Yusuke Takeda

Cortical current source estimation from electroencephalography in combination with near-infrared spectroscopy as a hierarchical prior

Previous simulation and experimental studies have demonstrated that the application of Variational Bayesian Multimodal EncephaloGraphy (VBMEG) to magnetoencephalography (MEG) data can be used to estimate cortical currents with high spatio-temporal resolution, by incorporating functional magnetic resonance imaging (fMRI) activity as a hierarchical prior. However, the use of combined MEG and fMRI is restricted by the high costs involved, a lack of portability and high sensitivity to body-motion artifacts. One possible solution for overcoming these limitations is to use a combination of electroencephalography (EEG) and near-infrared spectroscopy (NIRS). This study therefore aimed to extend the possible applications of VBMEG to include EEG data with NIRS activity as a hierarchical prior. Using computer simulations and real experimental data, we evaluated the performance of VBMEG applied to EEG data under different conditions, including different numbers of EEG sensors and different prior information. The results suggest that VBMEG with NIRS prior performs well, even with as few as 19 EEG sensors. These findings indicate the potential value of clinically applying VBMEG using a combination of EEG and NIRS.

Temporal decomposition of EEG during a simple reaction time task into stimulus- and response-locked components.

Brain activity during reaction time tasks has been reported to consist of stimulus- and response-locked components. The aim of this study is to apply a method for temporally extracting these components from human scalp electroencephalography (EEG) during an auditory simple reaction time task (SR-task). The stimulus- and response-locked components are extracted from each channel of the EEG epochs and reaction times (RTs) of all the trials by using a discrete Fourier transform; the performance of the method is verified using known simulation data. The extracted stimulus-/response-locked components are compared with the stimulus-/response-triggered average EEG during the SR-task, auditory-evoked potential (AEP) during the passive hearing of an auditory stimulus, and movement-related potential (MRP) during self-paced voluntary movement. For the EEG filtered with a bandpass of 1-40 Hz, the scalp distributions of negative peaks around 400 ms (N400) in the extracted stimulus-locked components are significantly different from those in the stimulus-triggered average EEG during the SR-task, suggesting that the late parts of the stimulus-triggered average EEG largely suffer from temporal smearing with the response-locked components. Furthermore, we show that the effect of the temporal smearing is large when slow waves remain in the EEG. In conclusion, these results confirm the feasibility and necessity of the decomposition method proposed.

A generalized method to estimate waveforms common across trials from EEGs

We propose a generalized method to estimate waveforms common across trials from electroencephalographic (EEG) data. From single/multi-channel EEGs, the proposed method estimates the number of waveforms common across trials, their delays in individual trials, and all of the waveforms. After verifying the performance of this method by a number of simulation tests with artificial EEGs, we apply it to EEGs during a Go/NoGo task. This method can be used in general situations where the number and the delays of EEG waveforms common across trials are unknown.

Non-destructive analysis of in situ ammonoid jaws by synchrotron radiation X-ray micro-computed tomography

We introduce high-resolution synchrotron radiation X-ray tomography for nondestructive, three-dimensional reconstruction of the jaw apparatus preserved within the body chamber of the Late Cretaceous phylloceratid ammonoid, Phyllopachyceras ezoensis, for the first time. Analysis of the X-ray images using linear absorption coefficient estimation reveals that the upper jaw consisted mainly of inner and outer lamellae composed of carbonate apatite, which originally might have been a chitin-protein complex, with angulated rims of thick calcareous material. The morphological features indicate that the jaw apparatus of this species is the rhynchaptychus-type. The threedimensional architecture of the jaw apparatus of these specimens is similar to that of other ammonoids, except for the development of a thick calcified deposit in both upper and lower jaws, which can be considered to support the predatory-scavenging feeding habits of the species. The jaw features of this species appear to have been constrained by both phylogenetic and functional morphological factors. Yusuke Takeda. Department of Earth and Planetary Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan. ytakeda@um.u-tokyo.ac.jp Kazushige Tanabe. Department of Earth and Planetary Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan. tanabe@um.u-tokyo.ac.jp Takenori Sasaki. The University Museum, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 1130033, Japan. sasaki@um.u-tokyo.ac.jp Kentaro Uesugi. Japan Synchrotron Radiation Research Institute (JASRI), 1-1-1, Kouto, Sayo-cho, Sayogun, Hyogo 679-5198 Japan. ueken@spring8.or.jp Masato Hoshino. Japan Synchrotron Radiation Research Institute (JASRI), 1-1-1, Kouto, Sayo-cho, Sayogun, Hyogo 679-5198 Japan. hoshino@spring8.or.jp

