Mental health during the COVID-19 pandemic: the importance of social support in midlife women.

OBJECTIVE: This study aimed to examine sex differences in factors associated with mood and anxiety in midlife men and women during the COVID-19 pandemic. METHODS: During a remote visit, 312 adults aged 40-60 years (167 female; 23.6% perimenopausal) from the Human Connectome Project in Aging completed PROMIS measures of depression, anxiety and anger/irritability; perceived stress; and questions about social support, financial stress and menopause stage. Multivariate linear regression models assessed sex differences in mental health and the association of social support, financial stress and menopause stage with mental health. RESULTS: Anxiety was higher in women than in men (b = 2.39, p = 0.02). For women only, decreased social support was associated with increased anxiety (b = -2.26, p = 0.002), anger/irritability (b = -1.89, p = 0.02) and stress (b = -1.67, p = 0.002). For women only, not having close family was associated with increased depressive symptoms (b = -6.60, p = 0.01) and stress (b = -7.03, p < 0.001). For both sexes, having children was associated with lower depressive symptoms (b = -3.08, p = 0.002), anxiety (b = -1.93, p = 0.07), anger/irritability (b = -2.73, p = 0.02) and stress (b = -1.44, p = 0.07). Menopause stage was unrelated to mental health. CONCLUSION: Social support, but not financial stress, influenced mental health during the COVID-19 pandemic at midlife, particularly for women.

Changes in white matter microstructure following serial ketamine infusions in treatment resistant depression.

Ketamine produces fast-acting antidepressant effects in treatment resistant depression (TRD). Though prior studies report ketamine-related changes in brain activity in TRD, understanding of ketamine's effect on white matter (WM) microstructure remains limited. We thus sought to examine WM neuroplasticity and associated clinical improvements following serial ketamine infusion (SKI) in TRD. TRD patients (N = 57, 49.12% female, mean age: 39.9) received four intravenous ketamine infusions (0.5 mg/kg) 2-3 days apart. Diffusion-weighted scans and clinical assessments (Hamilton Depression Rating Scale [HDRS-17]; Snaith Hamilton Pleasure Scale [SHAPS]) were collected at baseline and 24-h after SKI. WM measures including the neurite density index (NDI) and orientation dispersion index (ODI) from the neurite orientation dispersion and density imaging (NODDI) model, and fractional anisotropy (FA) from the diffusion tensor model were compared voxelwise pre- to post-SKI after using Tract-Based Spatial Statistics workflows to align WM tracts across subjects/time. Correlations between change in WM metrics and clinical measures were subsequently assessed. Following SKI, patients showed significant improvements in HDRS-17 (p-value = 1.8 E-17) and SHAPS (p-value = 1.97 E-10). NDI significantly decreased in occipitotemporal WM pathways (p < .05, FWER/TFCE corrected). ΔSHAPS significantly correlated with ΔNDI in the left internal capsule and left superior longitudinal fasciculus (r = -0.614, p-value = 6.24E-09). No significant changes in ODI or FA were observed. SKI leads to significant changes in the microstructural features of neurites within occipitotemporal tracts, and changes in neurite density within tracts connecting the basal ganglia, thalamus, and cortex relate to improvements in anhedonia. NODDI may be more sensitive for detecting ketamine-induced WM changes than DTI.

Modulation of brain networks during MR-compatible transcranial direct current stimulation.

Transcranial direct current stimulation (tDCS) can influence performance on behavioral tasks and improve symptoms of brain conditions. Yet, it remains unclear precisely how tDCS affects brain function and connectivity. Here, we measured changes in functional connectivity (FC) metrics in blood-oxygenation-level-dependent (BOLD) fMRI data acquired during MR-compatible tDCS in a whole-brain analysis with corrections for false discovery rate. Volunteers (n = 64) received active tDCS, sham tDCS, and rest (no stimulation), using one of three previously established electrode tDCS montages targeting left dorsolateral prefrontal cortex (DLPFC, n = 37), lateral temporoparietal area (LTA, n = 16), or superior temporal cortex (STC, n = 11). In brain networks where simulated E field was highest in each montage, connectivity with remote nodes decreased during active tDCS. During active DLPFC-tDCS, connectivity decreased between a fronto-parietal network and subgenual ACC, while during LTA-tDCS connectivity decreased between an auditory-somatomotor network and frontal operculum. Active DLPFC-tDCS was also associated with increased connectivity within an orbitofrontal network overlapping subgenual ACC. Irrespective of montage, FC metrics increased in sensorimotor and attention regions during both active and sham tDCS, which may reflect the cognitive-perceptual demands of tDCS. Taken together, these results indicate that tDCS may have both intended and unintended effects on ongoing brain activity, stressing the importance of including sham, stimulation-absent, and active comparators in basic science and clinical trials of tDCS.

