Faculty Bibliography

Reelin, an extracellular protein essential for neural migration and lamination, is also expressed in the adult brain. To unravel the function of this protein in the adult forebrain, we generated transgenic mice that overexpress Reelin under the control of the CaMKIIalpha promoter. Overexpression of Reelin increased adult neurogenesis and impaired the migration and positioning of adult-generated neurons. In the hippocampus, the overexpression of Reelin resulted in an increase in synaptic contacts and hypertrophy of dendritic spines. Induction of long-term potentiation (LTP) in alert-behaving mice showed that Reelin overexpression evokes a dramatic increase in LTP responses. Hippocampal field EPSP during a classical conditioning paradigm was also increased in these mice. Our results indicate that Reelin levels in the adult brain regulate neurogenesis and migration, as well as the structural and functional properties of synapses. These observations suggest that Reelin controls developmental processes that remain active in the adult brain.

Cross-sectional magnetic resonance imaging (MRI) studies have long hypothesized that the brain in children with autism undergoes an abnormal growth trajectory that includes a period of early overgrowth; however, this has never been confirmed by a longitudinal study. We performed the first longitudinal study of brain growth in toddlers at the time symptoms of autism are becoming clinically apparent using structural MRI scans at multiple time points beginning at 1.5 years up to 5 years of age. We collected 193 scans on 41 toddlers who received a confirmed diagnosis of autistic disorder at approximately 48 months of age and 44 typically developing controls. By 2.5 years of age, both cerebral gray and white matter were significantly enlarged in toddlers with autistic disorder, with the most severe enlargement occurring in frontal, temporal, and cingulate cortices. In the longitudinal analyses, which we accounted for age and gender effect, we found that all regions (cerebral gray, cerebral white, frontal gray, temporal gray, cingulate gray, and parietal gray) except occipital gray developed at an abnormal growth rate in toddlers with autistic disorder that was mainly characterized by a quadratic age effect. Females with autistic disorder displayed a more pronounced abnormal growth profile in more brain regions than males with the disorder. Given that overgrowth clearly begins before 2 years of age, future longitudinal studies would benefit from inclusion of even younger populations as well as further characterization of genetic and other biomarkers to determine the underlying neuropathological processes causing the onset of autistic symptoms

A role for prefrontal cortex has been proposed in systems consolidation of memory. The current study examined the effects of excitotoxic lesions of the orbitofrontal cortex (OFC) in rats on acquisition and remote recall of socially transmitted food preferences (STFP). Subjects received excitotoxic lesions of the OFC, and they were trained on two food preferences. They were tested 1h after the first training session to determine the effect of the lesion on acquisition. The following day, they were trained on a second preference and tested 10 days later to determine the effect of the lesion on remote recall. OFC lesions did not impair either STFP acquisition or remote recall in comparisons with sham-operated animals. In addition, a subset of animals underwent odor discrimination and reversal training. Consistent with previous reports, subjects with OFC lesions required more trials to reach criterion and made more errors during reversal training than did sham-operated animals. Taken together, the results of the present study indicate that the orbitofrontal cortex is not necessary for acquisition or systems consolidation of socially transmitted food preferences.

Understanding myelination in early brain development is of clinical importance, as many neurological disorders have their origin in early cerebral organization and maturation. The goal of this work is to study a large neonate database acquired with standard MR imagery to illuminate effects of early development in MRI. 90 neonates were selected from a study of healthy brain development. Subjects were imaged via MRI postnatally. MR acquisition included high-resolution structural and diffusion tensor images. Unbiased atlases for structural and DTI data were generated and co-registered into a single coordinate frame for voxel-wise comparison of MR and DTI appearance across time. All original datasets were mapped into this frame and structural image data was additionally intensity normalized. In addition, myelinated white matter probabilistic segmentations from our neonate tissue segmentation were mapped into the same space to study how our segmentation results were affected by the changing intensity characteristics in early development Linear regression maps and p-value maps were computed and visualized. The resulting visualization of voxels-wise corresponding maps of all MR and DTI properties captures early development information in MR imagery. Surprisingly, we encountered regions of seemingly decreased myelinated WM probability over time even though we expected a confident increase for all of the brain. The intensity changes in the MR images in those regions help explain this counterintuitive result. The regressional results indicate that this is an effect of intensity changes due not solely to myelination processes but also likely brain dehydration processes in early postnatal development.

Compared to region of interest based DTI analysis, voxel-based analysis gives higher degree of localization and avoids the procedure of manual delineation with the resulting intra and inter-rater variability. One of the major challenges in voxel-wise DTI analysis is to get high quality voxel-level correspondence. For that purpose, current DTI analysis tools are building on nonlinear registration algorithms that deform individual datasets into a template image that is either precomputed or computed as part of the analysis. A variety of matching criteria and deformation schemes have been proposed, but often comparative evaluation is missing. In our opinion, the use of consistent and unbiased measures to evaluate current DTI procedures is of great importance and our work presents two possible measures. Specifically, we propose the evaluation criteria generalization and specificity, originally introduced by the shape modeling community, to evaluate and compare different DTI nonlinear warping results. These measures are of indirect nature and have a population wise view. Both measures incorporate information of the variability of the registration results in the template space via a voxel-wise PCA model. Thus far, we have used these measures to evaluate our own DTI analysis procedure employing fluid-based registration on scalar DTI maps. Generalization and specificity from tensor images in the template space were computed for 8 scalar property maps. We found that for our procedure an intensity-normalized FA feature outperformed the other scalar measurements. Also, using the tensor images rather than the FA maps as a comparison frame seemed to produce more robust results.

