Curriculum Vitaes

Hidetoshi Urakubo

  (浦久保 秀俊)

Profile Information

Affiliation
Associate professor, Department of Biomedical Data Science, School of Medicine, Fujita Health University
Degree
Ph.D(Mar, 2003, Univresity of Tokyo)

Researcher number
40512140
J-GLOBAL ID
201101036451836391
researchmap Member ID
B000004615

External link

Reflected in our thoughts,
experience, by reforming our actions,
nurtures our well-being.

 

Motivated by an interest in the memorization mechanisms of the brain, I have conducted computer simulations to investigate whether current knowledge about molecular neuroscience provides a synaptic basis for learning and memory—that is, whether synaptic plasticity underlies the brain’s ability to learn and remember. My research goal is the derivation of mathematical models of synaptic plasticity. The rules of synaptic plasticity are not simple. Synaptic plasticity generally occurs in a synapse-specific manner, but in some case it occurs cooperatively among synapses. It is also significantly affected by age, emotional state, and psychiatric disorders. I focus on the first steps of how neural functions emerge from complex biochemical reactions at synapses. (more)


Committee Memberships

 1

Awards

 1

Papers

 25
  • Takayuki Onai, Noritaka Adachi, Hidetoshi Urakubo, Fumiaki Sugahara, Toshihiro Aramaki, Mami Matsumoto, Nobuhiko Ohno
    iScience, 108338-108338, Nov, 2023  Peer-reviewed
  • Sergey Mursalimov, Mami Matsumoto, Hidetoshi Urakubo, Elena Deineko, Nobuhiko Ohno
    Annals of Botany, mcad107, Jul 25, 2023  Peer-reviewed
    Abstract Background and Aims During the analysis of plant male meiocytes coming from destroyed meiocyte columns (united multicellular structures formed by male meiocytes in each anther locule), a considerable amount of information becomes unavailable. Therefore, in this study intact meiocyte columns were studied by volume microscopy in wild-type rye for the most relevant presentation of 3-D structure of rye meiocytes throughout meiosis. Methods We used two types of volume light microscopy: confocal laser scanning microscopy and non-confocal bright-field scanning microscopy combined with alcohol and aldehyde fixation, as well as serial block-face scanning electron microscopy. Key Results Unusual structures, called nuclear protuberances, were detected. At certain meiotic stages, nuclei formed protuberances that crossed the cell wall through intercellular channels and extended into the cytoplasm of neighbouring cells, while all other aspects of cell structure appeared to be normal. This phenomenon of intercellular nuclear migration (INM) was detected in most meiocytes at leptotene/zygotene. No cases of micronucleus formation or appearance of binucleated meiocytes were noticed. There were instances of direct contact between two nuclei during INM. No influence of fixation or of mechanical impact on the induction of INM was detected. Conclusions Intercellular nuclear migration in rye may be a programmed process (a normal part of rye male meiosis) or a tricky artefact that cannot be avoided in any way no matter which approach to meiocyte imaging is used. In both cases, INM seems to be an obligatory phenomenon that has previously been hidden by limitations of common microscopic techniques and by 2-D perception of plant male meiocytes. Intercellular nuclear migration cannot be ignored in any studies involving manipulations of rye anthers.
  • Sehyung Lee, Hideaki Kume, Hidetoshi Urakubo, Haruo Kasai, Shin Ishii
    Neural networks, 152 57-69, Aug, 2022  Peer-reviewed
  • Hidetoshi Urakubo, Sho Yagishita, Haruo Kasai, Yoshiyuki Kubota, Shin Ishii
    PLOS Computational Biology, 17(9) e1009364-e1009364, Sep 30, 2021  Peer-reviewedLead authorCorresponding author
