Randomized comparisons among health informatics students identify hypertutorial features as improving web-based instruction.

Hypertutorials optimize five features - presentation, learner control, practice, feedback, and elaborative learning resources. Previous research showed graduate students significantly and overwhelmingly preferred Web-based hypertutorials to conventional "Book-on-the-Web" statistics or research design lessons. The current report shows that the source of hypertutorials' superiority in student evaluations of instruction lies in their hypertutorial features. Randomized comparisons between the two methodologies were conducted in two successive iterations of a graduate level health informatics research design and evaluation course. The two versions contained the same text and graphics, but differed in the presence or absence of hypertutorial features: Elaborative learning resources, practice, feedback, and amount of learner control. Students gave high evaluations to both Web-based methodologies, but consistently rated the hypertutorial lessons as superior. Significant differences localized in the hypertutorial subscale that measured student responses to hypertutorial features.

Using technology to teach technology: design and evaluation of bilingual online physician education about electronic medical records.

The "EMR Tutorial" is designed to be a bilingual online physician education environment about electronic medical records. After iterative assessment and redesign, the tutorial was tested in two groups: U.S. physicians and Mexican medical students. Split-plot ANOVA revealed significantly different pre-test scores in the two groups, significant cognitive gains for the two groups overall, and no significant difference in the gains made by the two groups. Users rated the module positively on a satisfaction questionnaire.

An Innovative Approach to Impacting Student Academic Achievement and Attitudes: Pilot Study of the HEADS UP Virtual Molecular Biology Lab

Introduction: The Virtual Molecular Biology Lab is an innovative, computer-based educational program designed to teach advanced high school biology students how to create a transgenic mouse model in a simulated laboratory setting. It was created in an effort to combat the current decrease in adolescent enthusiasm for and academic achievement in science and science careers, especially in Hispanic students. Because studies have found that hands-on learning, particularly computer-based instruction, is effective in enhancing science achievement, the Virtual Lab is a potential tool for increasing the number of Hispanic students that choose to enter science fields. [See PDF for complete abstract]

Sustained attention in children with two etiologies of early hydrocephalus.

Several studies have shown that children with spina bifida meningomyelocele (SBM) and hydrocephalus have attention problems on parent ratings and difficulties in stimulus orienting associated with a posterior brain attention system. Less is known about response control and inhibition associated with an anterior brain attention system. Using the Gordon Vigilance Task (Gordon, 1983), we studied error rate, reaction time, and performance over time for sustained attention, a key anterior attention function, in 101 children with SBM, 17 with aqueductal stenosis (AS; another condition involving congenital hydrocephalus), and 40 typically developing controls (NC). In SBM, we investigated the relation between cognitive attention and parent ratings of inattention and hyperactivity and explored the impact of medical variables. Children with SBM did not differ from AS or NC groups on measures of sustained attention, but they committed more errors and responded more slowly. Approximately one-third of the SBM group had attention symptoms, although parent attention ratings were not associated with task performance. Hydrocephalus does not account for the attention profile of children with SBM, which also reflects the distinctive brain dysmorphologies associated with this condition.

Heart rate variability in response to pain stimulus in VLBW infants followed longitudinally during NICU stay.

The objective of this longitudinal study, conducted in a neonatal intensive care unit, was to characterize the response to pain of high-risk very low birth weight infants (<1,500 g) from 23 to 38 weeks post-menstrual age (PMA) by measuring heart rate variability (HRV). Heart period data were recorded before, during, and after a heel lanced or wrist venipunctured blood draw for routine clinical evaluation. Pain response to the blood draw procedure and age-related changes of HRV in low-frequency and high-frequency bands were modeled with linear mixed-effects models. HRV in both bands decreased during pain, followed by a recovery to near-baseline levels. Venipuncture and mechanical ventilation were factors that attenuated the HRV response to pain. HRV at the baseline increased with post-menstrual age but the growth rate of high-frequency power was reduced in mechanically ventilated infants. There was some evidence that low-frequency HRV response to pain improved with advancing PMA.

Generalized fuzzy clustering for segmentation of multi-spectral magnetic resonance images.

An integrated approach for multi-spectral segmentation of MR images is presented. This method is based on the fuzzy c-means (FCM) and includes bias field correction and contextual constraints over spatial intensity distribution and accounts for the non-spherical cluster's shape in the feature space. The bias field is modeled as a linear combination of smooth polynomial basis functions for fast computation in the clustering iterations. Regularization terms for the neighborhood continuity of intensity are added into the FCM cost functions. To reduce the computational complexity, the contextual regularizations are separated from the clustering iterations. Since the feature space is not isotropic, distance measure adopted in Gustafson-Kessel (G-K) algorithm is used instead of the Euclidean distance, to account for the non-spherical shape of the clusters in the feature space. These algorithms are quantitatively evaluated on MR brain images using the similarity measures.

Temporal lobe white matter asymmetry and language laterality in epilepsy patients.