The human brain undergoes significant changes in the first few years after birth, but knowledge about this critical period of development is quite limited. Previous neuroimaging studies have been mostly focused on morphometric measures such as volume and shape, although tissue property measures related to the degree of myelination and axon density could also add valuable information to our understanding of brain maturation. Our goal is to complement brain growth analysis via morphometry with the study of longitudinal tissue property changes as reflected in patterns observed in multi-modal structural MRI and DTI. Our preliminary study includes eight healthy pediatric subjects with repeated scans at the age of two weeks, one year, and two years with T1, T2, PD, and DT MRI. Analysis is driven by the registration of multiple modalities and time points within and between subjects into a common coordinate frame, followed by image intensity normalization. Quantitative tractography with diffusion and structural image parameters serves for multi-variate tissue analysis. Different patterns of rapid changes were observed in the corpus callosum and the posterior and anterior internal capsule, structures known for distinctly different myelination growth. There are significant differences in central versus peripheral white matter, and also a wm/gm contrast flip in both T1 and T2 images but not diffusion parameters. We demonstrate that the combined longitudinal analysis of structural and diffusion MRI proves superior to individual modalities and might provide a better understanding of the trajectory of early neurodevelopment.

Diffusion Tensor Imaging (DTI) has become an important MRI procedure to investigate the integrity of white matter in brain in vivo. DTI is estimated from a series of acquired Diffusion Weighted Imaging (DWI) volumes. DWI data suffers from inherent low SNR, overall long scanning time of multiple directional encoding with correspondingly large risk to encounter several kinds of artifacts. These artifacts can be too severe for a correct and stable estimation of the diffusion tensor. Thus, a quality control (QC) procedure is absolutely necessary for DTI studies. Currently, routine DTI QC procedures are conducted manually by visually checking the DWI data set in a gradient by gradient and slice by slice way. The results often suffer from low consistence across different data sets, lack of agreement of different experts, and difficulty to judge motion artifacts by qualitative inspection. Additionally considerable manpower is needed for this step due to the large number of images to QC, which is common for group comparison and longitudinal studies, especially with increasing number of diffusion gradient directions. We present a framework for automatic DWI QC. We developed a tool called DTIPrep which pipelines the QC steps with a detailed protocoling and reporting facility. And it is fully open source. This framework/tool has been successfully applied to several DTI studies with several hundred DWIs in our lab as well as collaborating labs in Utah and Iowa. In our studies, the tool provides a crucial piece for robust DTI analysis in brain white matter study.

Although it is being successfully implemented for exploration of the genome, discovery science has eluded the functional neuroimaging community. The core challenge remains the development of common paradigms for interrogating the myriad functional systems in the brain without the constraints of a priori hypotheses. Resting-state functional MRI (R-fMRI) constitutes a candidate approach capable of addressing this challenge. Imaging the brain during rest reveals large-amplitude spontaneous low-frequency (<0.1 Hz) fluctuations in the fMRI signal that are temporally correlated across functionally related areas. Referred to as functional connectivity, these correlations yield detailed maps of complex neural systems, collectively constituting an individual's 'functional connectome.' Reproducibility across datasets and individuals suggests the functional connectome has a common architecture, yet each individual's functional connectome exhibits unique features, with stable, meaningful interindividual differences in connectivity patterns and strengths. Comprehensive mapping of the functional connectome, and its subsequent exploitation to discern genetic influences and brain-behavior relationships, will require multicenter collaborative datasets. Here we initiate this endeavor by gathering R-fMRI data from 1,414 volunteers collected independently at 35 international centers. We demonstrate a universal architecture of positive and negative functional connections, as well as consistent loci of inter-individual variability. Age and sex emerged as significant determinants. These results demonstrate that independent R-fMRI datasets can be aggregated and shared. High-throughput R-fMRI can provide quantitative phenotypes for molecular genetic studies and biomarkers of developmental and pathological processes in the brain. To initiate discovery science of brain function, the 1000 Functional Connectomes Project dataset is freely accessible at www.nitrc.org/projects/fcon_1000/

As rates of HIV infection increase in adolescents, it is important to provide prevention programs targeting this population. Homeless adolescents living with their families in shelters are at greater risk of participating in risky sexual behavior and incurring negative health outcomes. A family based HIV-prevention pilot study was conducted with eight homeless families in a New York City shelter to explore: 1) the perceived impact of family communication, parental monitoring, family understanding of puberty, STD's and HIV on preventing risky behavior for the participating youth, and 2) the feasibility of conducting such a program within the shelter system. Qualitative and quantitative results indicate increased family communication, parental monitoring and decreased parental depressive symptoms.