    In behavioral learning, reward-related events are encoded into phasic dopamine (DA) signals in the brain. In particular, unexpected reward omission leads to a phasic decrease in DA (DA dip) in the striatum, which triggers long-term potentiation (LTP) in DA D2 receptor (D2R)-expressing spiny-projection neurons (D2 SPNs). While this LTP is required for reward discrimination, it is unclear how such a short DA-dip signal (0.5–2 s) is transferred through intracellular signaling to the coincidence detector, adenylate cyclase (AC). In the present study, we built a computational model of D2 signaling to determine conditions for the DA-dip detection. The DA dip can be detected only if the basal DA signal sufficiently inhibits AC, and the DA-dip signal sufficiently disinhibits AC. We found that those two requirements were simultaneously satisfied only if two key molecules, D2R and regulators of G protein signaling (RGS) were balanced within a certain range; this balance has indeed been observed in experimental studies. We also found that high level of RGS was required for the detection of a 0.5-s short DA dip, and the analytical solutions for these requirements confirmed their universality. The imbalance between D2R and RGS is associated with schizophrenia and DYT1 dystonia, both of which are accompanied by abnormal striatal LTP. Our simulations suggest that D2 SPNs in patients with schizophrenia and DYT1 dystonia cannot detect short DA dips. We finally discussed that such psychiatric and movement disorders can be understood in terms of the imbalance between D2R and RGS.
  • Laxmi Kumar Parajuli, Hidetoshi Urakubo, Ai Takahashi-Nakazato, Roberto Ogelman, Hirohide Iwasaki, Masato Koike, Hyung-Bae Kwon, Shin Ishii, Won Chan Oh, Yugo Fukazawa, Shigeo Okabe
    eNeuro, Oct 27, 2020  Peer-reviewed
    Precise information on synapse organization in a dendrite is crucial to understanding the mechanisms underlying voltage integration and the variability in the strength of synaptic inputs across dendrites of different complex morphologies. Here, we used focused ion beam/scanning electron microscope (FIB/SEM) to image the dendritic spines of mice in the hippocampal CA1 region, CA3 region, somatosensory cortex, striatum, and cerebellum (CB). Our results show that the spine geometry and dimensions differ across neuronal cell types. Despite this difference, dendritic spines were organized in an orchestrated manner such that the postsynaptic density (PSD) area per unit length of dendrite scaled positively with the dendritic diameter in CA1 proximal stratum radiatum (PSR), cortex and CB. The ratio of the PSD area to neck length was kept relatively uniform across dendrites of different diameters in CA1 PSR. Computer simulation suggests that a similar level of synaptic strength across different dendrites in CA1 PSR enables the effective transfer of synaptic inputs from the dendrites towards soma. Excitatory postsynaptic potentials (EPSPs), evoked at single spines by glutamate uncaging and recorded at the soma, show that the neck length is more influential than head width in regulating the EPSP magnitude at the soma. Our study describes thorough morphological features and the organizational principles of dendritic spines in different brain regions.Significance statement Little is known about the characteristic anatomical features underlying the organization of spine synapses in a dendrite. This study used volume electron microscopy to make an extensive characterization of dendritic spine synapses in multiple regions of the mouse brain to uncover the principles underlying their placement along a dendritic shaft. By using a combination of approaches such as two-photon imaging, glutamate uncaging, electrophysiology, and computer simulation, we reveal the functional importance of regulated spine placement along a dendritic trunk. Our research presents a crucial step in understanding the synaptic computational principle in dendrites by highlighting the generalizable features of dendritic spine organization in a neuron.

