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Lee DH, Chung CK, Kim JS, Ryun S. Unraveling tactile categorization and decision-making in the subregions of supramarginal gyrus via direct cortical stimulation. Clin Neurophysiol 2024; 158:16-26. [PMID: 38134532 DOI: 10.1016/j.clinph.2023.12.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 11/23/2023] [Accepted: 12/08/2023] [Indexed: 12/24/2023]
Abstract
OBJECTIVE This study aims to investigate the potential of direct cortical stimulation (DCS) to modulate tactile categorization and decision-making, as well as to identify the specific locations where these cognitive functions occur. METHODS We analyzed behavioral changes in three epilepsy patients with implanted electrodes using electrocorticography (ECoG) and a vibrotactile discrimination task. DCS was applied to investigate its impact on tactile categorization and decision-making processes. We determined the precise location of the electrodes where each cognitive function was modulated. RESULTS This functional discrimination was related with gamma band activity from ECoG. DCS selectively affected either tactile categorization or decision-making processes. Tactile categorization was modulated by stimulating the rostral part of the supramarginal gyrus, while decision-making was modulated by stimulating the caudal part. CONCLUSIONS DCS can enhance cognitive processes and map brain regions responsible for tactile categorization and decision-making within the supramarginal gyrus. This study also demonstrates that DCS and the gamma activity of ECoG can concordantly identify the detailed brain mapping in a tactile process compared to other functional neuroimaging. SIGNIFICANCE The combination of DCS and ECoG gamma activity provides a more nuanced and detailed understanding of brain function than traditional neuroimaging techniques alone.
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Affiliation(s)
- Dong Hyeok Lee
- Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul 08826, Republic of Korea
| | - Chun Kee Chung
- Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul 08826, Republic of Korea; Neuroscience Research Institute, Medical Research Center, College of Medicine, Seoul National University, Seoul 03080, Republic of Korea; Department of Neurosurgery, Seoul National University Hospital, Seoul 03080, Republic of Korea.
| | - June Sic Kim
- The Research Institute of Basic Sciences, College of Natural Sciences, Seoul National University, Seoul 08826, Republic of Korea
| | - Seokyun Ryun
- Neuroscience Research Institute, Medical Research Center, College of Medicine, Seoul National University, Seoul 03080, Republic of Korea
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Lee DH, Kim JS, Ryun S, Chung CK. Discrete tactile feature comparison subprocess in human brain during a decision-making process. Cortex 2024; 171:383-396. [PMID: 38101274 DOI: 10.1016/j.cortex.2023.11.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 10/03/2023] [Accepted: 11/02/2023] [Indexed: 12/17/2023]
Abstract
From sensory input to motor action, encoded sensory features flow sequentially along cortical networks for decision-making. Despite numerous studies probing the decision-making process, the subprocess that compares encoded sensory features before making a decision has not been fully elucidated in humans. In this study, we investigated sensory feature comparison by presenting two different tasks (a discrimination task, in which participants made decisions by comparing two sequential tactile stimuli; and a detection task, in which participants responded to the second tactile stimulus in two sequential stimuli) to epilepsy patients while recording electrocorticography (ECoG). By comparing tactile-specific gamma band (30-200 Hz) power between the two tasks, the decision-making process was divided into three subprocesses-categorization, comparison, and decision-consistent with a previous study (Heekeren et al., 2004). These subprocesses occurred sequentially in the dorsolateral prefrontal cortex, premotor cortex, secondary somatosensory cortex, and parietal lobe. Gamma power showed two different patterns of correlation with response time. In the inferior parietal lobule (IPL), there was a negative correlation. This means that as gamma power increased, response time decreased. In the secondary somatosensory cortex (S2), there was a positive correlation. Here, as gamma power increased, response time also increased. These results indicate that the IPL and S2 encode tactile feature comparison differently. Our connectivity analysis showed that the S2 transmitted tactile information to the IPL. Our findings suggest that multiple areas in the parietal lobe encode sensory feature comparison differently before making a decision.
