• The Journal of Korea Robotics Society
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• v.1 no.2
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• pp.163-171
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• 2006

This paper introduces the research progress on the artificial brain in the Telerobotics and Control Laboratory at KAIST. This series of studies is based on the assumption that it will be possible to develop an artificial intelligence by copying the mechanisms of the animal brain. Two important brain mechanisms are considered: spike-timing dependent plasticity and dopaminergic plasticity. Each mechanism is implemented in two coding paradigms: spike-codes and rate-codes. Spike-timing dependent plasticity is essential for self-organization in the brain. Dopamine neurons deliver reward signals and modify the synaptic efficacies in order to maximize the predicted reward. This paper addresses how artificial intelligence can emerge by the synergy between self-organization and reinforcement learning. For implementation issues, the rate codes of the brain mechanisms are developed to calculate the neuron dynamics efficiently.

• BMB Reports
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• v.54 no.8
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• pp.393-402
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• 2021

In animals, proper locomotion is crucial to find mates and foods and avoid predators or dangers. Multiple sensory systems detect external and internal cues and integrate them to modulate motor outputs. Proprioception is the internal sense of body position, and proprioceptive control of locomotion is essential to generate and maintain precise patterns of movement or gaits. This proprioceptive feedback system is conserved in many animal species and is mediated by stretch-sensitive receptors called proprioceptors. Recent studies have identified multiple proprioceptive neurons and proprioceptors and their roles in the locomotion of various model organisms. In this review we describe molecular and neuronal mechanisms underlying proprioceptive feedback systems in C. elegans, Drosophila, and mice.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.25-28
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• 2020

Automatic segmentation of brain tissues such as WM, GM, and CSF from brain MRI scans is helpful for the diagnosis of many neurological disorders. Accurate segmentation of these brain structures is a very challenging task due to low tissue contrast, bias filed, and partial volume effects. With the aim to improve brain MRI segmentation accuracy, we propose an end-to-end convolutional based U-SegNet architecture designed with multi-scale kernels, which includes cascaded dilated convolutions for the task of brain MRI segmentation. The multi-scale convolution kernels are designed to extract abundant semantic features and capture context information at different scales. Further, the cascaded dilated convolution scheme helps to alleviate the vanishing gradient problem in the proposed model. Experimental outcomes indicate that the proposed architecture is superior to the traditional deep-learning methods such as Segnet, U-net, and U-Segnet and achieves high performance with an average DSC of 93% and 86% of JI value for brain MRI segmentation.

• Communications for Statistical Applications and Methods
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• v.30 no.6
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• pp.561-575
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• 2023

Brain network analysis has attracted the interest of neuroscience researchers in studying brain diseases. Magnetoencephalography (MEG) is especially proper for analyzing functional connectivity due to high temporal and spatial resolution. The application of graph theory for functional connectivity analysis has been studied widely, but research on network modeling for MEG still needs more. Temporal exponential random graph model (TERGM) considers temporal dependencies of networks. We performed the brain network analysis, including static/temporal network statistics, on two groups of epilepsy patients who removed the left (LT) or right (RT) part of the brain and healthy controls. We investigate network differences using Multiset canonical correlation analysis (MCCA) and TERGM between epilepsy patients and healthy controls (HC). The brain network of healthy controls had fewer temporal changes than patient groups. As a result of TERGM, on the simulation networks, LT and RT had less stable state than HC in the network connectivity structure. HC had a stable state of the brain network.

• International Journal of Stem Cells
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• v.17 no.2
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• pp.158-181
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• 2024

This study offers a comprehensive overview of brain organoids for researchers. It combines expert opinions with technical summaries on organoid definitions, characteristics, culture methods, and quality control. This approach aims to enhance the utilization of brain organoids in research. Brain organoids, as three-dimensional human cell models mimicking the nervous system, hold immense promise for studying the human brain. They offer advantages over traditional methods, replicating anatomical structures, physiological features, and complex neuronal networks. Additionally, brain organoids can model nervous system development and interactions between cell types and the microenvironment. By providing a foundation for utilizing the most human-relevant tissue models, this work empowers researchers to overcome limitations of two-dimensional cultures and conduct advanced disease modeling research.

