Machizawa Maro

Last Updated :2023/11/07

Affiliations, Positions
Center for Brain, Mind and KANSEI Sciences Research, Associate Professor (Special Appointment)
Web Site
https://sites.google.com/view/digital-cogneuro/
Self-introduction
PhD in Cognitive Neurology The BMK Digital Cognitive Neuroscience lab (DCN lab) led by Maro Machizawa, PhD is a satellite laboratory dedicated for the Center for Brain, Mind and KANSEI Research Sciences ('The BMK Center') at Hiroshima University. We study a broad range of topics in psychology and cognitive neuroscience, such as human affective and cognitive aptitudes as a form of integrated mental representations, so-called KANSEI.

Basic Information

Educational Backgrounds

  • University College London, UCL Institute of Neurology & UCL Institute of Cognitive Neuroscience, Department of Brain Repair and Rehabilitation, UK, 2008, 2012

Academic Degrees

  • PhD (Neurology), University College London
  • MSc (Psychology), University of Oregon

Research Activities

Academic Papers

  1. oFVSD: a Python package of optimized forward variable selection decoder for high-dimensional neuroimaging data, FRONTIERS IN NEUROINFORMATICS, 2023
    Link to Paper Search Results by DOI
  2. Leveraging Self-Sovereign Identity in Decentralized Data Aggregation., 2022 Ninth International Conference on Software Defined Systems (SDS), 00, 1-8, 20230317
    Link to Paper Search Results by DOI
  3. Examination of evaluation method of environmental noise on EEG measurements, JAPANESE JOURNAL OF PHYSIOLOGICAL PSYCHOLOGY AND PSYCHOPHYSIOLOGY, 39(2), 135-135, 20210831
  4. Challenges on Establishing Mental Well-Being through Collection of EEG Big Data, The Japanese Journal of Ergonomics, 58(Supplement), S2A3-01, 2022
    Link to Paper Search Results by DOI
  5. The neuroanatomy of social trust predicts depression vulnerability, Scientific Reports, 20221006
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  6. Suppression of Neuroinflammation Attenuates Persistent Cognitive and Neurogenic Deficits in a Rat Model of Cardiopulmonary Bypass, FRONTIERS IN CELLULAR NEUROSCIENCE, 16, 20220224
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  7. Factor structure, reliability and validation of the Japanese version of the Body Perception Questionnaire-Body Awareness Very Short Form (BPQ-BAVSF-J), JAPANESE JOURNAL OF RESEARCH ON EMOTIONS, 28(2), 38-48, 2021
  8. Frequency drift in MR spectroscopy at 3T, NEUROIMAGE, 241, 20211101
    Link to Paper Search Results by DOI
  9. Resting-state brain activity can predict target-independent aptitude in fMRI-neurofeedback training, NEUROIMAGE, 245, 20211215
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  10. Design of a Database-Driven Kansei Feedback Control System Using a Hydraulic Excavators Simulator, JOURNAL OF ROBOTICS AND MECHATRONICS, 32(3), 652-661, 202006
    Link to Paper Search Results by DOI
  11. Gray Matter Volume in Different Cortical Structures Dissociably Relates to Individual Differences in Capacity and Precision of Visual Working Memory, CEREBRAL CORTEX, 30(9), 4759-4770, 202009
    Link to Paper Search Results by DOI
  12. The Shape of a Vehicle Windshield Affects Reaction Time and Brain Activity During a Target Detection Task, FRONTIERS IN HUMAN NEUROSCIENCE, 14, 20200526
    Link to Paper Search Results by DOI
  13. Verification of the reliability of MEG source localization using VBMEG in visual short-term memory, PERCEPTION, 45, 162-162, 2016
  14. Individual differences approach validates neural correlates and reveals separable contributory subsystems of attention and working memory capacity, NEUROSCIENCE RESEARCH, 68, E42-E42, 2010
  15. The Time Course of Ventrolateral Prefrontal Cortex Involvement in Memory Formation, JOURNAL OF NEUROPHYSIOLOGY, 103(3), 1569-1579, 2010
  16. Persistent cognitive deficits and neuroinflammation in a rat model of cardiopulmonary bypass, Journal of Thoracic and Cardiovascular Surgery, 160(4), e185-e188, 2020
  17. Evaluation of Communication methods for the Cloud-Computing Platform for the Neurophysiological Information, DICOMO2021, 1, 237-242, 2021
  18. Neural activity predicts individual differences in visual working memory capacity, Nature, 428(6984), 748-751, 20040415
  19. Neural measures reveal individual differences in controlling access to working memory, Nature, 438(7067), 500-503, 20051124
  20. Electrophysiological measures of maintaining representations in visual working memory, Cortex, 43(1), 77-94, 20070101
  21. Principal component analysis of behavioural individual differences suggests that particular aspects of visual working memory may relate to specific aspects of attention, Neuropsychologia, 49(6), 1518-1526, 20110501
  22. Human Visual Short-Term Memory Precision Can Be Varied at Will When the Number of Retained Items Is Low, Psychological Science, 23(6), 554-559, 20120101
  23. Overlearning hyperstabilizes a skill by rapidly making neurochemical processing inhibitory-dominant, Nature Neuroscience, 20(3), 470-475, 20170223
  24. Affective auditory stimulus database: An expanded version of the International Affective Digitized Sounds (IADS-E), Behavior Research Methods, 50(4), 1415-1429, 20180801
  25. Quantification of Anticipation of Excitement with A Three-Axial Model of Emotion with EEG, Journal of Neural Engineering, 17(3), 20200601
  26. Erratum: Quantification of anticipation of excitement with a three-axial model of emotion with EEG (Journal of Neural Engineering (2020) 17 (036011) DOI: 10.1088/1741-2552/ab93b4), Journal of Neural Engineering, 17(5), 20201007