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Affiliation(s)
- Dong Hyeok Lee
- Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, Republic of Korea
| | - June Sic Kim
- The Research Institute of Basic Sciences, College of Natural Sciences, Seoul National University, Seoul, Republic of Korea
| | - Seokyun Ryun
- Neuroscience Research Institute, Medical Research Center, College of Medicine, Seoul National University, Seoul, Republic of Korea
| | - Chun Kee Chung
- Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, Republic of Korea; Neuroscience Research Institute, Medical Research Center, College of Medicine, Seoul National University, Seoul, Republic of Korea; Department of Neurosurgery, Seoul National University Hospital, Seoul, Republic of Korea.
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Abstract
Tactile and movement-related somatosensory perceptions are crucial for our daily lives and survival. Although the primary somatosensory cortex is thought to be the key structure of somatosensory perception, various cortical downstream areas are also involved in somatosensory perceptual processing. However, little is known about whether cortical networks of these downstream areas can be dissociated depending on each perception, especially in human. We address this issue by combining data from direct cortical stimulation (DCS) for eliciting somatosensation and data from high-gamma band (HG) elicited during tactile stimulation and movement tasks. We found that artificial somatosensory perception is elicited not only from conventional somatosensory-related areas such as the primary and secondary somatosensory cortices but also from a widespread network including superior/inferior parietal lobules and premotor cortex. Interestingly, DCS on the dorsal part of the fronto-parietal area including superior parietal lobule and dorsal premotor cortex often induces movement-related somatosensations, whereas that on the ventral one including inferior parietal lobule and ventral premotor cortex generally elicits tactile sensations. Furthermore, the HG mapping results of the movement and passive tactile stimulation tasks revealed considerable similarity in the spatial distribution between the HG and DCS functional maps. Our findings showed that macroscopic neural processing for tactile and movement-related perceptions could be segregated.
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Affiliation(s)
- Seokyun Ryun
- Neuroscience Research Institute, Seoul National University Medical Research Center, Seoul, Korea
| | - Minkyu Kim
- Department of Cognitive Sciences, University of California Irvine, Irvine, USA
| | - June Sic Kim
- Department of Brain & Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Korea
| | - Chun Kee Chung
- Neuroscience Research Institute, Seoul National University Medical Research Center, Seoul, Korea; Department of Brain & Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Korea; Department of Neurosurgery, Seoul National University College of Medicine, Seoul, Korea.
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Jang SJ, Yang YJ, Ryun S, Kim JS, Chung CK, Jeong J. Decoding trajectories of imagined hand movement using electrocorticograms for brain-machine interface. J Neural Eng 2022; 19. [PMID: 35985293 DOI: 10.1088/1741-2552/ac8b37] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 08/19/2022] [Indexed: 11/12/2022]
Abstract
OBJECTIVE Reaching hand movement is an important motor skill actively examined in brain-computer interface (BCI). Among various components of movement analyzed is the hand's trajectory, which describes the hand's continuous positions in three-dimensional space. While a large body of studies have investigated the decoding of real movements and the reconstruction of real hand movement trajectories from neural signals, fewer studies have attempted to decode the trajectory of imagined hand movement. To develop BCI systems for patients with hand motor dysfunctions, the systems essentially require to achieve movement-free control of external devices, which is only possible through successful decoding of purely imagined hand movement. APPROACH To achieve this goal, this study used a machine learning technique (i.e., the variational Bayesian least square) to analyze the electrocorticogram (ECoG) of eighteen epilepsy patients obtained from when they performed movement execution (ME) and kinesthetic movement imagination (KMI) of the reach-and-grasp hand action. MAIN RESULTS The variational Bayesian decoding model was able to successfully predict the imagined trajectories of hand movement significantly above chance level. The Pearson's correlation coefficient between imagined and predicted trajectories was 0.3393 and 0.4936 for the KMI (KMI trials only) and MEKMI paradigm (alternating trials of ME and KMI) respectively. SIGNIFICANCE This study demonstrated a high accuracy of prediction for trajectories of imagined hand movement, and more importantly, higher decoding accuracy of imagined trajectories in the MEKMI paradigm than in the KMI paradigm solely.
