研究者データベース

西川 淳(ニシカワ ジユン)
情報科学研究院 生命人間情報科学部門 バイオエンジニアリング分野
准教授

基本情報

所属

  • 情報科学研究院 生命人間情報科学部門 バイオエンジニアリング分野

職名

  • 准教授

学位

  • 博士(工学)(北海道大学)

ホームページURL

J-Global ID

プロフィール

  • 脳の情報処理原理を知りたい.そのために微細加工技術を駆使し,神経活動及び神経伝達物質濃度を高密度に測定・制御することのできる次世代デバイスの開発に取り組んでいます.また,これを活用して,主に齧歯類の大脳皮質聴覚野の聴覚情報表現を明らかにする研究,様々な聴覚現象を支える神経活動を特定する研究,学習に伴う神経活動の変化とそのメカニズムを明らかにする研究,埋め込みデバイスによる神経活動制御を目指した研究などを進めています.計測した脳活動を数理モデル化し,背後に隠れる計算原理を解き明かそうとする研究も行っています.このように,ナノテクノロジーや数理科学を神経科学と統合することにより,神経科学分野でブレイクスルーを起こすとともに,将来的には神経疾患を抱える患者を救うことのできる新しい医療機器の開発へと繋げたい.

研究キーワード

  • MEMS   微細加工技術   学習   オペラント条件付け   聴覚皮質   ブレインマシンインターフェイス   神経工学   神経科学   発声学習   コミュニケーション   言語進化   言語情報処理   複雑ネットワーク   複雑系   フラクタル   カオス   非線形動力学   計算論的神経科学   神経行動学   鳥の歌   包括脳ネットワーク   

研究分野

  • ライフサイエンス / 動物生理化学、生理学、行動学
  • ものづくり技術(機械・電気電子・化学工学) / 制御、システム工学
  • ものづくり技術(機械・電気電子・化学工学) / 制御、システム工学
  • ナノテク・材料 / 分析化学
  • ナノテク・材料 / ナノマイクロシステム
  • 人文・社会 / 実験心理学
  • ライフサイエンス / 基盤脳科学
  • ライフサイエンス / 生体材料学
  • ライフサイエンス / 生体医工学
  • 情報通信 / 生命、健康、医療情報学
  • 情報通信 / 統計科学

職歴

  • 2013年11月 - 現在 北海道大学 大学院情報科学研究科 神経制御工学研究室(旧: 生体計測工学研究室) 准教授
  • 2011年12月 - 2013年10月 北海道大学 大学院情報科学研究科 生体計測工学研究室 特任講師
  • 2011年08月 - 2011年11月 大阪大学 大学院生命機能研究科 マイクロシステム神経工学研究室 特任助教
  • 2011年04月 - 2011年07月 独立行政法人理化学研究所 情動情報連携研究チーム 基礎科学特別研究員
  • 2009年04月 - 2011年03月 独立行政法人理化学研究所 生物言語研究チーム 基礎科学特別研究員
  • 2004年04月 - 2009年03月 独立行政法人理化学研究所 生物言語研究チーム 研究員

学歴

  • 2001年04月 - 2004年03月   北海道大学   工学研究科   量子物理工学専攻 博士後期課程
  • 1999年04月 - 2001年03月   北海道大学   工学研究科   量子物理工学専攻 修士課程
  • 1995年04月 - 1999年03月   北海道大学   工学部   応用物理学科

所属学協会

  • Society for Neuroscience   日本神経科学学会   日本神経回路学会   

研究活動情報

論文

  • Jun Nishikawa, Yuto Ohtaka, Yuishi Tachibana, Yasutaka Yanagawa, Hisayuki Osanai, Takeaki Haga, Takashi Tateno
    Journal of Neuroscience Methods 293 77 - 85 2018年01月01日 [査読有り][通常論文]
     
