Fumito Ishikawa

Estimation of temporary change of activation areas by moving an analysis time window in fMRI measurement

In this paper, we propose a method to acquire temporal changes of activations by moving an analysis time window. An advantage of this method is that it can acquire rough changes of activated areas even with the data having low time resolution. We ascertained that activations from our method do not contradict previous reports on the oddball paradigm, thus showing its effectiveness. Eight normal subjects participated in the study, which consisted of a random series of 30 target and 70 nontarget stimuli. We investigated the activated area in three kinds of analysis time sections, from stimulus onset to 5 s after the stimulus (time section A), from 2 to 7 s after (B) and from 4 to 9 s after (C). In time section A, representative activated areas were regions including the left and supplementary motor areas (SMA), and cerebellum. In B, regions including the left motor area and SMA, right parahippocampal gyrus (Broadmann Area (BA) 30), right limbic lobe and cerebellum were activated. In C, bilaterally postcentral gyrus (BA 3,40), right anterior cingulate (ACC, BA 32), left middle frontal gyrus (BA 9) and right parahippocampal gyrus were activated. Most activations were consistent with previous studies.

Quantitative evaluation of photic driving response for computer-aided diagnosis

The aim of our research is the quantification of the photic driving response, a routine electroencephalogram (EEG) examination, for computer-aided diagnosis. It is well known that the EEG responds not only to the fundamental frequency but also to all sub and higher harmonics of a stimulus. In this study, we propose a method for detecting and evaluating responses in screening data for individuals. This method consists of two comparisons based on statistical tests. One is an intraindividual comparison between the EEG at rest and the photic stimulation (PS) response reflecting enhancement and suppression by PS, and the other is a comparison between data from an individual and a distribution of normals reflecting the position of the individuals data in the distribution of normals in the normal database. These tests were evaluated using the Z-value based on the Mann-Whitney U-test. We measured EEGs from 130 normal subjects and 30 patients with any of schizophrenia, dementia and epilepsy. Normal data were divided into two groups, the first consisting of 100 data for database construction and the second of 30 data for test data. Using our method, a prominent statistical peak of the Z-value was recognized even if the harmonics and alpha band overlapped. Moreover, we found a statistical difference between patients and the normal database at diagnostically helpful frequencies such as subharmonics, the fundamental wave, higher harmonics and the alpha frequency band.

Robust estimation of event-related potentials via particle filter

BACKGROUND AND OBJECTIVE In clinical examinations and brain-computer interface (BCI) research, a short electroencephalogram (EEG) measurement time is ideal. The use of event-related potentials (ERPs) relies on both estimation accuracy and processing time. We tested a particle filter that uses a large number of particles to construct a probability distribution. METHODS We constructed a simple model for recording EEG comprising three components: ERPs approximated via a trend model, background waves constructed via an autoregressive model, and noise. We evaluated the performance of the particle filter based on mean squared error (MSE), P300 peak amplitude, and latency. We then compared our filter with the Kalman filter and a conventional simple averaging method. To confirm the efficacy of the filter, we used it to estimate ERP elicited by a P300 BCI speller. RESULTS A 400-particle filter produced the best MSE. We found that the merit of the filter increased when the original waveform already had a low signal-to-noise ratio (SNR) (i.e., the power ratio between ERP and background EEG). We calculated the amount of averaging necessary after applying a particle filter that produced a result equivalent to that associated with conventional averaging, and determined that the particle filter yielded a maximum 42.8% reduction in measurement time. The particle filter performed better than both the Kalman filter and conventional averaging for a low SNR in terms of both MSE and P300 peak amplitude and latency. For EEG data produced by the P300 speller, we were able to use our filter to obtain ERP waveforms that were stable compared with averages produced by a conventional averaging method, irrespective of the amount of averaging. CONCLUSIONS We confirmed that particle filters are efficacious in reducing the measurement time required during simulations with a low SNR. Additionally, particle filters can perform robust ERP estimation for EEG data produced via a P300 speller.

Analysis of P300 evoked by multisensory stimulus consisting of visual and auditory stimuli

In this study, we investigated P300 amplitude and latency when multisensory stimuli are presented, and compared the results with those in a single sensory stimulus. Here, visual and auditory stimulus were used as sensory stimulus, and these stimuli were presented to the subject simultaneously in the case of multisensory stimuli. In the experiment, three kinds of stimuli, visual, auditory, and multisensory stimuli were prepared, and either one of visual and auditory stimulus or both were set as target stimulus. The subject was instructed to push a button when target stimulus occurred. As a results, P300 amplitude of grand averaged waveform in visual evoked potential (VEP) changed a lot depending on the kind of target stimulus. The other hand, P300 amplitudes in auditory evoked potential (AEP) were almost same regardless of the kind. Furthermore, the amplitude in VEP and AEP was decreasing in the following order: target stimulus is consistent with the corresponding sensory stimulus; both visual and auditory stimuli are the target; the target is inconsistent with a sensory stimulus; and no target is set. The amplitude in multisensory evoked potential (MEP) was decreasing in the following order: both visual and auditory stimuli are the target; the target is auditory stimulus; the target is visual stimulus; no target is set. A significant difference was recognized in P300 amplitudes between visual target and no target. Regarding P300 latency of grand averaged waveform in VEP and AEP, the latencies with target stimulus were longer than that without target. However, in the case of MEP, there was rare difference in the existence of target stimulus. As for response time until button pushing, in MEP, the time when target is both of visual and auditory stimuli tended to be shorter than that when target is single sensory stimulus though significant difference could not be recognized.