Recent studies using diffusion tensor imaging (DTI) have advanced our knowledge of the organization of white matter subserving language function. It remains unclear, however, how DTI may be used to predict accurately a key feature of language organization: its asymmetric representation in one cerebral hemisphere. In this study of epilepsy patients with unambiguous lateralization on Wada testing (19 left and 4 right lateralized subjects; no bilateral subjects), the predictive value of DTI for classifying the dominant hemisphere for language was assessed relative to the existing standard-the intra-carotid Amytal (Wada) procedure. Our specific hypothesis is that language laterality in both unilateral left- and right-hemisphere language dominant subjects may be predicted by hemispheric asymmetry in the relative density of three white matter pathways terminating in the temporal lobe implicated in different aspects of language function: the arcuate (AF), uncinate (UF), and inferior longitudinal fasciculi (ILF). Laterality indices computed from asymmetry of high anisotropy AF pathways, but not the other pathways, classified the majority (19 of 23) of patients using the Wada results as the standard. A logistic regression model incorporating information from DTI of the AF, fMRI activity in Broca's area, and handedness was able to classify 22 of 23 (95.6%) patients correctly according to their Wada score. We conclude that evaluation of highly anisotropic components of the AF alone has significant predictive power for determining language laterality, and that this markedly asymmetric distribution in the dominant hemisphere may reflect enhanced connectivity between frontal and temporal sites to support fluent language processes. Given the small sample reported in this preliminary study, future research should assess this method on a larger group of patients, including subjects with bi-hemispheric dominance.

Diffusion tensor imaging of cocaine-treated rodents.

Studies in cocaine-dependent human subjects have shown differences in white matter on diffusion tensor imaging (DTI) compared with non-drug-using controls. It is not known whether the differences in fractional anisotropy (FA) seen on DTI in white matter regions of cocaine-dependent humans result from a pre-existing predilection for drug use or purely from cocaine abuse. To study the effect of cocaine on brain white matter, DTI was performed on 24 rats after continuous infusion of cocaine or saline for 4 weeks, followed by brain histology. Voxel-based morphometry analysis showed an 18% FA decrease in the splenium of the corpus callosum (CC) in cocaine-treated animals relative to saline controls. On histology, significant increase in neurofilament expression (125%) and decrease in myelin basic protein (40%) were observed in the same region in cocaine-treated animals. This study supports the hypothesis that chronic cocaine use alters white matter integrity in human CC. Unlike humans, where the FA in the genu differed between cocaine users and non-users, the splenium was affected in rats. These differences between rodent and human findings could be due to several factors that include differences in the brain structure and function between species and/or the dose, timing, and duration of cocaine administration.

Improved cerebellar tissue classification on magnetic resonance images of brain.

PURPOSE: To develop and implement a method for improved cerebellar tissue classification on the MRI of brain by automatically isolating the cerebellum prior to segmentation. MATERIALS AND METHODS: Dual fast spin echo (FSE) and fluid attenuation inversion recovery (FLAIR) images were acquired on 18 normal volunteers on a 3 T Philips scanner. The cerebellum was isolated from the rest of the brain using a symmetric inverse consistent nonlinear registration of individual brain with the parcellated template. The cerebellum was then separated by masking the anatomical image with individual FLAIR images. Tissues in both the cerebellum and rest of the brain were separately classified using hidden Markov random field (HMRF), a parametric method, and then combined to obtain tissue classification of the whole brain. The proposed method for tissue classification on real MR brain images was evaluated subjectively by two experts. The segmentation results on Brainweb images with varying noise and intensity nonuniformity levels were quantitatively compared with the ground truth by computing the Dice similarity indices. RESULTS: The proposed method significantly improved the cerebellar tissue classification on all normal volunteers included in this study without compromising the classification in remaining part of the brain. The average similarity indices for gray matter (GM) and white matter (WM) in the cerebellum are 89.81 (+/-2.34) and 93.04 (+/-2.41), demonstrating excellent performance of the proposed methodology. CONCLUSION: The proposed method significantly improved tissue classification in the cerebellum. The GM was overestimated when segmentation was performed on the whole brain as a single object.

Perfusion in rat brain at 7 T with arterial spin labeling using FAIR-TrueFISP and QUIPSS.

Measurement of perfusion in longitudinal studies allows for the assessment of tissue integrity and the detection of subtle pathologies. In this work, the feasibility of measuring brain perfusion in rats with high spatial resolution using arterial spin labeling is reported. A flow-sensitive alternating recovery sequence, coupled with a balanced gradient fast imaging with steady-state precession readout section was used to minimize ghosting and geometric distortions, while achieving high signal-to-noise ratio. The quantitative imaging of perfusion using a single subtraction method was implemented to address the effects of variable transit delays between the labeling of spins and their arrival at the imaging slice. Studies in six rats at 7 T showed good perfusion contrast with minimal geometric distortion. The measured blood flow values of 152.5+/-6.3 ml/100 g per minute in gray matter and 72.3+/-14.0 ml/100 g per minute in white matter are in good agreement with previously reported values based on autoradiography, considered to be the gold standard.

