• Journal of Biomedical Engineering Research
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• v.28 no.2
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• pp.258-264
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• 2007

Spatiotemporal changes of brain rhythmic activity at a certain frequency have been usually monitored in real time using scalp potential maps of multi-channel electroencephalography(EEG) or magnetic field maps of magnetoencephalography(MEG). In the present study, we investigate if it is possible to implement a real-time brain activity monitoring system which can monitor spatiotemporal changes of cortical rhythmic activity on a subject's cortical surface, neither on a sensor plane nor on a standard brain model, with a high temporal resolution. In the suggested system, a frequency domain inverse operator is preliminarily constructed, considering the individual subject's anatomical information, noise level, and sensor configurations. Spectral current power at each cortical vertex is then calculated for the Fourier transforms of successive sections of continuous data, when a single frequency or particular frequency band is given. An offline study which perfectly simulated the suggested system demonstrates that cortical rhythmic source changes can be monitored at the cortical level with a maximal delay time of about 200 ms, when 18 channel EEG data are analyzed under Pentium4 3.4GHz environment. Two sets of artifact-free, eye closed, resting EEG data acquired from a dementia patient and a normal male subject were used to show the feasibility of the suggested system. Factors influencing the computational delay are investigated and possible applications of the system are discussed as well.

• Science of Emotion and Sensibility
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• v.15 no.4
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• pp.585-592
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• 2012

Food is crucial for the nutrition and survival of humans. Taste system is one of the fundamental senses. Taste cells detect and respond to five basic taste modalities (sweet, bitter, salty, sour, and umami). However, the cortical processing of taste sensation is much less understood. Recently, there were many efforts to observe the brain activation in response to taste stimulation using functional magnetic resonance imaging (fMRI), magnetoencephalography (MEG), and optical imaging. These different techniques do not provide directly comparable data each other, but the complementary investigations with those techniques allowed the description and understanding of the sequence of events with the dynamics of the spatiotemporal pattern of activation in the brain in response to taste stimulation. The purpose of this study is the understanding of the brain activities to taste stimuli in sensory and affective aspects and the reviewing of the recent research of the gustotopic map by functional brain mapping.

• Korean Journal of Biological Psychiatry
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• v.18 no.1
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• pp.5-14
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• 2011

Neuroimaging in psychiatry encompasses the powerful tools available for the in vivo study of brain structure and function. MRI including the volumetry, voxel-base morphometry(VBM) and diffusion tensor imaging (DTI) are useful for assessing brain structure, whereas function MRI, positron emission tomography(PET) and magnetoencephalography(MEG) are well established for probing brain function. These tools are well tolerated by the vast majority of psychiatric patients because they provide a powerful but noninvasive means to directly evaluate the brain. Although neuroimaging technology is currently used only to rule in or rule out general medical conditions as opposed to diagnosing primary mental disorders, it may be used to confirm or make psychiatric diagnoses in the future. In addition, neuroimaging may be valuable for predicting the natural course of psychiatric illness as well as treatment response.

• Journal of Biomedical Engineering Research
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• v.35 no.3
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• pp.50-54
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• 2014

It is being tried to control robot arm using brain signal in the field of brain-machine interface (BMI). This study is focused on applying guidance laws for efficient robot arm control using 3D coordinates obtained from Magnetoencephalography (MEG) signal which represents movement of upper limb. The 3D coordinates obtained from brain signal is inappropriate to be used directly because of the spatial difference between human upper limb and robot arm's end-effector. The spatial difference makes the robot arm to be controlled from a third-person point of view with assist of visual feedback. To resolve this inconvenience, guidance laws which are frequently used for tactical ballistic missile are applied. It could be applied for the users to control robot arm from a first-person point of view which is expected to be more comfortable. The algorithm which enables robot arm to trace MEG signal is provided in this study. The algorithm is simulated and applied to 6-DOF robot arm for verification. The result was satisfactory and demonstrated a possibility in decreasing the training period and increasing the rate of success for certain tasks such as gripping object.

• Journal of Biomedical Engineering Research
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• v.25 no.6
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• pp.575-580
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• 2004

In this work, a method is presented to find an anatomical site of a current source crudely in a standard brain using grand average of MEG data. Minimum norm estimation algorithm and truncated singular value decomposition were applied to calculate the distributed sources that can reproduce the measured signals. Grand average over all subjects was obtained from the transformed signals, which would be detected in a standard sensor plane by the obtained distributed current sources. In the simulation study, it was shown that the localized dipole using the grand average is consistent with the mean location of localized dipoles of all subjects within several mm even with large inter-individual differences of sensor positions. This result suggests that the mean location of low level signal source can be estimated as a dipole source in grand average and it was confirmed in the localization of the current source of N100m. when the localized dipole is registered on a standard brain. This result also suggests that the activity region obtained from grand average can be crudely estimated on a standard brain using the source location of the N100m as a reference point.

• Progress in Superconductivity
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• v.5 no.2
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• pp.98-104
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• 2004

We analyzed a noise-sensitivity profile of a specific SQUID sensor system for the localization of brain activity. The location of a neuromagnetic current source is estimated from the recording of spatially distributed SQUID sensors. According to the specific arrangement of the sensors, each site in the source space has different sensitivity, that is, the difference in the lead field vectors. Conversely, channel noises on each sensor will give a different amount of the estimation error to each of the source sites. e.g., a distant source site from the sensor system has a small lead-field vector in magnitude and low sensitivity. However, when we solve the inverse problem from the recorded sensor data, we use the inverse of the lead-field vector that is rather large, which results in an overestimated noise power on the site. Especially, the spatial sensitivity profile of a gradiometer system measuring tangential fields is much more complex than a radial magnetometer system. This is one of the causes to make the solutions of inverse problems unstable on intervening of the sensor noise. In this study, in order to improve the localization accuracy, we calculated the noise-sensitivity profile of our 40-channel planar SQUID gradiometer system, and applied it as a normalization weight factor to the source localization using synthetic aperture magnetometry.