Anterior default mode network and posterior insular connectivity is predictive of depressive symptom reduction following serial ketamine infusion.

BACKGROUND: Ketamine is a rapidly-acting antidepressant treatment with robust response rates. Previous studies have reported that serial ketamine therapy modulates resting state functional connectivity in several large-scale networks, though it remains unknown whether variations in brain structure, function, and connectivity impact subsequent treatment success. We used a data-driven approach to determine whether pretreatment multimodal neuroimaging measures predict changes along symptom dimensions of depression following serial ketamine infusion. METHODS: Patients with depression (n = 60) received structural, resting state functional, and diffusion MRI scans before treatment. Depressive symptoms were assessed using the 17-item Hamilton Depression Rating Scale (HDRS-17), the Inventory of Depressive Symptomatology (IDS-C), and the Rumination Response Scale (RRS) before and 24 h after patients received four (0.5 mg/kg) infusions of racemic ketamine over 2 weeks. Nineteen unaffected controls were assessed at similar timepoints. Random forest regression models predicted symptom changes using pretreatment multimodal neuroimaging and demographic measures. RESULTS: Two HDRS-17 subscales, the HDRS-6 and core mood and anhedonia (CMA) symptoms, and the RRS: reflection (RRSR) scale were predicted significantly with 19, 27, and 1% variance explained, respectively. Increased right medial prefrontal cortex/anterior cingulate and posterior insula (PoI) and lower kurtosis of the superior longitudinal fasciculus predicted reduced HDRS-6 and CMA symptoms following treatment. RRSR change was predicted by global connectivity of the left posterior cingulate, left insula, and right superior parietal lobule. CONCLUSIONS: Our findings support that connectivity of the anterior default mode network and PoI may serve as potential biomarkers of antidepressant outcomes for core depressive symptoms.

Modulation of the functional connectome in major depressive disorder by ketamine therapy.

BACKGROUND: Subanesthetic ketamine infusion therapy can produce fast-acting antidepressant effects in patients with major depression. How single and repeated ketamine treatment modulates the whole-brain functional connectome to affect clinical outcomes remains uncharacterized. METHODS: Data-driven whole brain functional connectivity (FC) analysis was used to identify the functional connections modified by ketamine treatment in patients with major depressive disorder (MDD). MDD patients (N = 61, mean age = 38, 19 women) completed baseline resting-state (RS) functional magnetic resonance imaging and depression symptom scales. Of these patients, n = 48 and n = 51, completed the same assessments 24 h after receiving one and four 0.5 mg/kg intravenous ketamine infusions. Healthy controls (HC) (n = 40, 24 women) completed baseline assessments with no intervention. Analysis of RS FC addressed effects of diagnosis, time, and remitter status. RESULTS: Significant differences (p < 0.05, corrected) in RS FC were observed between HC and MDD at baseline in the somatomotor network and between association and default mode networks. These disruptions in FC in MDD patients trended toward control patterns with ketamine treatment. Furthermore, following serial ketamine infusions, significant decreases in FC were observed between the cerebellum and salience network (SN) (p < 0.05, corrected). Patient remitters showed increased FC between the cerebellum and the striatum prior to treatment that decreased following treatment, whereas non-remitters showed the opposite pattern. CONCLUSION: Results support that ketamine treatment leads to neurofunctional plasticity between distinct neural networks that are shown as disrupted in MDD patients. Cortico-striatal-cerebellar loops that encompass the SN could be a potential biomarker for ketamine treatment.

Hippocampal subregions and networks linked with antidepressant response to electroconvulsive therapy.