Extracting a stimulus-unlocked component from EEG during NoGo trials of a Go/NoGo task

Like electroencephalographic (EEG) activity during reaction time tasks, EEG activity during tasks without overt responses may also consist of two components: stimulus-locked and -unlocked components. The extraction of such stimulus-unlocked components has been difficult owing to the unknown delays. Here, we propose a novel method to extract both of the two components from single-channel EEG epochs. In this method, we initially set random values for the delays and extract uncontaminated stimulus-locked and -unlocked components using the preset delays and a discrete Fourier transform. Then, we reconstruct the EEG by overlapping the extracted components with the preset delays, and calculate the residual errors between the reconstructed and original EEG. This procedure is repeated by updating the delays until the residual errors become adequately small. After verifying the performance of this method by two kinds of simulations with artificial and EEG data, we apply the method to EEG during NoGo trials of a Go/NoGo task, and obtain the stimulus-unlocked components, the magnitudes of which are comparable with those of the stimulus-locked components. By applying this method, it is possible to study internal and subjective brain activity, which occurs with variable delays.

Estimating repetitive spatiotemporal patterns from resting-state brain activity data

Repetitive spatiotemporal patterns in spontaneous brain activities have been widely examined in non-human studies. These studies have reported that such patterns reflect past experiences embedded in neural circuits. In human magnetoencephalography (MEG) and electroencephalography (EEG) studies, however, spatiotemporal patterns in resting-state brain activities have not been extensively examined. This is because estimating spatiotemporal patterns from resting-state MEG/EEG data is difficult due to their unknown onsets. Here, we propose a method to estimate repetitive spatiotemporal patterns from resting-state brain activity data, including MEG/EEG. Without the information of onsets, the proposed method can estimate several spatiotemporal patterns, even if they are overlapping. We verified the performance of the method by detailed simulation tests. Furthermore, we examined whether the proposed method could estimate the visual evoked magnetic fields (VEFs) without using stimulus onset information. The proposed method successfully detected the stimulus onsets and estimated the VEFs, implying the applicability of this method to real MEG data. The proposed method was applied to resting-state functional magnetic resonance imaging (fMRI) data and MEG data. The results revealed informative spatiotemporal patterns representing consecutive brain activities that dynamically change with time. Using this method, it is possible to reveal discrete events spontaneously occurring in our brains, such as memory retrieval.

Low durophagous predation on Toarcian (Early Jurassic) ammonoids in the northwestern Panthalassa shelf basin

Predatory shell breakage is known to occur occasionally on the ventrolateral portion of the body chamber in Mesozoic ammonoids. Here we report, for the first time, quantitative data of shell breakage in large ammonoid samples that were recovered from the lower Toarcian (Lower Jurassic) strata in the Toyora area, western Japan. The strata yielding the ammonoid samples consisted mostly of well-laminated, bituminous black shale that was deposited in an oxygen-depleted shelf basin of the northwestern Panthalassa, under the influence of the early Toarcian oceanic anoxic event. Among a total of 1305 specimens from 18 localities, apparent shell breakage was recognised in 35 specimens belonging to 7 genera, resulting in only a 2.7% frequency of occurrence relative to the total number of specimens. The breakage occurs mostly on the ventrolateral side of the body chamber with a complete shell aperture. This fact, as well as the low energy bottom condition suggested for the ammonoid-bearing shale, indicate that the shell breaks observed in the examined ammonoids were not produced by non-biological, post-mortem biostratinomical processes but were lethal injuries inflicted by nektonic predators such as reptiles, jawed fishes, coleoids, nautiloids, and carnivorous ammonoids with calcified rostral tips in their upper and lower jaws. Similar predatory shell breaks on the ventrolateral side of the body chamber have been found in contemporaneous ammonoid assemblages of the Tethys Realm, with a much higher frequency of occurrence than in the examined samples from the northwestern Panthalassa, suggesting a weaker durophagous predation pressure on ammonoids in the latter bioprovince.

