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Objectives: Introduction of a new grid-based method for analyzing speech functions which takes into account the related information of patients' data and the oral air flow with pronouncing analyzed by computational fluid dynamics.Methods: An on-line speech analyzer was developed for clinical use utilizing GridPort2.3.1 based on globus2.4.2, comprising several computational tools such as unified data storage, semantic data analysis, computational fluid dynamics analysis and three-dimensional visualization of calculated results from different hardware sources with various types of operation systems.Results: The power transportation layer between dental clinics and computational and storage resources could be provided by using a WWW-based portal. The backend data management system could be constructed using a storage resource broker (SRB) and extensible mark up language (XML).Conclusions: The new method allows the construction of a data warehouse through this grid-based speech function analysis in order to extract the principal factors related to speech disorders. [ABSTRACT FROM AUTHOR]

Cortical stimulation has been used for brain mapping for over a century, and a standard assumption is that stimulation interferes with task execution due to local effects at the stimulation site. Stimulation can however produce afterdischarges which interfere with functional localization and can lead to unwanted seizures. We previously showed that (a) cognitive effort can terminate these afterdischarges, (b) when termination thus occurs, there are electrocorticography changes throughout the cortex, not just at sites with afterdischarges or sites thought functionally important for the cognitive task used, and (c) thresholds for afterdischarges and functional responses can change among stimulation trials. We here show that afterdischarge termination can occur prior to overt performance of the cognitive tasks used to terminate them. These findings, taken together, demonstrate that task-related brain changes are not limited to one or a group of functional regions or a specific network, and not limited to the time directly surrounding overt task execution. Discrete locations, networks and times importantly underpin clinical behaviors. However, brain activity that is diffuse in location and extended in time also affect task execution and can affect brain mapping. This may in part reflect fluctuating levels of attention, engagement, or motivation during testing., Competing Interests: RL or his wife has stock in the following companies which sell health care products: 3M, Abbott Labs, Abbvie, Apple, Avanos, Celgene, Express Scripts, Johnson and Johnson, Merck & Company, Pfizer. These have been disclosed to and approved by the Johns Hopkins University in accordance with its conflict of interest policies. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Lesser, Webber, Miglioretti, Mizuno-Matsumoto, Muramatsu and Yamamoto.)

Psychiatric symptoms are often accompanied by somatic symptoms induced by the activity of the autonomic nervous system (ANS). The aim of this study was to calculate the time lag between electroencephalography (EEG) and electrocardiography (ECG) responses, to clarify the changes in the relationship between the cerebral cortex (CC) and the sympathetic nervous system (SNS) during emotional recall processing. Twenty-two healthy young adults were examined. Their EEG and ECG data were simultaneously recorded during emotional audiovisual recall tasks using pleasant and unpleasant stimuli for 180 s, with three repetitions (Epochs 1 & 2 and Epoch 3). The EEG data were analyzed using a fast Fourier transform (FFT) to obtain a time series of relative power spectra, XE, in the theta 1, theta 2, alpha 1, alpha 2, alpha 3, beta 1, beta 2, and beta 3 bands. Time series of RR (inter-beat) intervals (time intervals between successive R waves) derived from the ECG spectral analysis using FFT was applied to the resampled time series of RR intervals over about 60 s to obtain a time series of power spectra for the ratio low frequency/high frequency (LH/HF), XC, which reflects the activity of the sympathetic nervous function. The time lag between XE and XC was calculated using wavelet-crosscorrelation analysis. The results demonstrated that the brain responded to unfamiliar emotionally pleasant stimuli in Epochs 1 & 2 earlier than the SNS, whereas the brain and SNS responded to unfamiliar unpleasant stimuli nearly simultaneously. The brain was activated rapidly in response to familiar unpleasant stimuli, although SNS responded more rapidly to familiar pleasant stimuli than the brain in Epoch 3. Our results quantitatively describe the relationship between the CC and the ANS during emotional recall., Competing Interests: The authors have declared that no competing interests exist.