Electroconvulsive therapy (ECT) has been repeatedly linked to hippocampal plasticity. However, it remains unclear what role hippocampal plasticity plays in the antidepressant response to ECT. This magnetic resonance imaging (MRI) study tracks changes in separate hippocampal subregions and hippocampal networks in patients with depression (n = 44, 23 female) to determine their relationship, if any, with improvement after ECT. Voxelwise analyses were restricted to the hippocampus, amygdala, and parahippocampal cortex, and applied separately for responders and nonresponders to ECT. In analyses of arterial spin-labeled (ASL) MRI, nonresponders exhibited increased cerebral blood flow (CBF) in bilateral anterior hippocampus, while responders showed CBF increases in right middle and left posterior hippocampus. In analyses of gray matter volume (GMV) using T1-weighted MRI, GMV increased throughout bilateral hippocampus and surrounding tissue in nonresponders, while responders showed increased GMV in right anterior hippocampus only. Using CBF loci as seed regions, BOLD-fMRI data from healthy controls (n = 36, 19 female) identified spatially separable neurofunctional networks comprised of different brain regions. In graph theory analyses of these networks, functional connectivity within a hippocampus-thalamus-striatum network decreased only in responders after two treatments and after index. In sum, our results suggest that the location of ECT-related plasticity within the hippocampus may differ according to antidepressant outcome, and that larger amounts of hippocampal plasticity may not be conducive to positive antidepressant response. More focused targeting of hippocampal subregions and/or circuits may be a way to improve ECT outcome.

The impact of prenatal alcohol exposure on gray matter volume and cortical surface area of 2 to 3-year-old children in a South African birth cohort.

BACKGROUND: There is a growing literature that demonstrates the effects of prenatal alcohol exposure (PAE) on brain development in school-aged children. Less is known, however, on how PAE impacts the brain early in life. We investigated the effects of PAE and child sex on subcortical gray matter volume, cortical surface area (CSA), cortical volume (CV), and cortical thickness (CT) in children aged 2 to 3 years. METHODS: The sample was recruited as a nested cross-sectional substudy of the Drakenstein Child Health Study. Images from T1-weighted magnetic resonance imaging were acquired on 47 alcohol-exposed and 124 control children (i.e., with no or minimal alcohol exposure), aged 2 to 3 years, some of whom were scanned as neonates. Brain images were processed through automated processing pipelines using FreeSurfer version 6.0. Subcortical and a priori selected cortical regions of interest were compared. RESULTS: Subcortical volume analyses revealed a PAE by child sex interaction for bilateral putamen volumes (Left: p = 0.02; Right: p = 0.01). There was no PAE by child sex interaction effect on CSA, CV, and CT. Analyses revealed an impact of PAE on CSA (p = 0.04) and CV (p = 0.04), but not CT in this age group. Of note, the inferior parietal gyrus CSA was significantly smaller in children with PAE compared to control children. CONCLUSIONS: Findings from this subgroup scanned at age 2 to 3 years build on previously described subcortical volume differences in neonates from this cohort. Findings suggest that PAE persistently affects gray matter development through the critical early years of life. The detectable influence of PAE on brain structure at this early age further highlights the importance of brain imaging studies on the impact of PAE on the young developing brain.

Detecting Vehicle Loading Events in Bridge Rotation Data Measured with Multi-Axial Accelerometers.

Structural Health Monitoring (SHM) is critical in the observation and analysis of our national infrastructure of bridges. Due to the ease of measuring bridge rotation, bridge SHM using rotation measurements is becoming more popular, as even a single DC accelerometer placed at each end of span can accurately capture bridge deformations. Event detection methods for SHM typically entail additional instrumentation, such as strain gauges or continuously recording video cameras, and thus the additional cost limits their utility in resource-constrained environments and for wider deployment. Herein, we present a more cost-effective event detection method which exploits the existing bridge rotation instrumentation (tri-axial MEMS accelerometers) to also act as a trigger for subsequent stages of the SHM system and thus obviates the need for additional vehicle detection equipment. We show how the generalised variance over a short sliding window can be used to robustly discriminate individual vehicle loading events, both in time and magnitude, from raw acceleration data. Numerical simulation results examine the operation of the event detector under varying operating conditions, including vehicle types and sensor locations. The method's application is demonstrated for two case studies involving in-service bridges experiencing live free-flow traffic. An initial implementation on a Raspberry Pi Zero 2 shows that the proposed functionality can be realised in less than 400 ARM A32 instructions with a latency of 47 microseconds.

Accounting for symptom heterogeneity can improve neuroimaging models of antidepressant response after electroconvulsive therapy.

