Kensuke Sato

Component Activities in the Autoregressive Activity of Physiological Systems

The higher-order autoregressive (AR) activity of a physiological system (Sato 1975a,b; Sato et al., 1977) was decomposed into first- and second-order activities. The former time-pattern displays a fast rise and an exponential decay, while the latter exhibits a damped sine wave. Application of this component analysis to EEG showed the first-order activity to coincide with the nonoscillatory delta component. The frequency distribution of the natural, damped and resonance frequencies of the second-order activities was found to show one, two or three modes in each frequency range of the delta, theta and beta rhythms in ninety normal adult EEGs. Hence, the second-order activities agree with the oscillatory delta, theta, alpha and beta rhythms. Some changes were induced not only in the frequency of theta and beta rhythms but also in that of alpha rhythm by over-breathing for about three minutes.

Cerebral visual evoked potentials in relation to EEG

Abstract The average occipital visual evoked potentials (VEPs) in response to single flash stimulus (1 f/sec), with little or no rhythmic after-discharge, were obtained from twelve human adult subjects and repetitively summed algebraically at varying intervals of approximately 0.5-0.04 sec for comparison with the average VEP driven by repetitive flash stimulation at the same intervals. Large oscillatory contours were obtained by repetitive summation of the VEP at time intervals corresponding to the period of delta, theta and alpha frequency ranges in EEG, whereas a small amplitude fast pattern was produced by summations at intervals corresponding to the period of beta frequencies. In this situation, alpha rhythm-like configuration resulted from summations at intervals of approximately 0.1 to 0.083 or 0.07 sec. Each of the main components in the average VEP to single flash was increased by summation at intervals corresponding to delta, theta and alpha frequencies, whereas they were decreased by that at intervals corresponding to beta frequencies. By summation and stimulation at a frequency corresponding to the alpha frequency range, deflections other than the second surface negative (N2) and third positive (P3) deflections in the VEP were fused or synchronised respectively to the N2 and P3 deflections to build up an enhanced surface negative-positive diphasic (alpha rhythm-like) configuration. By further increase in the frequencies of the summation and stimulations, the diphasic pattern deteriorated to form a small amplitude fast pattern. The rhythmically driven average VEP and the summed average VEP at frequencies of approximately 2–12 c/sec resembled each other in their contours, whereas at frequencies higher than 12/sec, the former was lower than the latter so as to indicate occlusive (negative interactive) effects between adjoining flashes of light in the photic stimulation. In addition to the above, some new findings were obtained from the contour maps created by drawing equipotential lines for both the rhythmically driven VEP and summed VEP in relation to the frequency of the stimulation and summation. These findings were also affirmed in the frequency patterns revealed by power spectra and the frequency response activities of both the summed and driven VEP. The large sinusoidal wave built up in both the summed and driven average VEP at a frequency corresponding to an alpha frequency was often preceded or followed by a hump in the rising and falling phases, respectively, but quite similar configurations have often been observed in the alpha activity in the spontaneous EEG traced by the authors and other investigators.

Favorable Effect of Transcranial Electrostimulation on Behavior Disorders in Elderly Patients With Dementia: A Double-Blind Study

The efficacy of transcranial electrostimulation for sleep-wake and behavior disorders in elderly patients with dementia was tested in a double-blind study. The subjects were 27 inpatients with multi-infarct dementia (12 males and 15 females, aged 58-86). They were randomly divided into two groups: active treatment (n = 14) and placebo treatment (n = 13). For electrostimulation, a device (HESS-100) was used which delivered repetitive rectangular electric pulses of 6-8 V at increasing frequencies from 6 to 80 Hz, each pulse lasting 0.2 ms and with a root mean square value of 256-530 microA. Electrostimulation was performed for 20 minutes from 10:00 h every morning. The active or placebo treatment was performed for 2 weeks in each group. The electrostimulation was significantly effective in behavior disorders such as wandering or nocturnal delirium, and decreased motivation during the daytime. It was also effective in improving night sleep. Electroencephalograms confirmed increased vigilance levels in the daytime both during and after the treatment.

Ontogenic development of EEG-asymmetry in early infantile autism

Autoregressive (AR) analysis and component analysis were done on EEGs during sleep stage 2 in normal and autistic children, since AR-coefficients of EEG characterize the autocovariance and power spectral density of EEG. In addition, as the generalized distance of the average AR-coefficient vector of an EEG group at one side from that at the opposite side exhibits an F-distribution, the statistical inferences were determined, as to whether there is hemispheric specialization in EEG in 21 right-handed autistic children and whether there is a difference between the AR-spectral pattern of EEG in the autistic children and that of 28 normal children of the same age range. The results obtained are as follows: 1. Significant hemispheric lateralization in EEG at the significant level of 0.01 was observed in normal children, whereas no lateralization was confirmed in autistic children. 2. Random click stimulation had cumulative effects on the hemispheric lateralization in the normal children, but not in the autistic children. On the contrary, the effects of random flash light stimulation on hemispheric asymmetry were verified in the autistic children as well as in the normal children. 3. The EEG components of autistic children were significantly different from the normal ones in the frequency range of alpha-2 component waves at bilateral frontal (Fp1 and Fp2) regions and the activity of these component waves was higher in the autistic children than in the normal ones over 5 years old. 4. These findings suggest that autistic children are not only less responsive to external stimuli, but also neurophysiologically less active in the internal regulatory mechanism.

