Steady-state visually evoked potentials/fields (SSVEPs/SSVEFs) has been shown to be useful for many paradigms in cognitive (visual attention, working memory, and brain rhythms) and clinical neuroscience (aging, stress, and neurodegenerative disorders). The aim of this study was to examine the SSVEFs associated with the processing of positive and negative impression images. We used the International Affective Picture System (IAPS) which is increasingly used in brain imaging studies to examine emotional processes. Their images also allow valence to be systematically investigated. Seventy-five IAPS images of positive, neutral and negative valence assessed by subjects prior to the magnetoencephalogram (MEG) measurement were used. The peripheral square, i. e., frame, of the image was flickered black and white at 15 Hz while the image was kept stationary. Those images were randomly presented for 2.0 s on screen set at 120 cm in front of the subject. Ten healthy subjects participated. MEG recordings were made with a 122-channel whole-head MEG system in a magnetically shielded room. The MEG signals were bandpass filtered from 0.03 to 100 Hz and sampled at 1000 Hz. At least 50 epochs were recorded for averaging. We made multi-dipole estimation of the averaged MEG signals and obtained the amplitude of souse waveform in 15 Hz component (using a bandpass filter at 14-16 Hz) of SSVEF in occipital area. The amplitude of the SSVEF source in the occipital area was larger in the negative impression images than the positive impression images (p < 0.05). This result suggests that the amplitude of SSVEF that originated from the surrounding field of visual object was modulated by the emotional object and that the SSVEF could be a measure of emotion of subjects.
The purpose of this study is to improve detection sensitivity of surface EMG variation caused by muscle fatigue by using 2 approaches. The first approach was to employ recurrence quantification analysis (RQA) instead of the traditional frequency analysis (FA) to compute the muscle fatigue index. The second approach was to employ a monopolar configuration for measuring surface EMG. We measured the surface EMG signal by using the monopolar and bipolar configurations simultaneously during low-level isometric contractions under blood flow-restricted (BFR) and unrestricted (CON) conditions, and then compared and evaluated the differences in detection of muscle fatigue. The results can be summarized as follows:(1)The effect of BFR is better detected by RQA than by FA. (2)The fatigability change is larger in the monopolar configuration than in the bipolar configuration.
This paper proposes a semi-automated organ segmentation algorithm using landmarks (LMs) from a computed tomography (CT) volume. Here, several LMs are manually defined by the user on a target organ's surface in an input volume. A patient-specific probabilistic atlas (PA) is constructed based on sparse representation obtained using training labels computed by minimizing the square error between the input and training label LMs as well as the L1 norm term. This paper presents the experimental results for the purpose of segmentation of the liver, gallbladder, and right and left kidneys, in which the proposed PA was proved to be effective in an organ of irregular shape. The average Jaccard Indices of the maximum a posteriori followed by graph cuts-based segmentation of all the target organs were 0.757 for a conventional PA, and 0.838 for the proposed PA, respectively. It was statistically confirmed that the segmentation performance using a proposed PA was superior to that using a conventional PA. We also discuss the pros and cons of the proposed PA by exploring the relationship between the organ's shape and segmentation performance.