It is well known that various types of information can be learned and memorized via repetitive training. In brain information science, it is very important to determine how neuronal networks comprising neurons with fluctuating characteristics reliably learn and memorize information. The aim of this study is to investigate the learning process in cultured neuronal networks and to address the question described above. Previously, we reported that the spikes resulting from stimulation at a specific neuron propagate as a cluster of excitation waves called spike wave propagation in cultured neuronal networks. We also reported that these waves have an individual spatiotemporal pattern that varies according to the type of neuron that is stimulated. Therefore, different spike wave propagations can be identified via pattern analysis of spike trains at particular neurons. Here, we assessed repetitive stimulation using intervals of 0.5 and 1.5 ms. Subsequently, we analyzed the relationship between the repetition of the stimulation and the identification of the different spike wave propagations. We showed that the various spike wave propagations were identified more precisely after stimulation was repeated several times using an interval of 1.5 ms. These results suggest the existence of a learning process in neuronal networks that occurs via repetitive training using a suitable interval., Competing Interests: Conflict of interest: The authors declare that there is no conflict of interest regarding the publication of this paper., (© 2019 the Author(s), licensee AIMS Press.)

Neurons behave like transistors, but have fluctuating characteristics. In this paper, we show that several asynchronous multiplex communication channels can be established in a 2-D mesh neural network with randomly generated weights between eight neighbors. Neurons were simulated by integrate-and-fire neuron models without leakage and with fluctuating refractory period and output delay. If one of the transmitting neuron groups is stimulated, the signal is propagated in the form of spike waves. The corresponding receiving neuron group is able to identify the signal after having learned to form an asynchronous multiplex communication channel. The channel is composed of many intermediate/interstitial neurons working as relays. Each neuron can work as an I/O and as a relay element, i.e., as a multiuse unit. Grouping and synchronic firing is often seen in natural neuronal networks and seems to be effective for stable/robust communication in conjunction with spatial multiplex communication. This communication pattern corresponds to our wet lab experiments on cultured neuronal networks and is similar to sound identification by the ear and mobile adaptive communication systems.

Neuronal networks have fluctuating characteristics, unlike the stable characteristics seen in computers. The underlying mechanisms that drive reliable communication among neuronal networks and their ability to perform intelligible tasks remain unknown. Recently, in an attempt to resolve this issue, we showed that stimulated neurons communicate via spikes that propagate temporally, in the form of spike trains. We named this phenomenon " spike wave propagation ". In these previous studies, using neural networks cultured from rat hippocampal neurons, we found that multiple neurons, e.g. , 3 neurons, correlate to identify various spike wave propagations in a cultured neuronal network. Specifically, the number of classifiable neurons in the neuronal network increased through correlation of spike trains between current and adjacent neurons. Although we previously obtained similar findings through stimulation, here we report these observations on a physiological level. Considering that individual spike wave propagation corresponds to individual communication, a correlation between some adjacent neurons to improve the quality of communication classification in a neuronal network, similar to a diversity antenna, which is used to improve the quality of communication in artificial data communication systems, is suggested., Competing Interests: Conflict of interest: The authors declare that there is no conflict of interest regarding the publication of this paper., (© 2018 the Author(s), licensee AIMS Press.)

Background: Few studies have focused on the imbalance of the autonomic nervous system in ultrafiltration rate (UFR) subjects without blood pressure variation during maintenance hemodialysis (HD), although the role of autonomic nervous system activation during HD has been proposed to be an important factor for the maintenance of blood pressure., Methods: Variations over time in autonomic nervous activity due to differences in UFR were evaluated by measuring heart rate variability (HRV) and approximate entropy (ApEn) in 35 HD patients without blood pressure variations during HD session. The subjects were divided into 3 groups, those with UFR <10 ml/h/kg; ≥10 ml/h/kg but ≤15 ml/h/kg; and >15 ml/h/kg, and Holter ECG was recorded continuously during HD session using frequency analysis of RR intervals. High frequency (HF) and low frequency (LF) spectral components are found to be representative of the parasympathetic nervous system and sympathovagal balance, respectively, with the ratio of LF to HF of HRV providing a measure of sympathetic nervous system., Results: In subjects with UFR >15 ml/h/kg, HF components were significantly lower, and LF/HF and ApEn values were significantly higher, in the latter half of an HD session than before starting HD., Conclusion: Removing water from these subjects would promote sustained sympathetic nervous overactivity. These findings indicate that the UFR during HD needs to be set at ≤15 ml/h/kg.

