Tomohiko Igasaki

Gustatory evoked magnetic fields in humans

Magnetic fields evoked by taste stimuli of the human tongue were measured over the whole head using a helmet-shaped 64 channel magnetoencephalography system in five normal subjects. The stimuli were 10% glucose and 0.3 M NaCl solutions and distilled water. The most prominent peak (N175m) appearing over the bilateral hemispheres had a latency of 150-210 ms. The N175m sources were located using a two-dipole model in a spherical conducting medium based on the individual head dimensions and superimposed on magnetic resonance images. The N175m dipoles due to 10% glucose and 0.3 M NaCl stimuli were located at the operculum and circum-insular areas in both hemispheres, but those due to distilled water could not be located accurately.

Effects of concurrent visual tasks on cortico-muscular synchronization in humans

To study the effects of external visual stimulation on motor cortex-muscle synchronization, coherence between electroencephalography (EEG) and electromyography (EMG) was measured in normal subjects under Before, Task (visual task: Ignore or Count, or arithmetic task) and After conditions. The control (Before and After) conditions required the subject to maintain first dorsal interosseous muscle contraction without visual stimulation. In the visual task, a random series of visual stimuli were displayed on a screen while the subjects maintained the muscle contraction. The subjects were asked to ignore the stimuli in the Ignore condition and to count certain stimuli in the Count condition. Also, in the arithmetic task, the subjects were asked to perform a simple subtraction. The EEG-EMG coherence found at C(3) site at 13-30 Hz (beta) was increased and sustained in magnitude during the Ignore and Count conditions, respectively. To examine the cause of the change of coherence, changes of EEG and EMG spectral power were computed for each frequency band. There was little change in the EMG spectral power in any frequency bands. While the spectral power of EEG unchanged in the beta band, it significantly increased and decreased in the range of 8-12 Hz and of 31-50 Hz, respectively, for both Ignore and Count conditions, not only at the C(3) site but at various sites as well. These results were in contrast to those obtained for the arithmetic task: the beta band EEG-EMG coherence was attenuated and the EEG spectral power at 4-7 Hz and at 31-50 Hz were significantly increased and decreased, respectively. As a conclusion, the present results are consistent with the idea that the enhanced 8-12 Hz/decreased 31-50 Hz oscillations affect strength of the beta band cortico-muscular synchronization by suppressing the visual processing.

Cardiac arrhythmia detection using combination of heart rate variability analyses and PUCK analysis

This paper presents cardiac arrhythmia detection using the combination of a heart rate variability (HRV) analysis and a “potential of unbalanced complex kinetics” (PUCK) analysis. Detection performance was improved by adding features extracted from the PUCK analysis. Initially, R-R interval data were extracted from the original electrocardiogram (ECG) recordings and were cut into small segments and marked as either normal or arrhythmia. HRV analyses then were conducted using the segmented R-R interval data, including a time-domain analysis, frequency-domain analysis, and nonlinear analysis. In addition to the HRV analysis, PUCK analysis, which has been implemented successfully in a foreign exchange market series to characterize change, was employed. A decision-tree algorithm was applied to all of the obtained features for classification. The proposed method was tested using the MIT-BIH arrhythmia database and had an overall classification accuracy of 91.73%. After combining features obtained from the PUCK analysis, the overall accuracy increased to 92.91%. Therefore, we suggest that the use of a PUCK analysis in conjunction with HRV analysis might improve performance accuracy for the detection of cardiac arrhythmia.

Chapter 5 Optimal methods of stimulus presentation and frequency analysis in P300-based brain–computer interfaces for patients with severe motor impairment

Publisher Summary This chapter presents new communication methods that may be applied to patients with motor disabilities. Three visual presentation methods are used for stimulus presentation: (1) background color change method (BCCM), (2) peripheral area presentation method (PAPM), and (3) central area presentation method (CAPM). Background color change or each picture is respectively displayed for 300 ms during the presentation period with a stimulus interval of 1500 ms. BCCM is found to provide the most effective means of stimulus presentation in the basic experiments. To shorten the time needed for communication, the chapter devises “yes or no,” “clinical BCCM,” and “pictorial symbols” paradigms where there are fewer selections. Although using the device is still time-consuming, it appears quite useful for patients with amyotrophic lateral sclerosis (ALS) who have lost all ability to communicate other than directly via the brain.

Language/Culture Modulates Brain and Gaze Processes in Audiovisual Speech Perception

Several behavioural studies have shown that the interplay between voice and face information in audiovisual speech perception is not universal. Native English speakers (ESs) are influenced by visual mouth movement to a greater degree than native Japanese speakers (JSs) when listening to speech. However, the biological basis of these group differences is unknown. Here, we demonstrate the time-varying processes of group differences in terms of event-related brain potentials (ERP) and eye gaze for audiovisual and audio-only speech perception. On a behavioural level, while congruent mouth movement shortened the ESs’ response time for speech perception, the opposite effect was observed in JSs. Eye-tracking data revealed a gaze bias to the mouth for the ESs but not the JSs, especially before the audio onset. Additionally, the ERP P2 amplitude indicated that ESs processed multisensory speech more efficiently than auditory-only speech; however, the JSs exhibited the opposite pattern. Taken together, the ESs’ early visual attention to the mouth was likely to promote phonetic anticipation, which was not the case for the JSs. These results clearly indicate the impact of language and/or culture on multisensory speech processing, suggesting that linguistic/cultural experiences lead to the development of unique neural systems for audiovisual speech perception.