Misc.

 26
  • Hidetoshi Urakubo, Akiya Watakabe, Ken Nakae, Shin Ishii, Kenji Doya
    Kaibogaku Zasshi / Acta anatomica Nipponica, 97(2) 41-44, Sep, 2022  InvitedLead author
  • Hidetoshi Urakubo
    Clinical neuroscience, 40(4) 534-536, Apr, 2022  InvitedLead authorCorresponding author
  • Hidetoshi Urakubo, Yoshiyuki Kubota
    KENBIKYO, 55(3) 120-124, Dec, 2020  Peer-reviewedInvitedLead authorCorresponding author
  • 中江健, 浦久保秀俊, 東広志, 田中康裕, 島崎秀昭, 尾藤晴彦, 石井信
    日本神経回路学会誌, 26(3) 99-103, Sep, 2019  
  • Hidetoshi Urakubo
    The brain & neural networks, 22(3) 133-144, Sep, 2015  Invited
  • 中江 健, 松田 道行, 石井 信, 本田 直樹, 浦久保 秀俊, 山尾 将隆, 近藤 洋平, 塚田 祐基, 小山 雅典, 村上 陽平, 松田 哲也
    日本神経回路学会誌, 22(2) 78-81, 2015  
  • HAYASHI Yuichiro, URAKUBO Hidetoshi, ISHII Shin
    IEICE technical report. Neurocomputing, 113(500) 31-36, Mar 17, 2014  
    Motion illusion is one of visual illusions that evokes motion by a static image. To elucidate operating principles of the human visual system, it is important to reveal the mechanisms of the motion illusions. One of such motion illusions is the peripheral drift illusion. The Faubert and Herbert image (FH image) is known as a stimulus image that evokes the peripheral drift illusion. When the FH image (pre-stimulus) disappears to a uniform background image (post-stimulus) after the presentation for several seconds, observers perceive illusory rotation of the afterimage (afterimage rotation) at the moment. Here, to explain this afterimage rotation, we proposed a simple mathematical model of retinal functions. In this model, the FH image was transferred to spatio-temporally varying noisy outputs, and those outputs produced focal points during the post-stimulus period. The focal time accompanied luminance-dependent lag, and this lag had the similar characteristics of the afterimage rotation. We quantified the afterimage rotation by psychophysical experiments, and compared them with the output of the model. We report that the proposed model successfully explained some characteristics of the afterimage rotation.
  • 中江 健, 本田 直樹, 浦久保 秀俊, 山尾 将隆, 近藤 洋平, 塚田 祐基, 石井 信
    日本神経回路学会誌, 21(2) 101-104, 2014  
  • 中江 健, 本田 直樹, 浦久保 秀俊, 山尾 将隆, 塚田 祐基, 石井 信
    日本神経回路学会誌 = The Brain & neural networks, 20(2) 84-87, Jun 5, 2013  
  • Hidetoshi Urakubo, Shinya Kuroda
    The Dictionary of Simulation, Jan, 2012  Peer-reviewedInvited
  • Hidetoshi Urakubo, Shinya Kuroda
    NEUROSCIENCE RESEARCH, 71 E325-E325, 2011  
  • Minoru Honda, Hidetoshi Urakubo, Shinya Kuroda
    NEUROSCIENCE RESEARCH, 68 E437-E437, 2010  
  • Minoru Honda, Hidetoshi Urakubo, Shinya Kuroda
    NEUROSCIENCE RESEARCH, 65 S65-S65, 2009  
  • Shinya Kuroda, Hidetoshi Urakubo
    Seitai-no Kagaku, 59(5) 416-417, 2008  Invited
  • SHINOZAKI Takashi, CATEAU Hidenori, URAKUBO Hidetoshi, OKADA Masato
    IEICE technical report, 106(279) 1-6, Oct 4, 2006  
    We report that the inhibitory synaptic input can control the transmission of synfire chain. Synfire chain is a phenomenon in which synchronous firings transmit between groups of neurons. Many previous studies discussed synfire chain as a fixed cable, and no studies investigated to control synfire chain flexibly. In this study, we numerically analyze the Hodgkin-Huxley model in order to examine whether the synfire chain can be controlled by topdown signals. As a result of simulation, inhibitory synaptic input 6ms before the pulse packet input with short duration strongly facilitated the transmission of synfire chain. Moreover, that 1ms after the pulse packet input strongly depressed the transmission of synfire chain. In Conclusion, synfire chain could be controlled by a inhibitory synaptic input, and could performed dynamically and functionally.
  • SHIUN Daisuke, URAKUBO Hidetoshi, AIHARA Takeshi, TSUKADA Minoru
    IEICE technical report, 105(657) 27-32, Mar 15, 2006  
    In the hippocampal CA1 area, repetitive correlated spiking of pre- and postsynaptic neurons can induce LTP and LTD, depending on the timing of the pre- and postsynaptic excitation (Spike timing Dependent Plasticity). To investigate the information processing on the dendrite of a single neuron during the induction of STDP in the hippocampal CA1 area, model simulation was performed using NEURON simulator. As a result, the effects of a back-propagating action potential to distal dendrites by synaptic inputs on the proximal dendrite, enhance or depress, were clarified.
  • Hidetoshi Urakubo, Shinya Kuroda, Takeshi Aihara
    Simulation, 25(1) 4-12, Mar, 2006  Invited
    Recent advance in neuroscience has revealed that neurons as information processors are not point nodes, but spatially distributed units, as represented by dendritic arborization. Computer simulation is very effective for analyzing the distributed properties of neurons; however, the implementation as computer programs is quite complicated. Here, we introduce the GENESIS and NEURON simulators, which have been developed for supporting such complex neuronal simulations. We firstly address the mathematical bases for modeling spatial properties of neurons, and then explain how the NEURON/GENESIS simulator handles the properties with sample programs. At last, we show the effectiveness of the simulators by introducing our computational researches about spike timing-dependent plasticity (STDP).