    Background Chronic neural recording in freely moving animals is important for understanding neural activities of cortical neurons associated with various behavioral contexts. In small animals such as mice, it has been difficult to implant recording electrodes into exact locations according to stereotactic coordinates, skull geometry, or the shape of blood vessels. The main reason for this difficulty is large individual differences in the exact location of the targeted brain area. New methods We propose a new electrode implantation procedure that is combined with transcranial flavoprotein fluorescence imaging. We demonstrate the effectiveness of this method in the auditory cortex (AC) of mice. Results Prior to electrode implantation, we executed transcranial flavoprotein fluorescence imaging in anesthetized mice and identified the exact location of AC subfields through the skull in each animal. Next, we surgically implanted a microdrive with a tungsten electrode into exactly the identified location. Finally, we recorded neural activity in freely moving conditions and evaluated the success rate of recording auditory responses. Comparison with existing method(s) These procedures dramatically improved the success rate of recording auditory responses from 21.1% without imaging to 100.0% with imaging. We also identified large individual differences in positional relationships between sound-driven response areas and the squamosal suture or blood vessels. Conclusions Combining chronic electrophysiology with transcranial flavoprotein fluorescence imaging before implantation enables the realization of reliable subfield-targeted neural recording from freely moving small animals.
  • M. Noto, J. Nishikawa, T. Tateno
    NEUROSCIENCE 318 58 - 83 2016年03月 [査読有り][通常論文]
     
    A sound interrupted by silence is perceived as discontinuous. However, when high-intensity noise is inserted during the silence, the missing sound may be perceptually restored and be heard as uninterrupted. This illusory phenomenon is called auditory induction. Recent electrophysiological studies have revealed that auditory induction is associated with the primary auditory cortex (A1). Although experimental evidence has been accumulating, the neural mechanisms underlying auditory induction in A1 neurons are poorly understood. To elucidate this, we used both experimental and computational approaches. First, using an optical imaging method, we characterized population responses across auditory cortical fields to sound and identified five subfields in rats. Next, we examined neural population activity related to auditory induction with high temporal and spatial resolution in the rat auditory cortex (AC), including the A1 and several other AC subfields. Our imaging results showed that tone-burst stimuli interrupted by a silent gap elicited early phasic responses to the first tone and similar or smaller responses to the second tone following the gap. In contrast, tone stimuli interrupted by broadband noise (BN), considered to cause auditory induction, considerably suppressed or eliminated responses to the tone following the noise. Additionally, tone-burst stimuli that were interrupted by notched noise centered at the tone frequency, which is considered to decrease the strength of auditory induction, partially restored the second responses from the suppression caused by BN. To phenomenologically mimic the neural population activity in the A1 and thus investigate the mechanisms underlying auditory induction, we constructed a computational model from the periphery through the AC, including a nonlinear dynamical system. The computational model successively reproduced some of the above-mentioned experimental results. Therefore, our results suggest that a nonlinear, self-exciting system is a key element for qualitatively reproducing A1 population activity and to understand the underlying mechanisms. (C) 2016 IBRO. Published by Elsevier Ltd. All rights reserved.
  • Takashi Tateno, Jun Nishikawa
    Frontiers in Neuroengineering 7 39  2014年10月10日 [査読有り][通常論文]
     
    In this report, we describe the system integration of a complementary metal oxide semiconductor (CMOS) integrated circuit (IC) chip, capable of both stimulation and recording of neurons or neural tissues, to investigate electrical signal propagation within cellular networks in vitro. The overall system consisted of three major subunits: a 5.0 × 5.0 mm CMOS IC chip, a reconfigurable logic device (field-programmable gate array, FPGA), and a PC. To test the system, microelectrode arrays (MEAs) were used to extracellularly measure the activity of cultured rat cortical neurons and mouse cortical slices. The MEA had 64 bidirectional (stimulation and recording) electrodes. In addition, the CMOS IC chip was equipped with dedicated analog filters, amplification stages, and a stimulation buffer. Signals from the electrodes were sampled at 15.6 kHz with 16-bit resolution. The measured input-referred circuitry noise was 10.1 μ V root mean square (10 Hz to 100 kHz), which allowed reliable detection of neural signals ranging from several millivolts down to approximately 33 μ Vpp. Experiments were performed involving the stimulation of neurons with several spatiotemporal patterns and the recording of the triggered activity. An advantage over current MEAs, as demonstrated by our experiments, includes the ability to stimulate (voltage stimulation, 5-bit resolution) spatiotemporal patterns in arbitrary subsets of electrodes. Furthermore, the fast stimulation reset mechanism allowed us to record neuronal signals from a stimulating electrode around 3 ms after stimulation. We demonstrate that the system can be directly applied to, for example, auditory neural prostheses in conjunction with an acoustic sensor and a sound processing system.
  • Takashi Tateno, Jun Nishikawa, Nobuyoshi Tsuchioka, Hirofumi Shintaku, Satoyuki Kawano
    Frontiers in neuroengineering 6 12 - 12 2013年 [査読有り][通常論文]
     
