[Show abstract][Hide abstract] ABSTRACT: 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.
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.
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.
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.
Full-text · Article · Jan 2016 · Alcoholism Clinical and Experimental Research
[Show abstract][Hide abstract] ABSTRACT: 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.
Full-text · Article · Nov 2015 · Metabolic Brain Disease
[Show abstract][Hide abstract] ABSTRACT: Background:
Ketamine elicits an acute antidepressant effect in patients with major depressive disorder (MDD). Here, we used diffusion imaging to explore whether regional differences in white matter microstructure prior to treatment may predict clinical response 24h following ketamine infusion in 10 MDD patients.
FSL's Tract-Based Spatial Statistics (TBSS) established voxel-level differences in fractional anisotropy (FA) between responders (patients showing >50% improvement in symptoms 24h post-infusion) and non-responders in major white matter pathways. Follow-up regions-of-interest (ROI) analyses examined differences in FA and radial (RD), axial (AD) and mean diffusivity (MD) between responders and non-responders and 15 age- and sex-matched controls, with groups compared pairwise.
Whole brain TBSS (p<0.05, corrected) and confirmatory tract-based regions-of-interest analyses showed larger FA values in the cingulum and forceps minor in responders compared to non-responders; complementary decreases in RD occurred in the cingulum (p<0.05). Only non-responders differed from controls showing decreased FA in the forceps minor, increased RD in the cingulum and forceps minor, and increased MD in the forceps minor (p<0.05).
Non-responders showed an earlier age of onset and longer current depressive episode than responders. Though these factors did not interact with diffusion metrics, results may be impacted by the limited sample size.
Though findings are considered preliminary, significant differences in FA, RD and MD shown in non-responders compared to responders and controls in fronto-limbic and ventral striatal pathways suggest that the structural architecture of specific functional networks mediating emotion may predict ketamine response in MDD.
No preview · Article · Nov 2015 · Journal of Affective Disorders
[Show abstract][Hide abstract] ABSTRACT: One of the most effective interventions for intractable major depressive episodes is electroconvulsive therapy (ECT). Because ECT is also relatively fast acting, longitudinal study of its neurobiological effects offers critical insight into the mechanisms underlying depression and antidepressant response. Here, we assessed modulation of intrinsic brain activity in corticolimbic networks associated with ECT and clinical response.
[Show abstract][Hide abstract] ABSTRACT: 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.
[Show abstract][Hide abstract] ABSTRACT: We present a fast variational approach for denoising signals from magnetic resonance spectroscopy (MRS). Differently from the TV approaches applied to denoising of images, this is the first time to our knowledge that it has been used for the processing of free induction decay signals from single-voxel spectroscopy (SVS) acquisitions. Another novelty in this study is the direct use of the Euler Lagrange formulation coupled with Gauss Seidel gradient updates to improve the speed of iteration and reduce ringing. Results from brain MRS signals show improvement in signal to noise ratio as well as reduction in estimation error in the quantification of metabolites.
[Show abstract][Hide abstract] ABSTRACT: 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.
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.
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.
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.
Full-text · Article · May 2015 · Acta Neuropsychiatrica
[Show abstract][Hide abstract] ABSTRACT: Disorders of the central nervous system are often accompanied by brain abnormalities detectable with MRI. Advances in biomedical imaging and pattern detection algorithms have led to classification methods that may help diagnose and track the progression of a brain disorder and/or predict successful response to treatment. These classification systems often use high-dimensional signals or images, and must handle the computational challenges of high dimensionality as well as complex data types such as shape descriptors. Here, we used shape information from subcortical structures to test a recently developed feature-selection method based on regularized random forests to 1) classify depressed subjects versus controls, and 2) patients before and after treatment with electroconvulsive therapy. We subsequently compared the classification performance of high-dimensional shape features with traditional volumetric measures. Shape-based models outperformed simple volumetric predictors in several cases, highlighting their utility as potential automated alternatives for establishing diagnosis and predicting treatment response.