• Radiation Oncology Journal
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• v.20 no.1
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• pp.1-16
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• 2002

Purpose : Three dimensional conformal radiotherapy planning is being used widely for the treatment of patients with brain tumor. However, it takes much time to develop an optimal treatment plan, therefore, it is difficult to apply this technique to all patients. To increase the efficiency of this technique, we need to develop standard radiotherapy plant for each site of the brain. Therefore we developed several 3 dimensional conformal radiotherapy plans (3D plans) for tumors at each site of brain, compared them with each other, and with 2 dimensional radiotherapy plans. Finally model plans for each site of the brain were decide. Materials and Methods : Imaginary tumors, with sizes commonly observed in the clinic, were designed for each site of the brain and drawn on CT images. The planning target volumes (PTVs) were as follows; temporal $tumor-5.7\times8.2\times7.6\;cm$, suprasellar $tumor-3\times4\times4.1\;cm$, thalamic $tumor-3.1\times5.9\times3.7\;cm$, frontoparietal $tumor-5.5\times7\times5.5\;cm$, and occipitoparietal $tumor-5\times5.5\times5\;cm$. Plans using paralled opposed 2 portals and/or 3 portals including fronto-vertex and 2 lateral fields were developed manually as the conventional 2D plans, and 3D noncoplanar conformal plans were developed using beam's eye view and the automatic block drawing tool. Total tumor dose was 54 Gy for a suprasellar tumor, 59.4 Gy and 72 Gy for the other tumors. All dose plans (including 2D plans) were calculated using 3D plan software. Developed plans were compared with each other using dose-volume histograms (DVH), normal tissue complication probabilities (NTCP) and variable dose statistic values (minimum, maximum and mean dose, D5, V83, V85 and V95). Finally a best radiotherapy plan for each site of brain was selected. Results : 1) Temporal tumor; NTCPs and DVHs of the normal tissue of all 3D plans were superior to 2D plans and this trend was more definite when total dose was escalated to 72 Gy (NTCPs of normal brain 2D $plans:27\%,\;8\%\rightarrow\;3D\;plans:1\%,\;1\%$). Various dose statistic values did not show any consistent trend. A 3D plan using 3 noncoplanar portals was selected as a model radiotherapy plan. 2) Suprasellar tumor; NTCPs of all 3D plans and 2D plans did not show significant difference because the total dose of this tumor was only 54 Gy. DVHs of normal brain and brainstem were significantly different for different plans. D5, V85, V95 and mean values showed some consistent trend that was compatible with DVH. All 3D plans were superior to 2D plans even when 3 portals (fronto-vertex and 2 lateral fields) were used for 2D plans. A 3D plan using 7 portals was worse than plans using fewer portals. A 3D plan using 5 noncoplanar portals was selected as a model plan. 3) Thalamic tumor; NTCPs of all 3D plans were lower than the 2D plans when the total dose was elevated to 72 Gy. DVHs of normal tissues showed similar results. V83, V85, V95 showed some consistent differences between plans but not between 3D plans. 3D plans using 5 noncoplanar portals were selected as a model plan. 4) Parietal (fronto- and occipito-) tumors; all NTCPs of the normal brain in 3D plans were lower than in 2D plans. DVH also showed the same results. V83, V85, V95 showed consistent trends with NTCP and DVH. 3D plans using 5 portals for frontoparietal tumor and 6 portals for occipitoparietal tumor were selected as model plans. Conclusion : NTCP and DVH showed reasonable differences between plans and were through to be useful for comparing plans. All 3D plans were superior to 2D plans. Best 3D plans were selected for tumors in each site of brain using NTCP, DVH and finally by the planner's decision.

