Yoichi MIYAWAKI
| Department of Mechanical and Intelligent Systems Engineering | Professor |
| Cluster II (Emerging Multi-interdisciplinary Engineering) | Professor |
| Center for Neuroscience and Biomedical Engineering | Professor |
| Department of Informatics | Professor |
| Cluster I (Informatics and Computer Engineering) | Professor |
Researcher Information
Degree
Research Keyword
Field Of Study
Career
- Sep. 2018
National Institute of Mental Health, National Institutes of Health, Section on Functional Imaging Methods, Laboratory of Brain and Cognition, Special Volunteer - 01 Oct. 2017
Japan Science and Technology Agency, PRESTO Researcher - 01 Mar. 2017
Graduate School of Informatics and Engineering, The University of Electro-Communications, Professor - 01 Mar. 2012 - 28 Feb. 2017
Center for Frontier Science and Engineering, The University of Electro-Communications, Associate Professor - 01 Apr. 2006 - 29 Feb. 2012
NICT/ATR Computation Neuroscience Laboratories, Researcher - 01 Apr. 2005 - 31 Mar. 2006
RIKEN Brain Science Institute, Laboratory for Mathematical Neuroscience, Researcher - 01 Apr. 2004 - 31 Mar. 2005
Japan Science and Technology Agency, PRESTO group member (researcher) - 01 Apr. 2001 - 31 Mar. 2004
RIKEN Brain Science Institute, Laboratory for Advanced Brain Signal Processing, Special Postdoctroal Researcher
Educational Background
Research Activity Information
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Paper
- 触覚刺激時における第一次視覚野の活動と情報表現の解析
野崎 恵; 中谷 駿; 衞藤 祥太; 高橋 陽香; 青木 直哉; 角谷 基文; 北田 亮; 定藤 規弘; 神谷 之康; 宮脇 陽一
Vision, 日本視覚学会, 29, 1, 34-34, Jan. 2017, Peer-reviwed
Japanese - Multivariate Analysis of Magnetic Resonance Imaging Signals of the Human Brain
Yoichi Miyawaki
CURRENT TOPICS IN MEDICINAL CHEMISTRY, BENTHAM SCIENCE PUBL LTD, 16, 24, 2685-2693, 2016, Peer-reviwed, Invited, Magnetic resonance imaging (MRI) of the human brain plays an important role in the field of medical imaging as well as basic neuroscience. It measures proton spin relaxation, the time constant of which depends on tissue type, and allows us to visualize anatomical structures in the brain. It can also measure functional signals that depend on the local ratio of oxyhemoglobin to deoxyhemoglobin in the blood, which is believed to reflect the degree of neural activity in the corresponding area. MRI thus provides anatomical and functional information about the human brain with high spatial resolution. Conventionally, MRI signals are measured and analyzed for each individual voxel. However, these signals are essentially multivariate because they are measured from multiple voxels simultaneously, and the pattern of activity might carry more useful information than each individual voxel does. This paper reviews recent trends in multivariate analysis of MRI signals in the human brain, and discusses applications of this technique in the fields of medical imaging and neuroscience.
Scientific journal, English - Inter-subject neural code converter for visual image representation
Kentaro Yamada; Yoichi Miyawaki; Yukiyasu Kamitani
NEUROIMAGE, ACADEMIC PRESS INC ELSEVIER SCIENCE, 113, 289-297, Jun. 2015, Peer-reviwed, Brain activity patterns differ from person to person, even for an identical stimulus. In functional brain mapping studies, it is important to align brain activity patterns between subjects for group statistical analyses. While anatomical templates are widely used for inter-subject alignment in functional magnetic resonance imaging (fMRI) studies, they are not sufficient to identify the mapping between voxel-level functional responses representing specific mental contents. Recent work has suggested that statistical learning methods could be used to transform individual brain activity patterns into a common space while preserving representational contents. Here, we propose a flexible method for functional alignment, "neural code converter," which converts one subject's brain activity pattern into another's representing the same content. The neural code converter was designed to learn statistical relationships between fMRI activity patterns of paired subjects obtained while they sawan identical series of stimuli. It predicts the signal intensity of individual voxels of one subject from a pattern of multiple voxels of the other subject. To test this method, we used fMRI activity patterns measured while subjects observed visual images consisting of random and structured patches. We show that fMRI activity patterns for visual images not used for training the converter could be predicted from those of another subject where brain activity was recorded for the same stimuli. This confirms that visual images can be accurately reconstructed from the predicted activity patterns alone. Furthermore, we show that a classifier trained only on predicted fMRI activity patterns could accurately classify measured fMRI activity patterns. These results demonstrate that the neural code converter can translate neural codes between subjects while preserving contents related to visual images. While this method is useful for functional alignment and decoding, it may also provide a basis for brain-to-brain communication using the converted pattern for designing brain stimulation. (C) 2015 Elsevier Inc. All rights reserved.
Scientific journal, English - 機能的磁気共鳴画像法を用いた神経コードの解読
宮脇陽一
システム/制御/情報, 59, 9, 353-359, 2015, Peer-reviwed
Scientific journal, Japanese - Relationship between timing of object category representation and the level of category abstraction in the human visual cortex
Masashi Sato; Yoichi Miyawaki
I-PERCEPTION, PION LTD, 5, 4, 295-295, 2014, Peer-reviwed
International conference proceedings, English - 脳活動から心を可視化する
堀川友慈; 宮脇陽一; 神谷之康
光学, 43, 3, 104-110, 2014
Scientific journal, Japanese - Neural Decoding of Visual Imagery During Sleep
T. Horikawa; M. Tamaki; Y. Miyawaki; Y. Kamitani
SCIENCE, AMER ASSOC ADVANCEMENT SCIENCE, 340, 6132, 639-642, May 2013, Peer-reviwed, Visual imagery during sleep has long been a topic of persistent speculation, but its private nature has hampered objective analysis. Here we present a neural decoding approach in which machine-learning models predict the contents of visual imagery during the sleep-onset period, given measured brain activity, by discovering links between human functional magnetic resonance imaging patterns and verbal reports with the assistance of lexical and image databases. Decoding models trained on stimulus-induced brain activity in visual cortical areas showed accurate classification, detection, and identification of contents. Our findings demonstrate that specific visual experience during sleep is represented by brain activity patterns shared by stimulus perception, providing a means to uncover subjective contents of dreaming using objective neural measurement.