No preview · Article · Apr 2015 · Proceedings / IEEE International Symposium on Biomedical Imaging: from nano to macro. IEEE International Symposium on Biomedical Imaging
[Show abstract][Hide abstract] ABSTRACT: Unlike mixtures consisting solely of non-Gaussian sources, mixtures including two or more Gaussian components cannot be separated using standard independent components analysis methods that are based on higher order statistics and independent observations. The mixed Independent Components Analysis/Principal Components Analysis (mixed ICA/PCA) model described here accommodates one or more Gaussian components in the independent components analysis model and uses principal components analysis to characterize contributions from this inseparable Gaussian subspace. Information theory can then be used to select from among potential model categories with differing numbers of Gaussian components. Based on simulation studies, the assumptions and approximations underlying the Akaike Information Criterion do not hold in this setting, even with a very large number of observations. Cross-validation is a suitable, though computationally intensive alternative for model selection. Application of the algorithm is illustrated using Fisher's iris data set and Howells' craniometric data set. Mixed ICA/PCA is of potential interest in any field of scientific investigation where the authenticity of blindly separated non-Gaussian sources might otherwise be questionable. Failure of the Akaike Information Criterion in model selection also has relevance in traditional independent components analysis where all sources are assumed non-Gaussian.
[Show abstract][Hide abstract] ABSTRACT: This paper reviews the magnetic resonance imaging (MRI) literature on the effects of prenatal alcohol exposure on the developing human brain.
A literature search was conducted through the following databases: PubMed, PsycINFO and Google Scholar. Combinations of the following search terms and keywords were used to identify relevant studies: 'alcohol', 'fetal alcohol spectrum disorders', 'fetal alcohol syndrome', 'FAS', 'FASD', 'MRI', 'DTI', 'MRS', 'neuroimaging', 'children' and 'infants'.
A total of 64 relevant articles were identified across all modalities. Overall, studies reported smaller total brain volume as well as smaller volume of both the white and grey matter in specific cortical regions. The most consistently reported structural MRI findings were alterations in the shape and volume of the corpus callosum, as well as smaller volume in the basal ganglia and hippocampi. The most consistent finding from diffusion tensor imaging studies was lower fractional anisotropy in the corpus callosum. Proton magnetic resonance spectroscopy studies are few to date, but showed altered neurometabolic profiles in the frontal and parietal cortex, thalamus and dentate nuclei. Resting-state functional MRI studies reported reduced functional connectivity between cortical and deep grey matter structures. Discussion There is a critical gap in the literature of MRI studies in alcohol-exposed children under 5 years of age across all MRI modalities. The dynamic nature of brain maturation and appreciation of the effects of alcohol exposure on the developing trajectory of the structural and functional network argue for the prioritisation of studies that include a longitudinal approach to understanding this spectrum of effects and potential therapeutic time points.
No preview · Article · Mar 2015 · Acta Neuropsychiatrica
[Show abstract][Hide abstract] ABSTRACT: The 83rd Annual Meeting of the American Association of Physical Anthropologists (2014)
Biological resources for genomic investigation in vervet monkey (Chlorocebus)
ANNA J. JASINSKA1, CHRISTOPHER A. SCHMITT1, DONGZHU MA2, YU HUANG1, HANNES SVARDAL3, JESSICA WASSERCHEID4, J. PAUL GROBLER5, MATHEW JORENSEN6, MICHAELA MULLER-TRUTWIN7, MARTIN ANTONIO8, KEN DEWAR4, WESLEY WARREN9, GEORGE WEINSTOCK9, IVONA PANDREA2, CRISTIAN APETREI2, MAGNUS NORDBORG3, ROGER WOODS10, DAVID JENTSCH11, TRUDY TURNER12,5 and NELSON FREIMER1.
1Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, 2Center for Vaccine Research, University of Pittsburgh, Pittsburgh, Pennsylvania USA, 3Gregor Mendel Institute, Austrian Academy of Sciences, Vienna, Austria, 4McGill University and Genome Quebec Innovation Centre, Montréal, Canada, 5Department of Genetics, University of the Free State, Bloemfontein, South Africa, 6Department of Pathology, Section on Comparative Medicine, Wake Forest School of Medicine, Winston-Salem, NC, 7Virology Department, Institut Pasteur, Paris, France, 8Medical Research Council, Fajara, The Gambia, 9The Genome Institute at Washington, University in St. Louis, 10Department of Neurology, University of California, Los Angeles, 11Department of Psychology, University of California, Los Angeles, 12Department of Anthropology, University of Wisconsin-Milwaukee, Milwaukee
The vervet monkey (Chlorocebus) is widely used as a model species in biomedical research. The utility of this species for investigations relevant to human health is twofold. First, extensive conservation between vervets and humans at the genomic, behavioral, and physiological levels makes the vervet excellent for studying the phenotypes involved in human diseases. Second, several adaptive traits relevant to disease resistance (e.g., SIV/AIDS) have emerged in vervets, providing the opportunity to better understand the biological mechanisms of protection against these diseases. To maximize this species’ utility for investigations relevant to human health, we created extensive biomaterial and data resources from more than 1,200 captive and 1,500 wild vervets handled by the UCLA Systems Biology Sample Repository (SBSR). To facilitate correlational studies between phenotypes and genomic mechanisms, we created the vervet genomic assembly (available through NCBI), assessed various phenotypes, and employed state of the art approaches to comprehensively characterize the vervet genome [using whole genome sequencing (WGS)] in 728 captive vervets and 130 wild vervets from major African subspecies and Caribbean populations. We also assessed the transcriptomes [using microarrays and RNA-sequencing (RNA-seq)] in over 400 vervets. Using these resources, we identified the genetic loci and transcriptomic networks associated with brain neuroanatomy, behavior, and handling of SIV/AIDS. In conclusion, the UCLA SBSR resources from vervets that have been extensively sampled, and genetically and phenotypically characterized, facilitate genomic investigations in this model species. Investigators interested in specific phenotypes can assess them in SBSR samples and relate them to existing phenotypic and genomic data.
This work was supported by the National Institutes of Health and Genome Quebec; and Genome Canada.
[Show abstract][Hide abstract] ABSTRACT: Whether plasticity of white matter (WM) microstructure relates to therapeutic response in major depressive disorder (MDD) remains uncertain. We examined diffusion tensor imaging (DTI) correlates of WM structural connectivity in patients receiving electroconvulsive therapy (ECT), a rapidly acting treatment for severe MDD. Tract-Based Spatial Statistics (TBSS) applied to DTI data (61 directions, 2.5 mm(3) voxel size) targeted voxel-level changes in fractional anisotropy (FA), and radial (RD), axial (AD) and mean diffusivity (MD) in major WM pathways in MDD patients (n=20, mean age: 41.15 years, 10.32 s.d.) scanned before ECT, after their second ECT and at transition to maintenance therapy. Comparisons made at baseline with demographically similar controls (n=28, mean age: 39.42 years, 12.20 s.d.) established effects of diagnosis. Controls were imaged twice to estimate scanning-related variance. Patients showed significant increases of FA in dorsal fronto-limbic circuits encompassing the anterior cingulum, forceps minor and left superior longitudinal fasciculus between baseline and transition to maintenance therapy (P<0.05, corrected). Decreases in RD and MD were observed in overlapping regions and the anterior thalamic radiation (P<0.05, corrected). Changes in DTI metrics associated with therapeutic response in tracts showing significant ECT effects differed between patients and controls. All measures remained stable across time in controls. Altered WM microstructure in pathways connecting frontal and limbic areas occur in MDD, are modulated by ECT and relate to therapeutic response. Increased FA together with decreased MD and RD, which trend towards normative values with treatment, suggest increased fiber integrity in dorsal fronto-limbic pathways involved in mood regulation.