    To improve the performance of cochlear implants, we have integrated a microdevice into a model of the auditory periphery with the goal of creating a microprocessor. We constructed an artificial peripheral auditory system using a hybrid model in which polyvinylidene difluoride was used as a piezoelectric sensor to convert mechanical stimuli into electric signals. To produce frequency selectivity, the slit on a stainless steel base plate was designed such that the local resonance frequency of the membrane over the slit reflected the transfer function. In the acoustic sensor, electric signals were generated based on the piezoelectric effect from local stress in the membrane. The electrodes on the resonating plate produced relatively large electric output signals. The signals were fed into a computer model that mimicked some functions of inner hair cells, inner hair cell-auditory nerve synapses, and auditory nerve fibers. In general, the responses of the model to pure-tone burst and complex stimuli accurately represented the discharge rates of high-spontaneous-rate auditory nerve fibers across a range of frequencies greater than 1 kHz and middle to high sound pressure levels. Thus, the model provides a tool to understand information processing in the peripheral auditory system and a basic design for connecting artificial acoustic sensors to the peripheral auditory nervous system. Finally, we discuss the need for stimulus control with an appropriate model of the auditory periphery based on auditory brainstem responses that were electrically evoked by different temporal pulse patterns with the same pulse number.
  • Cantor coding of song sequence in the Bengalese finch HVC
    Jun Nishikawa, Kazuo Okanoya
    Advances in Cognitive Neurodynamics (III) 629 - 634 2012年 [査読有り][通常論文]
  • Kentaro Katahira, Jun Nishikawa, Kazuo Okanoya, Masato Okada
    NEURAL COMPUTATION 22 9 2369 - 2389 2010年09月 [査読有り][通常論文]
     
    Neural activity is nonstationary and varies across time. Hidden Markov models (HMMs) have been used to track the state transition among quasi-stationary discrete neural states. Within this context, an independent Poisson model has been used for the output distribution of HMMs; hence, the model is incapable of tracking the change in correlation without modulating the firing rate. To achieve this, we applied a multivariate Poisson distribution with correlation terms for the output distribution of HMMs. We formulated a variational Bayes (VB) inference for the model. The VB could automatically determine the appropriate number of hidden states and correlation types while avoiding the overlearning problem. We developed an efficient algorithm for computing posteriors using the recursive relationship of a multivariate Poisson distribution. We demonstrated the performance of our method on synthetic data and real spike trains recorded from a songbird.
  • 西川淳
    生物物理 50 3 134 - 135 2010年 [査読有り][通常論文]
  • 西川淳, 高橋美樹, 加藤真樹, 岡ノ谷一夫
    生体の科学 61 1 30 - 40 2010年 [査読無し][通常論文]
  • Jun Nishikawa, Kazutoshi Gohara
    INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS 18 12 3665 - 3678 2008年12月 [査読有り][通常論文]
     