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Affiliation(s)
- Sang Jin Jang
- Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, 411 E16-1(YBS Building) Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon, South Korea 34141, Daejeon, Daejeon, 34141, Korea (the Republic of)
| | - Yu Jin Yang
- Seoul National University College of Natural Sciences, 103, Daehak-ro, Jongno-gu, Seoul, Republic of Korea, Seoul, 03080, Korea (the Republic of)
| | - Seokyun Ryun
- Seoul National University College of Natural Sciences, 103, Daehak-ro, Jongno-gu, Seoul, Republic of Korea, Seoul, 03080, Korea (the Republic of)
| | - June Sic Kim
- Seoul National University College of Natural Sciences, 103, Daehak-ro, Jongno-gu, Seoul, Republic of Korea, Seoul, 03080, Korea (the Republic of)
| | - Chun Kee Chung
- Seoul National University College of Natural Sciences, 103, Daehak-ro, Jongno-gu, Seoul, Republic of Korea, Seoul, 03080, Korea (the Republic of)
| | - Jaeseung Jeong
- Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, 514 E16-1(YBS Building) Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon, South Korea 34141, Daejeon, 34141, Korea (the Republic of)
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Lee D, Kim J, Ryun S, Chung C. Specific brain response of secondary somatosensory cortex and prefrontal cortex in vibrotactile discrimination. IBRO Rep 2019. [DOI: 10.1016/j.ibror.2019.07.514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
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Kang BK, Kim JS, Ryun S, Chung CK. Prediction of movement intention using connectivity within motor-related network: An electrocorticography study. PLoS One 2018; 13:e0191480. [PMID: 29364932 PMCID: PMC5783365 DOI: 10.1371/journal.pone.0191480] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2017] [Accepted: 01/05/2018] [Indexed: 01/14/2023] Open
Abstract
Most brain-machine interface (BMI) studies have focused only on the active state of which a BMI user performs specific movement tasks. Therefore, models developed for predicting movements were optimized only for the active state. The models may not be suitable in the idle state during resting. This potential maladaptation could lead to a sudden accident or unintended movement resulting from prediction error. Prediction of movement intention is important to develop a more efficient and reasonable BMI system which could be selectively operated depending on the user’s intention. Physical movement is performed through the serial change of brain states: idle, planning, execution, and recovery. The motor networks in the primary motor cortex and the dorsolateral prefrontal cortex are involved in these movement states. Neuronal communication differs between the states. Therefore, connectivity may change depending on the states. In this study, we investigated the temporal dynamics of connectivity in dorsolateral prefrontal cortex and primary motor cortex to predict movement intention. Movement intention was successfully predicted by connectivity dynamics which may reflect changes in movement states. Furthermore, dorsolateral prefrontal cortex is crucial in predicting movement intention to which primary motor cortex contributes. These results suggest that brain connectivity is an excellent approach in predicting movement intention.
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Affiliation(s)
- Byeong Keun Kang
- Human Brain Function Laboratory, Department of Neurosurgery, Seoul National University Hospital, Seoul, South Korea
- Interdisciplinary Program in Neuroscience, Seoul National University College of Natural Science, Seoul, South Korea
| | - June Sic Kim
- Human Brain Function Laboratory, Department of Neurosurgery, Seoul National University Hospital, Seoul, South Korea
- Department of Brain & Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
- * E-mail:
| | - Seokyun Ryun
- Human Brain Function Laboratory, Department of Neurosurgery, Seoul National University Hospital, Seoul, South Korea
- Interdisciplinary Program in Neuroscience, Seoul National University College of Natural Science, Seoul, South Korea
| | - Chun Kee Chung
- Human Brain Function Laboratory, Department of Neurosurgery, Seoul National University Hospital, Seoul, South Korea
- Interdisciplinary Program in Neuroscience, Seoul National University College of Natural Science, Seoul, South Korea
- Department of Brain & Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
- Department of Neurosurgery, Seoul National University College of Medicine, Seoul, South Korea
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Ryun S, Kim JS, Lee H, Chung CK. Tactile Frequency-Specific High-Gamma Activities in Human Primary and Secondary Somatosensory Cortices. Sci Rep 2017; 7:15442. [PMID: 29133909 PMCID: PMC5684355 DOI: 10.1038/s41598-017-15767-x] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2017] [Accepted: 11/01/2017] [Indexed: 01/29/2023] Open
Abstract
Humans can easily detect vibrotactile stimuli up to several hundred hertz, but underlying large-scale neuronal processing mechanisms in the cortex are largely unknown. Here, we investigated the macroscopic neural correlates of various vibrotactile stimuli including artificial and naturalistic ones in human primary and secondary somatosensory cortices (S1 and S2, respectively) using electrocorticography (ECoG). We found that tactile frequency-specific high-gamma (HG, 50–140 Hz) activities are seen in both S1 and S2 with different temporal dynamics during vibration (>100 Hz). Stimulus-evoked S1 HG power, which exhibited short-delayed peaks (50–100 ms), was attenuated more quickly in vibration than in flutter (<50 Hz), and their attenuation patterns were frequency-specific within vibration range. In contrast, S2 HG power, which was activated much later than that of S1 (150–250 ms), strikingly increased with increasing stimulus frequencies in vibration range, and their changes were much greater than those in S1. Furthermore, these S1-S2 HG patterns were preserved in naturalistic stimuli such as coarse/fine textures. Our results provide persuasive evidence that S2 is critically involved in neural processing for high-frequency vibrotaction. Therefore, we propose that S1-S2 neuronal co-operation is crucial for full-range, complex vibrotactile perception in human.
