• Korean Journal of Biological Psychiatry
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• v.4 no.2
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• pp.194-197
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• 1997

Neural network models, also known as connectionist models or PDP models, simulate some functions of the brain and may promise to give insight in understanding the cognitive brain functions. The models composed of neuron-like elements that are linked into circuits can learn and adapt to its environment in a trial and error fashion. In this article, the history and principles of the neural network modeling are briefly reviewed, and its applications to psychiatry are discussed.

• Journal of Biomedical Engineering Research
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• v.2 no.2
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• pp.127-140
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• 1981

This paper describes the mechanism of information processing in the nervous system through neuron pool model which is consisted of six single neural models. In the neuron pool model, summation characteristic of stimulus satisfies those of real nervous system and output impulse rate increases linearly to the input stimulus. Occlusion phenomena of the neuron pool model is approached to those of real nervous system and also if the threshold potential within sutlirninal fringe is increased, facilitation phenomena appreared. Therefore, the results of this study suggest that we can construct large neuron pool with many single neural models and verify the mechanism of information processing in the wide part of nervous system.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.60-64
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• 1995

The conventional neural network models are a parody of biological neural structures, and have very slow learning. In order to emulate some dynamic functions, such as learning and adaption, and to better reflect the dynamics of biological neurons, M.M. Gupta and D.H. Rao have developed a 'dynamic neural model'(DNU). Proposed neural unit model is to introduce some dynamics to the neuron transfer function, such that the neuron activity depends on internal states. Integrating an dynamic elementry processor within the neuron allows the neuron to act dynamic response Numerical examples are presented for a model system. Those case studies showed that the proposed DNU is so useful in practical sense.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.157-160
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• 1995

Neural networks potentially offer a general framework for modeling and control of nonlinear systems. The conventional neural network models are a parody of biological neural structures, and have very slow learning. In order to emulate some, dynamic functions, such as learning and adaption, and to better reflect the dynamics of biological neurons, M.M.Gupta and D.H.Rao have developed a 'dynamic neural model'(DNU). Proposed neural unit model is to introduce some dynamics to the neuron transfer function, such that the neuron activity depends on internal states. Numerical examples are presented for a model system. Those case studies showed that the proposed DNU is so useful in practical sense.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.4
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• pp.311-321
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• 2022

The report reviews recent research efforts in demonstrating a computing system whose operation principle mimics the dynamics of biological neurons. The temporal variation of the membrane potential of neurons is one of the key features that contribute to the information processing in the brain. We first summarize the neuron models that explain the experimentally observed change in the membrane potential. The function of ion channels is briefly introduced to understand such change from the molecular viewpoint. Dedicated circuits that can simulate the neuronal dynamics have been developed to reproduce the charging and discharging dynamics of neurons depending on the input ionic current from presynaptic neurons. Key elements include volatile memristors that can undergo volatile resistance switching depending on the voltage bias. This behavior called the threshold switching has been utilized to reproduce the spikes observed in the biological neurons. Various types of threshold switch have been applied in a different configuration in the hardware demonstration of neurons. Recent studies revealed that the memristor-based circuits could provide energy and space efficient options for the demonstration of neurons using the innate physical properties of materials compared to the options demonstrated with the conventional complementary metal-oxide-semiconductors (CMOS).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.150-152
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• 2022

In this work, we propose a model that considers the behavior and synaptic plasticity of sensory neurons based on Liquid Time-constant Network (LTC). The neuron connection structure was experimented with four types: the increasing number of neurons, the decreasing number, the decreasing number, and the decreasing number. In this study, we experimented using a time series prediction dataset to see if the performance of the changed model improved compared to LTC. Experimental results show that the application of modeling of sensory neurons does not always bring about performance improvements, but improves performance through proper selection of learning rules depending on the type of dataset. In addition, the connective structure of neurons showed improved performance when it was less than four layers.

• Biomolecules & Therapeutics
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• v.27 no.3
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• pp.265-275
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• 2019

Technological advances of mankind, through the development of electrical and communication technologies, have resulted in the exposure to artificial electromagnetic fields (EMF). Technological growth is expected to continue; as such, the amount of EMF exposure will continue to increase steadily. In particular, the use-time of smart phones, that have become a necessity for modern people, is steadily increasing. Social concerns and interest in the impact on the cranial nervous system are increased when considering the area where the mobile phone is used. However, before discussing possible effects of radiofrequency-electromagnetic field (RF-EMF) on the human body, several factors must be investigated about the influence of EMFs at the level of research using in vitro or animal models. Scientific studies on the mechanism of biological effects are also required. It has been found that RF-EMF can induce changes in central nervous system nerve cells, including neuronal cell apoptosis, changes in the function of the nerve myelin and ion channels; furthermore, RF-EMF act as a stress source in living creatures. The possible biological effects of RF-EMF exposure have not yet been proven, and there are insufficient data on biological hazards to provide a clear answer to possible health risks. Therefore, it is necessary to study the biological response to RF-EMF in consideration of the comprehensive exposure with regard to the use of various devices by individuals. In this review, we summarize the possible biological effects of RF-EMF exposure.

