Unified Heat Kernel Regression for Diffusion, Kernel Smoothing and Wavelets on Manifolds and Its Application to Mandible Growth Modeling in CT Images

We present a novel kernel regression framework for smoothing scalar surface data using the Laplace-Beltrami eigenfunctions. Starting with the heat kernel constructed from the eigenfunctions, we formulate a new bivariate kernel regression framework as a weighted eigenfunction expansion with the heat kernel as the weights. The new kernel regression is mathematically equivalent to isotropic heat diffusion, kernel smoothing and recently popular diffusion wavelets. Unlike many previous partial differential equation based approaches involving diffusion, our approach represents the solution of diffusion analytically, reducing numerical inaccuracy and slow convergence. The numerical implementation is validated on a unit sphere using spherical harmonics. As an illustration, we have applied the method in characterizing the localized growth pattern of mandible surfaces obtained in CT images from subjects between ages 0 and 20 years by regressing the length of displacement vectors with respect to the template surface.Comment: Accepted in Medical Image Analysi

DramaQA: Character-Centered Video Story Understanding with Hierarchical QA

Despite recent progress on computer vision and natural language processing, developing video understanding intelligence is still hard to achieve due to the intrinsic difficulty of story in video. Moreover, there is not a theoretical metric for evaluating the degree of video understanding. In this paper, we propose a novel video question answering (Video QA) task, DramaQA, for a comprehensive understanding of the video story. The DramaQA focused on two perspectives: 1) hierarchical QAs as an evaluation metric based on the cognitive developmental stages of human intelligence. 2) character-centered video annotations to model local coherence of the story. Our dataset is built upon the TV drama "Another Miss Oh" and it contains 16,191 QA pairs from 23,928 various length video clips, with each QA pair belonging to one of four difficulty levels. We provide 217,308 annotated images with rich character-centered annotations, including visual bounding boxes, behaviors, and emotions of main characters, and coreference resolved scripts. Additionally, we provide analyses of the dataset as well as Dual Matching Multistream model which effectively learns character-centered representations of video to answer questions about the video. We are planning to release our dataset and model publicly for research purposes and expect that our work will provide a new perspective on video story understanding research.Comment: 21 pages, 10 figures, submitted to ECCV 202

Association Between Visceral Fat and Brain Cortical Thickness in the Elderly: A Neuroimaging Study

BackgroundDespite emerging evidence suggesting that visceral fat may play a major role in obesity-induced neurodegeneration, little evidence exists on the association between visceral fat and brain cortical thickness in the elderly.PurposeWe aimed to examine the association between abdominal fat and brain cortical thickness in a Korean elderly population.MethodsThis cross-sectional study included elderly individuals without dementia (n = 316). Areas of visceral fat and subcutaneous fat (cm2) were estimated from computed tomography scans. Regional cortical thicknesses (mm) were obtained by analyzing brain magnetic resonance images. Given the inverted U-shaped relationship between visceral fat area and global cortical thickness (examined using a generalized additive model), visceral fat area was categorized into quintiles, with the middle quintile being the reference group. A generalized linear model was built to explore brain regions associated with visceral fat. The same approach was used for subcutaneous fat.ResultsThe mean (standard deviation) age was 67.6 (5.0) years. The highest quintile (vs. the middle quintile) group of visceral fat area had reduced cortical thicknesses in the global [β = –0.04 mm, standard error (SE) = 0.02 mm, p = 0.004], parietal (β = –0.04 mm, SE = 0.02 mm, p = 0.01), temporal (β = –0.05 mm, SE = 0.02 mm, p = 0.002), cingulate (β = –0.06 mm, SE = 0.02 mm, p = 0.01), and insula lobes (β = –0.06 mm, SE = 0.03 mm, p = 0.02). None of the regional cortical thicknesses significantly differed between the highest and the middle quintile groups of subcutaneous fat area.ConclusionThe findings suggest that a high level of visceral fat, but not subcutaneous fat, is associated with a reduced cortical thickness in the elderly

The relationship between dopamine receptor blockade and cognitive performance in schizophrenia: A [C-11]-raclopride PET study with aripiprazole

Aripiprazole's effects on cognitive function in patients with schizophrenia are unclear because of the difficulty in disentangling specific effects on cognitive function from secondary effects due to the improvement in other schizophrenic symptoms. One approach to address this is to use an intermediate biomarker to investigate the relationship between the drug's effect on the brain and change in cognitive function. This study aims to investigate aripiprazole's effect on working memory by determining the correlation between dopamine D2/3 (D2/3) receptor occupancy and working memory of patients with schizophrenia. Seven patients with schizophrenia participated in the study. Serial positron emission tomography (PET) scans with [C-11] raclopride were conducted at 2, 26, and 74 h after the administration of aripiprazole. The subjects performed the N-back task just after finishing the [C-11] raclopride PET scan. The mean (+/- SD) D2/3 receptor occupancies were 66.9 +/- 6.7% at 2 h, 65.0 +/- 8.6% at 26, and 57.7 +/- 11.2% at 74 h after administering aripiprazole. Compared with performance on the zero-back condition, performance in memory-loaded conditions (one-, two-, and three-back conditions) was significantly related to D2/3 receptor occupancy by aripiprazole (error rate: beta = -2.236, t = -6.631, df = 53.947, and p = 0.001; reaction time: beta = -9.567, t = -2.808, df = 29.967, and p = 0.009). Although the sample size was relatively small, these results suggest that aripiprazole as a dopamine-partial agonist could improve cognitive function in patients with schizophrenia.Y

Characterization of exosomal microRNAs in preterm infants fed with breast milk and infant formula

Breastfeeding not only reduces infection-related morbidity, but also increases growth of preterm infants. Advantages of breast milk (BM) for preterm infants are significant. They continue to be studied. However, because not all preterm infants can receive breastfeeding, bovine-based infant formula (IF) is used as an alternative, which may increase the risk of several preterm complications. Exosomes isolated from biofluids are emerging as biomarkers in research of various diseases. Here, we characterized miRNA contents of exosomes in urine and serum samples of preterm infants who were BM and IF fed and performed transcriptomic analysis of small RNA libraries. We identified significantly up-regulated 6 miRNAs and 10 miRNAs, respectively. Gene Ontology (GO) analysis revealed that target genes of these miRNAs might participate in neuronal development, immunity modulation, detoxification of reactive oxygen species, and transmembrane exchange. Our data suggest that exosome-based systemic screening for preterm infants with breastfeeding might be a screening tool for identifying target molecules involved in therapy for preterm infants in neonatal intensive care unit (NICU) and for future application as nutraceutical formulations or pharmaceuticals

LAPLACE-BELTRAMI EIGENFUNCTION EXPANSION OF CORTICAL MANIFOLDS

We represent a shape representation technique using the eigenfunctions of Laplace-Beltrami operator and compare the performance with the conventional spherical harmonic (SPHARM) representation. Cortical manifolds are represented as a linear combination of the Laplace-Beltrami eigenfunctions, which form orthonormal basis. Since the Laplace-Beltrami eigenfunctions reflect the intrinsic geometry of the manifolds, the new representation is supposed to more compactly represent the manifolds and outperform SPHARM representation. However, this is not demonstrated yet in brain imaging data. We demonstrate the superior reconstruction capability of the Laplace-Beltrami eigenfunction representation using cortical and amygdala surfaces as examples. Index Terms — Amygdala, cortical surface, Fourier representation, Laplace-Beltrami eigenfunctions, spherical harmonic