https://scholar.korea.ac.kr/handle/2021.sw.korea/830 Tue, 07 Apr 2026 19:49:25 GMT 2026-04-07T19:49:25Z https://scholar.korea.ac.kr/handle/2021.sw.korea/270746 Title: Association of APOC1 with cortical atrophy during conversion to Alzheimer's disease Authors: Oh, Sewook; Kim, Sunghun; Kim, Jun Pyo; Seo, Sang Won; Park, Bo-yong; Park, Hyunjin Abstract: Alzheimer's disease (AD) is a prevalent neurodegenerative disorder, with its progression influenced by aberrant gene expression and alterations in the brain network topology. Although APOE has been extensively studied in relation to AD, the role of APOC1 remains relatively underexplored. This study investigated the impact of APOC1 on changes in cortical thickness (CTh) during conversion to AD in a longitudinal setting. Using a normative modeling approach, we examined changes in CTh in patients with mild cognitive impairment (MCI). The spatial patterns of CTh changes were then correlated with APOC1 mRNA expression levels. We estimated the time to conversion to AD and compared progression rates between the low and high APOC1 expression groups. Finally, mediation analysis was performed to assess the indirect effects of APOC1 expression on memory function via CTh changes. In patients with MCI and AD, reduced CTh was observed in the limbic and default mode regions, with a notable impact on the entorhinal cortex, parahippocampus, and fusiform gyrus when comparing baseline and follow-up measurements. The degree of change in CTh was significantly associated with APOC1 expression, with the paralimbic regions identified as particularly vulnerable. Furthermore, the high APOC1 expression group demonstrated more rapid conversion to AD than that observed in the low expression group. Mediation analysis indicated a trend suggesting that APOC1 expression indirectly affected memory and cognitive function through its influence on CTh. These results highlight the potential of APOC1 as an additional focus of AD research, offering insights into the genetic influences on AD pathology. Thu, 15 May 2025 00:00:00 GMT https://scholar.korea.ac.kr/handle/2021.sw.korea/270746 2025-05-15T00:00:00Z https://scholar.korea.ac.kr/handle/2021.sw.korea/268553 Title: Identification of functional dynamic brain states based on graph attention networks Authors: Baek, Inyoung; Namgung, Jong Young; Park, Yeongjun; Jo, Seongil; Park, Bo-yong Abstract: Investigation of the functional dynamics of the human brain can help to unveil inherent cognitive systems. In this study, we adopted a graph attention network-based anomaly detection technique to identify abrupt changes in functional time series. We used the resting-state functional magnetic resonance imaging data of 1010 participants from the Human Connectome Project. By applying multivariate time series anomaly detection using the graph attention network approach, we identified three distinct brain states, termed S1, S2, and S3. We further generated low-dimensional representations of functional connectivity (i.e., gradients) for each brain state and compared these gradients among brain states. S1 and S3 exhibited segregated network patterns, whereas S2 displayed more integrated patterns. A topological analysis based on the graph measures revealed that the integrated state (S2) exhibited strong inter-regional connectivity. Further, the two segregated states exhibited distinct patterns, with S1 being more involved in the somatomotor network and S3 being related to higher-order association areas. When we assessed the transitions between brain states, transitions between the low-level sensory (S1) and higher-order default mode states (S3), as well as between the sensory-focused segregated state (S1) and integrated state (S2), were associated with sensory/motor and memory-related tasks. In contrast, the transitions between the integrated (S2) and segregated states with higher centrality in the default mode region (S3) were found to be related to language and reward tasks. These findings indicate that the proposed approach captures changes in individual participant-level brain dynamics, thereby enabling the assessment of inherently dynamic brain systems. © 2025 The Author(s) Thu, 01 May 2025 00:00:00 GMT https://scholar.korea.ac.kr/handle/2021.sw.korea/268553 2025-05-01T00:00:00Z https://scholar.korea.ac.kr/handle/2021.sw.korea/267390 Title: Retinal degeneration increases inter-trial variabilities of light-evoked spiking activities in ganglion cells Authors: Kim, Da Eun; Kim, Sein; Kim, Minju; Min, Byoung-Kyong; Im, Maesoon