Drowsiness estimation under driving environment by heart rate variability and/or breathing rate variability with logistic regression analysis

It is widely known that many traffic accidents occur every year, not only in Japan but also in the world. Drowsiness or sleepiness, which is the cause of dozing at the wheel, happens regardless of the physical condition of the driver after having meals or during midnight. This means that to avoid drivers drowsiness or sleepiness by oneself is hard. Therefore, various systems have been proposed to prevent traffic accidents caused by dozing at the wheel. In this study, we examined the relationship between psychological drowsiness during driving, which was evaluated by the Japanese version of the Karolinska sleepiness scale (KSS-J) and physiological parameters extracted from electrocardiogram and respiration signals. Then we tried to estimate the existence of drowsiness using logistic regression analysis on that parameters. In this study, since KSS-J score 7 indicates sleepy, we determined KSS-J score 7 and more as drowsiness state. The logistic regression method was performed using the half of the data for each subject and used the remaining data as the testing data. As a result, we got 71% of accuracy with heart rate variability (HRV), 72% of accuracy with breathing rate variability (BRV), 81% of accuracy with both signals in the whole subjects using logistic regression. Therefore, it is suggested that HRV and BRV parameters are relevant to drowsiness.

Pulse monitoring by sol-gel composite flexible piezoelectric sensors

Pulse monitoring at home would be effective to maintain personal health without increasing medical cost and development of the low cost pulse monitoring sensor is desired. Conventional PVDF sensors were too flexible so that ringing effect might not be ignorable and it would resulted in low signal to noise ratio (SNR). Piezoelectric films made by sol-gel composite itself was flexible and it could have less ringing effect so that SNR could be higher. PZT/PZT films with evaporated aluminum top electrode were fabricated onto various thickness stainless steel substrate in order to optimize the device design. For d33 measurement result, piezoelectric film thickness correlated highly with d33 value, whereas substrate thickness showed poor correlation. Pulse measurements on the wrist were attempt by PZT/PZT piezoelectric film sensors and PVDF film sensor and in several configurations, PZT/PZT sensors presented higher SNR than that of PVDF sensor.

Proposal for patient-specific automatic on-line detection of spike-and-wave discharges utilizing an artificial neural network

We aimed to develop an automatic on-line detection system of spike-and-wave discharges (SWDs), which are peculiar EEG waveforms in epileptic patients. In this study, an artificial neural network (ANN) was utilized for automatic online detection of SWDs for an epileptic patient. Upon detection, 100% specificity was intended for the safety of the patient during possible future magnetic stimulation therapy. Fifty-four samples of SWD and fifteen samples of pseudo-SWD, extracted from thirty minutes of four-channel EEG signals of an epileptic patient, were employed. The ANN was trained and examined by a standard backpropagation algorithm and a leave-one-out cross-validation, respectively. Results in the off-line classification section showed both the SWDs and the pseudo-SWDs were classified perfectly. In the on-line detection section, the undetected ratio for the SWDs increased, however, a 0% false-alarm ratio was obtained. Therefore, it is suggested that the proposed method is effective for automatic on-line detection of SWDs.

Drowsiness assessment using electroencephalogram in driving simulator environment

Traffic accident is one of the most important problems in many countries. One of traffic accident causes is drowsiness. Many studies have been done to solve this problem. One of them is to capture the drivers face expression and estimate the drivers drowsiness. Besides measuring the drivers physiological condition and use it to predict ones drowsiness is also considered. Since drowsiness is strongly related to human brain, by assessing drowsiness using biological signal especially brain signal become the most promising approach to evaluate drowsiness. We proposed a study to investigate the relationship between drowsiness and physiological condition by employing electroencephalogram (EEG) signal and Japanese version of Karolinska sleepiness scale (KSS-J) in driving simulator environment. The result showed alpha band power of EEG signal from occipital lobe in drowsy condition (KSS-J ≥ 7) increased significantly compared with that in alert condition (KSS-J <; 7) with P <; 0.001. Therefore, it is suggested that EEG is effective to find the drowsiness in driving simulator environment.

Band powers analysis of spontaneous EEG with uncooperative autism children during short sleep condition

This study presents an approach to evaluate brain abnormalities using spontaneous data of electroencephalogram (EEG) on autism subjects. Previous studies have shown abnormalities in the brains of autism subjects using spontaneous EEG while awake and resting state condition. However, this kind of method would be difficult in uncooperative subjects. Sixteen subjects (3-10 years old) were participated in this study. Eight subjects with autism and eight normal subjects were slept during EEG data retrieval. Ten minutes EEG data was chosen and for band powers evaluation within five bands EEG (delta, theta, alpha, beta, and gamma), Fast Fourier transform has been applied to extracts the frequency components. Band powers showed excessive activities in alpha band powers in autism group compare with the normal subjects (p <; 0.05). Brain abnormalities in autism subjects tend to occur both in right and left brain hemisphere (p <; 0.05), especially at frontal region (p <; 0.05). Our preliminary study during short sleep condition showed that brain abnormalities were also occurred with similar characteristics during resting state and awake condition. This kind of results was expected as pathologic problems in emotionally distressed and sensory problem.