Publications by authors named "Hae-Jeong Park"

Integrating multiscale, multimodal neuroimaging data is essential for a comprehensive understanding of neural circuits. However, this is challenging due to the inherent trade-offs between spatial coverage and resolution in each modality, necessitating a computational strategy that combines modality-specific information effectively. This study introduces a dynamic causal modeling (DCM) framework designed to address the challenge of combining partially observed, multiscale signals across a larger-scale neural circuit by employing a shared neural state model with modality-specific observation models.

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Objectives: The oral microbiome plays an important role in the development and progression of periodontal disease. The purpose of this study was to compare microbial profiles of oral cavities in good health, with gingivitis, and in a state of periodontitis, and to identify novel pathogens involved in periodontal diseases.

Methods: One hundred and two participants, including 33 healthy controls, 41 patients with gingivitis, and 28 patients with periodontitis, were included in this cross-sectional study.

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Attending to heartbeats for interoceptive awareness initiates distinct electrophysiological responses synchronized with the R-peaks of an electrocardiogram (ECG), such as the heartbeat-evoked potential (HEP). Beyond HEP, this study proposes heartbeat-related spectral perturbation (HRSP), a time-frequency map of the R-peak locked electroencephalogram (EEG), and explores its characteristics in identifying interoceptive attention states using a classification approach. HRSPs of EEG brain components specified by independent component analysis (ICA) were used for the offline and online classification of interoceptive states.

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In this research, we employed functional magnetic resonance imaging (fMRI) to examine the neurological basis for understanding wh-questions in wh-in-situ languages such as Korean, where wh-elements maintain their original positions instead of moving explicitly within the sentence. Our hypothesis centered on the role of the salience and attention network in comprehending wh-questions in wh-in-situ languages, such as the discernment of wh-elements, the demarcation between interrogative types, and the allocation of cognitive resources towards essential constituents vis-à-vis subordinate elements in order to capture the speaker's communicative intent. We explored subject and object wh-questions and scrambled wh-questions, contrasting them with yes/no questions in Korean.

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The current study investigates the neural correlates when processing prototypicality and simplicity-affecting the preference of product design. Despite its significance, not much is known about how our brain processes these visual qualities of design when forming design preferences. We posit that, although fluency is the perceptual judgment accounting for the positive effects of both prototypicality and simplicity on design preference, the neural substrates for the fluency judgment associated with prototypicality would differ from those associated with simplicity.

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Previous studies have reported that collagen tripeptide (CTP) derived from collagen hydrolysate has various beneficial effects on health by protecting against skin aging and improving bone formation and cartilage regeneration. Collagen-Tripep20 (CTP20), which is a low-molecular-weight CTP derived from fish skin, contains a bioactive CTP, Gly-Pro-Hyp >3.2% with a tripeptide content >20%.

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Artificial intelligence (AI) using deep learning approaches the capabilities of human experts in medical image diagnosis. However, due to liability issues in medical decisions, AI is often relegated to an assistant role. Based on this responsibility constraint, the effective use of AI to assist human intelligence in real-world clinics remains a challenge.

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The speed-accuracy tradeoff (SAT) often makes psychophysical data difficult to interpret. Accordingly, the SAT experimental procedure and model were proposed for an integrated account of the speed and accuracy of responses. However, the extensive data collection for a SAT experiment has blocked its popularity.

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The hierarchical characteristics of the brain are prominent in the pharmacological treatment of psychiatric diseases, primarily targeting cellular receptors that extend upward to intrinsic connectivity within a region, interregional connectivity, and, consequently, clinical observations such as an electroencephalogram (EEG). To understand the long-term effects of neuropharmacological intervention on neurobiological properties at different hierarchical levels, we explored long-term changes in neurobiological parameters of an N-methyl-D-aspartate canonical microcircuit model (CMM-NMDA) in the default mode network (DMN) and auditory hallucination network (AHN) using dynamic causal modeling of longitudinal EEG in clozapine-treated patients with schizophrenia. The neurobiological properties of the CMM-NMDA model associated with symptom improvement in schizophrenia were found across hierarchical levels, from a reduced membrane capacity of the deep pyramidal cell and intrinsic connectivity with the inhibitory population in DMN and intrinsic and extrinsic connectivity in AHN.

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Aim: In our pilot study, we found an increase in tyrosine hydroxylase (Th) mRNA expression in the prefrontal cortex of 72-h REM sleep-deprived (SD) rats, a mania model. Additionally, the expression levels of miR-325-3p, miR-326-3p, and miR-330-5p, the predicted target miRNAs on TH, were significantly decreased. Based on these results, in this study, we investigated whether miRNA-325-3p, miR-326-3p, and miR-330-5p modulate TH and manic-like behaviors in SD rats.

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The correlation matrix is a typical representation of node interactions in functional brain network analysis. The analysis of the correlation matrix to characterize brain networks observed in several neuroimaging modalities has been conducted predominantly in the Euclidean space by assuming that pairwise interactions are mutually independent. One way to take account of all interactions in the network as a whole is to analyze the correlation matrix under some geometric structure.

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Prior experiences of successful and failed treatments are known to influence the efficacy of a newly applied treatment. However, whether that carry-over effect applies to non-pharmacological treatments is unknown. This study investigated how a failed treatment history with placebo analgesic cream affected the therapeutic outcomes of cold-pack treatment.

