Authorship：Lead author   Publishing type：Research paper (scientific journal)   Publisher：AIP Publishing  

DOI： 10.1063/5.0064771

Language：English   Publishing type：Research paper (scientific journal)  

Organoid technology provides an opportunity to generate brain-like structures by recapitulating developmental steps in the manner of self-organization. Here we examined the vertical-mixing effect on brain organoid structures using bioreactors and established inverted brain organoids. The organoids generated by vertical mixing showed neurons that migrated from the outer periphery to the inner core of organoids, in contrast to orbital mixing. Computational analysis of flow dynamics clarified that, by comparison with orbital mixing, vertical mixing maintained the high turbulent energy around organoids, and continuously kept inter-organoid distances by dispersing and adding uniform rheological force on organoids. To uncover the mechanisms of the inverted structure, we investigated the direction of primary cilia, a cellular mechanosensor. Primary cilia of neural progenitors by vertical mixing were aligned in a multidirectional manner, and those by orbital mixing in a bidirectional manner. Single-cell RNA sequencing revealed that neurons of inverted brain organoids presented a GABAergic character of the ventral forebrain. These results suggest that controlling fluid dynamics by biomechanical engineering can direct stem cell differentiation of brain organoids, and that inverted brain organoids will be applicable for studying human brain development and disorders in the future.

DOI： 10.1038/s42003-021-02719-5

PubMed

Authorship：Lead author   Publishing type：Research paper (scientific journal)   Publisher：Elsevier BV  

DOI： 10.1016/j.scr.2021.102504

Authorship：Lead author   Language：English   Publishing type：Research paper (scientific journal)   Publisher：Elsevier BV  

Idiopathic basal ganglia calcification (IBGC) is a rare neurodegenerative disease, characterized by abnormal calcium deposits in basal ganglia of the brain. The affected individuals exhibit movement disorders, and progressive deterioration of cognitive and psychiatric ability. The genetic cause of the disease is mutation in one of several different genes, SLC20A2, PDGFB, PDGFRB, XPR1 or MYORG, which inheritably or sporadically occurs. Here we generated an induced pluripotent stem cell (iPSC) line from an IBGC patient, which is likely be a powerful tool for revealing the pathomechanisms and exploring potential therapeutic candidates of IBGC.

DOI： 10.1016/j.scr.2021.102274

PubMed

Authorship：Lead author   Publishing type：Research paper (scientific journal)   Publisher：Wiley  

DOI： 10.1002/ana.26047

Language：English   Publishing type：Research paper (scientific journal)   Publisher：Elsevier BV  

Glycogen storage disease type 1a (GSD1a) is an autosomal recessive disorder caused by mutations of the glucose-6-phosphatase (G6PC) gene. Mutations of the G6PC gene lead to excessive accumulation of glycogen in the liver, kidney, and intestinal mucosa due to the deficiency of microsomal glucose-6-phosphatase. Human induced pluripotent stem cells (iPSCs) enable the production of patient-derived hepatocytes in culture and are therefore a promising tool for modeling GSD1a. Here, we report the establishment of human iPSCs from a GSD1a patient carrying a G6PC mutation (c.648G > T; p.Leu216 = ).

DOI： 10.1016/j.scr.2020.102095

PubMed

Language：English  

Language：Japanese  

Language：English   Publishing type：Research paper (scientific journal)   Publisher：ACADEMIC PRESS INC ELSEVIER SCIENCE  

Synapse elimination and neurite pruning are essential processes for the formation of neuronal circuits. These regressive events depend on neural activity and occur in the early postnatal days known as the critical period, but what makes this temporal specificity is not well understood. One possibility is that the neural activities during the developmentally regulated shift of action of GABA inhibitory transmission lead to the critical period. Moreover, it has been reported that the shifting action of the inhibitory transmission on immature neurons overlaps with synapse elimination and neurite pruning and that increased inhibitory transmission by drug treatment could induce temporal shift of the critical period. However, the relationship among these phenomena remains unclear because it is difficult to experimentally show how the developmental shift of inhibitory transmission influences neural activities and whether the activities promote synapse elimination and neurite pruning. In this study, we modeled synapse elimination in neuronal circuits using the modified Izhikevich's model with functional shifting of GABAergic transmission. The simulation results show that synaptic pruning within a specified period like the critical period is spontaneously generated as a function of the developmentally shifting inhibitory transmission and that the specific firing rate and increasing synchronization of neural circuits are seen at the initial stage of the critical period. This temporal relationship was experimentally supported by an in vitro primary culture of rat cortical neurons in a microchannel on a multi-electrode array (MEA). The firing rate decreased remarkably between the 18-25 days in vitro (DIV), and following these changes in the firing rate, the neurite density was slightly reduced. Our simulation and experimental results suggest that decreasing neural activity due to developing inhibitory synaptic transmission could induce synapse elimination and neurite pruning at particular time such as the critical period. Additionally, these findings indicate that we can estimate the maturity level of inhibitory transmission and the critical period by measuring the firing rate and the degree of synchronization in engineered neural networks. (C) 2017 Elsevier Inc. All rights reserved.