• Journal of Korean Biological Nursing Science
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• v.4 no.1
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• pp.101-112
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• 2002

Peripheral nerve injury results in plastic changes in the dorsal ganglia (DRG) and spinal cord, and is often complicated with neuropathic pain. The mechanisms underlying these changes are not known, but these changes seem to be most likely related to the neurotrophic factors. This study investigated the effects of mechanical peripheral nerve injury on expression of brain-derived neurotrophic factor(BDNF) in the DRG and spinal cord in rats. 1) Bennett model and Chung model groups showed significantly increased percentage of small, medium and large BDNF-immunoreactive neurons in the ipsilateral $L_4$ DRG compared with those in the contralateral side at 1 and 2 weeks of the injury. 2) In the ipsilateral $L_5$ DRG of the Chung model, percentage of medium and large BDNF-immunoreactive neurons increased significantly at 1 week, whereas that of large BDNF-immunoreactive neurons decreased at 2 week when compared with those in the contralateral side. The intensity of immunoreactivity of each neuron was lower in the ipsilateral than in the contralateral DRG. 3) In the spinal cord, the Bennett and Chung model groups showed a markedly increased BDNF-immunoreactivity in axonal fibers of both superficial and deeper laminae. The present study demonstrates that peripheral nerve injury in neuropathic models altered the BDNF expression in the DRG and spinal cord. This may suggest important roles of BDNF in sensory abnormalities after nerve injury and in protecting the large-sized neurons in the damaged DRG.

• Development and Reproduction
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• v.11 no.1
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• pp.13-20
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• 2007

In all female mammals, reproductive system is one of the first biological systems to show age-related decline. Female mammals in reproductive aging, though the phenomena is somewhat species-specific, start to show declining fertility and changes of numerous physiological functions. This review will present a current information on the aging of the female reproductive hormonal axis and introduce three useful rodent models for studying this field. Middle age($8{\sim}12$ months old) in female rats and mice is comparable to the stage prior to the entry of menopause in human. In this period pulsatile and surge GnRH secretion from hypothalamus gradually attenuated, then reduced pulsatile and surge LH secretion is followed consequently. This age-related defects in GnRH-LH neuroendocrine axis seem to be highly correlated with the defects in brain signals which modulate the activities of GnRH neuron. Many researchers support the idea which the age-related hypothalamic defects are the main cause of reproductive aging, but some ovarian factors such as inhibin response also could contribute to the induction of reproductive senescence. Some rodent models are quite valuable in studying the reproductive aging. The follitropin receptor knockout(FORKO) mice, both of null and haploinsufficient state, could produce depletion of oocyte/follicle with age. Dioxin/aryl hydrocarbon receptor(AhR) knockout mice also show severe ovarian defects and poor reproductive success early in their life compared to the age-matched normal mice. Further studies on the reproductive aging will be a great help to evaluate the benefits and risks of hormone replacement therapy(HRT) and to improve the safety of HRT.

• Development and Reproduction
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• v.9 no.1
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• pp.1-5
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• 2005

The hypothalamo-pituitary-gonadal hormone axis is centrally controlled by a complex regulatory network of excitatory and inhibitory signals, that is dormant during infantile and juvenile periods and activated at puberty. The kisspeptins are the peptide products of the KiSS-1 gene and the endogenous agonists for the G protein-coupled receptor 54(GPR54). Although KiSS-1 was initially discovered as a metastasis suppressor gene, a recent evidence suggests the KiSS-1/GPR54 system is a key regulator of the reproductive system. Yet the actual role of the KiSS-1/GPR54 system in the neuroendocrine control of gonadotropin secretion remains largely unexplored, the system could be the first missing link in the reproductive hormonal axis. Central or peripheral administration of kisspeptin stimulates the hypothalamic-pituitary-gonadal axis, increasing circulating gonadotropin levels in rodents, sheep, monkey and human models. These effects appear likely to be mediated via the hypothalamic GnRH neuron system, although kisspeptins may have direct effects on the anterior pituitary gland. The loss of function mutations of the GPR54(GPR54-/-) have been associated with lack of puberty onset and idiopathic hypogonadotropic hypogonadism(IHH). So kisspeptin infusion may provide a novel mechanism for HPG axis manipulation in disorders of the reproductive system.