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Objective: Thalamotomy at the nucleus ventralis intermedius using MR-guided focused ultrasound has been an effective treatment method for essential tremor (ET). However, this is not true for all cases, even for successful ablation. How the brain differs in patients with ET between those with long-term good and poor outcomes is not clear.

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We explore potential cross-informant discrepancies between child- and parent-report measures with an example of the Child Behavior Checklist (CBCL) and the Youth Self Report (YSR), parent- and self-report measures on children's behavioral and emotional problems. We propose a new way of examining the parent- and child-report differences with an interaction map estimated using a Latent Space Item Response Model (LSIRM). The interaction map enables the investigation of the dependency between items, between respondents, and between items and respondents, which is not possible with the conventional approach.

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Background/aim: Sleep loss is proposed as a trigger for manic episodes in bipolar disorder in humans. It has been shown that sleep and wakefulness can affect changes in mitochondrial gene expression, oxidative phosphorylation (OXPHOS) activity, and morphology in the brain. In this study, we investigated alterations in mitochondrial bioenergetic function in the brain of rats after 72-h rapid eye movement sleep deprivation (REM-SD).

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The white matter in the brain is composed of neural fibers that wire the cortical and subcortical brain systems. Considering the complexity in terms of interconnections of many neural populations within the narrow space surrounded by the folding walls of the gray matter, the brain requires a certain way of structured wiring. To explore the three-dimensional organization of wiring in an accessible manner, we focused on voxel-level wiring patterns in the white matter according to cortical distributions in which each voxel mediates the wiring.

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Accumulating evidence indicates that the autophagy process is involved in the pathogenesis of schizophrenia. Autophagy plays a fundamental role in neuronal survival and function, and autophagy-related genes have been suggested to be associated with the pathogenesis of schizophrenia. The Unc-51-like autophagy activating kinase 2 (ULK2) gene has been implicated in autophagy regulation; therefore, we hypothesized that ULK2 polymorphisms may be associated with schizophrenia susceptibility.

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Background: Deep learning (DL)-based artificial intelligence may have different diagnostic characteristics than human experts in medical diagnosis. As a data-driven knowledge system, heterogeneous population incidence in the clinical world is considered to cause more bias to DL than clinicians. Conversely, by experiencing limited numbers of cases, human experts may exhibit large interindividual variability.

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Objectives: To evaluate the association of three single-nucleotide polymorphisms (SNPs) of growth hormone receptor (GHR) gene with mandibular prognathism (MP) and relationships between mandibular morphology and GHR gene SNPs in the Korean population.

Materials And Methods: A total of 325 subjects were divided into two groups based on sagittal maxillomandibular relationship by the lateral cephalography: the MP and control groups. From the SNPs in the GHR gene, three SNPs (rs6180, rs6182 and rs6184) were selected.

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The heterogeneous presentation of inattentive and hyperactive-impulsive core symptoms in attention deficit hyperactivity disorder (ADHD) warrants further investigation into brain network connectivity as a basis for subtype divisions in this prevalent disorder. With diffusion and resting-state functional magnetic resonance imaging data from the Healthy Brain Network database, we analyzed both structural and functional network efficiency and structure-functional network (SC-FC) coupling at the default mode (DMN), executive control (ECN), and salience (SAN) intrinsic networks in 201 children diagnosed with the inattentive subtype (ADHD-I), the combined subtype (ADHD-C), and typically developing children (TDC) to characterize ADHD symptoms relative to TDC and to test differences between ADHD subtypes. Relative to TDC, children with ADHD had lower structural connectivity and network efficiency in the DMN, without significant group differences in functional networks.

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IL-13 induces mucus metaplasia, which causes airway obstruction in asthma. Bee venom (BV) and its components have shown anti-inflammatory effects in allergic diseases such as atopic dermatitis and asthma. In this study, we investigated the effect of BV on IL-13-induced mucus metaplasia through activation of the signal transducer and activator of transcription (STAT6), and regulation of SAM-pointed domain containing Ets-like factor (SPDEF) and forkhead box A2 (FOXA2) in the airway epithelia cell line A549.

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The human brain at rest exhibits intrinsic dynamics transitioning among the multiple metastable states of the inter-regional functional connectivity. Accordingly, the demand for exploring the state-specific functional connectivity increases for a deeper understanding of mental diseases. Functional connectivity, however, lacks information about the directed causal influences among the brain regions, called effective connectivity.

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Systematic evaluation of cortical differences between humans and macaques calls for inter-species registration of the cortex that matches homologous regions across species. For establishing homology across brains, structural landmarks and biological features have been used without paying sufficient attention to functional homology. The present study aimed to determine functional homology between the human and macaque cortices, defined in terms of functional network properties, by proposing an iterative functional network-based registration scheme using surface-based spherical demons.

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The pairwise maximum entropy model (pMEM) has recently gained widespread attention to exploring the nonlinear characteristics of brain state dynamics observed in resting-state functional magnetic resonance imaging (rsfMRI). Despite its unique advantageous features, the practical application of pMEM for individuals is limited as it requires a much larger sample than conventional rsfMRI scans. Thus, this study proposes an empirical Bayes estimation of individual pMEM using the variational expectation-maximization algorithm (VEM-MEM).

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