We observed spike trains produced by one-shot electrical stimulation with 8 × 8 multielectrodes in cultured neuronal networks. Each electrode accepted spikes from several neurons. We extracted the short codes from spike trains and obtained a code spectrum with a nominal time accuracy of 1%. We then constructed code flow maps as movies of the electrode array to observe the code flow of "1101" and "1011," which are typical pseudorandom sequence such as that we often encountered in a literature and our experiments. They seemed to flow from one electrode to the neighboring one and maintained their shape to some extent. To quantify the flow, we calculated the "maximum cross-correlations" among neighboring electrodes, to find the direction of maximum flow of the codes with lengths less than 8. Normalized maximum cross-correlations were almost constant irrespective of code. Furthermore, if the spike trains were shuffled in interval orders or in electrodes, they became significantly small. Thus, the analysis suggested that local codes of approximately constant shape propagated and conveyed information across the network. Hence, the codes can serve as visible and trackable marks of propagating spike waves as well as evaluating information flow in the neuronal network.

Emotion regulation is the process that adjusts the type or amount of emotion when we experience an emotional situation. The aim of this study was to reveal quantitative changes in brain activity during emotional information processing related to psychosomatic states and to determine electrophysiological features of neuroticism. Twenty-two healthy subjects (mean age 25 years, 14 males and 8 females) were registered. Electroencephalography (EEG) was measured during an emotional audiovisual memory task under three conditions (neutral, pleasant and unpleasant sessions). We divided the subjects into two groups using the Cornell Medical Index (CMI): (CMI-I: control group, n = 10: CMI-II, III or IV: neuroticism group, n = 12). We analyzed the digital EEG data using exact low-resolution brain electromagnetic tomography (eLORETA) current source density (CSD) and functional connectivity analysis in several frequency bands (δ, θ, α, β, γ and whole band). In all subjects, bilateral frontal α CSD in the unpleasant session increased compared to the pleasant session, especially in the control group (p < 0.05). CSD of the neuroticism group was significantly higher than that of the control group in the full band at the amygdala and inferior temporal gyrus, and in the α band at the right temporal lobe (p < 0.05). Additionally, we found an increase in functional connectivity between the left insular cortex and right superior temporal gyrus in all subjects during the unpleasant session compared to the pleasant session (p < 0.05). In this study, using EEG analysis, we could find a novel cortical network related to brain mechanisms underlying emotion regulation. Overall findings indicate that it is possible to characterize neuroticism electrophysiologically, which may serve as a neurophysiological marker of this personality trait. © 2015 S. Karger AG, Basel.

The current study evaluated the effect of different anxiety states on information processing as measured by an electroencephalography (EEG) using emotional stimuli on a smartphone. Twenty-three healthy subjects were assessed for their anxiety states using The State Trait Anxiety Inventory (STAI) and divided into two groups: low anxiety (I, II) or high anxiety (III and IV, V). An EEG was performed while the participant was presented with emotionally laden audiovisual stimuli (resting, pleasant, and unpleasant sessions) and emotionally laden sentence stimuli (pleasant sentence, unpleasant sentence sessions) and EEG data was analyzed using propagation speed analysis. The propagation speed of the low anxiety group at the medial coronal for resting stimuli for all time segments was higher than those of high anxiety group. The low anxiety group propagation speeds at the medial sagittal for unpleasant stimuli in the 0-30 and 60-150 s time frames were higher than those of high anxiety group. The propagation speeds at 150 s for all stimuli in the low anxiety group were significantly higher than the correspondent propagation speeds of the high anxiety group. These events suggest that neural information processes concerning emotional stimuli differ based on current anxiety state.

When analyzing neuron spike trains, it is always the problem of how to set the time bin. Bin width affects much to analyzed results of such as periodicity of the spike trains. Many approaches have been proposed to determine the bin setting. However, these bins are fixed through the analysis. In this paper, we propose a randomizing method of bin width and location instead of conventional fixed bin setting. This technique is applied to analyzing periodicity of interspike interval train. Also the sensitivity of the method is presented.