Depression symptom heterogeneity limits the identifiability of treatment-response biomarkers. Whether improvement along dimensions of depressive symptoms relates to separable neural networks remains poorly understood. We build on work describing three latent symptom dimensions within the 17-item Hamilton Depression Rating Scale (HDRS) and use data-driven methods to relate multivariate patterns of patient clinical, demographic, and brain structural changes over electroconvulsive therapy (ECT) to dimensional changes in depressive symptoms. We included 110 ECT patients from Global ECT-MRI Research Collaboration (GEMRIC) sites who underwent structural MRI and HDRS assessments before and after treatment. Cross validated random forest regression models predicted change along symptom dimensions. HDRS symptoms clustered into dimensions of somatic disturbances (SoD), core mood and anhedonia (CMA), and insomnia. The coefficient of determination between predicted and actual changes were 22%, 39%, and 39% (all p < .01) for SoD, CMA, and insomnia, respectively. CMA and insomnia change were predicted more accurately than HDRS-6 and HDRS-17 changes (p < .05). Pretreatment symptoms, body-mass index, and age were important predictors. Important imaging predictors included the right transverse temporal gyrus and left frontal pole for the SoD dimension; right transverse temporal gyrus and right rostral middle frontal gyrus for the CMA dimension; and right superior parietal lobule and left accumbens for the insomnia dimension. Our findings support that recovery along depressive symptom dimensions is predicted more accurately than HDRS total scores and are related to unique and overlapping patterns of clinical and demographic data and volumetric changes in brain regions related to depression and near ECT electrodes.

Modulation of amygdala reactivity following rapidly acting interventions for major depression.

Electroconvulsive therapy (ECT) and ketamine treatment both induce rapidly acting antidepressant effects in patients with major depressive disorder unresponsive to standard treatments, yet their specific impact on emotion processing is unknown. Here, we examined the neural underpinnings of emotion processing within and across patients (N = 44) receiving either ECT (N = 17, mean age: 36.8, 11.0 SD) or repeated subanesthetic (0.5 mg/kg) intravenous ketamine therapy (N = 27, mean age: 37.3, 10.8 SD) using a naturalistic study design. MRI and clinical data were collected before (TP1) and after treatment (TP2); healthy controls (N = 31, mean age: 34.5, 13.5 SD) completed one MRI session (TP1). An fMRI face-matching task probed negative- and positive-valence systems. Whole-brain analysis, comparing neurofunctional changes within and across treatment groups, targeted brain regions involved in emotional facial processing, and included regions-of-interest analysis of amygdala responsivity. Main findings revealed a decrease in amygdalar reactivity after both ECT and ketamine for positive and negative emotional face processing (p < .05 family wise-error (FWE) corrected). Subthreshold changes were observed between treatments within the dorsolateral prefrontal cortex and insula (p < .005, uncorrected). BOLD change for positive faces in the inferior parietal cortex significantly correlated with overall symptom improvement, and BOLD change in frontal regions correlated with anxiety for negative faces, and anhedonia for positive faces (p < .05 FWE corrected). Both serial ketamine and ECT treatment modulate amygdala response, while more subtle treatment-specific changes occur in the larger functional network. Findings point to both common and differential mechanistic upstream systems-level effects relating to fast-acting antidepressant response, and symptoms of anxiety and anhedonia, for the processing of emotionally valenced stimuli.

Depressive Symptom Dimensions in Treatment-Resistant Major Depression and Their Modulation With Electroconvulsive Therapy.