Scientific journal, English - Modular Encoding and Decoding Models Derived from Bayesian Canonical Correlation Analysis
Yusuke Fujiwara; Yoichi Miyawaki; Yukiyasu Kamitani
NEURAL COMPUTATION, MIT PRESS, 25, 4, 979-1005, Apr. 2013, Peer-reviwed, Neural encoding and decoding provide perspectives for understanding neural representations of sensory inputs. Recent functional magnetic resonance imaging (fMRI) studies have succeeded in building prediction models for encoding and decoding numerous stimuli by representing a complex stimulus as a combination of simple elements. While arbitrary visual images were reconstructed using a modular model that combined the outputs of decoder modules for multiscale local image bases (elements), the shapes of the image bases were heuristically determined. In this work, we propose a method to establish mappings between the stimulus and the brain by automatically extracting modules from measured data. We develop a model based on Bayesian canonical correlation analysis, in which each module is modeled by a latent variable that relates a set of pixels in a visual image to a set of voxels in an fMRI activity pattern. The estimated mapping from a latent variable to pixels can be regarded as an image basis. We show that the model estimates a modular representation with spatially localized multiscale image bases. Further, using the estimated mappings, we derive encoding and decoding models that produce accurate predictions for brain activity and stimulus images. Our approach thus provides a novel means of revealing neural representations of stimuli by automatically extracting modules, which can be used to generate effective prediction models for encoding and decoding.
Scientific journal, English - Spike suppression in a local cortical circuit induced by transcranial magnetic stimulation
Yoichi Miyawaki; Takashi Shinozaki; Masato Okada
JOURNAL OF COMPUTATIONAL NEUROSCIENCE, SPRINGER, 33, 2, 405-419, Oct. 2012, Peer-reviwed, Transcranial magnetic stimulation (TMS) noninvasively interferes with human cortical function, and is widely used as an effective technique for probing causal links between neural activity and cognitive function. However, the physiological mechanisms underlying TMS-induced effects on neural activity remain unclear. We examined the mechanism by which TMS disrupts neural activity in a local circuit in early visual cortex using a computational model consisting of conductance-based spiking neurons with excitatory and inhibitory synaptic connections. We found that single-pulse TMS suppressed spiking activity in a local circuit model, disrupting the population response. Spike suppression was observed when TMS was applied to the local circuit within a limited time window after the local circuit received sensory afferent input, as observed in experiments investigating suppression of visual perception with TMS targeting early visual cortex. Quantitative analyses revealed that the magnitude of suppression was significantly larger for synaptically-connected neurons than for isolated individual neurons, suggesting that intracortical inhibitory synaptic coupling also plays an important role in TMS-induced suppression. A conventional local circuit model of early visual cortex explained only the early period of visual suppression observed in experiments. However, models either involving strong recurrent excitatory synaptic connections or sustained excitatory input were able to reproduce the late period of visual suppression. These results suggest that TMS targeting early visual cortex disrupts functionally distinct neural signals, possibly corresponding to feedforward and recurrent information processing, by imposing inhibitory effects through intracortical inhibitory synaptic connections.
Scientific journal, English - 脳情報デコーディング技術とその応用
宮脇陽一; 神谷之康
計測と制御, 50, 10, 888-894, 2011
Scientific journal, Japanese - Influence of Coherence Between Multiple Cortical Columns on Alpha Rhythm: A Computational Modeling Study
Yasushi Naruse; Ayumu Matani; Yoichi Miyawaki; Masato Okada
HUMAN BRAIN MAPPING, WILEY, 31, 5, 703-715, May 2010, Peer-reviwed, In electroencephalographic (EEG) and magnetoencephalographic (MEG) signals, stimulus-induced amplitude increase and decrease in the alpha rhythm, known as event-related synchronization and desynchronization (ERS/ERD), emerge after a task onset. ERS/ERD is assumed to reflect neural processes relevant to cognitive tasks. Previous studies suggest that several sources of alpha rhythm, each of which can serve as an alpha rhythm generator, exist in the cortex. Since EEG/MEG signals represent spatially summed neural activities, ERS/ERD of the alpha rhythm may reflect the consequence of the interactions between multiple alpha rhythm generators. Two candidates modulate the magnitude of ERS/ERD: (1) coherence between the activities of the alpha rhythm generators and (2) mean amplitude of the activities of the alpha rhythm generators. M this study, we use a computational model of multiple alpha rhythm generators to determine the factor that dominantly causes ERS/ERD. Each alpha rhythm generator is modeled based on local column circuits in the primary visual cortex and made to interact with the neighboring generators through excitatory connections. We observe that the model consistently reproduces spontaneous alpha rhythms, event-related potentials, phase-locked alpha rhythms, and ERS/ERD in a specific range of connectivity coefficients. Independent analyses of the coherence and amplitude of multiple alpha rhythm generators reveal that the ERS/ERD in the simulated data is dominantly caused by stimulus-induced changes in the coherence between multiple alpha rhythm generators. Nonlinear phenomena such as phase-resetting and entrainment of the alpha rhythm are related to the neural mechanism underlying ERS/ERD. Hum Brain Mapp 31:703-715, 2010. (C) 2009 Wiley-Liss, Inc.
