• Journal of Korean Neurosurgical Society
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• v.37 no.5
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• pp.325-328
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• 2005

Objective: Stereotactic thalamic procedure is well known to be a effective treatment for disabling upper limb tremor of essential tremor. However, the effect of this procedure for head tremor, which is midline symptom of that disease entity, has not been sufficiently established. The authors discuss the result of stereotactic thalamic operations for head tremor of their patients who suffered from essential tremor. Methods: We evaluated 4 patients of essential tremor who had head tremor combined with both upper limb tremor. One patient underwent unilateral ventralis intermedius thalamotomy, two patients had unilateral Vim deep brain stimulation(DBS) and one patient had unilateral Vim thalamotomy and contralateral DBS. Postoperative results of tremor were evaluated using our proposed scale. Results: Contralateral upper limb tremors to surgical side were markedly resolved in all patients but there was no meaningful effect for head tremor in 3 patients who underwent unilateral thalamic surgery. In a patient having simultaneously unilateral thalamotomy and contralateral DBS, remarkable improvement of head tremor was observed. Conclusion: Although it is difficult to evaluate the efficacy of thalamic surgery for axial symptom of essential tremor with a few cases, simultaneous unilateral thalamotomy and contralateral DBS would be expected to induce favorable outcomes for head tremor with significant economical advantages.

• Journal of Korean Neurosurgical Society
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• v.62 no.2
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• pp.166-174
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• 2019

Objective : Globus pallidus interna (GPi) is acknowledged as an essential treatment for advanced Parkinson's disease (PD). Nonetheless, the neurotransmitter study about its results is undiscovered. The goal of this research was to examine influences of entopeduncular nucleus (EPN) stimulation, identical to human GPi, in no-lesioned (NL) rat and 6-hydroxydopamine (6-HD)-lesioned rat on glutamate change in the striatum. Methods : Extracellular glutamate level changes in striatum of NL category, NL with deep brain stimulation (DBS) category, 6-HD category, and 6-HD with DBS category were examined using microdialysis and high-pressure liquid chromatography. Tyrosine hydroxylase (TH) immunoreactivities in substantia nigra and striatum of the four categories were also analyzed. Results : Extracellular glutamate levels in the striatum of NL with DBS category and 6-HD with DBS category were significantly increased by EPN stimulation compared to those in the NL category and 6-HD category. EPN stimulation had no significant effect on the expression of TH in NL or 6-HD category. Conclusion : Clinical results of GPi DBS are not only limited to direct inhibitory outflow to thalamus. They also include extensive alteration within basal ganglia.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.943-944
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• 2011

• Korean Journal of Radiology
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• v.23 no.10
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• pp.959-975
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• 2022

Objective: To investigate the agreement and reliability of estimating the volumes and normative percentiles (N%) of segmented brain regions among NeuroQuant (NQ), DeepBrain (DB), and FreeSurfer (FS) software programs, focusing on the comparison between NQ and DB. Materials and Methods: Three-dimensional T1-weighted images of 145 participants (48 healthy participants, 50 patients with mild cognitive impairment, and 47 patients with Alzheimer's disease) from a single medical center (SMC) dataset and 130 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset were included in this retrospective study. All images were analyzed with DB, NQ, and FS software to obtain volume estimates and N% of various segmented brain regions. We used Bland-Altman analysis, repeated measures ANOVA, reproducibility coefficient, effect size, and intraclass correlation coefficient (ICC) to evaluate inter-method agreement and reliability. Results: Among the three software programs, the Bland-Altman plot showed a substantial bias, the ICC showed a broad range of reliability (0.004-0.97), and repeated-measures ANOVA revealed significant mean volume differences in all brain regions. Similarly, the volume differences of the three software programs had large effect sizes in most regions (0.73-5.51). The effect size was largest in the pallidum in both datasets and smallest in the thalamus and cerebral white matter in the SMC and ADNI datasets, respectively. N% of NQ and DB showed an unacceptably broad Bland-Altman limit of agreement in all brain regions and a very wide range of ICC values (-0.142-0.844) in most brain regions. Conclusion: NQ and DB showed significant differences in the measured volume and N%, with limited agreement and reliability for most brain regions. Therefore, users should be aware of the lack of interchangeability between these software programs when they are applied in clinical practice.

• 재활복지
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• v.18 no.4
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• pp.237-255
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• 2014

Idiopathic Parkinson disease(IPD) is an neurodegenerative disease caused by the loss of dopamine cells in the substantia nigra, a region of midbrain. Its major symptoms are muscular rigidity, bradykinesia, resting tremor, and postural instability. An estimated 70~90% of patients with IPD also have hypokinetic dysarthria. Subthalamic nucleus deep brain stimulation (STN-DBS) has been reported to be successful in relieving the core motor symptoms of IPD in the advanced stages of the disease. However, data on the effects of STN-DBS on speech performance are inconsistent. A medline literature search was done to retrieve articles published from 1987 to 2012. The results were narrowed down to focus on speech performance under STN-DBS based perceptual, acoustic, and/or aerodynamic analyses. Among the 32 publications which dealt with speech performance after STN-DBS indicated improvement(42%), deterioration(29%), mixed results(26%), or no change(3%). The most favorite method was found to be based upon acoustic analysis by using a vowel prolongation and Unified Parkinson's Disease Rating Scale(UPDRS). For the purpose of verifying the effect of the STN-DBS, speech evaluation should be undertaken on all speech components such as articulation, resonance, phonation, respiration, and prosody by using a contextual speech task.