A simplified method for crosscorrelation analysis

Abstract A simple method of obtaining a crosscorrelogram between two waveforms has been described. Comparison between the formal method of crosscorelation and the simplified procedure demonstrates a good similarity of the results obtained.

A simplified method for autocorrelation analysis in electroencephalography.

Abstract a simple method of obtaining an auto-correlogram of the wave form has been described. Comparison between the orthodox method of auto-correlation and the simplified procedure demonstrates a good similarity of the results, provided that the wave form under analysis is of adequate lenght.

A simplified method for determining the average response time-pattern of the evoked potential in electroencephalography

Abstract A method has been described to obtain the average response time-pattern of evoked potentials in the electroencephalogram. This method is particularly useful for short recording periods. Comparison has been made to Dawsons summation technique of demonstrating evoked responses; improvement and clarity of the calculated responses is shown.

On some methods for EEG pattern discrimination.

Two methods of statistical inference for EEG pattern discrimination are described with examples of their application. One concerns whether an arbitrary EEG pattern belongs to a standard EEG group or not, and the other concerns whether a group of EEG belongs to the standard EEG group.

Ontogenic development of autoregressive component waves of waking EEG in normal infants and children

Waking EEGs of 150 normal children aged from 20 days to 15 years were subjected to analysis. Discrete time series of an artifact free segment of the EEG record at 50 samples/sec for twenty seconds was generated and autoregressive (AR) and component analyses were carried out with a minicomputer PDP 11/40 (DEC). The results may be summarized as follows: 1) In the group of 1 year old and less, the power increased with the monthly age, whereas the bio-informing activity amount decreased. In those older than 1 year, both parameters showed maximal values at 1 year and then decreased with age, and the decreases were marked from 1 to 3 years. 2) The first- and second-order component activities of 129 and 677 waves, respectively, were obtained by applying component analysis to 152 EEG records. The frequency polygons of natural frequency of second-order component waves verified several modes, each of which was enhanced in the frequency range of the well-known delta 0, delta 1, theta 1, theta 2, alpha 1, alpha 2, beta 1, beta 2 and beta 3 waves, respectively. 3) The average percent-power of the delta wave (delta 0 + delta 1) decreased with age, especially from 1 to 3 years old, whereas those of beta- and alpha-waves increased with advancing age. That of the theta wave tended to increase from 2 to 4 years of age, and thereafter decreased gradually with increasing age. 4) With increasing age, the durations of damped oscillations were significantly lengthened in delta 1, alpha 1 and beta 3 waves, whereas that in the theta 1 wave was significantly shortened. 5) The bio-informing activity amounts of alpha waves increased from 1 to 3 years with increasing age, whereas those of delta and theta waves decreased. No significant developmental change in the parameters, however, was observed in the beta wave. The results indicate that AR-power spectral and component analyses of EEG are sensitive methods for obtaining valuable information regarding the electrical brain maturation in childhood.

On the Eeg Component Waves of Multi-Infarct Dementia Seniles

Component waves of EEGs led from the F3-A1, C3-A1, O1-A1, and O2-A2 scalp regions of 24 multi-infarct dementia seniles (MID) patients (ages 58 to 85 years, average 73.3 years) and eight to 19 normal, healthy, adult (NA) subjects were obtained by autoregressive component analysis. Some differences in the component waves were demonstrated between the two groups of subjects. (1) The characteristics of the EEG component waves, including the natural, damping, and resonance frequencies, their power, regularity, etc. were determined, and compared between MID patients and NA subjects. (2) No significant difference was found between male and female patients in the occurrence rate of 11 types of component waves. (3) On the average, the alpha wave frequency was lower in MID patients. (4). Slow alpha waves (7.5 to 9.4 Hz) of MID patients were superior to those of NA subjects, whereas typical alpha waves (9.5 to 11.4 Hz) were inferior to those of NA subjects. (5) The power of alpha waves in the F3-A1 and C3-A1 regions of MID patients was superior to that of NA subjects, whereas the result was reversed in the O1-A1 and O2-A2 regions. However, there was less regularity of alpha waves in all regions among MID patients. (6) The theta wave frequency in all regions was higher in MID patients than in NA subjects. (7) Both the power and regularity of theta waves of MID patients were superior to those of NA subjects in all regions. (8) The average number of delta waves that appeared in the O1-A1 and O2-A2 regions was larger in MID patients than in NA subjects. EEG were led from the F3-A1, C3-A1, O1-A1, and O2-A2 scalp regions of multi-infarct dementia seniles (MID) patients, who had sleep disorders, such as reversed day-time sleep patterns or irregular sleep-wake patterns, frequently accompanied by behavior disorders, such as wandering, violent behavior, and/or delirium. Examination by the method of EEG pattern discrimination revealed some differences in EEG component waves in comparison with normal, healthy, adult (NA) subjects.