Biomedical subjects

Hiroaki Mizuhara

Publications and source records attributed to Hiroaki Mizuhara.

3 recordsLinked to original sources

PubMed2005

Long-range EEG phase synchronization during an arithmetic task indexes a coherent cortical network simultaneously measured by fMRI.

An open question lies in whether or not distributed activities in the distant brain regions are integrated into a coherent ensemble for cognitive information processing. Long-range phase synchronization is often observed by scalp EEG measurements during cognitive tasks and is considered to provide a possible neural principle for the functional integration of distributed neural activities. Synchronization could be reflected at the neuron firing level or at the local field potential and could appear in the scalp EEG under certain conditions on neural spatial and temporal coherence. To examine if phase synchronization is concerned with the integration of distant regions, we proposed a method to extract brain activities associated with task-dependent phase synchronization by combining simultaneous fMRI and EEG. By applying this method in a mental arithmetic task, we found a dominant task-dependent increase of phase synchronization around 14 Hz (in beta frequency) across bilateral parietal sites that were associated with both negative and positive BOLD responses. Functional connectivity analyses of these regions demonstrated that an increase in hemispheric beta synchronization was associated with a linking between the cross-hemispheric regions (left angular gyrus and right superior parietal gyrus) and also among the anterior-posterior regions (right dorsolateral prefrontal cortex, putamen, and right superior temporal gyrus). These findings indicate that the positive BOLD regions (dorsolateral prefrontal cortex and superior parietal lobule) are linked with other negative BOLD regions. We also discussed the possible importance of beta synchronization in the formation of a working memory network.

Adult↗

PubMed2004

A long-range cortical network emerging with theta oscillation in a mental task.

Human scalp EEG has demonstrated that global coherence among distant areas increases during cognitive tasks, suggesting that oscillating neural activities work to generate global neuronal assemblies for cognitive functions. The theta oscillation in a frequency range of 4-8 Hz with large amplitudes which emerges during mental tasks around the frontal midline region is called fm theta. If theta oscillation concerns the global neuronal assemblies, fm theta should be associated with regional activities that depend on task conditions. In the present study, we examine the EEG-related brain activities by developing simultaneous EEG and fMRI during a mental calculation task. EEG-related negative BOLD was dominant over anterior medial regions, suggesting a major contribution of negative BOLD to fm theta. Negative and positive BOLD were found over distant regions. Functional connectivity analyses revealed that the connectivity varied remarkably according to mental conditions. In the rest condition, the connectivity was localized, whereas in the task condition, a long-range coherent network was formed by the anterior midline, posterior cingulate and right middle temporal cortices with linking between the right middle temporal and left lateral cortices during numerical processing. Further EEG analyses indicate that the long-range coherent network executing cognitive functions is coordinated in the time window of theta oscillations.

Action Potentials↗

PubMed2004

Decomposing EEG data into space-time-frequency components using Parallel Factor Analysis.

Finding the means to efficiently summarize electroencephalographic data has been a long-standing problem in electrophysiology. A popular approach is identification of component modes on the basis of the time-varying spectrum of multichannel EEG recordings--in other words, a space/frequency/time atomic decomposition of the time-varying EEG spectrum. Previous work has been limited to only two of these dimensions. Principal Component Analysis (PCA) and Independent Component Analysis (ICA) have been used to create space/time decompositions; suffering an inherent lack of uniqueness that is overcome only by imposing constraints of orthogonality or independence of atoms. Conventional frequency/time decompositions ignore the spatial aspects of the EEG. Framing of the data being as a three-way array indexed by channel, frequency, and time allows the application of a unique decomposition that is known as Parallel Factor Analysis (PARAFAC). Each atom is the tri-linear decomposition into a spatial, spectral, and temporal signature. We applied this decomposition to the EEG recordings of five subjects during the resting state and during mental arithmetic. Common to all subjects were two atoms with spectral signatures whose peaks were in the theta and alpha range. These signatures were modulated by physiological state, increasing during the resting stage for alpha and during mental arithmetic for theta. Furthermore, we describe a new method (Source Spectra Imaging or SSI) to estimate the location of electric current sources from the EEG spectrum. The topography of the theta atom is frontal and the maximum of the corresponding SSI solution is in the anterior frontal cortex. The topography of the alpha atom is occipital with maximum of the SSI solution in the visual cortex. We show that the proposed decomposition can be used to search for activity with a given spectral and topographic profile in new recordings, and that the method may be useful for artifact recognition and removal.

Alpha Rhythm↗