A5058623592- Functional Brain Connectivity Studies
- Neural dynamics and brain function
- EEG and Brain-Computer Interfaces
- Advanced Neuroimaging Techniques and Applications
- Dementia and Cognitive Impairment Research
- Mental Health Research Topics
- Neural and Behavioral Psychology Studies
- Neurological disorders and treatments
- Parkinson's Disease Mechanisms and Treatments
- Advanced MRI Techniques and Applications
- Visual perception and processing mechanisms
- Motor Control and Adaptation
- Action Observation and Synchronization
- RNA regulation and disease
- Alzheimer's disease research and treatments
- Diet and metabolism studies
- Memory and Neural Mechanisms
- Topology Optimization in Engineering
- Remote-Sensing Image Classification
- Advanced Wireless Communication Techniques
- Complex Network Analysis Techniques
- Mitochondrial Function and Pathology
- Reading and Literacy Development
- Histone Deacetylase Inhibitors Research
- Cognitive Science and Mapping
Samsung Medical Center
2023-2025
Sungkyunkwan University
2023-2025
Yale University
2017-2024
Samsung (South Korea)
2023-2024
La Jolla Institute for Immunology
2024
The University of Texas Health Science Center at San Antonio
2022
One Cell Systems (United States)
2022
Korea Advanced Institute of Science and Technology
2010-2018
Korea Institute of Brain Science
2015-2018
Genome Research Foundation
2018
Abstract Genome editing has been harnessed through the development of CRISPR system, and from Prevotella Francisella 1 (Cpf1) system emerged as a promising alternative to CRISPR-Cas9 for use in various circumstances. Despite inherent multiple advantages Cpf1 over Cas9, adoption unsatisfactory because target-dependent insufficient indel efficiencies. Here, we report an engineered RNA (crRNA) highly efficient genome by Cpf1, which includes 20-base target-complementary sequence uridinylate-rich...
Dynamic functional connectivity (DFC) aims to maximize resolvable information from brain scans by considering temporal changes in network structure. Recent work has demonstrated that static, i.e. time-invariant resting-state and task-based FC predicts individual differences behavior, including attention. Here, we show DFC attention performance across individuals. Sliding-window matrices were generated fMRI data collected during rest task calculating Pearson's r between every pair of nodes a...
Resting-state functional connectivity (rs-FC) is a promising neuromarker for cognitive decline in aging population, based on its ability to reveal differences associated with impairment across individuals, and because rs-fMRI may be less taxing participants than task-based fMRI or neuropsychological tests. Here, we employ an approach that uses rs-FC predict the Alzheimer's Disease Assessment Scale (11 items; ADAS11) scores, which measure range of abilities, novel individuals. We applied this...
Individual differences in working memory relate to performance general cognitive ability. The neural bases of such individual differences, however, remain poorly understood. Here, using a data-driven technique known as connectome-based predictive modeling, we built models predict from whole-brain functional connectivity patterns. Using n-back or rest data the Human Connectome Project, significantly predicted novel individuals' 2-back accuracy. Model predictions also correlated with measures...
Background: Default mode network (DMN) functional connectivity is one of the neuroimaging candidate biomarkers Alzheimer disease. However, no studies have investigated DMN at different stages mild cognitive impairment (MCI). The aim this study was to investigate patterns and its breakdown among cognitively normal (CN), early MCI (EMCI), late (LMCI) subjects. Methods: Magnetic resonance imaging data neuropsychological test scores from 130 subjects (CN=43, EMCI=47, LMCI=40) were obtained...
Sustained attention (SA) and working memory (WM) are critical processes, but the brain networks supporting these abilities in development unknown. We characterized functional architecture of SA WM 9- to 11-year-old children adults. First, we found that adult network predictors generalized predict individual differences fluctuations youth. A model predicted performance both across within children-and captured later recognition memory-but underperformed youth relative next connections...
The differences in how our brain is connected are often thought to reflect the individual personalities and cognitive abilities. Individual connectivity has long been recognized neuroscience community however it yet manifest itself methodology of resting state analysis. This evident as previous studies use same region interest (ROIs) for all subjects. In this paper we demonstrate that ROIs which standardized across individuals leads inaccurate calculations functional connectivity. We also...
Although we must prioritize the processing of task-relevant information to navigate life, our ability do so fluctuates across time. Previous work has identified fMRI functional connectivity (FC) networks that predict an individual's sustain attention and vary with attentional state from 1 min next. However, traditional dynamic FC approaches typically lack temporal precision capture moment-to-moment network fluctuations. Recently, researchers have "unfurled" matrices in "edge cofluctuation...
Abstract Brain connectivity analyses have been widely performed to investigate the organization and functioning of brain, or observe changes in neurological psychiatric conditions. However, analysis inevitably introduces problem mass‐univariate hypothesis testing. Although, several cluster‐wise correction methods suggested address this shown provide high sensitivity, these approaches fundamentally two drawbacks: lack spatial specificity (localization power) arbitrariness an initial...
Patterns of whole-brain fMRI functional connectivity, or connectomes, are unique to individuals. Previous work has identified subsets connections within these patterns whose strength predicts aspects attention and cognition. However, overall features such as how stable they over time similar a group-average (typical) high-performance (optimal) connectivity pattern, may also reflect cognitive attentional abilities. Here, we test whether individuals who express more stable, typical, optimal,...
Hyperspectral imaging (HSI) enables detailed spectral analysis across numerous bands, offering transformative potential in diverse domains such as remote sensing, agriculture, and medical diagnostics. However, the inherent challenges of inter-class similarity, intra-class variability, limitations existing similarity metrics hinder its effectiveness. To address these challenges, we propose CRNSim, a novel index that integrates three complementary components: Chebyshev-based term to capture...
We investigate the changes in functional connectivity of left and right hippocampus by comparing resting-state low-frequency fluctuations blood oxygen level-dependent signal from these regions with relation to Alzheimer disease (AD) progression. AD patients were divided into subgroups based on clinical dementia rating (CDR) scores. Patients amnestic mild cognitive impairment (aMCI) also analyzed as an intermediate stage between normal controls AD. found that total both was maintained during...
We present an example-based multi-atlas approach for classifying white matter (WM) tracts into anatomic bundles. Our exploits expert-provided example data to automatically classify the WM of a subject. Multiple atlases are constructed model from multiple subjects in order reflect individual variability bundle shapes and trajectories over subjects. For each subject, atlas is maintained allow subject be added or deleted flexibly. A voting scheme proposed facilitate exploitation data....
Intrinsic functional connectivity from resting state magnetic resonance imaging (rsfMRI) has increasingly received attention as a possible predictor of cognitive function and performance. In this study, we investigated the influence practicing skillful tool manipulation on intrinsic in brain. Acquisition tool-use skill two aspects such formation motor representation for acquisition concept. To dissociate these processes, chose chopsticks-handling with non-dominant hand. Because participants...
Early-onset Alzheimer's disease (EAD) shows distinct features from late-onset (LAD). To explore the characteristics of EAD, clinical, neuropsychological, and functional imaging studies have been conducted. However, differences between EAD LAD are not clear, especially in terms brain connectivity networks. In this study, we investigated metabolic by adopting graph theory measures.We analyzed (18)F-fluorodeoxyglucose-positron emission tomography (FDG-PET) images to investigate LAD. Using...