DOI： 10.1016/j.bbrc.2017.03.082

Web of Science

Authorship：Lead author   Language：English   Publishing type：Research paper (scientific journal)   Publisher：PERGAMON-ELSEVIER SCIENCE LTD  

Self-organized criticality (SoC), a spontaneous dynamic state established and maintained in networks of moderate complexity, is a universal characteristic of neural systems. Such systems produce cascades of spontaneous activity that are typically characterized by power -law distributions and rich, stable spatiotemporal patterns (i.e., neuronal avalanches). Since the dynamics of the critical state confer advantages in information processing within neuronal networks, it is of great interest to determine how criticality emerges during development. One possible mechanism is developmental, and includes axonal elongation during synaptogenesis and subsequent synaptic pruning in combination with the maturation of GABAergic inhibition (i.e., the integration then fragmentation process). Because experimental evidence for this mechanism remains inconclusive, we studied the developmental variation of neuronal avalanches in dissociated cortical neurons using high density complementary metal-oxide semiconductor (CMOS) microelectrode arrays (MEAs). The spontaneous activities of nine cultures were monitored using CMOS MEAs from 4 to 30 days in vitro (DIV) at single-cell spatial resolution. While cells were immature, cultures demonstrated random-like patterns of activity and an exponential avalanche size distribution; this distribution was followed by a bimodal distribution, and finally a power-law-like distribution. The bimodal distribution was associated with a large-scale avalanche with a homogeneous spatiotemporal pattern, while the sub sequent power-law distribution was associated with diverse patterns. These results suggest that the SoC emerges through a two-step process: the integration process accompanying the characteristic large-scale avalanche and the fragmentation process associated with diverse middle-size avalanches. (C) 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

DOI： 10.1016/j.neuroscience.2016.11.031

Web of Science

Authorship：Lead author   Language：English   Publishing type：Research paper (scientific journal)   Publisher：WILEY  

A small subset of neurons, called leader neurons, has been assumed as the sources of network bursts in dissociated neuronal cultures. In this paper, we proposed a network burst generation model that a network burst is considered as a sequential transition of spatial activity patterns lead by a leader pattern. We recorded spontaneous activities of cultured cortical networks with high-density CMOS-based microelectrode arrays. Spatial patterns were extracted from the high-dimensional recorded data using nonnegative matrix factorization. Then, we hypothesized the state-space model where the leader pattern served as input and the others served as states, respectively. After estimating the model parameters from the learning data, we attempted to restore the activities of test data with the estimated model. As a result, the spatio-temporal patterns in network bursts were successfully reconstructed from the model, suggesting that the leader pattern is a crucial predictor of the network burst. (C). 2016 Wiley Periodicals, Inc.

DOI： 10.1002/ecj.11905

Web of Science

Authorship：Lead author   Language：English   Publishing type：Research paper (scientific journal)   Publisher：FRONTIERS MEDIA SA  

Repeating stable spatiotemporal patterns emerge in synchronized spontaneous activity in neuronal networks. The repertoire of such patterns can serve as memory, or a reservoir of information, in a neuronal network; moreover, the variety of patterns may represent the network memory capacity. However, a neuronal substrate for producing a repertoire of patterns in synchronization remains elusive. We herein hypothesize that state dependent propagation of a neuronal sub-population is the key mechanism. By combining high-resolution measurement with a 4096-channel complementary metal-oxide semiconductor (CMOS) microelectrode array (MEA) and dimensionality reduction with non-negative matrix factorization (NMF), we investigated synchronized bursts of dissociated rat cortical neurons at approximately 3 weeks in vitro. We found that bursts had a repertoire of repeating spatiotemporal patterns, and different patterns shared a partially similar sequence of sub-population, supporting the idea of sequential structure of neuronal sub-populations during synchronized activity. We additionally found that similar spatiotemporal patterns tended to appear successively and periodically, suggesting a state-dependent fluctuation of propagation, which has been overlooked in existing literature. Thus, such a state-dependent property within the sequential sub-population structure is a plausible neural substrate for performing a repertoire of stable patterns during synchronized activity.