In circuit theory, it is well known that a linear feedback shift register (LFSR) circuit generates pseudorandom bit sequences (PRBS), including an M-sequence with the maximum period of length. In this study, we tried to detect M-sequences known as a pseudorandom sequence generated by the LFSR circuit from time series patterns of stimulated action potentials. Stimulated action potentials were recorded from dissociated cultures of hippocampal neurons grown on a multielectrode array. We could find several M-sequences from a 3-stage LFSR circuit (M3). These results show the possibility of assembling LFSR circuits or its equivalent ones in a neuronal network. However, since the M3 pattern was composed of only four spike intervals, the possibility of an accidental detection was not zero. Then, we detected M-sequences from random spike sequences which were not generated from an LFSR circuit and compare the result with the number of M-sequences from the originally observed raster data. As a result, a significant difference was confirmed: a greater number of "0-1" reversed the 3-stage M-sequences occurred than would have accidentally be detected. This result suggests that some LFSR equivalent circuits are assembled in neuronal networks.

Purpose: The occurrence of unwanted afterdischarges (ADs) impedes cortical stimulation for mapping purposes. We investigated the safety of several stimulation paradigms., Methods: We compared the incidence of ADs and behavioral responses of two stimulation frequencies (50 and 100 Hz), at two intensities (1 and 0.2 ms pulse widths)., Results: Stimulation with 100 Hz was more likely to cause ADs than 50 Hz, and stimulation using 1 ms pulse width was more likely to cause ADs than 0.2 ms., Conclusions: Stimulation using 50 Hz frequency with a pulse width of 0.2 ms might be safer during cortical mapping.

Background: 'Shiritori' (capping verses) is a traditional Japanese word generation game, and is very familiar to native Japanese speakers. The shiritori task is expected to more strongly activate temporal language-related regions than conventional word generation to letters because of its characteristic way to make cue letters., Objectives: The aim of this study was to examine the cortical oscillatory changes in basic brain rhythms during silently performing a shiritori task., Methods: Using synthetic aperture magnetometry (SAM) analysis of magnetoencephalography, we estimated the tomographic distributions of the statistically significant differences of the power in the alpha and beta frequency bands between the resting and the task periods., Results: Significant event-related desynchronization (ERD) in the 8- to 25-Hz band, thought to reflect neural activation, was localized within task-related cortical regions with left-side dominance. The significant ERDs were estimated in both the frontal and temporal language-related regions encompassing Broca's and Wernicke's areas, although previous neuroimaging studies using word generation to letters showed neural activation predominantly in frontal regions., Conclusions: Our results show the potential of SAM analysis for reliable brain mapping of language processing, and suggest that the shiritori task might be more suitable for examining the language-related network in the brain than conventional word generation to letters.

Using a spatially filtered magnetoencephalography analysis (synthetic aperture magnetometry), we estimated neural activations in the Stroop task in nearly real time for schizophrenic patients with/without auditory hallucinations and for normal control subjects. In addition, auditory hallucinations were examined through the information processing flow of the brain neural network, including the frontal regions. One hundred unaveraged magnetoencephalography signals during the incongruent stimulus responses were analyzed with a time window of 200 ms in steps of 50 ms. In the 25-60-Hz band, cortical regions that showed significant current source density changes were examined for each time window. The three groups showed significantly decreased current source density, corresponding to neural activation, with temporal overlap along the fundamental cognitive information processing flow: sensory input system, executive control system, motor output system. Transient neural activations in the dorsolateral prefrontal cortex were bilateral with left-side dominancy for normal controls, left-lateralized for nonhallucinators and right-lateralized for hallucinators. Our results suggest that the dysfunction in the left dorsolateral prefrontal cortex was related to auditory hallucinations, while the information processing flow was unaffected in the schizophrenic subjects in the Stroop task., (Copyright (c) 2005 S. Karger AG, Basel.)