  • Takeshi Aihara, Yuki Uchikune, Daisuke Shiun, Minoru Tsukada, Norihiro Yoshida, Hidetoshi Urakubo
    NEUROSCIENCE RESEARCH, 55 S52-S52, 2006  
  • AIHARA Takeshi, NISHIYAMA Makoto, URAKUBO Hidetoshi
    The brain & neural networks, 12(2) 94-99, Jun, 2005  Invited
    In the hippocampal CA1 area, repetitive correlated spiking of pre- and postsynaptic neurons can induce LTP and LTD, depending on the timing of the pre- and postsynaptic excitation (Spike timing Dependent Plasticity). To investigate the information processing on the dendrite of a single neuron during the induction of STDP in the hippocampal CA1 area, model simulation was performed using NEORON simulator. As a result, (1) the location dependency of amplifying synapse, (2) the effect of gating a back-propagating action potential to distal dendrites by inputs on the proximal dendrite, and (3) the effect of inhibitory input to the induction of STDP were clarified.
  • AIHARA Takeshi, URAKUBO Hidetoshi, NISHIYAMA Makoto
    IEICE technical report. Neurocomputing, 104(759) 43-48, Mar 22, 2005  
    In the hippocampal CA1 area, repetitive correlated spiking of pre- and postsynaptic neurons can induce LTP and LTD, depending on the timing of the pre- and postsynaptic excitation (Spike timing Dependent Plasticity). To investigate the information processing on the dendrite of a single neuron during the induction of STDP in the hippocampal CA1 area, model simulation was performed using NEORON simulator. As a result, (1) the location dependency of amplifying synapse, (2) the effect of gating a back-propagating action potential to distal dendrites by inputs on the proximal dendrite, and (3) the effect of inhibitory input to the induction of STDP were clarified.
  • Hidetoshi Urakubo, Shinya Kuroda
    BME : Bio Medical Engineering, 18(2) 12-18, Apr, 2004  Invited
  • URAKUBO Hidetoshi, WATANABE Masataka, KONDO Shunsuke
    The Transactions of the Institute of Electronics,Information and Communication Engineers., 87(2) 695-704, Feb, 2004  Peer-reviewed
  • Hidetoshi Urakubo
    The brain & neural networks, 10(4) 223-224, Dec, 2003  Invited
  • URAKUBO Hidetoshi, WATANABE Masataka
    IEICE technical report. Neurocomputing, 101(735) 227-233, Mar 11, 2002  
    Recent studies gave new insight on synaptic plasticity that the sign and magnitude of plasticity depends critically on the precise timing of pre- and post-synaptic firing, which is termed the spike-timing dependent plasticity (STDP). To examine the generalized behavior of this plasticity, we quantified [Ca2+]in transient in a spine by simulating the pairing experiment of a hippocampal CA1 pyramidal cell. This simulation showed the robustness of timing window at low frequency, and predicts any timing LTP at high frequency.
  • URAKUBO Hidetoshi, WATANABE Masataka
    IEICE technical report. Neurocomputing, 101(238) 33-39, Jul 20, 2001  
    In this paper, we analyze input-ouput function of a comartmental model neuron with Hodgkin-Huxley-like channel kinetics. Under bombardment of input spikes, Inverse correlations of the model neuron show main peaks before firings to achieve a certain membrane potentials, which shorten their time windows with the increase of input frequency. The neuron with the large time window is known to work as an integrator, which is easily affected by noise input, and the neuron with the short time window is to work as a coincidence detector, which keeps the precision of firing time against noise input. We demonstrate that the high frequency input gives more precisely timed firings than the low frequency input, in the condition of the same signal-to-noise ratio.
  • URAKUBO Hidetoshi, WATANABE Masataka
    IEICE technical report. Neurocomputing, 100(191) 37-42, Jul 11, 2000  
    Correlation analyses for neuronal spikes, which have been developed recently, generally give the information on the basic topology of networks as well as the functions of the brain. To analyze the network temporal dynamics, we develop a statistical way on the assumption of probabilistic firing neurons that let through spikes at a certain probability. In this study, we firstly use this assumption on the firing neurons to analyze temporal structure of the network with random connectivity;and, give an explanation of the irregularity of spike sequences generally observed in the cortical neurons. Moreover, considering the spatial structure of a network, we secondly analyze the spatiotemporal interaction of a network with local connectivity. We also discuss the possibility of information processing with the results.

Teaching Experience

 6

Research Projects

 9