https://scholar.dgist.ac.kr/handle/20.500.11750/757 2026-04-04T13:36:07Z 2026-04-04T13:36:07Z Woo, Sung-Ho Jeon, Hyeon-Ae Kang, Soyoung Joo, Hyeyeon Seo, Min-Hee Lee, Eunbeen Heo, Jae-Hyeok Cha, Jeong-In Ryu, Jeh-Kwang Kim, Min-Jeong https://scholar.dgist.ac.kr/handle/20.500.11750/17340 2025-07-25T03:23:24Z 2022-10-31T15:00:00Z

Title: A Memorial Tribute to Kyoung-Min Lee: An Outstanding Behavioral Neurologist and Cognitive Neuroscientist Author(s): Woo, Sung-Ho; Jeon, Hyeon-Ae; Kang, Soyoung; Joo, Hyeyeon; Seo, Min-Hee; Lee, Eunbeen; Heo, Jae-Hyeok; Cha, Jeong-In; Ryu, Jeh-Kwang; Kim, Min-Jeong Abstract: [No abstract available]

2022-10-31T15:00:00Z Park, Jungtak Janacsek, Karolina Nemeth, Dezso Jeon, Hyeon-Ae https://scholar.dgist.ac.kr/handle/20.500.11750/16949 2025-07-24T07:29:36Z 2022-09-30T15:00:00Z

Title: Reduced functional connectivity supports statistical learning of temporally distributed regularities Author(s): Park, Jungtak; Janacsek, Karolina; Nemeth, Dezso; Jeon, Hyeon-Ae Abstract: Statistical learning is a powerful ability that extracts regularities from our environment and makes predictions about future events. Using functional magnetic resonance imaging, we aimed to probe how a wide range of brain areas are intertwined to support statistical learning, characterising its architecture in the whole-brain functional connectivity (FC). Participants performed a statistical learning task of temporally distributed regularities. We used refined behavioural learning scores to associate individuals’ learning performances with the FC changed by statistical learning. As a result, the learning performance was mediated by the activation strength in the lateral occipital cortex, angular gyrus, precuneus, anterior cingulate cortex, and superior frontal gyrus. Through a group independent component analysis, activations of the superior frontal network showed the largest correlation with the statistical learning performances. Seed-to-voxel whole-brain and seed-to-ROI FC analyses revealed that the FC between the superior frontal gyrus and the salience, language, and dorsal attention networks were reduced during statistical learning. We suggest that the weakened functional connections between the superior frontal gyrus and brain regions involved in top-down control processes serve a pivotal role in statistical learning, supporting better processing of novel information such as the extraction of new patterns from the environment. © 2022 The Author(s)

2022-09-30T15:00:00Z Kim, Eunho Yu, Jin-Woo Kim, Bomin Lim, Sung‐Ho Lee, Sang-Ho Kim, Kwangsu Son, Gowoon Jeon, Hyeon-Ae Moon, Cheil Sakong, Joon Choi, Ji-Woong https://scholar.dgist.ac.kr/handle/20.500.11750/15892 2025-07-25T03:36:20Z 2021-10-31T15:00:00Z

Title: Refined prefrontal working memory network as a neuromarker for Alzheimer’s disease Author(s): Kim, Eunho; Yu, Jin-Woo; Kim, Bomin; Lim, Sung‐Ho; Lee, Sang-Ho; Kim, Kwangsu; Son, Gowoon; Jeon, Hyeon-Ae; Moon, Cheil; Sakong, Joon; Choi, Ji-Woong Abstract: Detecting Alzheimer’s disease (AD) is an important step in preventing pathological brain damage. Working memory (WM)-related network modulation can be a pathological feature of AD, but is usually modulated by untargeted cognitive processes and individual variance, resulting in the concealment of this key information. Therefore, in this study, we comprehensively investigated a new neuromarker, named “refined network,” in a prefrontal cortex (PFC) that revealed the pathological features of AD. A refined network was acquired by removing unnecessary variance from the WM-related network. By using a functional near-infrared spectroscopy (fNIRS) device, we evaluated the reliability of the refined network, which was identified from the three groups classified by AD progression: healthy people (N=31), mild cognitive impairment (N=11), and patients with AD (N=18). As a result, we identified edges with significant correlations between cognitive functions and groups in the dorsolateral PFC. Moreover, the refined network achieved a significantly correlating metric with neuropsychological test scores, and a remarkable three-class classification accuracy (95.0%). These results implicate the refined PFC WM-related network as a powerful neuromarker for AD screening. © 2021 Optical Society of America

2021-10-31T15:00:00Z Lee, Sun-Young Cho, Jeonghwa Nam, Kichun Jeon, Hyeon-Ae Kim, Youngjoo https://scholar.dgist.ac.kr/handle/20.500.11750/15846 2025-07-25T03:22:36Z 2022-02-28T15:00:00Z

Title: An ERP study on the perception of Korean stop sounds /t/, /t’/, and /th/ Author(s): Lee, Sun-Young; Cho, Jeonghwa; Nam, Kichun; Jeon, Hyeon-Ae; Kim, Youngjoo Abstract: This study investigated the sound change of aspirated stops in Korea by comparing neural and behavioral responses between younger and older generations of Korean speakers. Neural sensitivities were examined using event-related potentials (ERPs) in four conditions: /t/ vs. /th/, /t/ vs. /t’/, /th/ vs. /t/, and /t’/ vs. /t/. In addition, accuracies and reaction times in an AX discrimination task were measured. A total of 40 Korean native speakers participated in the study: 20 in the younger generation group in their 20 s and 20 in the older generation group in their 50 s. The results were as follows: (i) in the behavioral task, both the younger and the older generations did well at distinguishing aspirated stops from lax stops with high accuracy rates over 90% and similar reaction times, (ii) while the ERP results showed generational differences; mismatch negativity (MMN) was elicited for the aspirated and lax stops distinction only for the older generation, but not for the younger generation. Such group differences were not found for the tense and lax stop distinctions. The findings of this study provide neurophysiological evidence for the ongoing sound change of aspirated stops in Korea. © 2021

2022-02-28T15:00:00Z