenatal alcohol exposure (PAE); 2) differences in gray matter volumes of brain areas supporting social cognition between children and adolescents with and without PAE; 3) correlations between gray matter volumes of brain areas supporting social cognition and parent-reported prosocial and antisocial behaviors. Parents of children and adolescents ages 8-16 years completed measures on their prosocial and antisocial behaviors (i.e., Behavior Assessment Scale for Children, Vineland Adaptive Behaviors Scales, and Child Behavior Checklist) (n = 84; 41 with PAE, 43 without PAE). Seventy-nine participants (40 with PAE, 39 without PAE) also completed a structural Magnetic Resonance Imaging (MRI) scan with quality data. Gray matter volumes of seven brain areas supporting social cognitive processes were computed using automated procedures (FreeSurfer 6.0): bilateral fusiform gyrus, superior temporal gyrus, medial orbitofrontal cortex, lateral orbitofrontal cortex, posterior cingulate cortex, precuneus, and temporal pole. Children and adolescents with PAE showed decreased prosocial behaviors and increased antisocial behaviors as well as smaller volumes of the precuneus and lateral orbitofrontal cortex, even when controlling for total intracranial volume. Social brain volumes were not significantly correlated with prosocial or antisocial behaviors. These findings suggest that children and adolescents with PAE show worse social functioning and smaller volumes of brain areas supporting self-awareness, perspective-taking and emotion-regulation than their same-age peers without PAE.

Brain entropy and neurotrophic molecular markers accompanying clinical improvement after ketamine: Preliminary evidence in adolescents with treatment-resistant depression

BACKGROUND

Current theory suggests that treatment-resistant depression (TRD) involves impaired neuroplasticity resulting in cognitive and neural rigidity, and that clinical improvement may require increasing brain flexibility and adaptability.

AIMS

In this hypothesis-generating study, we sought to identify preliminary evidence of brain flexibility correlates of clinical change within the context of an open-label ketamine trial in adolescents with TRD, focusing on two promising candidate markers of neural flexibility: (a) entropy of resting-state functional magnetic resonance imaging (fMRI) signals; and (b) insulin-stimulated phosphorylation of mammalian target of rapamycin (mTOR) and glycogen synthase-3-beta (GSK3β) in peripheral blood mononuclear cells.

METHODS

We collected resting-state functional magnetic resonance imaging data and blood samples from 13 adolescents with TRD before and after a series of six ketamine infusions over 2 weeks. Usable pre/post ketamine data were available from 11 adolescents for imaging and from 10 adolescents for molecular signaling. We examined correlations between treatment response and changes in the central and peripheral flexibility markers.

RESULTS

Depression reduction correlated with increased nucleus accumbens entropy. Follow-up analyses suggested that physiological changes were associated with treatment response. In contrast to treatment non-responders (n=6), responders (n=5) showed greater increase in nucleus accumbens entropy after ketamine, together with greater post-treatment insulin/mTOR/GSK3β signaling.

CONCLUSIONS

These data provide preliminary evidence that changes in neural flexibility may underlie symptom relief in adolescents with TRD following ketamine. Future research with adequately powered samples is needed to confirm resting-state entropy and insulin-stimulated mTOR and GSK3β as brain flexibility markers and candidate targets for future clinical trials.

CLINICAL TRIAL NAME

Ketamine in adolescents with treatment-resistant depressionURL: https://clinicaltrials.gov/ct2/show/NCT02078817Registration number: NCT02078817.

Exploratory study of how Cognitive Multisensory Rehabilitation restores parietal operculum connectivity and improves upper limb movements in chronic stroke

Cognitive Multisensory Rehabilitation (CMR) is a promising therapy for upper limb recovery in stroke, but the brain mechanisms are unknown. We previously demonstrated that the parietal operculum (parts OP1/OP4) is activated with CMR exercises. In this exploratory study, we assessed the baseline difference between OP1/OP4 functional connectivity (FC) at rest in stroke versus healthy adults to then explore whether CMR affects OP1/OP4 connectivity and sensorimotor recovery after stroke. We recruited 8 adults with chronic stroke and left hemiplegia/paresis and 22 healthy adults. Resting-state FC with the OP1/OP4 region-of-interest in the affected hemisphere was analysed before and after 6 weeks of CMR. We evaluated sensorimotor function and activities of daily life pre- and post-CMR, and at 1-year post-CMR. At baseline, we found decreased FC between the right OP1/OP4 and 34 areas distributed across all lobes in stroke versus healthy adults. After CMR, only four areas had decreased FC compared to healthy adults. Compared to baseline (pre-CMR), participants improved on motor function (MESUPES arm p = 0.02; MESUPES hand p = 0.03; MESUPES total score p = 0.006); on stereognosis (p = 0.03); and on the Frenchay Activities Index (p = 0.03) at post-CMR and at 1-year follow-up. These results suggest enhanced sensorimotor recovery post-stroke after CMR. Our results justify larger-scale studies.