SAM(g2) analysis, a combination of synthetic aperture magnetometry (SAM) and excess kurtosis (g2) method, is a novel epilepsy analysis procedure based on a spatial filtering technique. By producing a three-dimensional image of the g2 values and superimposing them onto a patient's MR images, this analysis can automatically estimate spike localization from raw MEG epilepsy signals including spikes. The aim of this study is to examine SAM(g2) analysis using MEG signals of an epileptic patient, whose clinical symptoms of colored elementary visual auras had ceased in accordance with the changes of the estimated localizations of the equivalent current dipoles (ECDs) of the interictal spikes. His visual auras were experienced in 1997, while they ceased in 1999 with effective medication. The patient provided written informed consent for the experimental procedures. The MEG signals were recorded in 1997 and 1999, and were analyzed using both ECD and SAM(g2) analyses. For the MEG signals of 1997, ECD analysis estimated most of the interictal spikes in the right fusiform and inferior temporal gyri, which subserve human color processing. SAM(g2) analysis also estimated them in the same areas. For those of 1999, both ECD and SAM(g2) analyses estimated them in the right transverse gyrus of Heschl. As well as ECD analysis, SAM(g2) analysis successfully estimated the changes of the localizations of the interictal spikes in accordance with the changes of the patient's clinical symptoms, indicating that SAM(g2) analysis is useful for detection of interictal spike localization in epileptic patients.

Electroencepholographs (EEGs) of neonatal seizures differ from those of children and adults. This study evaluated whether wavelet transform analysis, a nonstationary frequency analysis of EEG, can recognize and characterize neonatal seizures. Twenty-second segments were analyzed from 69 EEG seizures in 15 neonatal patients whose seizures lasted 10 seconds or longer. The wavelet transform results were examined, as were EEG seizure durations and dominant frequencies. The wavelet transform results were correlated with the occurrence, after an 18-month follow-up, of postneonatal seizures. Wavelet transform analysis identified 40 seizures (58%) with a "sustained dominant frequency component" that lasted 10 seconds or longer and 29 seizures without a sustained dominant frequency component. The mean seizure duration of the 40 seizures with sustained dominant frequency components was 63.3 seconds, longer than the mean duration (33.6 seconds) of the seizures without sustained dominant frequency components, P < 0.01. Eleven patients manifested postneonatal epileptic seizures. Fifty-two EEG seizures in these 11 patients revealed more sustained dominant frequency components (74%) than 17 seizures in the 4 patients without postneonatal seizures (only 12%), P < 0.05. Wavelet transform analysis can identify neonatal EEG seizures and characterize their epileptic components. The presence of sustained dominant frequency components may predict postneonatal epileptic seizures.

Parallel distributed processing neuroimaging in the Stroop color word interference task in five healthy subjects was studied. The total reaction time was set at 650 ms with a time window of 200 ms in steps of 50 ms. Spatially filtered magnetoencephalography analysis, as used in synthetic aperture magnetometry, was used. Neural activation began in the left posterior parietal-occipital area (150-250 ms post-stimulus), followed by the right prefrontal polar area (250-350 ms), the left dorsolateral prefrontal cortex (250-400 ms), and the mid- to lower- primary motor area (350-400 ms). Successive and temporally overlapping activation of various cortical regions were successfully estimated within a short 200 ms time interval, contrary to previous positron emission tomography and fMRI studies., (Copyright 2002 Elsevier Science Ireland Ltd.)

Purpose: We previously reported that brief pulses of electrical stimulation (BPSs) can terminate afterdischarges (ADs) during cortical stimulation. We investigated conditions under which BPS is more likely to suppress ADs., Methods: We analyzed parameters altering BPS effectiveness on 200 ADs in seven patients with implanted subdural electrodes., Results: The odds of BPSs stopping ADs was 8.6 times greater at primary sites (directly stimulated electrodes) than at secondary sites (adjacent electrodes) (p = 0.016). BPS applied within 4.5 s after onset of AD had 2 times greater odds of stopping ADs (p = 0.014). BPS applied when AD voltage was negative was 1.9 times more likely to stop ADs (p = 0.012). ADs with rhythmic pattern responded best (p < 0.0001). BPS stopped 100% of ADs not starting immediately after localization stimulus (LS) versus 29% of those starting immediately (p < 0.0001)., Conclusions: BPS is more likely to terminate ADs at primary electrodes, if given early, if applied to the negative peak of the AD waveform, if AD has a rhythmic pattern, and if AD did not start immediately after LS.