Scientific journal, English - Estimating image bases for visual image reconstruction from human brain activity
Yusuke Fujiwara; Yoichi Miyawaki; Yukiyasu Kamitani
Advances in Neural Information Processing Systems, 22, 576-584, 2010, Peer-reviwed
Scientific journal, English - Visual image reconstruction from human brain activity: A modular decoding approach
Yoichi Miyawaki; Hajime Uchida; Okito Yamashita; Masa-aki Sato; Yusuke Morito; Hiroki C. Tanabe; Norihiro Sadato; Yukiyasu Kamitani
INTERNATIONAL WORKSHOP ON STATISTICAL-MECHANICAL INFORMATICS 2009 (IW-SMI 2009), IOP PUBLISHING LTD, 197, 2009, Peer-reviwed, Brain activity represents our perceptual experience. But the potential for reading out perceptual contents from human brain activity has not been fully explored. In this study, we demonstrate constraint-free reconstruction of visual images perceived by a subject, from the brain activity pattern. We reconstructed visual images by combining local image bases with multiple scales, whose contrasts were independently decoded from fMRI activity by automatically selecting relevant voxels and exploiting their correlated patterns. Binary-contrast, 10 x 10-patch images (2(100) possible states), were accurately reconstructed without any image prior by measuring brain activity only for several hundred random images. The results suggest that our approach provides an effective means to read out complex perceptual states from brain activity while discovering information representation in multi-voxel patterns.
International conference proceedings, English - Automatic extraction of visual image bases from fMRI response patterns
Yusuke Fujiwara; Yoichi Miyawaki; Yukiyasu Kamitani
NEUROSCIENCE RESEARCH, ELSEVIER IRELAND LTD, 65, S108-S108, 2009, Peer-reviwed
English - Visual Image Reconstruction from Human Brain Activity using a Combination of Multiscale Local Image Decoders
Yoichi Miyawaki; Hajime Uchida; Okito Yamashita; Masa-aki Sato; Yusuke Morito; Hiroki C. Tanabe; Norihiro Sadato; Yukiyasu Kamitani
NEURON, CELL PRESS, 60, 5, 915-929, Dec. 2008, Peer-reviwed, Perceptual experience consists of an enormous number of possible states. Previous fMRI studies have predicted a perceptual state by classifying brain activity into prespecified categories. Constraint-free visual image reconstruction is more challenging, as it is impractical to specify brain activity for all possible images. In this study, we reconstructed visual images by combining local image bases of multiple scales, whose contrasts were independently decoded from fMRI activity by automatically selecting relevant voxels and exploiting their correlated patterns. Binary-contrast, 10 x 10-patch images (2100 possible states) were accurately reconstructed without any image prior on a single trial or volume basis by measuring brain activity only for several hundred random images. Reconstruction was also used to identify the presented image among millions of candidates.,The results suggest that our approach provides an effective means to read out complex perceptual states from brain activity while discovering information representation in multivoxel patterns.
Scientific journal, English - Rate reduction for associative memory model in Hodgkin-Huxley-type network
Masafumi Oizumi; Yoichi Miyawaki; Masato Okada
JOURNAL OF THE PHYSICAL SOCIETY OF JAPAN, PHYSICAL SOC JAPAN, 77, 6, 064802:1-6, Jun. 2008, Peer-reviwed, We proposed a systematic method for reducing Hodgkin-Huxley-type networks to networks of rate equations on the basis of Shriki et al.'s formulation. Our rate model predicts the results of numerical simulations of the Hodgkin-Huxley-type network model very precisely over a broad range of synaptic conductances. However, in the proposed framework, we ad hoc assumed that the firing threshold and the gain of the f-I curve of the Hodgkin-Huxley-type conductance-based model have a second-order dependence on leak conductance. Here, we discuss optimal model selection with respect to the dependence of the threshold and the gain on the f-I curve, using the Akaike information criterion. We then apply our rate reduction method to an associative memory model of Hodgkin-Huxley neurons. Most associative memory models have been studied using two-state neurons or graded-response neurons. We check the correspondence between an associative memory model of Hodgkin-Huxley neurons and that of graded-response neurons, particularly in terms of phase diagrams. We store correlated patterns in the network and investigate the phase transition between the memory state and the mixed state. We demonstrate that our rate model, which is obtained by the reduction method, explains the phase diagram of the Hodgkin-Huxley-type network very well.
Scientific journal, English - Decoding heading directions from human brain activity(Summary of Awarded Presentation at the 26th Annual Meeting)
SHIGEMASU Hiroaki; MIYAWAKI Yoichi; KAMITANI Yukiyasu; KITAZAKI Michiteru
The Japanese Journal of Psychonomic Science, The Japanese Psychonomic Society, 27, 1, 121-122, 2008, We investigated whether fMRI-derived cortical activity patterns induced by optic flow can predict the direction of heading. The cortical activity from hMT+, which is related to motion perception, led to good predictions. Focusing on the good performance of heading perception with eye movement, we also measured the cortical activity from an optic flow with eye movement. The decoder was trained with the activity patterns without eye movement and tested on those with actual eye movements, and vice versa. hMT+ exhibited a less robust, though still relatively the best, decoding performance. These results suggest that hMT+ is involved in heading perception and coding head-centric motion along with compensating for extra-retinal information. More generally, our study shows that decoding techniques can be used as effective tools in identifying the functions associated with cortical activity.