    We studied a hybrid dynamical system composed of a higher module with discrete dynamics and a lower module with continuous dynamics. Two typical examples of this system were investigated from the viewpoint of dynamical systems. One example is a nonfeedback system whose higher module stochastically switches inputs to the lower module. The dynamics was characterized by attractive and invariant fractal sets with hierarchical clusters addressed by input sequences. The other example is a feedback system whose higher module switches in response to the states of the lower module at regular intervals. This system converged into various switching attractors that correspond to infinite switching manifolds, which de. ne each feedback control rule at the switching point. We showed that the switching attractors in the feedback system are subsets of the fractal sets in the nonfeedback system. The feedback system can be considered an automaton that generates various sequences from the fractal set by choosing the typical switching manifold. We can control this system by adjusting the switching interval to determine the fractal set as a constraint and by adjusting the switching manifold to select the automaton from the fractal set. This mechanism might be the key to developing information processing that is neither too soft nor too rigid.
  • Jun Nishikawa, Masato Okada, Kazuo Okanoya
    EUROPEAN JOURNAL OF NEUROSCIENCE 27 12 3273 - 3283 2008年06月 [査読有り][通常論文]
     
    Birdsong is a complex vocalization composed of various song elements organized according to sequential rules. Two alternative views exist that explain the neural representation of song element sequences in the songbird brain. The finding of sequential selective neurons supports the idea that the song element sequence is encoded in a chain of rigid selective neurons. Alternatively, song structure could be encoded in an ensemble of relatively broad selective neurons arranged in a distributed manner. Here we attempted to determine which neural representation actually occurs in the song system by recording neural responses to various stimuli and performing information-theoretic analysis on the data obtained. We recorded the neural responses to all possible element pairs of stimuli in the Bengalese finch brain nucleus high vocal centre (HVC). Our results showed that each neuron has broad but differential response properties to element sequences beyond the structure of self-generated song. To quantify the transmitted information by such a broadly tuned neural population, we calculated the time course of mutual information between auditory stimuli and neural activities. Confounded information, which represents the relationship between present and previous elements, increased significantly immediately after stimulus presentation. These results indicate that the song element sequence is encoded in a neural ensemble in the HVC via population coding. These findings give us a new encoding scheme for the song element sequence using a distributed neural representation rather than the chain model of rigid selective neurons.
  • Jun Nishikawa, Kazutoshi Gohara
    Physical Review E - Statistical, Nonlinear, and Soft Matter Physics 77 3 036210  2008年03月18日 [査読有り][通常論文]
     
    We studied an anomaly in fractal dimensions measured from the attractors of dynamical systems driven by stochastically switched inputs. We calculated the dimensions for different switching time lengths in two-dimensional linear dynamical systems, and found that changes in the dimensions due to the switching time length had a singular point when the system matrix had two different real eigenvalues. Using partial dimensions along each eigenvector, we explicitly derived a generalized dimension Dq and a multifractal spectrum f (α) to explain this anomalous property. The results from numerical calculations agreed well with those from analytical equations. We found that this anomaly is caused by linear independence, inhomogeneity of eigenvalues, and overlapping conditions. The mechanism for the anomaly could be identified for various inhomogeneous systems including nonlinear ones, and this reminded us of anomalies in some physical values observed in critical phenomena. © 2008 The American Physical Society.
  • 西川淳, 岡ノ谷一夫
    日本神経回路学会誌 14 2 79 - 93 2007年 [査読無し][通常論文]
  • 鳥のさえずりとヒトの言語: 共通性の生物学的基盤
    高橋美樹, 西川淳, 岡ノ谷一夫
    生物科学 59 2 77 - 84 2007年 [査読有り][通常論文]
  • Jun Nishikawa, Kazuo Okanoya
    Ornithological Science 5 1 95 - 103 2006年 [査読有り][通常論文]
     
