Alterations in white matter microstructure in neurofibromatosis-1.

Neurofibromatosis (NF1) represents the most common single gene cause of learning disabilities. NF1 patients have impairments in frontal lobe based cognitive functions such as attention, working memory, and inhibition. Due to its well-characterized genetic etiology, investigations of NF1 may shed light on neural mechanisms underlying such difficulties in the general population or other patient groups. Prior neuroimaging findings indicate global brain volume increases, consistent with neural over-proliferation. However, little is known about alterations in white matter microstructure in NF1. We performed diffusion tensor imaging (DTI) analyses using tract-based spatial statistics (TBSS) in 14 young adult NF1 patients and 12 healthy controls. We also examined brain volumetric measures in the same subjects. Consistent with prior studies, we found significantly increased overall gray and white matter volume in NF1 patients. Relative to healthy controls, NF1 patients showed widespread reductions in white matter integrity across the entire brain as reflected by decreased fractional anisotropy (FA) and significantly increased absolute diffusion (ADC). When radial and axial diffusion were examined we found pronounced differences in radial diffusion in NF1 patients, indicative of either decreased myelination or increased space between axons. Secondary analyses revealed that FA and radial diffusion effects were of greatest magnitude in the frontal lobe. Such alterations of white matter tracts connecting frontal regions could contribute to the observed cognitive deficits. Furthermore, although the cellular basis of these white matter microstructural alterations remains to be determined, our findings of disproportionately increased radial diffusion against a background of increased white matter volume suggest the novel hypothesis that one potential alteration contributing to increased cortical white matter in NF1 may be looser packing of axons, with or without myelination changes. Further, this indicates that axial and radial diffusivity can uniquely contribute as markers of NF1-associated brain pathology in conjunction with the typically investigated measures

Multiplex Networks to Characterize Seizure Development in Traumatic Brain Injury Patients

Traumatic brain injury (TBI) may cause secondary debilitating problems, such as post-traumatic epilepsy (PTE), which occurs with unprovoked recurrent seizures, months or even years after TBI. Currently, the Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) has been enrolling moderate-severe TBI patients with the goal to identify biomarkers of epileptogenesis that may help to prevent seizure occurrence and better understand the mechanism underlying PTE. In this work, we used a novel complex network approach based on segmenting T1-weighted Magnetic Resonance Imaging (MRI) scans in patches of the same dimension (network nodes) and measured pairwise patch similarities using Pearson's correlation (network connections). This network model allowed us to obtain a series of single and multiplex network metrics to comprehensively analyze the different interactions between brain components and capture structural MRI alterations related to seizure development. We used these complex network features to train a Random Forest (RF) classifier and predict, with an accuracy of 70 and a 95% confidence interval of [67, 73%], which subjects from EpiBioS4Rx have had at least one seizure after a TBI. This complex network approach also allowed the identification of the most informative scales and brain areas for the discrimination between the two clinical groups: seizure-free and seizure-affected subjects, demonstrating to be a promising pilot study which, in the future, may serve to identify and validate biomarkers of PTE

Dysregulation of specialized delay/interference-dependent working memory following loss of dysbindin-1A in schizophrenia-related phenotypes

Dysbindin-1, a protein that regulates aspects of early and late brain development, has been implicated in the pathobiology of schizophrenia. As the functional roles of the three major isoforms of dysbindin-1, (A, B, and C) remain unknown, we generated a novel mutant mouse, dys-1A -/-, with selective loss of dysbindin-1A and investigated schizophrenia-related phenotypes in both males and females. Loss of dysbindin-1A resulted in heightened initial exploration and disruption in subsequent habituation to a novel environment, together with heightened anxiety-related behavior in a stressful environment. Loss of dysbindin-1A was not associated with disruption of either long-term (olfactory) memory or spontaneous alternation behavior. However, dys-1A -/-showed enhancement in delay-dependent working memory under high levels of interference relative to controls, ie, impairment in sensitivity to the disruptive effect of such interference. These findings in dys-1A -/-provide the first evidence for differential functional roles for dysbindin-1A vs dysbindin-1C isoforms among phenotypes relevant to the pathobiology of schizophrenia. Future studies should investigate putative sex differences in these phenotypic effects

Voxelwise analysis of radial diffusion, at a threshold of p<.05 and p<.005.

<p>Green colors reflect increased radial diffusion in the NF1 group.</p

Differences in Fractional Anisotropy (NF1 Patients vs. Controls).

<p>Region of interest based FA analysis.</p

Voxelwise analysis of axial diffusion, at a threshold of p<.05 and p<.005.

<p>Brown colors reflect increased axial diffusion in the NF1 group.</p

Voxelwise analysis of ADC, at a threshold of p<.05 and p<.005.

<p>Blue colors reflect increased ADC in the NF1 group.</p

Voxelwise analysis of FA, at a threshold of p<.05 (left) and p<.005 (right).

<p>Red colors reflect areas of decreased FA in the NF1 group.</p

DTI diagram showing radial diffusion, axial diffusion and ADC as related to FA.

<p>DTI diagram showing radial diffusion, axial diffusion and ADC as related to FA.</p

Demographics.

*<p>IQ data was only available for 8/12 control subjects.</p>**<p>Race and ethnicity statistics were calculated for Caucasian vs non-Caucasian subjects.</p