Abstract: Retinal ganglion cells (RGCs) transmit visual information to the brain in the form of spike trains, which form visual perception. The reliabilities of spike timing and count are thought to play a crucial role in generating stable percepts. However, the effect of retinal degeneration on spike reproducibility remains underexplored. In this study, we examined longitudinal changes of both spike timing and count across different RGC types in response to repeated presentations of an identical light stimulus in retinal degeneration 10 (rd10) mice (B6.CXBlPde6brd10/J), a well-established model of retinitis pigmentosa (RP). We recorded the spiking responses of RGC populations to repeated white flashes using 256-channel multielectrode array (MEA) at four rd10 age groups representing various stages of retinal degeneration. Our experimental results revealed a significant reduction in both spike timing and count consistencies compared to those in wild-type RGC recordings. Furthermore, the inter-trial variability patterns of different RGC types were found to differ throughout the degeneration process. For instance, when the spike time tiling coefficient (STTC) was used to evaluate inter-trial spike timing consistency, contrast-sensitive RGCs (ON, OFF, and ON-OFF types) exhibited a systematic decrease in spike timing consistency as degeneration progressed, whereas the remaining units did not show similar trends. Thus, we concluded that light-evoked spike trains become less consistent as degeneration progresses, with variability in spike timing and spike count varying across cell types. Given the critical role of spiking reliability in visual perception, our findings highlight the importance of accounting for cell type-specific degeneration patterns and inter-trial spiking inconsistencies when developing visual rehabilitation therapies to achieve enhanced performance. The underlying mechanism(s) driving the intertrial spiking inconsistencies warrant further investigation. Tue, 01 Apr 2025 00:00:00 GMT https://scholar.korea.ac.kr/handle/2021.sw.korea/267390 2025-04-01T00:00:00Z https://scholar.korea.ac.kr/handle/2021.sw.korea/268557 Title: Revealing the Multivariate Associations Between Autistic Traits and Principal Functional Connectome Authors: Lee, Jong-Eun; Byeon, Kyoungseob; Kim, Sunghun; Park, Bo-Yong; Park, Hyunjin Abstract: Autism Spectrum Disorder (ASD) is a multifaceted neurodevelopmental condition characterized by a spectrum of behavioral and cognitive traits. As the characteristics of ASD are highly heterogeneous across individuals, a dimensional approach that overcomes the limitation of the categorical approach is preferred to reveal the symptomatology of ASD. Previous neuroimaging studies demonstrated strong links between large-scale brain networks and autism phenotypes. However, the existing studies have primarily focused on univariate association analysis, which limits our understanding of autism connectopathy. Using resting-state functional magnetic resonance imaging data from 309 participants (168 individuals with ASD and 141 typically developing controls) across a discovery dataset and two independent validation datasets, we identified multivariate associations between high-dimensional neuroimaging features and diverse phenotypic measures (20 or 7 measures). We generated low-dimensional representations of functional connectivity (i.e., gradients) and assessed their multivariate associations with autism-related phenotypes of social, behavioral, and cognitive problems using sparse canonical correlation analysis (SCCA). We selected three functional gradients that represented the cortical axes of the sensory-transmodal, motor-visual, and multiple demand-rests of the brain. The SCCA revealed multivariate associations between gradients and phenotypic measures, which were noted as linked dimensions. We identified three linked dimensions: the links between (1) the first gradient and social impairment, (2) the second and internalizing/externalizing problems, and (3) the third and metacognitive problems. Our findings were partially replicated in two independent validation datasets, indicating robustness. Multivariate association analysis linking high-dimensional neuroimaging and phenotypic features may offer promising avenues for establishing a dimensional approach to autism diagnosis. © The Author(s) 2025. Tue, 01 Apr 2025 00:00:00 GMT https://scholar.korea.ac.kr/handle/2021.sw.korea/268557 2025-04-01T00:00:00Z