DOI： 10.3389/fnsys.2016.00028

Web of Science

Authorship：Lead author   Language：English   Publishing type：Research paper (international conference proceedings)  

Language：English   Publishing type：Research paper (international conference proceedings)  

Authorship：Lead author   Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Institute of Electrical Engineers of Japan  

A small subset of neurons, called "leader neurons," has been assumed as the sources of network bursts in dissociated neuronal cultures. In this paper, we proposed a network burst generation model that a network burst is considered as a sequential transition of spatial activity patterns lead by a "leader pattern". We recorded spontaneous activities of cultured cortical networks with high-density CMOS microelectrode arrays. Spatial patterns were extracted from the high dimensional recorded data using non-negative matrix factorization (NMF). Then, we hypothesized the state-space model where the leader pattern served as input and the others served as states, respectively. After estimating the model parameters from the training data, we attempted to restore the activities of test data with the estimated model. As a result, the spatio-temporal patterns in network bursts were successfully reconstructed from the model, suggesting that the leader pattern is a crucial predictor of the network burst.

DOI： 10.1541/ieejeiss.135.971

Scopus

Authorship：Lead author   Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：IEEE  

Synchrony in a neuronal network is not just a spontaneous event but rather a representation of inner information. In this point of view, the variety of synchrony patterns is considered to be related to inner capacity of the network. However, evaluating and comparing the variety of synchrony patterns, especially between different samples or different times, is difficult. In this paper, we proposed to identify the variety of synchrony based on Bayesian model selection. Hypothesizing that globally synchronized activity consists of partial synchrony, we attempted to identify reproducible-spatial pattern bases in spontaneous bursting activities of dissociated cortical cultures using Bayesian non-negative matrix factorization. Neuronal activity was recorded with high-density CMOS electrode arrays. Bayesian treatment provides evidence for selection of the number of bases based on marginal likelihood. We compared model evidence of the activity in juvenile and matured cultures. Our results suggested that the variety of synchrony patterns diversify through maturation.

DOI： 10.1109/NER.2015.7146630

Web of Science

Authorship：Lead author   Language：English   Publishing type：Research paper (scientific journal)   Publisher：WILEY-BLACKWELL  

Plasticity of neuronal networks is widely investigated as the basis of learning and stimulus-induced plasticity is one of the remarkable topics. For inducing plasticity and leading a network to a desired state, effective stimuli have to be applied to the network. However, the effect of stimuli on living neuronal networks is difficult to evaluate because of the unsteadiness of the network property. In this paper, we produce a simulated neuronal network and compare the effects of tetanic stimulus at various sites of networks in silico. Using simulation, the tetanic effects can be evaluated irrespective of network transition. We confirmed that the direction of the network plasticity is determined by the tetanized site in the network, and this can be observed only when the proper test-stimulus site is selected. We conclude that this simulation-based approach effectively evaluates the stimulus effect on neuronal networks. (C) 2014 Wiley Periodicals, Inc.

DOI： 10.1002/ecj.11673

Web of Science

Authorship：Lead author   Language：English   Publishing type：Research paper (international conference proceedings)  

Authorship：Lead author   Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Institute of Electrical Engineers of Japan (IEE Japan)  

DOI： 10.1541/ieejeiss.133.1485

Authorship：Lead author   Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：SOC INSTRUMENT CONTROL ENGINEERS JAPAN  

We developed a novel method for displacement measurement of distant target. Both lateral and rotational displacements can be measured with high accuracy using dual mode reflector and a multizeros optical beam. Proposed structure enables us to dissolve the requirement of electrical power supply on a target. Experimental results show that the precision of lateral displacement is approximately 20 mu m and that of rotational displacement is higher than 0.001 deg at 4.1m distance.

Web of Science

Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：IEEE  

DOI： 10.1109/INSS.2012.6240538

Other Link： https://dblp.uni-trier.de/db/conf/inss/inss2012.html#KuriharaYAYSN12