Evaluation of brain aging by EEG analysis of photic driving response

In this paper, we examined the possibility to estimate brain aging by EEG photic driving response. Normal subjects are classified into 3 age groups by age, 20s, 21 – 59, and over 60. We obtained the Z-score from EEG at rest and during photic stimulus (PS) by using the method for evaluating intraindividual EEG we have already proposed. Here, we showed the averaged Z-score of 3 age groups for 6 Hz PS as a representative example. As a results, in 20s, significant difference (|Z|>1.96, p<0.05) was recognized at fundamental and higher harmonic frequencies of PS frequency except second harmonic. With increase of age, we could see the decrease of Z-score at fundamental frequency and higher harmonics. In the group over 60, no significant difference at any frequencies was recognized.

The temporal change of activations in the visual target oddball stimulus

In recent years, many researchers have been studying activated regions in the brain using fMRI to investigate the source of brain activity for various sensory stimuli. However, previous reports have not necessarily been consistent. We examined the activation for a visual target task in the oddball paradigm as a first step to investigating sources associated with the functions of decision and recognition. In our analysis, we examined the activated area in the brain in three kinds of analysis time sections, from stimulus onset to 5 seconds after the stimulus (time section A), from 2 to 7 seconds (time section B) and from 4 to 9 seconds (time section C). In the temporal change, in the time section A, many activated areas could be seen. On the whole, the flow of activation from the parietal area activated in time section A to the prefrontal area activated in the time section B and C could be seen. It is considered from our results that various areas are involved in the visual target response.

Preliminary study for extraction of P300 and SSVEP by stimulus presentation using phase inversion technique in hybrid BCI

In this study, we propose a novel stimulation presentation method for the hybrid BCI of the P300 and steady state visual evoked potential (SSVEP) to separate the two components efficiently. The method produces the separation by generating the P300 at two time points whose phase difference is π radians in the SSVEP component corresponding to stimulus frequency. Assuming that the consecutive two P300 responses are identical and the SSVEP is sinusoidal, the P300 can be extracted as a summation of the above two responses by suppressing the SSVEP. Also, the SSVEP can be detected by the subtraction of the above two responses. Accordingly, this method is realized by a stimulus pair consisting of the above two stimuli. In an EEG experiment, we used a checkerboard stimulus and character presentation for obtaining the SSVEP and P300, respectively. The stimulus frequencies of the checkerboard were assigned to 5 Hz and 3 Hz to classify the target character from the two given characters. The results showed the appearance of a prominent P300 component from only one pair of stimuli, even though the fundamental and harmonic frequency components of the SSVEP for lower stimulus frequencies are not very stable. This is because of the asymmetry of the positive and negative potentials for the SSVEP. It is a good idea to use a stimulus frequency that overlaps with the P300 frequency band, because this method does not separate the P300 and SSVEP by EEG frequency difference. Moreover, it reduces the measurement time (i.e., it shortens the number of averagings required for P300 estimation) because the SSVEP cancels out if it is sinusoidal. We consider that this will be a useful method to estimate the P300 and SSVEP simultaneously from these aspects.

Correction of fMRI signals by using the vessel diameter extracted from MRA images

Functional MRI (fMRI) is already one of the most useful tools to investigate brain activities. Normally, activations are defined by the significant difference between distributions of signal intensities on the two kinds of conditions. However, intensities of these signals depend on the vessel diameter because they reflect blood flow volume. Correction using vessel diameter will be needed when we compare signal intensities at two different areas accurately. In this study, we measured the vessel diameter by magnetic resonance angiography (MRA) and correct the fMRI signals by using the diameter. We then evaluated the signals at different areas. Here, we considered the spatial resolution of MRA images and focused on the thick vessel around motor area.

Estimation of EEG macro-state based on the EEG micro-states

On the purpose of monitoring the shift and variation of wakefulness and EEG states of patients in EEG laboratory, we used the micro-state power series of several scalp areas. Original time-series of the micro-states were also preserved. Many secondary and tertiary application could be developed on the basis of this formatted data. An example of these was reported here.

The relationship between the amplitude and phase of alpha waves and the task existence in a single stimulus paradigm

In this paper, we studied the relationship between the amplitude and phase of an alpha wave and task existence as a first step to investigating changes in the background wave after sensory stimulus. We examined the effect of a single sensory stimulus, visual or auditory, on the amplitude and the phase of alpha waves using a complex demodulation method. This experiment was performed with four conditions which were combinations of two kinds of tasks, task and no task, and two kinds of sensory stimulus, visual and auditory A flash pulse was used as the visual stimulus and a tone burst sound as an auditory stimulus in the eyes-closed condition. As a result, the amplitude in the task condition was larger than in the no task condition. Alpha blocking and rebound after the stimulus appears, regardless of the kind of sensory stimulus, whether a visual or an auditory stimulus. However, that on the task condition in the visual stimulus is not so prominent. We saw two peaks in the rebound section. One appears just after the alpha blocking and the other appears at around 2000 ms. The degree of alpha blocking on the task is larger than that on no task. However, the degree of rebound on the task is nearly the same as with that of no task. As for the phase change, it varied in the section from after the stimulus onset to 2500 ms after the stimulus. This phenomenon is more prominent in the visual stimulus compared with the auditory stimulus. The phase change returned to the level it was at before the stimulus, at around 3000 ms.