Quantification of the spatiotemporal microstructural organization of the human brain association, projection and commissural pathways across the lifespan using diffusion tensor tractography.

Using diffusion tensor tractography, we quantified the microstructural changes in the association, projection, and commissural compact white matter pathways of the human brain over the lifespan in a cohort of healthy right-handed children and adults aged 6-68 years. In both males and females, the diffusion tensor radial diffusivity of the bilateral arcuate fasciculus, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, uncinate fasciculus, corticospinal, somatosensory tracts, and the corpus callosum followed a U-curve with advancing age; fractional anisotropy in the same pathways followed an inverted U-curve. Our study provides useful baseline data for the interpretation of data collected from patients.

Cryo-EM model of the bullet-shaped vesicular stomatitis virus.

Vesicular stomatitis virus (VSV) is a bullet-shaped rhabdovirus and a model system of negative-strand RNA viruses. Through direct visualization by means of cryo-electron microscopy, we show that each virion contains two nested, left-handed helices: an outer helix of matrix protein M and an inner helix of nucleoprotein N and RNA. M has a hub domain with four contact sites that link to neighboring M and N subunits, providing rigidity by clamping adjacent turns of the nucleocapsid. Side-by-side interactions between neighboring N subunits are critical for the nucleocapsid to form a bullet shape, and structure-based mutagenesis results support this description. Together, our data suggest a mechanism of VSV assembly in which the nucleocapsid spirals from the tip to become the helical trunk, both subsequently framed and rigidified by the M layer.

Organization of hue selectivity in macaque V2 thin stripes.

V2 has long been recognized to contain functionally distinguishable compartments that are correlated with the stripelike pattern of cytochrome oxidase activity. Early electrophysiological studies suggested that color, direction/disparity, and orientation selectivity were largely segregated in the thin, thick, and interstripes, respectively. Subsequent studies revealed a greater degree of homogeneity in the distribution of response properties across stripes, yet color-selective cells were still found to be most prevalent in the thin stripes. Optical recording studies have demonstrated that thin stripes contain both color-preferring and luminance-preferring modules. These thin stripe color-preferring modules contain spatially organized hue maps, whereas the luminance-preferring modules contain spatially organized luminance-change maps. In this study, the neuronal basis of these hue maps was determined by characterizing the selectivity of neurons for isoluminant hues in multiple penetrations within previously characterized V2 thin stripe hue maps. The results indicate that neurons within the superficial layers of V2 thin stripe hue maps are organized into columns whose aggregated hue selectivity is closely related to the hue selectivity of the optically defined hue maps. These data suggest that thin stripes contain hue maps not simply because of their moderate percentage of hue-selective neurons, but because of the columnar and tangential organization of hue selectivity.

Symmetric inverse consistent nonlinear registration driven by mutual information.

A nonlinear viscoelastic image registration algorithm based on the demons paradigm and incorporating inverse consistent constraint (ICC) is implemented. An inverse consistent and symmetric cost function using mutual information (MI) as a similarity measure is employed. The cost function also includes regularization of transformation and inverse consistent error (ICE). The uncertainties in balancing various terms in the cost function are avoided by alternatively minimizing the similarity measure, the regularization of the transformation, and the ICE terms. The diffeomorphism of registration for preventing folding and/or tearing in the deformation is achieved by the composition scheme. The quality of image registration is first demonstrated by constructing brain atlas from 20 adult brains (age range 30-60). It is shown that with this registration technique: (1) the Jacobian determinant is positive for all voxels and (2) the average ICE is around 0.004 voxels with a maximum value below 0.1 voxels. Further, the deformation-based segmentation on Internet Brain Segmentation Repository, a publicly available dataset, has yielded high Dice similarity index (DSI) of 94.7% for the cerebellum and 74.7% for the hippocampus, attesting to the quality of our registration method.

Volume and shape in feature space on adaptive FCM in MRI segmentation.

Intensity non-uniformity (bias field) correction, contextual constraints over spatial intensity distribution and non-spherical cluster's shape in the feature space are incorporated into the fuzzy c-means (FCM) for segmentation of three-dimensional multi-spectral MR images. The bias field is modeled by a linear combination of smooth polynomial basis functions for fast computation in the clustering iterations. Regularization terms for the neighborhood continuity of either intensity or membership are added into the FCM cost functions. Since the feature space is not isotropic, distance measures, other than the Euclidean distance, are used to account for the shape and volumetric effects of clusters in the feature space. The performance of segmentation is improved by combining the adaptive FCM scheme with the criteria used in Gustafson-Kessel (G-K) and Gath-Geva (G-G) algorithms through the inclusion of the cluster scatter measure. The performance of this integrated approach is quantitatively evaluated on normal MR brain images using the similarity measures. The improvement in the quality of segmentation obtained with our method is also demonstrated by comparing our results with those produced by FSL (FMRIB Software Library), a software package that is commonly used for tissue classification.