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.

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.

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.

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.

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.

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.

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.

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.

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.

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 .

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.

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.

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.

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.

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.

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.