• Clinical and Experimental Pediatrics
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• v.63 no.3
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• pp.88-95
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• 2020

Accurate localization of the seizure onset zone is important for better seizure outcomes and preventing deficits following epilepsy surgery. Recent advances in neuroimaging techniques have increased our understanding of the underlying etiology and improved our ability to noninvasively identify the seizure onset zone. Using epilepsy-specific magnetic resonance imaging (MRI) protocols, structural MRI allows better detection of the seizure onset zone, particularly when it is interpreted by experienced neuroradiologists. Ultra-high-field imaging and postprocessing analysis with automated machine learning algorithms can detect subtle structural abnormalities in MRI-negative patients. Tractography derived from diffusion tensor imaging can delineate white matter connections associated with epilepsy or eloquent function, thus, preventing deficits after epilepsy surgery. Arterial spin-labeling perfusion MRI, simultaneous electroencephalography (EEG)-functional MRI (fMRI), and magnetoencephalography (MEG) are noinvasive imaging modalities that can be used to localize the epileptogenic foci and assist in planning epilepsy surgery with positron emission tomography, ictal single-photon emission computed tomography, and intracranial EEG monitoring. MEG and fMRI can localize and lateralize the area of the cortex that is essential for language, motor, and memory function and identify its relationship with planned surgical resection sites to reduce the risk of neurological impairments. These advanced structural and functional imaging modalities can be combined with postprocessing methods to better understand the epileptic network and obtain valuable clinical information for predicting long-term outcomes in pediatric epilepsy.

• Journal of Korea Multimedia Society
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• v.24 no.5
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• pp.684-694
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• 2021

Resting-state Functional Magnetic Resonance Imaging(fMRI) data detects the temporal correlations in Blood Oxygen Level Dependent(BOLD) signal and these temporal correlations are regarded to reflect intrinsic cortical connectivity, which is deactivated during attention demanding, non-self referential tasks, called Default Mode Network(DMN). The relationship between fMRI and anatomical connectivity has not been studied in detail, however, the preceded studies have tried to clarify this relationship using Diffusion Tensor Imaging(DTI) and fMRI. These studies use method that fMRI data assists DTI data or vice versa and it is used as guider to perform DTI tractography on the brain image. In this study, we hypothesized that functional connectivity in resting state would reflect anatomical connectivity of DMN and the combined images include information of fMRI and DTI showed visible connection between brain regions related in DMN. In the previous study, functional connectivity was determined by subjective region of interest method. However, in this study, functional connectivity was determined by objective and advanced method through Independent Component Analysis. There was a stronger connection between Posterior Congulate Cortex(PCC) and PHG(Parahippocampa Gyrus) than Anterior Cingulate Cortex(ACC) and PCC. This technique might be used in several clinical field and will be the basis for future studies related to aging and the brain diseases, which are needed to be translated not only functional connectivity, but structural connectivity.

• International Journal of Contents
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• v.8 no.4
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• pp.56-63
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• 2012

In recent decades, analyzing the activities of human brain achieved some accomplishments by using the functional Magnetic Resonance Imaging (fMRI) technique. fMRI data provide a sequence of three-dimensional images related to human brain's activity which can be used to detect instantaneous cognitive states by applying machine learning methods. In this paper, we propose a new approach for distinguishing human's cognitive states such as "observing a picture" versus "reading a sentence" and "reading an affirmative sentence" versus "reading a negative sentence". Since fMRI data are high dimensional (about 100,000 features in each sample), extremely sparse and noisy, feature selection is a very important step for increasing classification accuracy and reducing processing time. We used the Fisher Discriminant Ratio to select the most powerful discriminative features from some Regions of Interest (ROIs). The experimental results showed that our approach achieved the best performance compared to other feature extraction methods with the average accuracy approximately 95.83% for the first study and 99.5% for the second study.