OBJECTIVE: Symptom heterogeneity in major depressive disorder obscures diagnostic and treatment-responsive biomarker identification. Whether symptom constellations are differentially changed by electroconvulsive therapy (ECT) remains unknown. We investigate the clustering of depressive symptoms over the ECT index and whether ECT differentially influences symptom clusters. METHODS: The 17-item Hamilton Depression Rating Scale (HDRS-17) was collected from 111 patients with current depressive episode before and after ECT from 4 independent participating sites of the Global ECT-MRI Research Collaboration. Exploratory factor analysis of HDRS-17 items pre- and post-ECT treatment identified depressive symptom dimensions before and after ECT. A 2-way analysis of covariance was used to determine whether baseline symptom clusters were differentially changed by ECT between treatment remitters (defined as patients with posttreatment HDRS-17 total score ≤8) and nonremitters while controlling for pulse width, titration method, concurrent antidepressant treatment, use of benzodiazepine, and demographic variables. RESULTS: A 3-factor solution grouped pretreatment HDRS-17 items into core mood/anhedonia, somatic, and insomnia dimensions. A 2-factor solution best described the symptoms at posttreatment despite poorer separation of items. Among remitters, core mood/anhedonia symptoms were significantly more reduced than somatic and insomnia dimensions. No differences in symptom dimension trajectories were observed among nonremitting patients. CONCLUSIONS: Electroconvulsive therapy targets the underlying source of depressive symptomatology and may confer differential degrees of improvement in certain core depressive symptoms. Our findings of differential trajectories of symptom clusters over the ECT index might help related predictive biomarker studies to refine their approaches by identifying predictors of change along each latent symptom dimension.

The Lifespan Human Connectome Project in Aging: An overview.

The original Human Connectome Project yielded a rich data set on structural and functional connectivity in a large sample of healthy young adults using improved methods of data acquisition, analysis, and sharing. More recent efforts are extending this approach to include infants, children, older adults, and brain disorders. This paper introduces and describes the Human Connectome Project in Aging (HCP-A), which is currently recruiting 1200 + healthy adults aged 36 to 100+, with a subset of 600 + participants returning for longitudinal assessment. Four acquisition sites using matched Siemens Prisma 3T MRI scanners with centralized quality control and data analysis are enrolling participants. Data are acquired across multimodal imaging and behavioral domains with a focus on factors known to be altered in advanced aging. MRI acquisitions include structural (whole brain and high resolution hippocampal) plus multiband resting state functional (rfMRI), task fMRI (tfMRI), diffusion MRI (dMRI), and arterial spin labeling (ASL). Behavioral characterization includes cognitive (such as processing speed and episodic memory), psychiatric, metabolic, and socioeconomic measures as well as assessment of systemic health (with a focus on menopause via hormonal assays). This dataset will provide a unique resource for examining how brain organization and connectivity changes across typical aging, and how these differences relate to key characteristics of aging including alterations in hormonal status and declining memory and general cognition. A primary goal of the HCP-A is to make these data freely available to the scientific community, supported by the Connectome Coordination Facility (CCF) platform for data quality assurance, preprocessing and basic analysis, and shared via the NIMH Data Archive (NDA). Here we provide the rationale for our study design and sufficient details of the resource for scientists to plan future analyses of these data. A companion paper describes the related Human Connectome Project in Development (HCP-D, Somerville et al., 2018), and the image acquisition protocol common to both studies (Harms et al., 2018).

Extending the Human Connectome Project across ages: Imaging protocols for the Lifespan Development and Aging projects.

The Human Connectome Projects in Development (HCP-D) and Aging (HCP-A) are two large-scale brain imaging studies that will extend the recently completed HCP Young-Adult (HCP-YA) project to nearly the full lifespan, collecting structural, resting-state fMRI, task-fMRI, diffusion, and perfusion MRI in participants from 5 to 100+ years of age. HCP-D is enrolling 1300+ healthy children, adolescents, and young adults (ages 5-21), and HCP-A is enrolling 1200+ healthy adults (ages 36-100+), with each study collecting longitudinal data in a subset of individuals at particular age ranges. The imaging protocols of the HCP-D and HCP-A studies are very similar, differing primarily in the selection of different task-fMRI paradigms. We strove to harmonize the imaging protocol to the greatest extent feasible with the completed HCP-YA (1200+ participants, aged 22-35), but some imaging-related changes were motivated or necessitated by hardware changes, the need to reduce the total amount of scanning per participant, and/or the additional challenges of working with young and elderly populations. Here, we provide an overview of the common HCP-D/A imaging protocol including data and rationales for protocol decisions and changes relative to HCP-YA. The result will be a large, rich, multi-modal, and freely available set of consistently acquired data for use by the scientific community to investigate and define normative developmental and aging related changes in the healthy human brain.

Direct Visualization and Mapping of the Spatial Course of Fiber Tracts at Microscopic Resolution in the Human Hippocampus.

