• The Journal of Korean Academy of Sensory Integration
• /
• v.9 no.2
• /
• pp.51-60
• /
• 2011

Objective : The characteristics of physiological responses of ADHD children to sensory stimulation were examined by types of sensory stimulation, measurement tools, and responses. In addition the behavioral characteristics were examined by analyzing items of common problems according to the measuring tool, frequency, and measurement tools. Methods : A systematic review methods were used. Papers published in the Journal between January, 1990 and December 31, 2011 were searched through Riss4U, MEDLINE /PubMed, CINAH. The main terms searched were "ADHD, Children, Sensory processing, Sensory integration, SP, SSP, SOR, TIE, CSP, SEP, EDR", and 15 papers were analyzed. Results : 1. The number of studies on physiological responses of children with ADHD to sensory stimulation was five (33.33 percent), the number of studies on behavioral responses was ten(66.67%), and the number of studies combined the two kinds of study was two (13.33%), where a total of 15 (100%) papers were analyzed. 2. In five studies on the physiological response, there were three studies using tactile and proprioceptive stimulations and two studies using olfactory, auditory, visual, tactile, and vestibular sensories. 3. In ten studies on the behavioral responses, there were five studies using SP, three studies using SSP, two studies using SOR, one study using TIE, and one study using CSP. Conclusion : In the characteristics of physiological responses of children with ADHD children to sensory stimulation, there was in the action potential of the cells in hand region of the primary sensorimotor cortex neurons. It was analyzed that there was an initial state and it appeared show a obvious and fast habituation in the later state; the time of recovery seemed to have many non-specific responses. In the characteristics of behavioral responses, there were inattention / distraction, vestibular processing, sensory processing related to endurance / tone, modulation of sensory input affecting emotional responses, low energy/weak.

• The Korean Journal of Nuclear Medicine
• /
• v.35 no.1
• /
• pp.23-32
• /
• 2001

Purpose: Cortical dysplasia (CD) designates a diverse group of malformations resulting from one or more abnormalities in the development of the cerebral cortex. We investigated the findings of interictal SPECT and the diagnostic usefulness of interical and ictal SFECT according to pathological grading (PG) in comparison with MRI. Materials and Methods: This study included 16 patients (M:F=9:7, age: $19.9{\pm}11.8$ yrs) with pathologically proven CD. Tc-99m ECD SPECT was performed in all patients: interictal 11, interictal and ictal 3, ictal 2. MRI were obtained in all patients and image analysis was done blindly as to the result of SPECT. Pathologic findings of CD were classified into grade 1 G1, dyslamination), grade 2 (G2, dysplastic neurons) and grade 3 (G3, balloon cells). We compared SFECT with MRI in lesions-to-lesions and analyzed the result according to PG. Results: In SFECT and MRI. 38 and 27 lesions were visually recognized. In 14 interictal SPECT, variable findings in 35 lesions were demonstrated: 25 were hypoperfusion, 7 hyperperfusion, 2 heterotopic perfusion in the white matter. By comparison between two studios, missed lesions were founded: SPECT were 1 lesion, MRI 12. Review of missed 12 lesions of MRI were followed according to PG: G1 patients were 16.7% (4/19), G2 40.0% (6/15), and G3 50% (2/4). Conclusion: Interictal SFECT in CD showed variable findings such as hypoperfusion, hyperperfusion or heterotopic perfusion. However, for detection of missed CD on MRI, SFECT may help to detect a functional abnormality of the lesion with high PG.

• The korean journal of orthodontics
• /
• v.28 no.3 s.68
• /
• pp.441-452
• /
• 1998

The c-fos is known as neuronal marker of second neurons which is activated by noxious peripheral stimulation. To investigate the changes of c-fos el(pression in the trigeminal nucleus complex during tooth movement, immunohistochemical study was performed. Experimental rats(9 weeks old, 210 gm 21 rats) were divided into seven groups(normal, 1 hour group, 3 hour group, 6 hour group, 12 hour group, 1 day group,3 day group). Rats in the normal group were anesthesized without orthodontic force. Rats in the experimental groups were applied orthodontic force (approximately 30 gm) to upper right maxillary molar. Frozen sections of brain stem were immunostained using rabbit antisera. The changes of c-fos expression were observed with respect to rostrocaudal distribution, laminar organization, md duration of orthodontic force application. The study results were as follows $\cdot$The c-fos nuclei in the dorsal part were observed from ipsilateral transition zone of subnucleus interpolaris and subnucleus caudalis to $C_1$ cervical dorsal horn rostrocaudally. The maximal peak point was the rostral part of subnucleus caudalis. The greatest proportion of c-fos cells were located within lamina I and II. $\cdot$The c-fos nuclei in the dorsal Part were observed from the most caudal part of subnucleus interpolaris to the middle part of the subnucleus caudalis. $\cdot$The number of c-fos immunoreactive dot increased at 1 hour group, reached its maximum at the 3 and 6 hour groups, and showed a decreasing trend after 12 hours. These results imply that nociceptive stimulation caused by continuous orthodontic force might be modulated by transition zone of subnucleus interpolaris and subnucleus caudalis, subnucleus caudalis, $C_1$ spinal dorsal hem.

• Clinical and Experimental Pediatrics
• /
• v.52 no.5
• /
• pp.594-602
• /
• 2009

Purpose : Transforming growth factor (TGF)-${\beta}1$ reportedly increases neuronal survival by inhibiting the induction of inducible nitric oxide synthase (NOS) in astrocytes and protecting neurons after excitotoxic injury. However, the neuroprotective mechanism of $TGF-{\beta}1$ on hypoxic-ischemic (HI) brain injury in neonatal rats is not clear. The aim of this study was to determine whether $TGF-{\beta}1$ has neuroprotective effects via a NO-mediated mechanism and N-methyl-D-aspartate (NMDA) receptor modulation on perinatal HI brain injury. Methods : Cortical cells were cultured using 19-day-pregnant Sprague-Dawley (SD) rats treated with $TGF-{\beta}1$ (1, 5, or 10 ng/mL) and incubated in a 1% O2 incubator for hypoxia. Seven-day-old SD rat pups were subjected to left carotid occlusion followed by 2 h of hypoxic exposure (7.5% $O_2$). $TGF-{\beta}1$ (0.5 ng/kg) was administered intracerebrally to the rats 30 min before HI brain injury. The expressions of NOS and NMDA receptors were measured. Results : In the in vitro model, the expressions of endothelial NOS (eNOS) and neuronal NOS (nNOS) increased in the hypoxic group and decreased in the 1 ng/mL $TGF-{\beta}1-treated$ group. In the in vivo model, the expression of inducible NOS (iNOS) decreased in the hypoxia group and increased in the $TGF-{\beta}1$-treated group. The expressions of eNOS and nNOS were reversed compared with the expression of iNOS. The expressions of all NMDA receptor subunits decreased in hypoxia group and increased in the $TGF-{\beta}1$-treated group except NR2C. Conclusion : The administration of $TGF-{\beta}1$ could significantly protect against perinatal HI brain injury via some parts of the NO-mediated or excitotoxic mechanism.

• Journal of Intelligence and Information Systems
• /
• v.27 no.1
• /
• pp.65-82
• /
• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.