• Electronics and Telecommunications Trends
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• v.36 no.3
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• pp.106-118
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• 2021

The field of brain science (or neuroscience in a broader sense) has inspired researchers in artificial intelligence (AI) for a long time. The outcomes of neuroscience such as Hebb's rule had profound effects on the early AI models, and the models have developed to become the current state-of-the-art artificial neural networks. However, the recent progress in AI led by deep learning architectures is mainly due to elaborate mathematical methods and the rapid growth of computing power rather than neuroscientific inspiration. Meanwhile, major limitations such as opacity, lack of common sense, narrowness, and brittleness have not been thoroughly resolved. To address those problems, many AI researchers turn their attention to neuroscience to get insights and inspirations again. Biologically plausible neural networks, spiking neural networks, and connectome-based networks exemplify such neuroscience-inspired approaches. In addition, the more recent field of brain network analysis is unveiling complex brain mechanisms by handling the brain as dynamic graph models. We argue that the progress toward the human-level AI, which is the goal of AI, can be accelerated by leveraging the novel findings of the human brain network.

• Journal of Korean Neurosurgical Society
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• v.57 no.1
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• pp.6-11
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• 2015

Objective : Neuropathic pain causes patients feel indescribable pain. Deep Brain Stimulation (DBS) is one of the treatment methods in neuropathic pain but the action mechanism is still unclear. To study the effect and mechanism of analgesic effects from DBS in neuropathic pain and to enhance the analgesic effect of DBS, we stimulated the ventral posterolateral nucleus (VPL) in rats. Methods : To observe the effect from VPL stimulation, we established 3 groups : normal group (Normal group), neuropathic pain group (Pain group) and neuropathic pain+DBS group (DBS group). Rats in DBS group subjected to electrical stimulation and the target is VPL. Results : We observed the behavioral changes by DBS in VPL (VPL-DBS) on neuropathic pain rats. In our study, the pain score which is by conventional test method was effectively decreased. In specific, the time of showing withdrawal response from painful stimulation which is not used measuring method in our animal model was also decreased by DBS. Conclusion : The VPL is an effective target on pain modulation. Specifically we could demonstrate changes of pain response duration which is not used, and it was also significantly meaningful. We thought that this study would be helpful in understanding the relation between VPL-DBS and neuropathic pain.

• Korean Chemical Engineering Research
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• v.57 no.2
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• pp.274-282
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• 2019

In recent years, big data analysis has been expanded to include automatic control through reinforcement learning as well as prediction through modeling. Research on the utilization of image data is actively carried out in various industrial fields such as chemical, manufacturing, agriculture, and bio-industry. In this paper, we applied NASNet, which is an AutoML reinforced learning algorithm, to DeepU-Net neural network that modified U-Net to improve image semantic segmentation performance. We used BRATS2015 MRI data for performance verification. Simulation results show that DeepU-Net has more performance than the U-Net neural network. In order to improve the image segmentation performance, remove dropouts that are typically applied to neural networks, when the number of kernels and filters obtained through reinforcement learning in DeepU-Net was selected as a hyperparameter of neural network. The results show that the training accuracy is 0.5% and the verification accuracy is 0.3% better than DeepU-Net. The results of this study can be applied to various fields such as MRI brain imaging diagnosis, thermal imaging camera abnormality diagnosis, Nondestructive inspection diagnosis, chemical leakage monitoring, and monitoring forest fire through CCTV.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.3
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• pp.132-137
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• 2019

The amount of data generated from medical images is increasingly exceeding the limits of professional visual analysis, and the need for automated medical image analysis is increasing. For this reason, this study evaluated the classification and accuracy according to the presence or absence of tumor using Inception V3 deep learning model, using MRI medical images showing normal and tumor findings. As a result, the accuracy of the deep learning model was 90% for the training data set and 86% for the validation data set. The loss rate was 0.56 for the training data set and 1.28 for the validation data set. In future studies, it is necessary to secure the data of publicly available medical images to improve the performance of the deep learning model and to ensure the reliability of the evaluation, and to implement modeling by improving the accuracy of labeling through labeling classification.

• BMB Reports
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• v.49 no.2
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• pp.71-72
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• 2016

Focal cortical dysplasia type II (FCDII) is a focal malformation of the developing cerebral cortex and the major cause of intractable epilepsy. However, since the molecular genetic etiology of FCD has remained enigmatic, the effective therapeutic target for this condition has remained poorly understood. Our recent study on FCD utilizing various deep sequencing platforms identified somatic mutations in MTOR (existing as low as 1% allelic frequency) only in the affected brain tissues. We observed that these mutations induced hyperactivation of the mTOR kinase. In addition, focal cortical expression of mutant MTOR using in utero electroporation in mice, recapitulated the neuropathological features of FCDII, such as migration defect, cytomegalic neuron and spontaneous seizures. Furthermore, seizures and dysmorphic neurons were rescued by the administration of mTOR inhibitor, rapamycin. This study provides the first evidence that brain somatic activating mutations in MTOR cause FCD, and suggests the potential drug target for intractable epilepsy in FCD patients.