While hippocampal connectivity is essential to normal memory function, our knowledge of human hippocampal circuitry is largely inferred from animal studies. Using polarized light microscopy at 1.3 µm resolution, we have directly visualized the 3D course of key medial temporal pathways in 3 ex vivo human hemispheres and 2 ex vivo vervet monkey hemispheres. The multiple components of the perforant path system were clearly identified: Superficial sheets of fibers emanating from the entorhinal cortex project to the presubiculum and parasubiculum, intermixed transverse and longitudinal angular bundle fibers perforate the subiculum and then project to the cornu ammonis (CA) fields and dentate molecular layer, and a significant alvear component runs from the angular bundle to the CA fields. From the hilus, mossy fibers localize to regions of high kainate receptor density, and the endfolial pathway, mostly investigated in humans, merges with the Schaffer collaterals. This work defines human hippocampal pathways underlying mnemonic function at an unprecedented resolution.

Neurochemical correlates of rapid treatment response to electroconvulsive therapy in patients with major depression.

BACKGROUND: Electroconvulsive therapy (ECT) is a highly effective brain stimulation treatment for severe depression. Identifying neurochemical changes linked with ECT may point to biomarkers and predictors of successful treatment response. METHODS: We used proton magnetic resonance spectroscopy (1H-MRS) to measure longitudinal changes in glutamate/glutamine (Glx), creatine (Cre), choline (Cho) and N-acetylaspartate (NAA) in the dorsal (dACC) and subgenual anterior cingulate cortex (sgACC) and bilateral hippocampus in patients receiving ECT scanned at baseline, after the second ECT session and after the ECT treatment series. Patients were compared with demographically similar controls at baseline. Controls were assessed twice to establish normative values and variance. RESULTS: We included 50 patients (mean age 43.78 ± 14 yr) and 33 controls (mean age 39.33 ± 12 yr) in our study. Patients underwent a mean of 9 ± 4.1 sessions of ECT. At baseline, patients showed reduced Glx in the sgACC, reduced NAA in the left hippocampus and increased Glx in the left hippocampus relative to controls. ECT was associated with significant increases in Cre in the dACC and sgACC and decreases in NAA in the dACC and right hippocampus. Lower NAA levels in the dACC at baseline predicted reductions in depressive symptoms. Both ECT and symptom improvement were associated with decreased Glx in the left hippocampus and increased Glx in the sgACC. LIMITATIONS: Attrition and clinical heterogeneity may have masked more subtle findings. CONCLUSION: ECT elicits robust effects on brain chemistry, impacting Cre, NAA and Glx, which suggests restorative and neurotrophic processes. Differential effects of Glx in the sgACC and hippocampus, which approach control values with treatment, may reflect previously implicated underactive cortical and overactive subcortical limbic circuitry in patients with major depression. NAA levels at baseline are predictive of therapeutic outcome and could inform future treatment strategies.

Desynchronization and Plasticity of Striato-frontal Connectivity in Major Depressive Disorder.

Major depressive disorder (MDD) is associated with dysfunctional corticolimbic networks, making functional connectivity studies integral for understanding the mechanisms underlying MDD pathophysiology and treatment. Resting-state functional connectivity (RSFC) studies analyze patterns of temporally coherent intrinsic brain activity in "resting-state networks" (RSNs). The default-mode network (DMN) has been of particular interest to depression research; however, a single RSN is unlikely to capture MDD pathophysiology in its entirety, and the DMN itself can be characterized by multiple RSNs. This, coupled with conflicting previous results, underscores the need for further research. Here, we measured RSFC in MDD by targeting RSNs overlapping with corticolimbic regions and further determined whether altered patterns of RSFC were restored with electroconvulsive therapy (ECT). MDD patients exhibited hyperconnectivity between ventral striatum (VS) and the ventral default-mode network (vDMN), while simultaneously demonstrating hypoconnectivity with the anterior DMN (aDMN). ECT influenced this pattern: VS-vDMN hyperconnectivity was significantly reduced while VS-aDMN hypoconnectivity only modestly improved. RSFC between the salience RSN and dorsomedial prefrontal cortex was also reduced in MDD, but was not affected by ECT. Taken together, our results support a model of ventral/dorsal imbalance in MDD and further suggest that the VS is a key structure contributing to this desynchronization.

Interhemispheric Functional Brain Connectivity in Neonates with Prenatal Alcohol Exposure: Preliminary Findings.

