Browsing by Author "Lee, Sangkyun"

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    Acquired self-control of insula cortex modulates emotion recognition and brain network connectivity in schizophrenia
    (2013) Ruiz Poblete, Sergio Marcelo; Lee, Sangkyun; Soekadar, Surjo R.; Caria, Andrea; Veit, Ralf; Kircher, Tilo; Birbaumer, Niels; Sitaram, Ranganatha
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    Detection of Cerebral Reorganization Induced by Real-Time fMRI Feedback Training of Insula Activation: A Multivariate Investigation
    (2011) Lee, Sangkyun; Ruiz, Sergio; Caria, Andrea; Veit, Ralf; Birbaumer, Niels; Sitaram, Ranganatha
    Background. Studies with real-time functional magnetic resonance imaging (fMRI) demonstrate that humans volitionally regulate hemodynamic signals from circumscribed regions of the brain, leading to area-specific behavioral consequences. Methods to better determine the nature of dynamic functional interactions between different brain regions and plasticity due to self-regulation training are still in development. Objective. The authors investigated changes in brain states while training 6 healthy participants to self-regulate insular cortex by real-time fMRI feedback. Methods. The authors used multivariate pattern analysis to observe spatial pattern changes and a multivariate Granger causality model to show changes in temporal interactions in multiple brain areas over the course of 5 repeated scans per subject during positive and negative emotional imagery with feedback about the level of insular activation. Results. Feedback training leads to more spatially focused recruitment of areas relevant for learning and emotion. Effective connectivity analysis reveals that initial training is associated with an increase in network density; further training "prunes" presumably redundant connections and "strengthens" relevant connections. Conclusions. The authors demonstrate the application of multivariate methods for assessing cerebral reorganization during the learning of volitional control of local brain activity. The findings provide insight into mechanisms of training-induced learning techniques for rehabilitation. The authors anticipate that future studies, specifically designed with this hypothesis in mind, may be able to construct a universal index of cerebral reorganization during skill learning based on multiple similar criteria across various skilled tasks. These techniques may be able to discern recovery from compensation, dose-response curves related to training, and ways to determine whether rehabilitation training is actively engaging necessary networks.
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    Motor Intentions Decoded from fMRI Signals
    (2024) Ruiz, Sergio; Lee, Sangkyun; Dalboni da Rocha, Josue Luiz; Ramos, Ander; Pasqualotto, Emanuele; Soares, Ernesto; García, Eliana; Fetz, Eberhard; Birbaumer, Niels; Sitaram Ranganatha
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    Real-time support vector classification and feedback of multiple emotional brain states
    (2011) Sitaram, Ranganatha; Lee, Sangkyun; Ruiz, Sergio; Rana, Mohit; Veit, Ralf; Birbaumer, Niels
    An important question that confronts current research in affective neuroscience as well as in the treatment of emotional disorders is whether it is possible to determine the emotional state of a person based on the measurement of brain activity alone. Here, we first show that an online support vector machine (SVM) can be built to recognize two discrete emotional states, such as happiness and disgust from fMRI signals, in healthy individuals instructed to recall emotionally salient episodes from their lives. We report the first application of real-time head motion correction, spatial smoothing and feature selection based on a new method called Effect mapping. The classifier also showed robust prediction rates in decoding three discrete emotional states (happiness, disgust and sadness) in an extended group of participants. Subjective reports ascertained that participants performed emotion imagery and that the online classifier decoded emotions and not arbitrary states of the brain. Offline whole brain classification as well as region-of-interest classification in 24 brain areas previously implicated in emotion processing revealed that the frontal cortex was critically involved in emotion induction by imagery. We also demonstrate an fMRI-BCI based on real-time classification of BOLD signals from multiple brain regions, for each repetition time (TR) of scanning, providing visual feedback of emotional states to the participant for potential applications in the clinical treatment of dysfunctional affect. (C) 2010 Elsevier Inc. All rights reserved.
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    The Effect of Wealth Shocks on Loss Aversion: Behavior and Neural Correlates
    (2017) Chandrasekhar Pammi, V. S.; Ruiz Poblete, Sergio Marcelo; Lee, Sangkyun; Noussair, Charles N.; Sitaram, Ranganatha