White matter microstructure relates to lassitude but not diagnosis in adolescents with depression

The neurobiology of adolescent depression remains poorly understood. Initial studies suggested impaired white matter microstructure in adults and adolescents, but findings have not been consistent. Challenges in this literature have included small samples, medication confounds and inconsistent correction for type I error. This study addressed these issues in a new examination of fractional anisotropy (FA) in adolescents with major depressive disorder (MDD) using diffusion tensor imaging. We examined FA in 81 adolescents aged 12-19 (44 MDD [all unmedicated], 37 controls). We conducted logistic regression analyses to examine the odds of MDD versus control based on FA within standard white matter tracts that were delineated by probabilistic tractography. We also examined relationships between FA and disease severity (overall depression and dimensions of illness). Finally, we conducted a voxel-wise group comparison of FA. All analyses covaried for age, sex and socioeconomic status, and applied rigorous corrections for multiple testing. Logistic regression did not reveal significant associations between diagnosis and FA within white matter tracts defined by probabilistic tractography. Dimensional analyses revealed that greater lassitude was associated with higher FA in right cingulum bundle and bilateral corticospinal tracts, but with lower FA in right anterior thalamic radiation. Voxel-wise group comparisons of FA did not reveal significant group differences. The current findings do not support low FA as a neurobiological marker of adolescent depression. Dimensional results suggest that FA relates to lassitude but not overall depression. Given the clinical and neurobiological heterogeneity of depression, future work utilizing dimensional approaches may help elucidate the role of white matter microstructure in adolescent depression neurobiology.

Meta-Modal Information Flow: A Method for Capturing Multimodal Modular Disconnectivity in Schizophrenia

OBJECTIVE

Multimodal measurements of the same phenomena provide complementary information and highlight different perspectives, albeit each with their own limitations. A focus on a single modality may lead to incorrect inferences, which is especially important when a studied phenomenon is a disease. In this paper, we introduce a method that takes advantage of multimodal data in addressing the hypotheses of disconnectivity and dysfunction within schizophrenia (SZ).

METHODS

We start with estimating and visualizing links within and among extracted multimodal data features using a Gaussian graphical model (GGM). We then propose a modularity-based method that can be applied to the GGM to identify links that are associated with mental illness across a multimodal data set. Through simulation and real data, we show our approach reveals important information about disease-related network disruptions that are missed with a focus on a single modality. We use functional MRI (fMRI), diffusion MRI (dMRI), and structural MRI (sMRI) to compute the fractional amplitude of low frequency fluctuations (fALFF), fractional anisotropy (FA), and gray matter (GM) concentration maps. These three modalities are analyzed using our modularity method.

RESULTS

Our results show missing links that are only captured by the cross-modal information that may play an important role in disconnectivity between the components.

CONCLUSION

We identified multimodal (fALFF, FA and GM) disconnectivity in the default mode network area in patients with SZ, which would not have been detectable in a single modality.

SIGNIFICANCE

The proposed approach provides an important new tool for capturing information that is distributed among multiple imaging modalities.

Para-limbic Structural Abnormalities Are Associated With Internalizing Symptoms in Children With Prenatal Alcohol Exposure

BACKGROUND

Prenatal alcohol exposure (PAE) is associated with a variety of structural abnormalities in the brain, including several within the para-limbic system. Children with PAE have higher rates of internalizing disorders, including depression and anxiety, which may be related to underlying limbic system anomalies.

METHODS

Children aged 8 to 16 with PAE (n = 41) or without PAE (n = 36) underwent an magnetic resonance imaging of the brain and parents completed behavioral questionnaires about their children. Semi-automated procedures (FreeSurfer) were used to derive para-limbic volumes from T1-weighted anatomical images.

RESULTS

There were significant group differences (PAE vs. nonexposed controls) in the caudate, hippocampus, and the putamen; children with PAE had smaller volumes in these regions even after controlling for total intracranial volume. A trend-level association was seen between caudate volume and internalizing symptoms in children with PAE; smaller caudate volumes (presumably reflecting less optimal neurodevelopment) were associated with higher levels of anxiety and depression symptoms in these children.

CONCLUSIONS

Caudate structure may be disproportionately affected by PAE and may be associated with the later development of internalizing symptoms in those affected by PAE.