A5029674397- Advanced Neuroimaging Techniques and Applications
- Functional Brain Connectivity Studies
- Topological and Geometric Data Analysis
- Medical Image Segmentation Techniques
- Advanced MRI Techniques and Applications
- Neural dynamics and brain function
- Bioinformatics and Genomic Networks
- Morphological variations and asymmetry
- 3D Shape Modeling and Analysis
- Cell Image Analysis Techniques
- Alzheimer's disease research and treatments
- Fluid Dynamics and Turbulent Flows
- Mental Health Research Topics
- Complex Network Analysis Techniques
- Advanced Graph Neural Networks
- Fetal and Pediatric Neurological Disorders
- Fractal and DNA sequence analysis
- Image and Signal Denoising Methods
- Tensor decomposition and applications
- Turbomachinery Performance and Optimization
- Wind and Air Flow Studies
- Image Retrieval and Classification Techniques
- Autism Spectrum Disorder Research
- Speech Recognition and Synthesis
- Numerical methods in inverse problems
University of Wisconsin–Madison
2015-2024
Seoul National University
2009-2024
Maria Fertility Hospital
2023
Yonsei University
2015-2019
University of Wisconsin System
2006-2018
University of California, Irvine
2018
Dongguk University Ilsan Hospital
2014
Seoul National University Hospital
2014
University of Pennsylvania
2012
Google (United States)
2010
Individuals who experience early adversity, such as child maltreatment, are at heightened risk for a broad array of social and health difficulties. However, little is known about how this behavioral instantiated in the brain. Here we examine neurobiological contribution to individual differences human behavior using methodology appropriate use with pediatric populations paired an in-depth measure behavior. We show that alterations orbitofrontal cortex among individuals experienced physical...
The brain network is usually constructed by estimating the connectivity matrix and thresholding it at an arbitrary level. problem with this standard method that we do not have any generally accepted criteria for determining a proper threshold. Thus, propose novel multiscale framework models all networks generated over every possible Our approach based on persistent homology its various representations such as Rips filtration, barcodes, dendrograms. This new homological enables us to quantify...
Cognitive deficits have been reported in children who experienced early neglect, especially raised institutionalized settings. Previous research suggests that neglect may differentially affect the directional organization of white matter prefrontal cortex (PFC). This be one mechanism to explain cognitive associated with neglect. To test this idea, properties and neurocognitive performance were assessed suffered those typical environments (n = 63, Mage 11.75 years). As predicted,...
A large corpus of research indicates that exposure to stress impairs cognitive abilities, specifically executive functioning dependent on the prefrontal cortex (PFC). We collected structural MRI scans (<i>n</i> = 61), well-validated assessments functioning, and detailed interviews assessing in humans examine whether cumulative life affected brain morphometry one type spatial working memory, during adolescence—a critical time development reorganization. Analysis variations structure revealed...
The growth of the vocal tract (VT) is known to be non-uniform insofar as there are regional differences in anatomic maturation. This study presents quantitative data on oral and pharyngeal portions VT from 605 imaging studies for individuals between birth 19 years. (horizontal) portion was segmented into lip-thickness, anterior-cavity-length, oropharyngeal-width, VT-oral, (vertical) posterior-cavity-length, nasopharyngeal-length. were analyzed determine trend, rate, type (neural or somatic)....
Partial correlation is a useful connectivity measure for brain networks, especially, when it needed to remove the confounding effects in highly correlated networks. Since difficult estimate exact partial under small- <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> large- xmlns:xlink="http://www.w3.org/1999/xlink">p</i> situation, sparseness constraint generally introduced. In this paper, we consider sparse linear regression model with...
We present a novel weighted Fourier series (WFS) representation for cortical surfaces. The WFS is data smoothing technique that provides the explicit smooth functional estimation of unknown boundary as linear combination basis functions. basic properties are investigated in connection with self-adjoint partial differential equation and traditional spherical harmonic (SPHARM) representation. To reduce steep computational requirements, new iterative residual fitting (IRF) algorithm developed....
We present a new tensor-based morphometric framework that quantifies cortical shape variations using local area element. The element is computed from the Riemannian metric tensors, which are obtained smooth functional parametrization of mesh. For parametrization, we have developed novel weighted spherical harmonic (SPHARM) representation, generalizes traditional SPHARM as special case. specific choice weights, weighted-SPHARM shown to be least squares approximation solution an isotropic heat...
It is known that the brain network has small-world and scale-free topology, but structures drastically change depending on how to threshold a connectivity matrix. The exact criterion difficult determine. In this paper, instead of trying determine one fixed optimal threshold, we propose look at topological changes while increasing continuously. This process continuously changing level looking resulting feature related Rips filtration in persistent homology. sequence features obtained during...
Epilepsy is a neurological disorder marked by sudden recurrent episodes of sensory disturbance, loss consciousness, or convulsions, associated with abnormal electrical activity in the brain. Statistical analysis neurophysiological recordings, such as electroencephalography (EEG), facilitates understanding epileptic seizures. Standard statistical methods typically analyze amplitude and frequency information EEG signals. In current study, we propose topological data (TDA) framework to...
The present study has tested most of the loss models previously published in open literature and found an optimum set empirical for a reliable performance prediction centrifugal compressors. In order to improve efficiency curves, this paper recommends modified parasitic model. analyses by using various are also compared with those two-zone modelling. Predicted curves proposed agree fairly well experimental data variety method developed through can serve as tool preliminary design assist...
Conditional averages of turbulent flow quantities can be approximated in terms unconditional correlation data by means stochastic estimation. The validity and accuracy this procedure are investigated comparing estimates to conditional measured four flows: grid turbulence, the axisymmetric shear layer a round jet, plane layer, pipe flow. Comparisons made for that separated from time or space, pressures, as well velocities. In each case, linear estimate accurately represents large scale...
Alzheimer's disease (AD) research has recently witnessed a great deal of activity focused on developing new statistical learning tools for automated inference using imaging data. The workhorse many these techniques is the support vector machine (SVM) framework (or more generally kernel-based methods). Most require, as first step, specification kernel matrix K between input examples (i.e., images). inner product images I(i) and I(j) in feature space can be written closed form so it convenient...