Invited Lecture, Oral Presentation, Poster Presentation

  1. Design of a Database-Driven Kansei Feedback Control System using EEG Data and an Analysis of Experimental Data, Takuya Kinoshita, Takuya Kinoshita, Shiho Murakami, Toru Yamamoto, Maro Machizawa, Kiyokazu Tanaka, IFAC WORLD CONGRESS 2023, 2023/07/10, Without Invitation, English
  2. Quantification of anticipatory excitement and its application for innovation, Maro Machizawa, Seminar: "Quantification of KANSEI" and its Application for Innovation, 2022/10/12, With Invitation, Japanese
  3. Hope for the integration of brain science DX and nursing, Maro Machizawa, The 42nd Annual Conference of Japan Academy of Nursing Science, 2022/12/04, With Invitation, Japanese
  4. Hope for the integration of Brain Science DX and Nursing, Maro Machizawa, The 42nd Annual Conference of Japan Academy of Nursing Science, With Invitation, Japanese
  5. Design of a Kansei Feedback Control System using EEG Data for a hydraulic excavator, S. Murakami, T. Kinoshita, T. Yamamoto, M. Machizawa and K. Tanaka, 65th JSME, 2022/11/12, Without Invitation, English
  6. Applicability and Issues on the quantification of anticipatory excitement by the 'KANSEI Meter' using EEG sensing, Maro Machizawa, JEITA, 2022/12/12, With Invitation, Japanese, JEITA, online
  7. How visual is visual working memory? Neural evidence for a distinction between the subjective experience of quality and quantity of mental imagery, K. BATES, M. L. SMITH, E. K. FARRAN, M. G. MACHIZAWA, Society for Neuroscience Annual Conference (Neuroscience 2022), 2022/11/14, Without Invitation, English, Society for Neuroscience, San Diego, USA
  8. Evaluation of influence of positions and numbers of EEG electrodes on quantification of independent component matrix, Ingon Chanpornpakdi, Ryohei Mizuochi, Maro G Machizawa, APSIPA ASC 2022, 2022/11/17, Without Invitation, English, Asia-Pacific Signal and Information Processing Association (APSIPA), Chiang Mai, Thailand
  9. Making a bridge over the valley of death in applied neuroscience: Challenges in Establishing Mental Well-Being through Collection of EEG Big Data, Maro Machizawa, 2022-2023 Seminars of Department of Computer Science and Engineering Technology at the University of Houston – Downtown, 2022/11/14, With Invitation, English, Department of Computer Science and Engineering Technology at the University of Houston – Downtown, Virtual
  10. Automatic decoding package supported by forward variable selection for neuroimaging data optimizes, Tung Dang, Alan S. R. Fermin, Maro G. Machizawa, Neuro2022, 2022/06/30, Without Invitation, English
  11. Design of a Database-Driven Kansei Feedback Control System Using a Simulator of Hydraulic Excavator, Shiho Murakami, Takuya Kinoshita, Toru Yamamoto, Maro G. Machizawa, Kiyokazu Tanaka, 2022 SICE Annual Conference (SICE), 2022/09/06, Without Invitation, English
  12. Decoding of Emotional Valence Based on a Scale Mixture Model of EEG, Shunya Fukuda, Akira Furui, Ryou Kumagai, Hiroto Sakai, Maro Machizawa, Toshio Tsuji, 2022 The Institute of Electrical Engineers of Japan, 2022/08/31, Without Invitation, Japanese
  13. Brain interoception network structures linked with cardiac dysfunction in depression, Alan S. R. Fermin, Hui-Ling Chan, Naho Ichikawa, Masahiro Takamura, Satoshi Yokoyama, Maro G. Machizawa, Atsuo Yoshino, Ayumu Matani, Shigeto Yamawaki, Go Okada, Yasumasa Okamoto, Neuro2022, 2022/06/30, Without Invitation, English
  14. Insular responses to 1-Hz transcutaneous auricular vagus nerve stimulation from human intracranial recordings, Hui-Ling Chan, Tokiko Harada, Masaya Katagiri, Koji Iida, Maro G. Machizawa, Kentaro Ono, Alan R. Fermin, Shigeto Yamawaki, Neuro2022, 2022/06/30, Without Invitation, English
  15. Automatic package for optimized decoding of neuroimaging data supported by forward variable selection, Tung Dang; Alan S. R. Fermin; Maro G. Machizawa, Neuro2022, 2022/06/30, Without Invitation, English
