Sang H Lee

Nathan Kline Institute, Orangeburg, New York, United States

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Publications (4)12.91 Total impact

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    ABSTRACT: We propose a fused lasso logistic regression to analyze callosal thickness profiles. The fused lasso regression imposes penalties on both the l1-norm of the model coefficients and their successive differences, and finds only a small number of non-zero coefficients which are locally constant. An iterative method of solving logistic regression with fused lasso regularization is proposed to make this a practical procedure. In this study we analyzed callosal thickness profiles sampled at 100 equal intervals between the rostrum and the splenium. The method was applied to corpora callosa of elderly normal controls (NCs) and patients with very mild or mild Alzheimer's disease (AD) from the Open Access Series of Imaging Studies (OASIS) database. We found specific locations in the genu and splenium of AD patients that are proportionally thinner than those of NCs. Callosal thickness in these regions combined with the Mini Mental State Examination scores differentiated AD from NC with 84% accuracy.
    Journal of neuroscience methods 10/2013; · 2.30 Impact Factor
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    ABSTRACT: We propose a new method to test the order between two high-dimensional mean curves. The new statistic extends the approach of Follmann (1996) to high-dimensional data by adapting the strategy of Bai and Saranadasa (1996). The proposed procedure is an alternative to the non-negative basis matrix factorization (NBMF) based test of Lee et al. (2008) for the same hypothesis, but it is much easier to implement. We derive the asymptotic mean and variance of the proposed test statistic under the null hypothesis of equal mean curves. Based on theoretical results, we put forward a permutation procedure to approximate the null distribution of the new test statistic. We compare the power of the proposed test with that of the NBMF-based test via simulations. We illustrate the approach by an application to tidal volume traces.
    Journal of Statistical Planning and Inference 09/2012; 142(9):2719–2725. · 0.71 Impact Factor
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    ABSTRACT: Correctly identifying voxels or regions of interest (ROI) that actively respond to a given stimulus is often an important objective/step in many functional magnetic resonance imaging (fMRI) studies. In this article, we study a nonparametric method to detect active voxels, which makes minimal assumption about the distribution of blood oxygen level-dependent (BOLD) signals. Our proposal has several interesting features. It uses time lagged correlation to take into account the delay in response to the stimulus, due to hemodynamic variations. We introduce an input permutation method (IPM), a type of block permutation method, to approximate the null distribution of the test statistic. Also, we propose to pool the permutation-derived statistics of preselected voxels for a better approximation to the null distribution. Finally, we control multiple testing error rate using the local false discovery rate (FDR) by Efron [Correlation and large-scale simultaneous hypothesis testing. J Am Stat Assoc 102 (2007) 93-103] and Park et al. [Estimation of empirical null using a mixture of normals and its use in local false discovery rate. Comput Stat Data Anal 55 (2011) 2421-2432] to select the active voxels.
    Magnetic Resonance Imaging 07/2012; · 2.06 Impact Factor
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    ABSTRACT: This study was designed to understand molecular and cellular mechanisms underlying aggressive behaviors in mice exposed to repeated interactions in their homecage with conspecifics. A resident-intruder procedure was employed whereby two males were allowed to interact for 10 min trials, and aggressive and/or submissive behaviors (e.g., degree of attacking, biting, chasing, grooming, rearing, or upright posture) were assessed. Following 10 days of behavioral trials, brains were removed and dissected into specific regions including the cerebellum, frontal cortex, hippocampus, midbrain, pons, and striatum. Gene expression analysis was performed using real-time quantitative polymerase-chain reaction (qPCR) for catechol-O-methyltransferase (COMT) and tyrosine hydroxylase (TH). Compared to naive control mice, significant up regulation of COMT expression of residents was observed in the cerebellum, frontal cortex, hippocampus, midbrain, and striatum; in all of these brain regions the COMT expression of residents was also significantly higher than that of intruders. The intruders also had a significant down regulation (compared to naive control mice) within the hippocampus, indicating a selective decrease in COMT expression in the hippocampus of submissive subjects. Immunoblot analysis confirmed COMT up regulation in the midbrain and hippocampus of residents and down regulation in intruders. qPCR analysis of TH expression indicated significant up regulation in the midbrain of residents and concomitant down regulation in intruders. These findings implicate regionally- and behaviorally-specific regulation of COMT and TH expression in aggressive and submissive behaviors. Additional molecular and cellular characterization of COMT, TH, and other potential targets is warranted within this animal model of aggression.
    Brain Structure and Function 04/2011; 216(4):347-56. · 7.84 Impact Factor