English - fMRIによる自己運動方向知覚の復号化(日本基礎心理学会第26回大会,大会発表要旨)
繁桝 博昭; 宮脇 陽一; 神谷 之康; 北崎 充晃
基礎心理学研究, 日本基礎心理学会, 26, 2, 220-220, 2008
Japanese - Higher order effects on rate reduction for networks of Hodgkin-Huxley neurons
Masafumi Oizumi; Yoichi Miyawaki; Masato Okada
JOURNAL OF THE PHYSICAL SOCIETY OF JAPAN, PHYSICAL SOC JAPAN, 76, 4, 044803:1-6, Apr. 2007, Peer-reviwed, We propose a systematic method of rate reduction for a Hodgkin-Huxley type neural network model. In this context, Shriki et al. assumed that the threshold of the f-I curve for the reduced rate model depends linearly on the leak conductance of the Hodgkin-Huxley equation, while its gain remains constant. First, we show that the threshold and gain have second order dependence on the leak conductance. Second, we show that the Hodgkin-Huxley type network with second order interaction can be naturally reduced to an analog type neural network model with higher order interaction based on this finding. Finally, we construct statistical mechanics for the Hodgkin-Huxley type network with the Mexican-hat interaction through our rate reduction technique.
Scientific journal, English - 経頭蓋磁気刺激による視知覚抑制の神経メカニズム
宮脇陽一
日本神経回路学会誌, 14, 1, 44-57, 2007
Scientific journal, Japanese - 川人光男 ASCONE 2006 特別講義: 小脳の学習理論，LTD のシステムバイオロジーモデル，そして操作脳科学へ
田中宏和; 宮脇陽一
日本神経回路学会誌, 14, 2, 104-140, 2007
Scientific journal, Japanese - Mechanisms of spike inhibition in a cortical network induced by transcranial magnetic stimulation
Y Miyawaki; M Okada
NEUROCOMPUTING, ELSEVIER SCIENCE BV, 65, 463-468, Jun. 2005, Peer-reviwed, We propose mechanisms of neural interference induced by transcranial magnetic stimulation (TMS). TMS is widely used as a powerful and unique experimental tool to stimulate the human brain noninvasively, which typically induces inhibitory effect on the cortical functions. However, the fundamental mechanism of TMS-induced suppression is still unclear. In this paper, we computationally demonstrate that TMS induces sustained spike inhibition in a conductance-based network model without the ion channel which is necessary for spike inhibition in an isolated single neuron, suggesting that each individual neuron is not necessarily suppressed by TMS; rather, a collapse of excitatory and inhibitory input balance in the cortical network is crucial for TMS-induced suppression. (c) 2004 Elsevier B.V. All rights reserved.
Scientific journal, English - A network model of perceptual suppression induced by transcranial magnetic stimulation
Y Miyawaki; M Okada
NEURAL COMPUTATION, M I T PRESS, 16, 2, 309-331, Feb. 2004, Peer-reviwed, We modeled the inhibitory effects of transcranial magnetic stimulation (TMS) on a neural population. TMS is a noninvasive technique, with high temporal resolution, that can stimulate the brain via a brief magnetic pulse from a coil placed on the scalp. Because of these advantages, TMS is extensively used as a powerful tool in experimental studies of motor, perception, and other functions in humans. However, the mechanisms by which TMS interferes with neural activities, especially in terms of theoretical aspects, are totally unknown. In this study, we focused on the temporal properties of TMS-induced perceptual suppression, and we computationally analyzed the response of a simple network model of a sensory feature detector system to a TMS-like perturbation. The perturbation caused the mean activity to transiently increase and then decrease for a long period, accompanied by a loss in the degree of activity localization. When the afferent input consisted of a dual phase, with a strong transient component and a weak sustained component, there was a critical latency period of the perturbation during which the network activity was completely suppressed and converged to the resting state. The range of the suppressive period increased with decreasing afferent input intensity and reached more than 10 times the time constant of the neuron. These results agree well with typical experimental data for occipital TMS and support the conclusion that dynamical interaction in a neural population plays an important role in TMS-induced perceptual suppression.
Scientific journal, English - Mechanism of neural interference by transcranial magnetic stimulation: network or single neuron?
Y Miyawaki; M Okada
ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 16, M I T PRESS, 16, 1295-1302, 2004, Peer-reviwed, This paper proposes neural mechanisms of transcranial magnetic stimulation (TMS). TMS can stimulate the brain non-invasively through a brief magnetic pulse delivered by a coil placed on the scalp, interfering with specific cortical functions with a high temporal resolution. Due to these advantages, TMS has been a popular experimental tool in various neuroscience fields. However, the neural mechanisms underlying TMS-induced interference are still unknown; a theoretical basis for TMS has not been developed. This paper provides computational evidence that inhibitory interactions in a neural population, not an isolated single neuron, play a critical role in yielding the neural interference induced by TMS.
International conference proceedings, English - Unconscious adaptation: a new illusion of depth induced by stimulus features without depth
R Hayashi; Y Miyawaki; T Maeda; S Tachi
VISION RESEARCH, PERGAMON-ELSEVIER SCIENCE LTD, 43, 26, 2773-2782, Dec. 2003, Peer-reviwed, Here, we show a new illusion of depth induced by psychophysical adaptation to dynamic random-dot stereograms (RDS) that are interocularly anticorrelated (i.e., in which the images for the two eyes have reversed contrast polarity with each other). After prolonged viewing of anticorrelated RDS, the presentation of uncorrelated RDS (i.e., in which two images are mutually independent random-dot patterns) produces the sensation of depth, although both anticorrelated and uncorrelated RDSs are perceptually rivalrous with no consistent depth by themselves. Contrary to other aftereffects demonstrated in a number of visual dimensions, including motion, orientation, and disparity, this illusion results from unconscious adaptation; observers are not aware of what they are being adapted to during the process of adaptation. We further demonstrate that this illusion can be predicted from the simulated responses of disparity-selective neurons based on a local filtering model. Model simulations indicate that the inspection of anticorrelated RDS causes the adaptation of all disparity detectors except one sensitive to its disparity; therefore, those selectively unadapted detectors show relatively strong activation in response to the Subsequent presentation of uncorrelated RDS and produce depth perception. (C) 2003 Elsevier Ltd. All rights reserved.