BACKGROUND: Children exposed to alcohol in utero demonstrate reduced white matter microstructural integrity. While early evidence suggests altered functional brain connectivity in the lateralization of motor networks in school-age children with prenatal alcohol exposure (PAE), the specific effects of alcohol exposure on the establishment of intrinsic connectivity in early infancy have not been explored. METHODS: Sixty subjects received functional imaging at 2 to 4 weeks of age for 6 to 8 minutes during quiet natural sleep. Thirteen alcohol-exposed (PAE) and 14 age-matched control (CTRL) participants with usable data were included in a multivariate model of connectivity between sensorimotor intrinsic functional connectivity networks. Seed-based analyses of group differences in interhemispheric connectivity of intrinsic motor networks were also conducted. The Dubowitz neurological assessment was performed at the imaging visit. RESULTS: Alcohol exposure was associated with significant increases in connectivity between somatosensory, motor networks, brainstem/thalamic, and striatal intrinsic networks. Reductions in interhemispheric connectivity of motor and somatosensory networks did not reach significance. CONCLUSIONS: Although results are preliminary, findings suggest PAE may disrupt the temporal coherence in blood oxygenation utilization in intrinsic networks underlying motor performance in newborn infants. Studies that employ longitudinal designs to investigate the effects of in utero alcohol exposure on the evolving resting-state networks will be key in establishing the distribution and timing of connectivity disturbances already described in older children.

Alcohol exposure in utero is associated with decreased gray matter volume in neonates.

Neuroimaging studies have indicated that prenatal alcohol exposure is associated with alterations in the structure of specific brain regions. However, the temporal specificity of such changes and their behavioral consequences are less known. Here we explore the brain structure of infants with in utero exposure to alcohol shortly after birth. T2 structural MRI images were acquired from 28 alcohol-exposed infants and 45 demographically matched healthy controls at 2-4 weeks of age on a 3T Siemens Allegra system as part of large birth cohort study, the Drakenstein Child Health Study (DCHS). Neonatal neurobehavior was assessed at this visit; early developmental outcome assessed on the Bayley Scales of Infant Development III at 6 months of age. Volumes of gray matter regions were estimated based on the segmentations of the University of North Carolina neonatal atlas. Significantly decreased total gray matter volume was demonstrated for the alcohol-exposed cohort compared to healthy control infants (p < 0.001). Subcortical gray matter regions that were significantly different between groups after correcting for overall gray matter volume included left hippocampus, bilateral amygdala and left thalamus (p < 0.01). These findings persisted even when correcting for infant age, gender, ethnicity and maternal smoking status. Both early neurobehavioral and developmental adverse outcomes at 6 months across multiple domains were significantly associated with regional volumes primarily in the temporal and frontal lobes in infants with prenatal alcohol exposure. Alcohol exposure during the prenatal period has potentially enduring neurobiological consequences for exposed children. These findings suggest the effects of prenatal alcohol exposure on brain growth is present very early in the first year of life, a period during which the most rapid growth and maturation occurs.

A study of the effects of prenatal alcohol exposure on white matter microstructural integrity at birth.

BACKGROUND: Neuroimaging studies have indicated that prenatal alcohol exposure is associated with alterations in the structure of specific brain regions in children. However, the temporal and regional specificity of such changes and their behavioural consequences are less known. Here we explore the integrity of regional white matter microstructure in infants with in utero exposure to alcohol, shortly after birth. METHODS: Twenty-eight alcohol-exposed and 28 healthy unexposed infants were imaged using diffusion tensor imaging sequences to evaluate white matter integrity using validated tract-based spatial statistics analysis methods. Second, diffusion values were extracted for group comparisons by regions of interest. Differences in fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity were compared between groups and associations with measures from the Dubowitz neonatal neurobehavioural assessment were examined. RESULTS: Lower AD values (p<0.05) were observed in alcohol-exposed infants in the right superior longitudinal fasciculus compared with non-exposed infants. Altered FA and MD values in alcohol-exposed neonates in the right inferior cerebellar were associated with abnormal neonatal neurobehaviour. CONCLUSION: These exploratory data suggest that prenatal alcohol exposure is associated with reduced white matter microstructural integrity even early in the neonatal period. The association with clinical measures reinforces the likely clinical significance of this finding. The location of the findings is remarkably consistent with previously reported studies of white matter structural deficits in older children with a diagnosis of foetal alcohol spectrum disorders.