• PNF and Movement
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• v.14 no.1
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• pp.41-47
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• 2016

Purpose: In general, confabulation is defined as confusion of reality with past events without apparent prompting, in association with disruption of the capacity for retrieval and encoding of memory. We report on a patient who showed spontaneous confabulation associated with injury of the Papez circuit following middle cerebral artery (MCA) infarction. Methods: A 67-year-old female patient suffered cerebral infarct resulting from spontaneous MCA territory. After onset of the MCA infarct, she showed severe memory impairment and provoked confabulation. The Papez circuit was reconstructed for evaluation of part of it using diffusion tensor tractography (DTT). Fractional anisotropy (FA), mean diffusivity (MD), and tract volume were measured. Results: The right thalamocingulate tract showed a significant decrement of FA value and tract volume, and an increment of MD value by more than two standard deviations of that of normal control subjects. The tract volume in the left fornix and mammillothalamic tract decreased by more than two standard deviations of that of normal control subjects. Conclusion: Injuries of the Papez circuit were demonstrated in a patient who showed severe memory impairment and provoked confabulation following MCA infarct. We believe that analysis of the Papez circuit tract using DTT is useful in elucidating the cause of provoked confabulation in patients with MCA infarct.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.175-178
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• 2002

인간은 두뇌의 일부를 이용하여 감각 정보를 수집하고 이에 대한 분석 및 판단을 행한 후에 행동을 취하는 일반적인 과정에 의해, 느끼고 생각하고 말한다. 이런 일련의 과정은 신경생리학적으로 밝혀진 바에 의하면, 대뇌의 시상에 분포한 일차 감각영역에서 감각 정보를 수집한다. 수집된 감각 정보는 과거 기억과의 비교를 통해 인식되고 인식된 정보는 일차 운동영역으로 전달되어 행동으로 나타난다. 수집된 감각 정보를 판단하는 기관은 감각 연합 영역으로 알려져 있으며, 과거 정보를 통해 비교하여 판단하는 방식이고, 과거 정보에 없는 새로운 정보의 경우 파페즈회로를 통해 새로운 정보로 기억하게 된다. 본 논문에서는 신경회로망의 적응적 학습 기법을 통해 파페즈회로의 기능을 구현하고자 한다. 기존 학습의 내용에 의해 알고 있는 감각 입력에 대해서는 인식 결과를 출력하고 그렇지 않은 입력에 대해서는 학습을 통해 이후 과정에 대응하도록 적응적인 구조와 학습 방법을 지닌 신경회로망을 이용하여 구현하고자 한다.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1243-1246
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• 2003

It is known that structure of Human's brain information system is controlled by cerebral cortex mainly. Cerebral cortex is divided by sensory area, motor area and associated area largely. Sensory area takes part in information from environment and motor area is actuation by decision as associated area determined. It is possible to copy brain information system by input-output pattern. but there is difficulty in modeling of memorizing new information. Such action is performed by Limbic Lobe and Papez circuit which is controlled by intrinsic emotion. So we need of definition of emotion's role in decision. In this paper, we define roles of emotion in intrinsic decision using Dynamic Cognitive Maps(DCMs). The emotion is evaluated by outside information then intrinsic decision performed as how much emotion variated. The dynamic cognitive maps take part in emotion evaluating process.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.423-426
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• 2003

In this paper, we use the modular neural network and recurrent neural network structure to implement the artificial brain information processing. We also select related adaptive learning methods to learn the entirely new input in the existed neural network. With this, a part of information process in brain is implemented as and autonomous and adaptive model by neural network and further more, the entire model for information process in brain can be introduced.