    The Bengalese Finch Lonchura striata var. domestica has highly complex songs with element sequences similar in syntactic structure to that of human language. Because young learn songs by comparing their auditory memory of their father's songs to the auditory feedback of a self-generated song, it is important to understand the auditory neural representation of element sequences. We developed a spiking neural network model of the song-control nucleus HVC that changes the weight among connected neurons via spike-timing-dependent plasticity (STDP), a biologically plausible learning rule. In the model, the dynamics of neural population converged into a stable activity distribution after sufficient learning steps. The network activity differentiated element pairs included in the input sequence from those that were not. Linear input sequences had better fine response selectivity for typical pairs than random or syntax inputs. However, real HVC neurons of Bengalese Finch respond to a wider range of pair stimuli. Thus, the actual neural representation of Bengalese Finch may be more broadly distributed, possibly because of simple STDP and other additive parameters or components. From a theoretical viewpoint, one of the most reliable neural coding schemes, Cantor coding, is a distributed, sequential coding system using fractal properties. We hypothesize that Bengalese Finch learn their complex song element sequences via Cantor coding. © 2006, The Ornithological Society of Japan. All rights reserved.
  • 小鳥の歌学習の神経回路は?
    西川淳, 岡ノ谷一夫
    Clinical Neuroscience 24 5 609 - 609 2006年 [査読無し][通常論文]
  • 鳥の歌学習と誤差修正機構
    関義正, 西川淳
    生物の科学 遺伝 59 6 44 - 48 2005年 [査読無し][通常論文]
  • Kazutoshi Gohara, Jun Nishikawa
    Artificial Life and Robotics 7 4 189 - 192 2004年 [査読有り][通常論文]
  • J Nishikawa, K Gohara
    INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS 12 4 827 - 834 2002年04月 [査読有り][通常論文]
     
    We have proposed a process of generating fractals not from the results of chaotic dynamics, but from the switching of ordinary differential equations. This paper experimentally and numerically analyzes the dynamics of an electronic circuit driven by stochastically switching inputs. The following two results are obtained. First, the dynamics is characterized by a set Gamma(C) of trajectories in the cylindrical phase space, where C is a set of initial states on the Poincare section. Gamma(C) and C are attractive and unique invariant fractal sets that satisfy specific equations. The second result is that the correlation dimension of C is in inverse proportion to the interval of the switching inputs. These two findings move beyond the conventional theory based on contraction maps. It should be noted that the set C is constructed by noncontraction maps.

受賞

  • 2010年 包括脳ネットワーク 若手優秀発表賞
     鳥類歌中枢HVCにおけるカントールコーディングのin vivoによる実験的検証 
    受賞者: 西川 淳
  • 2009年 日本神経回路学会 研究賞
     鳥類歌制御神経核HVC局所回路における機能的ネットワーク 
    受賞者: 西川 淳
  • 2008年 日本生物物理学会 若手奨励賞招待講演者
     多点同時記録によって抽出されたジュウシマツHVC局所回路における機能的ネットワーク 
    受賞者: 西川淳
  • 2008年 日本神経回路学会 奨励賞
     小鳥の脳神経核HVCにおける歌要素系列の集団符号化 
    受賞者: 西川淳

共同研究・競争的資金等の研究課題

  • 加齢に伴う聴覚機能低下を自律的に補償する人工聴覚スマートインプラントの研究
    公益財団法人 大川情報通信基金:研究助成
    研究期間 : 2014年03月 -2015年02月 
    代表者 : 西川 淳
  • 加齢における聴覚の機能低下機構とその補償機器開発の基礎研究
    ノーステック財団:研究開発助成事業 若手研究人材・ネットワーク育成補助金(Talent補助金)
    研究期間 : 2013年09月 -2014年03月 
    代表者 : 西川 淳
  • 聴覚中枢神経マイクロインプラントに応用する音情報神経符号化の基礎技術開発
    公益財団法人 立石科学技術振興財団:研究助成 (A)
    研究期間 : 2013年04月 -2014年03月 
    代表者 : 西川 淳
  • マウスの超音波発声とその認知を司る神経機構の解明
    文部科学省:科学研究費補助金 挑戦的萌芽研究
    研究期間 : 2012年04月 -2014年03月 
    代表者 : 西川 淳
  • 時系列信号によるコミュニケーションを司る神経情報表現の解明
    文部科学省:科学研究費補助金 新学術領域研究(伝達創成機構)(公募研究)
    研究期間 : 2010年04月 -2012年03月 
    代表者 : 西川淳
  • 複雑な時系列処理を支える局所神経回路におけるネットワークダイナミクスの解明
    独立行政法人理化学研究所:基礎科学特別研究員研究費
    研究期間 : 2009年04月 -2011年07月 
    代表者 : 西川淳
  • 音声時系列分節化を支える神経細胞集団の同期的活動
    文部科学省:科学研究費補助金 若手(B)
    研究期間 : 2008年04月 -2010年03月 
    代表者 : 西川淳
  • 複雑な時系列を産出する神経モジュール間の相互作用
    文部科学省:科学研究費補助金 若手(B)
    研究期間 : 2006年04月 -2008年03月 
    代表者 : 西川淳