[Show abstract][Hide abstract] ABSTRACT: Reductions in brain volumes represent a neurobiological signature of fetal alcohol spectrum disorders (FASD). Less clear is how regional brain tissue reductions differ after normalizing for brain size differences linked with FASD and whether these profiles can predict the degree of prenatal exposure to alcohol. To examine associations of regional brain tissue excesses/deficits with degree of prenatal alcohol exposure and diagnosis with and without correction for overall brain volume, tensor-based morphometry (TBM) methods were applied to structural imaging data from a well-characterized, demographically homogeneous sample of children diagnosed with FASD (n = 39, 9.6–11.0 years) and controls (n = 16, 9.5–11.0 years). Degree of prenatal alcohol exposure was significantly associated with regionally pervasive brain tissue reductions in: (1) thalamus, midbrain, and ventromedial frontal lobe, (2) superior cerebellum and inferior occipital lobe, (3) dorsolateral frontal cortex, and (4) precuneus and superior parietal lobule. When overall brain size was factored out of the analysis on a subject-by-subject basis, no regions showed significant associations with alcohol exposure. FASD diagnosis was associated with a similar deformation pattern, but few of the regions survived FDR correction. In data-driven independent component analyses (ICA) regional brain tissue deformations successfully distinguished individuals based on extent of prenatal alcohol exposure and to a lesser degree, diagnosis. The greater sensitivity of the continuous measure of alcohol exposure compared with the categorical diagnosis across diverse brain regions, underscores the dose dependence of these effects. The ICA results illustrate that profiles of brain tissue alterations may be a useful indicator of prenatal alcohol exposure when reliable historical data are not available and facial features are not apparent.
[Show abstract][Hide abstract] ABSTRACT: Nonhuman primates (NHP) provide crucial biomedical model systems intermediate between rodents and humans. The vervet monkey
(also called the African green monkey) is a widely used NHP model that has unique value for genetic and genomic investigations
of traits relevant to human diseases. This article describes the phylogeny and population history of the vervet monkey and
summarizes the use of both captive and wild vervet monkeys in biomedical research. It also discusses the effort of an international
collaboration to develop the vervet monkey as the most comprehensively phenotypically and genomically characterized NHP, a
process that will enable the scientific community to employ this model for systems biology investigations.
Full-text · Article · Nov 2013 · ILAR journal / National Research Council, Institute of Laboratory Animal Resources
[Show abstract][Hide abstract] ABSTRACT: Purpose: To quantify in vivo GABA concentration levels using a novel parametric proton magnetic resonance signal quantification algorithm called the Fast Pade Transform. Methods: Single voxel MEGA‐PRESS data were collected on a Siemens 3T Tim Trio system using 12‐channel phased‐array head coil (TE=68 ms, TR=2000 ms, Voxel size=30×30×30 mm3, Vector size=1024, NEX=64). Both water reference and water suppressed spectra were obtained. A total of three phantoms (containing NAA, Cr, Cho, GABA, and Lac) were created with different GABA concentration levels of 1 mMol, 2 mMol and 3 mMol. In vivo data were collected from the anterior cingulate cortex region in 5 human volunteers. The fast Pade transform algorithm was implemented in MATLAB. Spectral data were processed with this FPT program to obtain parametric information such as frequency, line‐width, phase and amplitude. GABA concentration levels were calculated using the ratio of metabolite and water amplitude information, since signal amplitudes are directly proportional to the amount of protons present in the acquisition volume. Results: The results suggest that the Fast Pade Transform algorithm measured GABA concentrations in phantoms are very close to the actual known values. And this method is capable of quantifying in vivo MEGA‐PRESS proton spectra in 5 human brain data with a mean measurement of 2.01 mMol, which agrees with literature reported human brain in vivo GABA concentration level. Conclusion: This work demonstrates the potential of the fast Pade transform technique to quantify the GABA C‐4 doublet resonance signals with the MEGA‐PRESS acquisition. We plan to test this method with more in vivo data as well as with other MRS acquisition techniques in the future. NIH funding – R01MH092301