June Sic Kim

Symptoms of schizophrenia are related to deficits in self-monitoring function, which may be a consequence of irregularity in aspects of the default mode network (DMN). Schizophrenia can also be characterized by a functional abnormality of the brain activity that is reflected in the resting state. Oscillatory analysis provides an important understanding of resting brain activity. However, conventional methods using electroencephalography are restricted because of low spatial resolution, despite t

Previous studies have reported conflicting results regarding the effect of direct electrical stimulation of the human hippocampus on memory performance. A major function of the hippocampus is to form associations between individual elements of experience. However, the effect of direct hippocampal stimulation on associative memory remains largely inconclusive, with most evidence coming from studies employing non-invasive stimulation. Here, we therefore tested the hypothesis that direct electrical

Abstract Electrocorticogram (ECoG) is an electrophysiological signal that results from the summation of neuronal activity near the cortical surface. To record ECoG signals, the scalp and skull are surgically opened and electrodes are placed on the cortical surface, either epidurally or subdurally. Owing to its improved spatiotemporal resolution and signal quality compared with electroencephalography, it is widely used to diagnose and treat neurological disorders in clinical settings for several

Background: Despite its potential to revolutionize the treatment of memory dysfunction, the efficacy of direct electrical hippocampal stimulation for memory performance has not yet been well characterized. One of the main challenges to cross-study comparison in this area of research is the diversity of the cognitive tasks used to measure memory performance. Objective: We hypothesized that the tasks that differentially engage the hippocampus may be differentially influenced by hippocampal stimula

Power changes in specific frequency bands are typical brain responses during motor planning or preparation. Many studies have demonstrated that, in addition to the premotor, supplementary motor, and primary sensorimotor areas, the prefrontal area contributes to generating such responses. However, most brain-computer interface (BCI) studies have focused on the primary sensorimotor area and have estimated movements using postonset period brain signals. Our aim was to determine whether the prefront

Cerebral cortical representation of motor kinematics is crucial for understanding human motor behavior, potentially extending to efficient control of the brain-computer interface. Numerous single-neuron studies have found the existence of a relationship between neuronal activity and motor kinematics such as acceleration, velocity, and position. Despite differences between kinematic characteristics, it is hard to distinguish neural representations of these kinematic characteristics with macroscop

The Bereitschaftspotential (BP) is a slow negative cortical potential preceding voluntary movement. Since movement preparation is dependent upon the synchronous activity of a variety of neurons, BP may develop through the exchange of information among motor-related neurons. However, the relationship between BP and information flow is not yet well-known. In the present study, we aimed to investigate how the connectivity in the prefrontal cortex (PFC) changes during the occurrence of BP. Electroco

Most brain-machine interface (BMI) studies have focused only on the active state of which a BMI user performs specific movement tasks. Therefore, models developed for predicting movements were optimized only for the active state. The models may not be suitable in the idle state during resting. This potential maladaptation could lead to a sudden accident or unintended movement resulting from prediction error. Prediction of movement intention is important to develop a more efficient and reasonable

Sensory feedback is very important for movement control. However, feedback information has not been directly used to update movement prediction model in the previous BMI studies, although the closed-loop BMI system provides the visual feedback to users. Here, we propose a BMI framework combining image processing as the feedback information with a novel prediction method. The feedback-prediction algorithm (FPA) generates feedback information from the positions of objects and modifies movement pre

본 연구는 미술 교육의 보다 효율적인 방안으로 지역사회와의 연계 필요성을 인식하고 이의 이론적 배경에 대해 고찰하였다. 지역사회에 기반한 미술 교육에서 핵심이 되는 지역사회 교육을 정의하는 다양한 학자들의 견해와 지역사회에 기반한 미술 교육의 교육적 특성을 이해하기 위하여 존 듀이(John Dewey)의 진보주의 교육 이론, 파울로 프레이리(Paulo Freire)의 자유주의 교육 이론, 포스트모더니즘 교육 이론을 중심으로 살펴보았다. 또 지역사회에 기반한 미술 교육이 현대로 오면서 다양한 학자들에 의해 특징지어지는 내용들을 살펴보며, 교육 주체적, 교육 내용적, 교육 형식별, 교육 목적별로 구분하여 각 접근별 특징을 알아보았다. 이러한 문헌 연구는 지역사회에 기반한 미술 교육의 주요 특징인 경험 중심, 과정 중심, 주제 중심이 중시되어야 하는 교육적 필요성을 밝혀 주며, 지역사회에 기반한 미술 교육을 이해하는데 보다 쉽게 접근할 수 있는 기틀을 제공하고 있다.

Studying the motor-control mechanisms of the brain is critical in academia and also has practical implications because techniques such as brain-computer interfaces (BCIs) can be developed based on brain mechanisms. Magnetoencephalography (MEG) signals have the highest spatial resolution (~3 mm) and temporal resolution (~1 ms) among the non-invasive methods. Therefore, the MEG is an excellent modality for investigating brain mechanisms. However, publicly available MEG data remains scarce due to e