教育活動情報

主要な担当授業

  • 生体制御工学特論
    開講年度 : 2019年
    課程区分 : 修士課程
    開講学部 : 情報科学研究科
    キーワード : 中枢神経系,神経シグナル伝達,感覚情報処理とその補償器,脳刺激法,学習・記憶,運動プログラムと制御,神経活動の大規模計測,計算論的神経科学,神経活動の制御技術,脳の機能補償と機能拡張
  • 神経制御工学特論
    開講年度 : 2019年
    課程区分 : 修士課程
    開講学部 : 情報科学院
    キーワード : 中枢神経系,神経シグナル伝達,感覚情報処理とその補償器,脳刺激法,学習・記憶,運動プログラムと制御,神経活動の大規模計測,計算論的神経科学,神経活動の制御技術,脳の機能補償と機能拡張
  • バイオエンジニアリング特論
    開講年度 : 2019年
    課程区分 : 修士課程
    開講学部 : 情報科学研究科
    キーワード : 遺伝情報, genetic information, バイオインフォマティクス, bioinformatics, イメージング, imaging, 生体医工学, biomedical engineering, 細胞力学, cell mechanics
  • 生体制御工学特論
    開講年度 : 2019年
    課程区分 : 博士後期課程
    開講学部 : 情報科学研究科
    キーワード : 中枢神経系,神経シグナル伝達,感覚情報処理とその補償器,脳刺激法,学習・記憶,運動プログラムと制御,神経活動の大規模計測,計算論的神経科学,神経活動の制御技術,脳の機能補償と機能拡張
  • 神経制御工学特論
    開講年度 : 2019年
    課程区分 : 博士後期課程
    開講学部 : 情報科学院
    キーワード : 中枢神経系,神経シグナル伝達,感覚情報処理とその補償器,脳刺激法,学習・記憶,運動プログラムと制御,神経活動の大規模計測,計算論的神経科学,神経活動の制御技術,脳の機能補償と機能拡張
  • バイオエンジニアリング特論
    開講年度 : 2019年
    課程区分 : 博士後期課程
    開講学部 : 情報科学研究科
    キーワード : 遺伝情報, genetic information, バイオインフォマティクス, bioinformatics, イメージング, imaging, 生体医工学, biomedical engineering, 細胞力学, cell mechanics
  • 生体情報工学演習Ⅱ
    開講年度 : 2019年
    課程区分 : 学士課程
    開講学部 : 工学部
    キーワード : 数値計算法,シミュレーション,統計と検定,データベース,情報検索
  • 生体情報工学実験Ⅱ
    開講年度 : 2019年
    課程区分 : 学士課程
    開講学部 : 工学部
    キーワード : 遺伝情報,生体電気現象,生体機能情報,生体計測,バイオエレクトロニクス
  • データ解析
    開講年度 : 2019年
    課程区分 : 学士課程
    開講学部 : 工学部
    キーワード : 記述統計,統計的推定,統計的検定,t検定,F検定,分散分析(ANOVA),多重比較,ノンパラメトリック手法,多変量解析,重回帰分析,主成分分析(PCA),因子分析,判別分析,クラスター分析,一般化線形モデル(GLM),ベイズ統計,機械学習
  • 一般教育演習(フレッシュマンセミナー)
    開講年度 : 2019年
    課程区分 : 学士課程
    開講学部 : 全学教育
    キーワード : 多点電極計測,カルシウムイメージング,光遺伝学,ブレインマシンインターフェース,代謝,メタボローム,質量分析,超偏極磁気共鳴画像(MRI)


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