  16. A possible link between spontaneously explored brain dynamics at rest and driven brain state during fMRI-neurofeedback training, Masahiro Takamura, Takashi Nakano, Haruki Nishimura, Maro Machizawa, Naho Ichikawa, Atsuo Yoshino, Go Okada, Yasumasa Okamoto, Shigeto Yamawaki, Makiko Yamada, Tetsuya Surahara, Junichiro Yoshimoto, Neuro2022, 2022/06/30, Without Invitation, Japanese
  17. The underlying causes of individual differences in brain decodability, Maro Machizawa, Aurelio Cortese, 2020/07/29, Without Invitation, English
  18. A primer towards the understanding of individual variabilities on decoding neural information, 2020/07/29, Without Invitation, English
  19. The multi-axial model of emotion reflects variable types for KANSEI, Maro Machizawa, Naomi Moore, Barbara Mrtiv, Shigeto Yamawaki, Society for Affective Science 2021 Annual Conference, 2021/04/13, Without Invitation, English
  20. Dissociable Neural Markers for Integrative Emotional States Relates to Separable Types of Personality Traits, Nature Conferences Technologies for neuroengineering, 2021/05/27, Without Invitation, English
  21. Validation of personality-dependent optimized emotion (KANSEI) decoding using EEGs, Maro G. Machizawa, Phuong Thi Mai Nguyen, Ryohei Mizuochi, Shigeto Yamawaki, the 44th Annual Meeting of the Japan Neuroscience Society, 2021/07, Without Invitation, English
  22. Abnormal brain interoception network structures linked with loss of cardiac autonomic regulation in major depressive disorder, Alan S. R. Fermin, Hui-Ling Chan, Naho Ichikawa, Masahiro Takamura, Toko Kiyonari, Yoshie Matsumoto, Haruto Takagishi, Yang Li, Ryota Kanai, Masamichi Sakagami, Satoshi Yokoyama, Maro Machizawa, Ayumu Matani, Shigeto Yamawaki, Go Okada, Toshio Yamagishi, Yasumasa Okamoto, the 44th Annual Meeting of the Japan Neuroscience Society, 2021/07, Without Invitation, English
  23. Cardiac responses to uncertainty and heart-brain relations reflect depressed mood, Hui-Ling Chan, Maro G. Machizawa, Noriaki Kanayama, Makita Kai, Ryohei Mizuochi, Shigeto Yamawaki, the 44th Annual Meeting of the Japan Neuroscience Society, 2021/07/25, Without Invitation, English
  24. Neurofeedback-supported mental imagery training selectively boosts the capacity of visual working memory and attention and reveals a causal role of contralateral delay activity and visual working memory capacity, Maro Machizawa, M. MACHIZAWA, R. MIZUOCHI, S. YAMAWAKI, T. WATANABE, Society for Neuroscience 2021 Annual Meeting, 2021/11/08, Without Invitation, English
  25. development and application of KANSEI Meter®, Maro Machizawa, 2021/12/08, With Invitation, Japanese
  26. The necessity of EEG data collection platform and global collaboration, Maro Machizawa, JST COI Young Collaborative Digital Fund Symposium, 2022/03/09, Without Invitation, Japanese
  27. “Functional Neuroanatomy underlying Quality and Quantity of Visual Attention and Working Memory”, University of South Carolina, Institute for Mind and Brain Colloquium Series, 2015/08/25, With Invitation, English, When we enter things into our memory, information is manipulated and temporarily retained in a mental representation, the so-called working memory. This seemingly natural and common ability to retain is, however, astonishingly limited to only a few items on average, with large inter-individual differences ranging from 1 to 6 items in young adults. Number of items to be retained is one characteristic of working memory, but precision with which information is retained is a fundamental aspect as well. Various models of visual working memory have been proposed and functional correlates of number have been revealed; however, little is known about whether and how our brain structure may constrain these potentially separable aspects of working memory. In this talk, I will present behavioral and neuroanatomical correlates of visual working memory in association with separable aspects of attention (alerting, orienting, and executive control), with a particular focus on 'quality' and 'quantity'. As it turns out, distinct occipitoparietal regions predicted individuals' working memory abilities in a hemispherically specific manner. Such results are meaningful on one hand; however, these relations are correlational, thus lacking causal force. At the end of my talk, I will share my recent work using "neurofeedback training" not only as to improve attention and working memory abilities but also as a way to causally examine this hemispheric specificity. Altogether, these pieces of evidence would suggest a view that separable aspects of attention dissociably supports working memory, putatively supported by hemispherically unique functional neuroanatomy.