Scientific journal, English - A network model of inhibitory effects induced by transcranial magnetic stimulation
Y Miyawaki; M Okada
NEUROCOMPUTING, ELSEVIER SCIENCE BV, 52-4, 837-842, Jun. 2003, Peer-reviwed, We have studied the inhibitory effects of transcranial magnetic stimulation (TMS) on a neural population. Because TMS can affect the electromagnetic activities inside our brain with high temporal resolution and noninvasively, it is widely used as a powerful tool both in the field of cognitive neuroscience and for clinical treatment. However, the neural mechanisms underlying these effects remain unclear, especially from a theoretical perspective. In our study, we employed a simple neural population model and computationally analyzed the responses to a TMS-like perturbation. When the perturbation was applied, the mean activity of the network transiently increased, and then decreased for a relatively long period followed by the loss of a localized activity pattern. When the afferent input had a strong transient component and a weak sustained component, there was a critical latency period during which the perturbation completely suppressed the network activity. These results suggest that the inhibitory effects typically observed in TMS studies can be yielded through dynamical interaction in a neural population. (C) 2002 Elsevier Science B.V. All rights reserved.
Scientific journal, English - Probing the neural mechanism of binocular information processing with VEPs
Ryusuke Hayashi; Yoichi Miyawaki; Taro Maeda; Susumu Tachi
Electronics and Communications in Japan, Part II: Electronics (English translation of Denshi Tsushin Gakkai Ronbunshi), 86, 3, 47-60, Mar. 2003, The visual evoked potential (VEP) for random-dot stereogram (RDS) presentation was examined. It was found that the peak latency is greatly affected by the stimulus presentation position, the disparity, and the correlation between the images of the two eyes. Based on simulation of the response of the disparity-selective neuron in the binocular energy model, a mechanism was established in which the position is detected as the interocularly unpaired region, based on the activities of various disparity-selective neurons for each position on the retina.
Scientific journal - Computational model of transcranial magnetic stimulation: Temporal property and subthreshold prolongation of visual suppression induced by neural population
Yoichi Miyawaki; Masato Okada
Journal of Vision, 3, 9, 749, 2003, Peer-reviwed, We modeled suppressive effect on visual perception induced by TMS. TMS is widely used in experimental studies about visual perception, however neural mechanisms underlying TMS interference are still unclear, especially in theoretical perspective. Here we used the simplest excitatory-inhibitory balanced network showing orientation selectivity in V1 as a model of neural population and analyzed the response to a TMS-like perturbation, simulating the fundamental property that TMS briefly and simultaneously stimulates neural population in local cortical area under the coil. Applying the perturbation, mean activity of the network transiently increased and then decreased for a longer period followed by a loss of an orientation tuning profile. If afferent input had a large transient and weak sustained component, there was a critical latency period during which the perturbation could completely suppress the network activity. The range of the suppressive latency period increased with decrease of afferent intensity and reached over 100ms if the afferent intensity approached excitation threshold of the network. These results well agree with typical experimental data of visual suppression by occipital TMS. In occipital TMS experiments, applying multiple pulses can facilitate phosphene or suppression even if each single pulse cannot induce any perceptible effects. Such subthreshold accumulation was also observed in the network model in comparable time range to experimental data, but not in isolated single neuron model. In the network model, a subthreshold conditioning stimulus could induce sustained inhibitory bias so that the following suppressive threshold was decreased and the range of suppressive latency period was prolonged, which are also parallel to experimental data of occipital paired TMS. These results suggest that, in addition to effect on a single neuron, inhibitory interaction in neural population plays an important role in TMS-induced visual suppression.
Scientific journal, English - 立体視過程の時間推移-遅延性誘発電位と図地分離過程-
宮脇陽一; 林隆介; 前田太郎; 舘暲
電子情報通信学会論文誌, J85-D-II, 2, 337-350, 2002, Peer-reviwed
Scientific journal, Japanese - 視覚誘発電位計測に基づく両眼視覚情報処理過程の解析
林隆介; 宮脇陽一; 前田太郎; 舘暲
電子情報通信学会論文誌, J84-D-II, 3, 559-570, 2001, Peer-reviwed
Scientific journal, Japanese - 奥行き知覚時の視覚誘発電位における２峰性波の性質
宮脇陽一; 柳田康幸; 前田太郎; 舘暲
電子情報通信学会論文誌, J82-D-II, 5, 961-972, 1999, Peer-reviwed
Scientific journal, Japanese
MISC
- 触覚刺激弁別課題時における複数脳領域における活動と情報表現の相互作用
佐藤海渡; 野崎恵; 中谷駿; 高橋陽香; 角谷基文; 北田亮; 定藤規弘; 定藤規弘; 神谷之康; 神谷之康; 宮脇陽一
2022, 日本神経化学会大会抄録集(Web), 65th, 202302279388204112 - 触覚刺激時におけるヒト視覚野の活動と触覚情報表現
中谷駿; 高橋陽香; 高橋陽香; 青木直哉; 青木直哉; 北田亮; 北田亮; 定藤規弘; 定藤規弘; 神谷之康; 神谷之康; 宮脇陽一
02 Sep. 2015, 日本神経回路学会全国大会講演論文集, 25th, 6-7, Japanese, 201502206094907257 - Temporal relationship between object category representation and the level of category abstraction in the human visual cortex
SATO Masashi; MIYAWAKI Yoichi
