Browsing by Author "Song, Inuk"

Now showing 1 - 4 of 4
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    Age-Related Intrinsic Functional Connectivity Changes of Locus Coeruleus from Childhood to Older Adults
    Song, Inuk; Neal, Joshua; Lee, Tae-Ho (MDPI, 2021-11-10)
    The locus coeruleus is critical for selective information processing by modulating the brain’s connectivity configuration. Increasingly, studies have suggested that LC controls sensory inputs at the sensory gating stage. Furthermore, accumulating evidence has shown that young children and older adults are more prone to distraction and filter out irrelevant information less efficiently, possibly due to the unoptimized LC connectivity. However, the LC connectivity pattern across the life span is not fully examined yet, hampering our ability to understand the relationship between LC development and the distractibility. In this study, we examined the intrinsic network connectivity of the LC using a public fMRI dataset with wide-range age samples. Based on LC-seed functional connectivity maps, we examined the age-related variation in the LC connectivity with a quadratic model. The analyses revealed two connectivity patterns explicitly. The sensory-related brain regions showed a positive quadratic age effect (u-shape), and the frontal regions for the cognitive control showed a negative quadratic age effect (inverted u-shape). Our results imply that such age-related distractibility is possibly due to the impaired sensory gating by the LC and the insufficient top-down controls by the frontal regions. We discuss the underlying neural mechanisms and limitations of our study.
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    Moment-to-moment Variability of Intrinsic Functional Connectivity and Its Usefulness
    Song, Inuk (Virginia Tech, 2022-10-26)
    The brain connectivity of resting-state fMRI (rs-fMRI) represents an intrinsic state of brain architecture, and it has been used as a useful neural marker for detecting psychiatric conditions such as autism spectrum disorder, as well as for predicting psychosocial characteristics such as age. However, most studies using brain connectivity have focused more on the strength of functional connectivity over time (static-FC) than temporal features of connectivity changes (connectome variability). The primary goal of the current study was to investigate the effectiveness of using the connectome variability in classifying an individual’s pathological characteristics from others and predicting psychosocial characteristics. In addition, the current study aimed to prove that benefits of the connectome variability are reliable across various analysis procedures. To this end, three open public large rs-fMRI datasets including ABIDE, COBRE, and NKI were used. The static-FC and the connectome variability metrics were calculated with various brain parcellations and parameters and then utilized for subsequent machine learning (ML) classification and prediction. The results demonstrated that including the connectome variability increased the ML performances significantly in most cases of analytical variations. In addition, including the connectome variability prevented ML performance deterioration when excessive components were used. In conclusion, the current finding proved the usefulness of the connectome variability and its reliability.
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    Neural circuit pathology driven by Shank3 mutation disrupts social behaviors
    Kim, Sunwhi; Kim, Yong-Eun; Song, Inuk; Ujihara, Yusuke; Kim, Namsoo; Jiang, Yong-Hui; Yin, Henry H.; Lee, Tae-Ho; Kim, Il Hwan (Elsevier, 2022-06-07)
    Dysfunctional sociability is a core symptom in autism spectrum disorder (ASD) that may arise from neural-network dysconnectivity between multiple brain regions. However, pathogenic neural-network mechanisms underlying social dysfunction are largely unknown. Here, we demonstrate that circuit-selective mutation (ctMUT) of ASD-risk Shank3 gene within a unidirectional projection from the prefrontal cortex to the basolateral amygdala alters spine morphology and excitatory-inhibitory balance of the circuit. Shank3 ctMUT mice show reduced sociability as well as elevated neural activity and its amplitude variability, which is consistent with the neuroimaging results from human ASD patients. Moreover, the circuit hyper-activity disrupts the temporal correlation of socially tuned neurons to the events of social interactions. Finally, optogenetic circuit activation in wild-type mice partially recapitulates the reduced sociability of Shank3 ctMUT mice, while circuit inhibition in Shank3 ctMUT mice partially rescues social behavior. Collectively, these results highlight a circuit-level pathogenic mechanism of Shank3 mutation that drives social dysfunction.
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    Neurodivergence in Sound: Sonification as a Tool for Mental Health Awareness
    Nadri, Chihab; Al Matar, Hamza; Morrison, Spencer; Tiemann, Allison; Song, Inuk; Lee, Tae Ho; Jeon, Myounghoon (International Community for Auditory Display, 2023-06)
    The need to build greater mental health awareness as an important factor in decreasing stigma surrounding individuals with neurodivergent conditions has led to the development of programs and activities that seek to increase mental health awareness. Using a sonification approach with neural activity can effectively convey an individual’s psychological and mental characteristics in a simple and intuitive manner. In this study, we developed a sonification algorithm that alters existing music clips according to fMRI data corresponding to the salience network activity from neurotypical and neurodivergent individuals with schizophrenia. We conducted an evaluation of these sonifications with 24 participants. Results indicate that participants were able to differentiate between sound clips stemming from different neurological conditions and that participants gained increased awareness of schizophrenia through this brief intervention. Findings indicate sonification could be an effective tool in raising mental health awareness and relate neurodivergence to a neurotypical audience.