Objective: Extraoperative cortical localizing stimulation (LS) is a standard clinical tool used to assess brain function before epilepsy surgery. However, LS can produce unwanted afterdischarges (ADs). We previously have shown that brief pulses of electrical stimulation (BPS) can terminate ADs caused by cortical stimulation. Our objective was to assess whether wavelet-crosscorrelation analysis could help predict the conditions under which BPS would be most likely to terminate ADs., Methods: We used wavelet-crosscorrelation analysis to get wavelet-correlation coefficients (WCC), and determine time lag (TL) and absolute value of TL (ATL) between two electrodes. For Analysis-1, we compared WCC and ATL in epoch 1 which was before LS, epoch 2 which was after LS but before BPS, and epoch 3 which was after BPS. For Analysis 2, we compared WCC and ATL during epoch 1 under 4 conditions: epochs when ADs subsequently terminated within 2 s after the end of BPS (1A), terminated within 2-5 s (1B), did not terminate within 5 s (1C), and when ADs did not appear (1D)., Results: We found that BPS efficacy in terminating ADs was predicted by (1) low correlation and (2) slow propagation speed between electrode pairs in the 2-10 s period before stimulation., Conclusions: Wavelet-crosscorrelation analysis can help predict conditions during which BPS can abort ADs. It is possible that similar analyses could help predict when BPS or other interventions could abort clinical seizures.

A patient who had experienced an attack of transient global amnesia (TGA) was examined using neurophysiological methods. Magnetoencephalography (MEG) was performed and the Wechsler Memory Scale-Revised (WMS-R) test was administered at 5 days and at more than a month after the TGA episode. MEG data on neuronal activity obtained while the patient was undertaking a working memory task and during rest were analyzed using the wavelet-crosscorrelation method, which reveals time-lag and information flow between related sites in the brain. The WMS-R memory scores showed dramatic improvement when the test was administered a month following the attack, although no significant changes were observed in EEG, MRI and SPECT data. The MEG study revealed that under a working memory load how the neuron works functionally and the information propagates assembly within the right hemisphere, and that these brain functions were not performed adequately shortly after the TGA attack.

Magnetoencephalographic findings in a 6-year-old patient suffering from acquired aphasia with convulsive disorder (Landau-Kleffner Syndrome, LKS) are presented. The data were analyzed using wavelet-cross-correlation analysis, a nonstationary analysis method developed to analyze the localization of an epileptogenic lesion and the propagation of epileptiform discharges. The results indicate that LKS might be a disorder of the primary temporal cortex, and that the auditory neural network may function as the circuit for the epileptic discharge propagation.

Auditory hallucinations (AH), the perception of sounds and voices in the absence of external stimuli, remain a serious problem for a large subgroup of patients with schizophrenia. Functional imaging of brain activity associated with AH is difficult, since the target event is involuntary and its timing cannot be predicted. Prior efforts to image the patterns of cortical activity during AH have yielded conflicting results. In this study, MEG was used to directly image the brain electrophysiological events associated with AH in schizophrenia. We observed an increase in theta rhythm, as sporadic bursts, in the left superior temporal area during the AH states, whereas there was steady theta band activity in the resting state. The present finding suggests strong association of the left superior temporal cortex with the experience of AH in this patient. This is consistent with the hypothesis that AH arises from areas of auditory cortex subserving receptive language processing.

The relationships of background EEG to epileptiform discharge development were studied in 9 epileptic patients having generalized spike and wave complexes (SWCs) with a maximum at the frontal location on either side. The instantaneous power spectrum of EEGs at F3, F4, C3, C4, P3, P4, O1, O2, T3 and T4 was estimated with wavelet transform. Subsequently, the similarity of power spectra between SWCs and background EEG was determined by use of Kullback-Leibler information and artificial neural network in each patient. Both similarity measures revealed that EEG patterns similar to SWCs occurred in the background activity just before SWCs at frontal locations. These findings suggested that these SWC-like EEG events occurred as poorly developed epileptiform discharges buried in the background activity.