Object categories can be hierarchically ordered from abstract to concrete levels. Previous studies showed that the corresponding hierarchy can be found in spatial patterns of human brain activity. However, it remains unclear when each object category is represented in human brain activity patterns and whether it is also ordered in a hierarchical manner in the time domain according to the level of category abstraction. In this study, we measured human brain activity patterns in high temporal resolution using magnetoencephalography while subjects observed object images selected from multiple categories. We estimated cortical current distributions and then applied multivariate pattern analyses to estimate the timings at which each object category is represented in brain activity patterns. Our present results showed no significant difference in latency of object category representation along the level of category abstraction, suggesting possibility that object category information is represented at similar latency in the human brain irrespective of their levels of abstraction., The Institute of Electronics, Information and Communication Engineers, 17 Mar. 2014, IEICE technical report. Neurocomputing, 113, 500, 227-232, Japanese, 0913-5685, 110009862364, AN10091178 - Visual image reconstruction from human brain activity
MIYAWAKI Yoichi; UCHIDA Hajime; YAMASHITA Okito; SATO Masa-aki; MORITO Yusuke; TANABE Hiroki; SADATO Norihiro; KAMITANI Yukiyasu
Recent functional magnetic resonance imaging (fMRI) studies have shown that visual stimuli that a subject observes can be predicted from fMRI activity patterns using machine learning techniques. However, previous approach has focused on classifying brain activity into pre-specified categories, thereby predicting only simple visual features such as orientation and motion direction, and cannot reconstruct a visual image as it is. Constraint-free visual image reconstruction is more challenging than classification, as it is impractical to specify brain activity for all possible images. Here we reconstructed visual images that subjects observe by combining local image bases of multiple scales, whose contrasts were independently predicted from fMRI activity by automatically selecting relevant voxels and exploiting their correlated patterns. The results suggest that our approach provides an effective means to read out complex perceptual states from brain activity while discovering information representation in multivoxel patterns. We also discuss about future applications of our method to prediction of arbitrary finger/limb movements from human brain activity., The Institute of Electronics, Information and Communication Engineers, 08 Jun. 2009, IEICE technical report, 109, 83, 51-56, Japanese, 0913-5685, 110007360627, AN10487237 - 脳デコーディング技術を用いた物体間,物体内奥行き知覚の処理過程の検討
繁桝博昭; 宮脇陽一; 神谷之康; 北崎充晃
日本基礎心理学会, 31 Mar. 2009, 基礎心理学研究, 27, 2, 182-183, Japanese, 0287-7651, 200902227859703913, 110007228135 - Reconstruction of visual images by combining multi-resolution local image decoders
UCHIDA Hajime; MIYAWAKI Yoichi; YAMASHITA Okito; SATO Masa-aki; TANABE Hiroki C; SADATO Norihiro; KAMITANI Yukiyasu
Recent studies have shown that human brain activity measured by functional magnetic resonance imaging (fMRI) can be decoded to predict visual perceptual parameters such as orientation and motion direction. In this study, we present methods to reconstruct arbitrary visual images from fMRI signals. The image decoder was constructed by combining local image decoders that were trained to predict the mean contrast of local image segments of multiple scales from fMRI activity patterns. We examined three methods for combining local image decoders 1) pixel representation, 2) multi-scale representation, 3) bayes estimation based on generative model for fMRI signals. These methods showed high reconstruction accuracy for arbitrary visual images. Our approach for reconstructing visual images provides a unique tool to study detailed representaion and processing in the visual cortex., The Institute of Electronics, Information and Communication Engineers, 07 Mar. 2007, IEICE technical report. Neurocomputing, 106, 588, 79-84, Japanese, 0913-5685, 110006249030, AN10091178 - 21aWB-7 Rate Reduction for Network of Hodgkin-Huxley Neurons with Auto-correlation Type Interaction
Oizumi Masafumi; Miyawaki Yoichi; Okada Masato
The Physical Society of Japan (JPS), 28 Feb. 2007, Meeting abstracts of the Physical Society of Japan, 62, 1, 299-299, Japanese, 1342-8349, 110007191246, AA11439205 - Rate reduction for a Hodgkin-Huxley type network model with a Hebbian connection
OIZUMI Masafumi; MIYAWAKI Yoichi; OKADA Masato
We proposed a systematic reduction method from a Hodgkin-Huxley type network model to a rate network model according to Shriki et al.'s formulation [1] [2]. However, in the proposed framework, we ad hoc assumed that the threshold and gain of the f-I curve of the Hodgkin-Huxley type conductance-based model have second order dependence on the leak conductance. Here we discuss an optimal model selection with respect to the dependence of the threshold and gain on the f-I curve by making use of Akaike information criterion. We then apply our rate reduction method to the Hodgkin-Huxley type network with a Hebbian connection. We store three correlated patterns in this network and investigate the phase transition between memory state and mixed state. We show that our rate model reproduce the results of the Hodgkin-Huxley type network very well., The Institute of Electronics, Information and Communication Engineers, 18 Jan. 2007, IEICE technical report, 106, 500, 37-42, Japanese, 0913-5685, 110006204904, AN10091178 - Reconstruction of visual images from fMRI signals by combination of multi-resolution local image decoders
Yoichi Miyawaki; Hajime Uchida; Okito Yamashita; Masa-aki Sato; Hiroki C. Tanabe; Norihiro Sadato; Yukiyasu Kamitani
ELSEVIER IRELAND LTD, 2007, NEUROSCIENCE RESEARCH, 58, S55-S55, English, Summary international conference, 0168-0102, WOS:000249272800321 - Multiple generators model based on neural mass model for MEG/EEG
Yasushi Naruse; Ayumu Matani; Yoichi Miyawaki; Masato Okada
