• Journal of the Ergonomics Society of Korea
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• v.35 no.4
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• pp.225-235
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• 2016

Objective: The aim of this study is to model all levels of situation awareness (SA), which would be able to predict situation awareness quantitatively. Background: When measuring situation awareness, directly measuring SA methods such as SAGAT and SART have been utilized. Several approaches (cognitive modeling approaches) were introduced to model SA but level 3 SA was not completed. For real-life situation, however, it is necessary to detect the problematic level of SA rather than overall SA. Therefore, we proposed a new model of all levels of SA in this study. Method: In order to model all levels of SA, this study chose factors in ACT-R architecture through literature review. ATC (Air Traffic Control)-related simulation task was video-taped to analyze human behaviors in order to model all levels of SA including level 3. Results: As a result, regression analyses show that cognitive activities (neural activations) represented for all levels of SA were highly correlated with SAGAT. Conclusion: In conclusion, neural activations in ACT-R could be proved to be effective to model all levels of SA. Application: Our SA model could be used to predict all levels of SA quantitatively without directly measuring the SA of operators.

• Korean Journal of Cognitive Science
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• v.13 no.1
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• pp.23-40
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• 2002

This study is to examine brain regions that are involved in picture encoding in normal adults using fMRI methods. In Scan 1, the picture encoding was studied during a semantic categorization task in comparison with word. In Scan 2 task type effects were studied both during a picture naming task and during a semantic categorization task with pictures. Subjects were asked to make decision either by pressing a mouse button (Scan 1) or by responding subvocally (naming or saying yes/no) (Scan 2). Regardless of stimulus type, left prefrontal, bilateral occipital, and parietal activations were observed during semantic processing in comparison with fixation baseline. Processing of word stimulus relative to picture resulted in activations in prefrontal and parieto-temporal regions in the left side while that of picture stimulus relative to word resultd in activations in bilateral extrastriatal visual cortices and parahippocampal regions. In spite of the same task demands, stimulus-specific information processings were involved and mediated by different neural substrates; the word encoding was associated with more semantic/lexical processings than pictures and the picture processing associated with more perceptual and novelty related information processings than word. Activations of dorsal part of inferior prefrontal region, i.e., Broca's areas were found both during the picture naming and during the semantic tasks subvocally performed Especially, during the picture naming task, greater occipital activations were found bilaterally relative to the semantic categorization task. indicating a possibility that greater and higher visual processing was involved in retrieving the name referred by picture stimuli.

• Journal of Biomedical Engineering Research
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• v.28 no.1
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• pp.139-147
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• 2007

The aim of this study was to evaluate effects of short-tenn repetitive-bilateral excercise on the activation of motor network using functional magnetic resonance imaging (fMRI). The training program was performed at 1 hr/day, 5 days/week during 6 weeks. Fugl-Meyer Assessments (FMA) were performed every two weeks during the training. We compared cerebral and cerebellar cortical activations in two different tasks before and after the training program: (1) the only unaffected hand movement (Task 1); and (2) passive movements of affected hand by the active movement of unaffected hand (Task 2). fMRI was performed at 3T with wrist flexion-extension movement at 1 Hz during the motor tasks. All patients showed significant improvements of FMA scores in their paretic limbs after training. fMRI studies in Task 1 showed that cortical activations decreased in ipsilateral sensorimotor cortex but increased in contralateral sensorimotor cortex and ipsilateral cerebellum. Task 2 showed cortical reorganizations in bilateral sensorimotor cortex, premotor area, supplemetary motor area and cerebellum. Therefore, this study demonstrated that plastic changes of motor network occurred as a neural basis of the improvement subsequent to repetitive-bilateral excercise using the symmetrical upper-limb ann motion trainer.

• Journal of Advanced Marine Engineering and Technology
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• v.21 no.1
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• pp.66-70
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• 1997

In this paper a new learning algorithm for curvature smoothing and improved generalization for multi-layer neural networks is proposed. To enhance the generalization ability a constraint term of hidden neuron activations is added to the conventional output error, which gives the curvature smoothing characteristics to multi-layer neural networks. When the total cost consisted of the output error and hidden error is minimized by gradient-descent methods, the additional descent term gives not only the Hebbian learning but also the synaptic weight decay. Therefore it incorporates error back-propagation, Hebbian, and weight decay, and additional computational requirements to the standard error back-propagation is negligible. From the computer simulation of the time series prediction with Santafe competition data it is shown that the proposed learning algorithm gives much better generalization performance.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.6
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• pp.71-78
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• 1997