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Affiliation(s)
- Seokyun Ryun
- Interdisciplinary Program in Neuroscience, Seoul National University College of Natural Sciences, Seoul, 08826, Korea
| | - June Sic Kim
- Department of Brain & Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, 08826, Korea.
| | - Hyeongrae Lee
- Department of Mental Health Research, National Center for Mental Health, Seoul, 04933, Korea
| | - Chun Kee Chung
- Interdisciplinary Program in Neuroscience, Seoul National University College of Natural Sciences, Seoul, 08826, Korea. .,Department of Brain & Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, 08826, Korea. .,Department of Neurosurgery, Seoul National University College of Medicine, Seoul, 03080, Korea.
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Ryun S, Kim JS, Jeon E, Chung CK. Movement-Related Sensorimotor High-Gamma Activity Mainly Represents Somatosensory Feedback. Front Neurosci 2017; 11:408. [PMID: 28769747 PMCID: PMC5509940 DOI: 10.3389/fnins.2017.00408] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2017] [Accepted: 06/30/2017] [Indexed: 11/18/2022] Open
Abstract
Somatosensation plays pivotal roles in the everyday motor control of humans. During active movement, there exists a prominent high-gamma (HG >50 Hz) power increase in the primary somatosensory cortex (S1), and this provides an important feature in relation to the decoding of movement in a brain-machine interface (BMI). However, one concern of BMI researchers is the inflation of the decoding performance due to the activation of somatosensory feedback, which is not elicited in patients who have lost their sensorimotor function. In fact, it is unclear as to how much the HG component activated in S1 contributes to the overall sensorimotor HG power during voluntary movement. With regard to other functional roles of HG in S1, recent findings have reported that these HG power levels increase before the onset of actual movement, which implies neural activation for top-down movement preparation or sensorimotor interaction, i.e., an efference copy. These results are promising for BMI applications but remain inconclusive. Here, we found using electrocorticography (ECoG) from eight patients that HG activation in S1 is stronger and more informative than it is in the primary motor cortex (M1) regardless of the type of movement. We also demonstrate by means of electromyography (EMG) that the onset timing of the HG power in S1 is later (49 ms) than that of the actual movement. Interestingly, we show that the HG power fluctuations in S1 are closely related to subtle muscle contractions, even during the pre-movement period. These results suggest the following: (1) movement-related HG activity in S1 strongly affects the overall sensorimotor HG power, and (2) HG activity in S1 during voluntary movement mainly represents cortical neural processing for somatosensory feedback.
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Affiliation(s)
- Seokyun Ryun
- Interdisciplinary Program in Neuroscience, Seoul National University College of Natural SciencesSeoul, South Korea
| | - June S Kim
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural SciencesSeoul, South Korea
| | - Eunjeong Jeon
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural SciencesSeoul, South Korea
| | - Chun K Chung
- Interdisciplinary Program in Neuroscience, Seoul National University College of Natural SciencesSeoul, South Korea.,Department of Brain and Cognitive Sciences, Seoul National University College of Natural SciencesSeoul, South Korea.,Department of Neurosurgery, Seoul National University College of MedicineSeoul, South Korea
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