ELSEVIER IRELAND LTD, 2007, NEUROSCIENCE RESEARCH, 58, S215-S215, English, Summary international conference, 0168-0102, WOS:000249272801278 - 26pXD-1 Higher Order Effects on Rate Reduction for Network of Hodgkin-Huxley Neurons
Oizumi Masafumi; Miyawaki Yiochi; Okada Masato
The Physical Society of Japan (JPS), 18 Aug. 2006, Meeting abstracts of the Physical Society of Japan, 61, 2, 244-244, Japanese, 1342-8349, 110007183205, AA11439205 - Higher Order Effects on Rate Reduction for Network of Hodgkin-Huxley Neurons
OIZUMI Masafumi; MIYAWAKI Yoichi; OKADA Masato
We propose a systematic method of rate reduction for a Hodgkin-Huxley type neural network model. In this context, Shriki et al. assumed that the threshold of f-I cureve for the reduced rate model linearly depends on the leak conductance of the Hodgkin-Huxley equation, while its gain remains constant. First, we will show that they have second order dependence. Second, we show that we can naturally reduce the Hodgkin-Huxley type network with second order interaction to an analog type neural network model with higher order interaction based on this finding. Finally, we construct statistical mechanics for the Hodgkin-Huxley type network with the Mexican-hat type interaction through our rate reduction technique., The Institute of Electronics, Information and Communication Engineers, 07 Jul. 2006, IEICE technical report, 106, 163, 13-18, Japanese, 0913-5685, 110004809700, AN10091178 - 29pXH-10 Macroscopic Equations for Network of Hodgkin-Huxley Neurons
Oizumi Masafumi; Miyawaki Yoichi; Okada Masato
The Physical Society of Japan (JPS), 04 Mar. 2006, Meeting abstracts of the Physical Society of Japan, 61, 1, 308-308, Japanese, 1342-8349, 110007181352, AA11439205 - 13pTC-3 Relaxation dynamics of HH system and solvable analog neural network
MIYAWAKI Y; OKADA M
The Physical Society of Japan (JPS), 25 Aug. 2004, Meeting abstracts of the Physical Society of Japan, 59, 2, 220-220, Japanese, 1342-8349, 110002051979, AA11439205 - Neural mechanism of transcranial magnetic stimulation : spike inhibition in a recurrent cortical network
MIYAWAKI Yoishi; OKADA Masato
We propose mechanisms of neural interference induced by transcranial magnetic stimulation (TMS). TMS is widely used as a powerful and unique experimental tool to stimulate the human brain noinvasively, which typically induces inhibitory effect on the cortical functions. However, the fundamental neural mechanism of TMS-induced suppression is still unclear, even though twenty years have passed science the first TMS technique has developped. In this paper, we assume TMS as an brief perturbation that is uniformly applied onto a neural population, and computationally analyze the mechanism of TMS-induced suppression. Here, in particular, we employed a conductance-based recurrent network model exhibiting feature selectivity in the cortex. We demonstrate that the TMS-like perturbation induces sustained spike inhibition in the network without the ion channel which is necessary for spike inhibition in an isolated single neuron, suggesting that each individual neuron is not necessarily suppressed by TMS; rather, a collapse of excitatory and inhibitory input balance in the cortical network is crucial for TMS-induced suppression., The Institute of Electronics, Information and Communication Engineers, 21 May 2004, IEICE technical report. Neurocomputing, 104, 99, 55-60, English, 0913-5685, 110003234041, AN10091178 - A network model of perceptual suppression induced by transcranial magnetic stimulation
MIYAWAKI Yoichi; OKADA Masato
We studied inhibitory effects of transcranial magnetic stimulation (TMS) on neural population. TMS can affect the electromagnetic activities inside our brain with high temporal resolution and without any invasions. Due to these advantages, TMS is widely used as a powerful tool not only in cognitive neuroscience field but also as a clinical treatment. However, the neural mechanisms underlying the effect, especially in theoretical aspect, are quite unclear. In this study, we employed a simple neural population model and computationally analyzed their responses to a TMS-like brief pulsed perturbation. Applying the perturbation, the averaged network activity transiently increased, and then decreased for relatively long lasting period followed by loss of a localized activity pattern. When afferent input has a strong transient component and weak sustained component, there exists a critical latency period in which the perturbation completely suppresses the network activity. These results suggest that inhibitory effects typically observed in TMS studies can be yielded by dynamical interaction in neural population., The Institute of Electronics, Information and Communication Engineers, 11 Mar. 2002, IEICE technical report. Neurocomputing, 101, 735, 197-204, English, 0913-5685, 110003234269, AN10091178 - The illusion of depth induced by adaptation to anticorrelated RDS.
R Hayashi; Y Miyawaki; T Maeda; S Tachi
ASSOC RESEARCH VISION OPHTHALMOLOGY INC, Mar. 2001, INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 42, 4, S503-S503, English, Summary international conference, 0146-0404, WOS:000168392102685 - The VEP component related to figure-ground processes in the time course of stereopsis.
Y Miyawaki; R Hayashi; T Maeda; S Tachi
ASSOC RESEARCH VISION OPHTHALMOLOGY INC, Mar. 2001, INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 42, 4, S404-S404, English, Summary international conference, 0146-0404, WOS:000168392102147 - The late negative figure - ground VEP modulated by focal attention
Y. Miyawaki; R. Hayashi; T. Maeda; S. Tachi
PION LTD, 2001, PERCEPTION, 30, 44-45, English, Summary international conference, 0301-0066, WOS:000207113100138 - Probing the time course of disparity processing with visual evoked potentials.