• Smart Media Journal
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• v.13 no.4
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• pp.86-93
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• 2024

The development of functional magnetic resonance imaging (fMRI) has significantly contributed to mapping brain functions and understanding brain networks during rest. This paper proposes a CNN-LSTM-based classification model to classify the progression stages of Alzheimer's disease. Firstly, four preprocessing steps are performed to remove noise from the fMRI data before feature extraction. Secondly, the U-Net architecture is utilized to extract spatial features once preprocessing is completed. Thirdly, the extracted spatial features undergo LSTM processing to extract temporal features, ultimately leading to classification. Experiments were conducted by adjusting the temporal dimension of the data. Using 5-fold cross-validation, an average accuracy of 96.4% was achieved, indicating that the proposed method has high potential for identifying the progression of Alzheimer's disease by analyzing fMRI data.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.11
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• pp.173-176
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• 1995

We have developed a fast steady state free precession interferometry (SSFPI) technique which is useful for the fMRI (functional Magnetic Resonance Imaging). As is known, SSFP sequence with a suitable adjustment of gradient (readout) allows us to measure precession angle $\theta$ which is in turn related to the field inhomogeneity [1-3]. When the method is applied to the susceptibility effect based functional magnetic resonance imaging (fMRI), it was found that the direct susceptibility effect measurement was possible without perturbations such as the backgrounds and inflow effect. In this paper, simulation results and experimental results obtained with 2.0 Tesla MRI system are also presented.

• Dementia and Neurocognitive Disorders
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• v.16 no.2
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• pp.48-53
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• 2017

Background and Purpose Torrance Tests of Creative Thinking (TTCT) is a well-known and commonly used measure of creativity. However, the TTCT-induced creative hemodynamic brain activity is rarely revealed. The purpose of this study is to elucidate the neural correlates of creative thinking in the setting of a modified version of the figural TTCT adapted for an functional magnetic resonance imaging (fMRI) experiment. Methods We designed a blocked fMRI experiment. Twenty-five participants (11 males, 14 females, mean age $19.9{\pm}1.8$) were asked to complete the partially presented line drawing of the figural TTCT (creative drawing imagery; creative). As a control condition, subjects were asked to keep tracking the line on the screen (line tracking; control). Results Compared to the control condition, creative condition revealed greater activation in the distributed and bilateral brain regions including the left anterior cingulate, bilateral frontal, parietal, temporal and occipital regions as shown in the previous creativity studies. Conclusions The present revealed the neural basis underlying the figural TTCT using fMRI, providing an evidence of brain areas encompassing the figural TTCT. Considering the significance of a creativity test for dementia patients, the neural correlates of TTCT elucidated by this study may be valuable to evaluate the brain function of patients in the clinical field.

• Journal of Biomedical Engineering Research
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• v.26 no.4
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• pp.223-230
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• 2005

This paper presents a new approach to investigate spatial correlation between independent components of brain alpha activity in functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). To avoid potential problems of simultaneous fMRI and EEG acquisitions in imaging pure alpha activity, data from each modality were acquired separately under a 'three conditions' setup where one of the conditions involved closing eyes and relaxing, thus making it conducive to generation of alpha activity. The other two conditions -- eyes open in a lighted room or engaged in a mental arithmetic task, were designed to attenuate alpha activity. Using a Mixture Density Independent Component Analysis (MD-ICA) that incorporates flexible non-linearity functions into the conventional ICA framework, we could identify the spatiotemporal components of fMRI activations and EEG activities associated with the alpha rhythm. Then, the sources of the individual EEG alpha activity component were localized by a Maximum Entropy (ME) method that is specially designed to find the most probable dipole distribution minimizing the localization error in sense of LMSE. The resulting active dipoles were spatially transformed to 3D MRls of the subject and compared to fMRI alpha activity maps. A good spatial correlation was found in the spatial distribution of alpha sources derived independently from fMRI and EEG, suggesting the proposed method can localize the cortical areas responsible for generating alpha activity successfully in either fMRI or EEG. Finally a functional connectivity analysis was applied to show that alpha activity sources of both modalities were also functionally connected to each other, implying that they are involved in performing a common function: 'the generation of alpha rhythms'.