In this paper, a new neural network training algorithm will be devised for function approximator with good generalization characteristics and tested with the time series prediction problem using santaFe competition data sets. To enhance the generalization ability a constraint term of hidden neuraon activations is added to the conventional output error, which gives the curvature smoothing characteristics to multi-layer neural networks. A hybrid learning algorithm of the error-back propagation and Hebbian learning algorithm with weight decay constraint will be naturally developed by the steepest decent algorithm minimizing the proposed cost function without much increase of computational requriements.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.11a
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• pp.210-213
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• 1999

In this paper, we propose a new neural network for the control of a robot manipulator The proposed neural network structure is that all of network outputs feed bark into hidden units and output units from feedback units The feedback units are only to memorize the previous activations of the hidden units and output units and can be considered to function as one-step time delays. The proposed neural network works standard back-propagation Loaming algorithm. The simulation and experiment results showed the effectiveness of using the modified neural network structure in the control of the robot manipulator.

• The Journal of Korean Medicine
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• v.31 no.5
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• pp.167-178
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• 2010

Objectives: The present study investigated the effects of acupuncture treatment and their mechanism by using the kainic acid (KA)-induced epilepsy mouse model. Materials and Methods: The seizure was induced by an intraperitoneal (i.p.) injection of 30 mg/kg KA, and the acupuncture treatment was subsequently administered to acupoint Shaofu(HT8) bilaterally with two pretreatment sessions before injection (total 3 times over 3 days). Twenty four hours after injection, we observed the survival of neuronal cells in the CA3 region of the hippocampus. In addition, the activation of microglia and astrocytes was observed by using CD11b and GFAP immunohistochemistry in the same region. Results: The results indicate that acupuncture treatment reduced the rate of neural cell death in the CA3 region of the hippocampus and decreased the activations of microglia and astrocytes in this region. Conclusion: These results demonstrate that acupuncture treatment protects hippocampal neuronal cell death from KA-induced epileptic seizure by inhibiting the activations of microglia and astrocytes.

• Annals of Clinical Neurophysiology
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• v.8 no.1
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• pp.44-47
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• 2006

Background: The present study used magnetoencephalography (MEG) to investigate the neural substrates for modified version of Treisman's visual search task. Methods: Two volunteers who gave informed consent participated MEG experiment. One was 27- year old male and another was 24-year-old female. All were right handed. Experiment were performed using a 306-channel biomagnetometer (Neuromag LTD). There were three task conditions in this experiment. The first was searching an open circle among seven closed circles (open condition). The second was searching a closed circle among seven uni-directionally open circles (closed condition). And the third was searching a closed circle among seven eight-directionally open circles (random (closed) condition). In one run, participants performed one task condition so there were three runs in one session of experiment. During one session, 128 trials were performed during every three runs. One participant underwent one session of experiment. The participant pressed button when they found targets. Magnetic source localization images were generated using software programs that allowed for interactive identification of a common set of fiduciary points in the MRI and MEG coordinate frames. Results: In each participant we can found activations of anterior cingulate, primary visual and association cortices, posterior parietal cortex and brain areas in the vicinity of thalamus. Conclusions: we could find activations corresponding to anterior and posterior visual attention systems.

• Korean Journal of Cognitive Science
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• v.21 no.1
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• pp.77-93
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• 2010

The aim of this study was to identify neural correlates underlying the detection of faux pas, a test of theory of mind (ToM), in Korean healthy adults. Using functional magnetic resonance imaging, we compared the brain activities associated with faux pas stories and the activities associated with control stories. Faux pas stories compared with the control stories produced activations bilaterally in the superior frontal gyrus (BA 9) and in the precuneus (BA 7). The left medial frontal gyrus (BA 9), the left superior temporal gyrus (BA 38), the left inferior temporal gyrus (BA 20) and the right inferior parietal lobule (BA 40), the right postcentral gyrus (BA 1), the right lingual gyrus (BA 18), the right transverse temporal gyrus (BA 41) were also activated. The orbitofrontal cortex and the amygdala were not found to be involved in the detection of faux pas. This result suggests that brain activations associated with ToM are dependent on the type of mental state drawn by the task.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.8
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• pp.211-218
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• 1994

In this paper we develope a hybrid learning rule to improve the robustness of multi-layer Perceptions. In most neural networks the activation of a neuron is deternined by a nonlinear transformation of the weighted sum of inputs to the neurons. Investigating the behaviour of activations of hidden layer neurons a new learning algorithm is developed for improved robustness for multi-layer Perceptrons. Unlike other methods which reduce the network complexity by putting restrictions on synaptic weights our method based on error-backpropagation increases the complexity of the underlying proplem by imposing it saturation requirement on hidden layer neurons. We also found that the additional gradient-descent term for the requirement corresponds to the Hebbian rule and our algorithm incorporates the Hebbian learning rule into the error back-propagation rule. Computer simulation demonstrates fast learning convergence as well as improved robustness for classification and hetero-association of patterns.