R Hayashi; Y Miyawaki; T Maeda; S Tachi
ASSOC RESEARCH VISION OPHTHALMOLOGY INC, Mar. 2000, INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 41, 4, S735-S735, English, Summary international conference, 0146-0404, WOS:000086246703981 - Study of Visual Evoked Potencials with Depth Perception
MIYAWAKI Yoichi; MAEDA Taro; TACHI Susumu
04 Sep. 1997, 生体・生理工学シンポジウム論文集, 12, 301-304, Japanese, 10016712161, AN10442953
Books and other publications
Courses
- Fundamental of Mechanical and Intelligent Systems Engineering
The University of Electro-Communications - Fundamentals of Measurement Engineering
The University of Electro-Communications - Human-Machine System
The University of Electro-Communications - 人間機械システム
電気通信大学 - Complex Analysis
The University of Electro-Communications - 複素関数論
電気通信大学 - 工学解析および演習
The University of Electro-Communications - 機械知能システム学専攻基礎
The University of Electro-Communications - 機械知能システム学専攻基礎
電気通信大学 - 計測工学基礎
The University of Electro-Communications - 工学解析および演習
The University of Electro-Communications - 工学解析および演習
電気通信大学 - 大学院総合コミュニケーション科学
The University of Electro-Communications - 大学院総合コミュニケーション科学
電気通信大学 - 知能機械工学専攻基礎
The University of Electro-Communications - 知能機械工学専攻基礎
電気通信大学 - 計測工学基礎
The University of Electro-Communications - 計測工学基礎
電気通信大学
Research Themes
- Exploration of latent spatio-temporal resolution of human brain activity analysis using fusion technology of ultra-high field magnetic resonance imaging and magnetoencephalography
宮脇 陽一; 福永 雅喜; 山下 宙人
Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research, The University of Electro-Communications, Grant-in-Aid for Scientific Research (A), 20H00600
01 Apr. 2020 - 31 Mar. 2024 - 自然光景下における視線移動と視覚的物体認識ダイナミクスの統合的研究
宮脇陽一
Principal investigator
01 Apr. 2017 - 31 Mar. 2021 - Study on high spatiotemporal resolution measurement and analysis of human brain activity using ultra-high field functional magnetic resonance imaging
宮脇 陽一
Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research, The University of Electro-Communications, Fund for the Promotion of Joint International Research (Fostering Joint International Research (A)), 本年度は，課題１である超高磁場fMRIを用いた高S/N比かつ高速な脳活動信号計測の実施を行いつつ，課題２である高速計測fMRI信号の高時間分解能解析に取り組んだ．本研究課題の推進にあたり２０１９年４月１日からの米国立衛生研究所（National Institutes of Health, NIH）滞在下での研究を予定していたが，実際にはそれに先んじて２０１８年９月初旬からNIHでの滞在を開始した．実験開始までの期間において必要な研修等が多くあったため，それらを先行滞在期間中に実施できたことにより，本研究期間を有効に使って研究を進めることができた． 課題１では，従来使用してきたサンプリングレートの約１６倍程度の高速撮像を実現するための計測パラメータの調整および予備データの取得を経て，高品質での脳活動画像データを取得する手法を確立することができた．当初はmulti-echo法を用いることも想定していたが，こうした手法を用いずとも目標が部分的に達成できたため，この手順は今年度においては採用しなかった． こうして確立した実験系を活用し，課題２を進めた．課題２の目的を達成するため，本年度は視覚刺激提示後の脳活動の時間変化を解析した．特に，機械学習の方法を応用することで刺激提示後のどのタイミングからfMRI信号に提示した視覚刺激の情報が表現されているかを定量化した．加えて，視覚刺激提示後の各ボクセルの細かな血行動態反応のタイミングと，視覚刺激の情報表現のタイミングを比較することにより，両者の時間的な関係についての新たな知見を得ることに成功した． 本研究課題としての滞在期間は短くはあったものの，高頻度での実験と解析を効率的に循環させることができ，極めて有意義な滞在および研究の推進を実現することができた．, 18KK0311
2019 - 2021 - 深層ニューラルネットワークを用いた細胞形態特徴抽出と疾患変異性形態特徴の可視化
宮脇陽一
Principal investigator
01 Apr. 2017 - 31 Mar. 2019 - スパースモデリングを用いたヒト脳活動の高時空間分解能解析と脳情報源の同定
01 Apr. 2016 - 31 Mar. 2018 - 人工手指を自分の手指のように動かす：ヒト脳活動を用いた人工手指の自然な学習
01 Apr. 2015 - 31 Mar. 2017 - 脳情報復号化技術を用いた視覚野における触覚情報表現の解明
宮脇陽一
Principal investigator
01 Apr. 2014 - 31 Mar. 2017 - スパースモデリングによるヒト脳内での物体画像表現ダイナミクスの解明
宮脇陽一
Principal investigator
01 Mar. 2014 - 31 Mar. 2016 - ヒト脳の物体表現様式の解明
KDDI財団, 調査研究助成
2014 - ヒト脳における物体認識メカニズムの時間特性の解明
成茂神経科学研究助成基金, 研究助成
2014 - 神経情報表現に基づく高速物体画像認識アルゴリズムの研究開発
総務省戦略的情報通信研究開発推進制度（ＳＣＯＰＥ）ICTイノベーション創出型研究開発, 研究助成
2014 - ヒト脳神経活動の高時空間分解能解析法の開発と応用
内藤記念科学奨励金, 研究助成
2014 - ヒト脳活動からの画像認識情報の高速抽出技術の研究
矢崎科学技術振興記念財団, 特定研究助成
2014 - 脳情報復号化とデータ・マイニング技術による脳内質感情報表現の抽出
2011 - 2012 - 感覚知覚世界の可視化技術の研究開発
宮脇陽一
総務省, 戦略的情報通信研究開発推進制度（ＳＣＯＰＥ）若手ＩＣＴ研究者育成型研究開発, Principal investigator
2007 - 2009 - 経頭蓋磁気刺激による神経活動干渉機構の理論的解明
2005 - 2007 - 大脳皮質磁気刺激による神経活動干渉メカニズムの理論的解明
宮脇 陽一
日本学術振興会, 科学研究費助成事業, 独立行政法人理化学研究所, 若手研究(B), 16700375
2004 - 2004