Revealing Time-Unlocked Brain Activity from MEG Measurements by Common Waveform Estimation

Brain activities related to cognitive functions, such as attention, occur with unknown and variable delays after stimulus onsets. Recently, we proposed a method (Common Waveform Estimation, CWE) that could extract such brain activities from magnetoencephalography (MEG) or electroencephalography (EEG) measurements. CWE estimates spatiotemporal MEG/EEG patterns occurring with unknown and variable delays, referred to here as unlocked waveforms, without hypotheses about their shapes. The purpose of this study is to demonstrate the usefulness of CWE for cognitive neuroscience. For this purpose, we show procedures to estimate unlocked waveforms using CWE and to examine their role. We applied CWE to the MEG epochs during Go trials of a visual Go/NoGo task. This revealed unlocked waveforms with interesting properties, specifically large alpha oscillations around the temporal areas. To examine the role of the unlocked waveform, we attempted to estimate the strength of the brain activity of the unlocked waveform in various conditions. We made a spatial filter to extract the component reflecting the brain activity of the unlocked waveform, applied this spatial filter to MEG data under different conditions (a passive viewing, a simple reaction time, and Go/NoGo tasks), and calculated the powers of the extracted components. Comparing the powers across these conditions suggests that the unlocked waveforms may reflect the inhibition of the task-irrelevant activities in the temporal regions while the subject attends to the visual stimulus. Our results demonstrate that CWE is a potential tool for revealing new findings of cognitive brain functions without any hypothesis in advance.

3D Visualization of Calcified and Non-calcified Molluscan Tissues Using Computed Tomography

Three-dimensional (3D) reconstruction is an essential approach in morphological studies in biology and paleontology. Seeking an optimized protocol for nondestructive observations, we attempted 3D visualization of various molluscan shells and animals with X-ray micro-computed tomography (micro-CT). Calcified parts of molluscs were easily visualized except for cases with marked differences in thickness heterogeneity. 3D imaging of shell microstructure was difficult. Visualization of soft tissue requires staining to enhance the image contrast. Especially for soft tissues, synchrotron X-ray microtomography is the most advanced method to generate clear 3D images. 3D data facilitates morphological quantification, enabling calculations of length and volume even for very complex forms. X-ray micro-CT is extremely useful in the morphologic examination of mineralized and soft tissues, although microstructural and histological details should be supplemented by other microscopic techniques.

Dynamic Information Flow Based on EEG and Diffusion MRI in Stroke: A Proof-of-Principle Study

In hemiparetic stroke, functional recovery of paretic limb may occur with the reorganization of neural networks in the brain. Neuroimaging techniques, such as magnetic resonance imaging (MRI), have a high spatial resolution which can be used to reveal anatomical changes in the brain following a stroke. However, low temporal resolution of MRI provides less insight of dynamic changes of brain activity. In contrast, electro-neurophysiological techniques, such as electroencephalography (EEG), have an excellent temporal resolution to measure such transient events, however are hindered by its low spatial resolution. This proof-of-principle study assessed a novel multimodal brain imaging technique namely Variational Bayesian Multimodal Encephalography (VBMEG), which aims to improve the spatial resolution of EEG for tracking the information flow inside the brain and its changes following a stroke. The limitations of EEG are complemented by constraints derived from anatomical MRI and diffusion weighted imaging (DWI). EEG data were acquired from individuals suffering from a stroke as well as able-bodied participants while electrical stimuli were delivered sequentially at their index finger in the left and right hand, respectively. The locations of active sources related to this stimulus were precisely identified, resulting in high Variance Accounted For (VAF above 80%). An accurate estimation of dynamic information flow between sources was achieved in this study, showing a high VAF (above 90%) in the cross-validation test. The estimated dynamic information flow was compared between chronic hemiparetic stroke and able-bodied individuals. The results demonstrate the feasibility of VBMEG method in revealing the changes of information flow in the brain after stroke. This study verified the VBMEG method as an advanced computational approach to track the dynamic information flow in the brain following a stroke. This may lead to the development of a quantitative tool for monitoring functional changes of the cortical neural networks after a unilateral brain injury and therefore facilitate the research into, and the practice of stroke rehabilitation.