• Investigative Magnetic Resonance Imaging
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• v.16 no.2
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• pp.136-141
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• 2012

Purpose : To investigate the pharmacologic modulation of motor task-dependent physiologic responses by antiplatelet agent, clopidogrel, during hand motor tasks in healthy subjects. Materials and Methods: Ten healthy, right-handed subjects underwent three functional magnetic resonance (fMRI) sessions: one before drug administration, one after high dose drug administration and one after reaching drug steady state. For the motor task fMRI, finger flexion-extension movements were performed. Blood oxygenation level dependent (BOLD) contrast was collected for each subject using a 3.0 T VHi (GE Healthcare, Milwaukee, USA) scanner. $T2^*$-weighted echo planar imaging was used for fMRI acquisition. The fMRI data processing and statistical analyses were carried out using SPM2. Results: Second-level analysis revealed significant increases in the extent of activation in the contralateral motor cortex including primary motor area (M1) after drug administration. The number of activated voxels in motor cortex was 173 without drug administration and the number increased to 1049 for high dose condition and 673 for steady-state condition respectively. However, there was no significant difference in the magnitude of BOLD signal change in terms of peak T value. Conclusion: The current results suggest that cerebral motor activity can be modulated by clopidogrel in healthy subjects and that fMRI is highly senstive to evidence such changes.

• Journal of Korean Neurosurgical Society
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• v.58 no.3
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• pp.242-247
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• 2015

Objective : The purpose of this study is to determine whether the changes of contralateral sensorimotor cortical activation on functional magnetic resonance imaging (fMRI) can predict the neurological outcome among spinal cord injury (SCI) patients when the great toes are stimulated without notice. Methods : This study enrolled a total of 49 patients with SCI and investigated each patient's preoperative fMRI, postoperative fMRI, American Spinal Injury Association (ASIA) score, and neuropathic pain occurrence. Patients were classified into 3 groups according to the change of blood oxygenation level dependent (BOLD) response on perioperative fMRI during proprioceptive stimulation with repetitive passive toe movements : 1) patients with a response of contralateral sensorimotor cortical activation in fMRI were categorized; 2) patients with a response in other regions; and 3) patients with no response. Correlation between the result of fMRI and each parameter was analyzed. Results : In fMRI data, ASIA score was likely to show greater improvement in patients in group A compared to those belonging to group B or C (p<0.001). No statistical significance was observed between the result of fMRI and neuropathic pain (p=0.709). However, increase in neuropathic pain in response to the signal change of the ipsilateral frontal lobe on fMRI was statistically significant (p=0.030). Conclusion : When there was change of BOLD response at the contralateral sensorimotor cortex on perioperative fMRI after surgery, relief of neurological symptoms was highly likely for traumatic SCI patients. In addition, development of neuropathic pain was likely to occur when there was change of BOLD response at ipsilateral frontal lobe.

• Journal of Korea Multimedia Society
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• v.24 no.4
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• pp.583-592
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• 2021

Obsessive-compulsive disorder (OCD) is a mental disorder in which a person repeated a particular thought or feels. The domain of beliefs and guilt predicted OCD symptoms. Although there were some neuroimaging studies investigating OCD symptoms, resting-state functional magnetic resonance imaging (rs-fMRI) study investigating intra-network functional connectivity associated with guilt for OCD is not reported yet. Therefore, in the current study, we assessed the differences between intra-network functional connectivity of healthy control group and OCD group using independent component analysis (ICA) method. In addition, we also aimed to investigate the correlation between changed functional connectivity and guilt score in OCD. Total 86 participants, which consisted of 42 healthy control volunteers and 44 OCD patients, acquired rs-fMRI data using the 3T MRI. After preprocessing the fMRI data, a functional connectivity was used for group independent component analysis. The results showed that OCD patients had higher score in emotion state in beliefs and lower functional connectivity in fronto-parietal network (FPN) than control group. A decrease of functional connectivity in FPN was negatively correlated with feelings of guilt in OCD. Our results suggest excessive increase in guilt negatively affect to process emotional state and behavior or cognitive processing by influencing intrinsic brain activity.