• Journal of the korean Society of Automotive Engineers
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• v.11 no.5
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• pp.76-89
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• 1989

With the objective of studying the response of brain tissue in a transient rotational acceleration of the head, as occurs in car crash, the problem of a cylindrical case containing a prototype brain material of silicone gel and subjected to a rotational acceleration around the axis of the cylinder is analysed. The prototype material is considered to be homogeneous and isotropic, and is modeled alternatively as a linear elastic or a linear viscoelastic solid. The computational model for the present problem consists of a 3-dimensional isoparametric finite element model, wherein large deformations and large strains are treated through the updated Lagrangian approach. A comparison of the results of the present 3-dimensional computations, with the attendant assumptions on material data, is made with the results of independent experimental study. The deformation profiles and the major characteristics of response of the brain material are in good agreement with the test results. Moreover, the study suggests the possibility that the use of more accurate material data may yield very useful results even appropriate for accurate quantification of deformations.

• Journal of Korea Multimedia Society
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• v.16 no.9
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• pp.1018-1030
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• 2013

The corpus callosum is the largest connective structure in the brain, and its shape and size are correlated to sex, age, brain growth and degeneration, handedness, musical ability, and neurological diseases. Manually segmenting the corpus callosum from brain magnetic resonance (MR) image is time consuming, error prone, and operator dependent. In this paper, two semi-automatic segmentation methods are present: the active contour model-based approach and the active shape model-based approach. We tested these methods on an MR image of the human brain and found that the active contour approach had better segmentation accuracy but was slower than the active shape approach.

• The Korean Journal of Applied Statistics
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• v.29 no.6
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• pp.1129-1145
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• 2016

Functional neuro-connectivity is one of the main issues in brain science in the sense that it is closely related to neurodynamics in the brain. In the paper, we choose fMRI as a main form of response data to brain activity due to its high resolution. We review methods for analyzing functional neuro-connectivity assuming that measurements are made on physiological responses to neuron activation. This means that we deal with a state-space and measurement model, where the state-space model is assumed to represent neurodynamics. Analysis methods and their interpretation should vary subject to what was measured. We included analysis results of real fMRI data by applying a high-dimensional autoregressive model, which indicated that different neurodynamics were required for solving different types of geometric problems.

• Journal of Korean Neurosurgical Society
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• v.67 no.5
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• pp.521-530
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• 2024

Objective : Dexpanthenol (DXP), which has known neuroprotective effects, has been shown to be beneficial in various experimental models and ischaemic diseases. The aim of this study was to investigate the possible neuroprotective effects of DXP in a traumatic brain injury (TBI) model. Methods : Thirty-six Wistar-Albino female rats, approximately 6 months old, weighing 220-285 g were used. All rats were subjected to closed head trauma by dropping a weight of 350 g on the parietal region from a height of 50 cm at an angle of 180 degrees in the prepared head trauma model setup. The rats were divided into four groups as control (group 1), trauma (group 2), trauma + DXP (group 3), and DXP (group 4). In group 3, DXP was administered intraperitoneally at a dose of 500 mg/kg for six times at 30 minutes, 6, 12, 24, 36, and 48 hours. In group 4, DXP was administered intraperitoneally simultaneously with group 3 without causing head trauma. Blood samples were taken from all rats 72 hours later for biochemical examination. After blood samples were taken, rats were decapitated under general anaesthesia. Cerebral tissue samples were taken from decapitated rats for immunohistochemical and histopathological examination. Results : Cytokine markers were found to be increased in posttraumatic brain tissue. Malondialdehyde and glutathione reductase levels were lower in group 3 compared to group 2. In addition, superoxide dismutase, glutathione peroxidase and catalase levels were significantly higher in group 3 compared to group 2. In histological evaluation, congestion in the piamater layer, cell infiltration, vascular congestion, hemorrhage and neuronal degeneration were significantly decreased in group 3 compared to group 2. DXP seems to be beneficial in neurological recovery in terms of histological and oxidative changes after head trauma in rats. Conclusion : DXP should be further evaluated for its possible therapeutic effect in TBI.