  28. A multi- axis affective and cognitive decoded neurofeedback technique can visualize anticipation of excitement, The 40th Annual Meeting of the Japan Neuroscience Society, 2017/07/20, Without Invitation, English, Recent empirical models of emotion is diverging, it has been debated whether emotion can be expressed on a 2-dimensional circumplex or rather be expressed as a categorical manner without forming a particular topology of emotion. With classical approaches along the circumplex model suggest linear associations between emotion and neural activities in a particularly selected brain regions. In contrast, recent developments of machine learning or meta-analytical approaches instead suggest distributed role of remotely interconnected brain regions dedicated for each categorical emotion. This rivalry encourages the comparison of classical approaches on average against individually decoded neural activities. A majority of research on neural signatures of emotional responses relied on the Russell’s circumplex model have only focused on valence and arousal dimensions of the model. However, the typical 2D model lacks its ability to explain a particular type of emotion, such as a feeling of excitement in expectation of an upcoming rewarding event, introducing another dimension of time. For such an instance, both affective and cognitive processes should co- occur in parallel. A pure emotional response to the event also requires cognitive visualization (or imagination) of an expected reward or punishment. Here, we have created a real-time decoded neurofeedback (DecNef) system as a meter for the feeling of excitement based on the proposed 3- dimensional psychological model to visualize instantaneous affective and cognitive status. Twenty-six young adult participants took part in a visual image expectation task using the International Affective Picture System, a collection of emotionally evoking pictures, while electroencephalography (EEG) was recorded from 64 channels placed on ones scalp. Participants were instructed and conditioned to expect high or low valence pictures followed by corresponding auditory cue. Sparse logistic regression technique was applied to time-frequency domain of the EEG data to individually decode neural signature for each axis. Once decoding accuracy was confirmed, the same procedures were repeated on a new participant to actually visualize the person’s feeling towards a new set of pictures. Our brain-emotion-interface based on the multi-axis model can visualize ones mental status in real time and supports the need for individualized DecNef.
  29. “Functional Neuroanatomy underlying Quality and Quantity of Visual Attention and Working Memory”, Maro Machizawa, Institute for Mind and Brain Colloquium Series, With Invitation, English, University of South Carolina Institute for Mind and Brain, University of South Carolina Institute for Mind and Brain

Awards

  1. 2022/12/15, Best Paper Award at the 9th IEEE International Conference on Software Defined Systems (SDS-2020), Chair of "The 9th IEEE International Conference on Software Defined Systems (SDS-2020)", Leveraging Self-Sovereign Identity in Decentralized Data Aggregation
  2. 2021/06/20, Best Paper Award, Japan Society for Research on Emotion
  3. 2022/03/22, SCSK Award, SCSK
  4. 2022/03/22, Hiroshima VS Award, Hiroshima Venture Capital

Patented

  1. Patent, JP第7122730号, 2022/08/12
  2. Patent, JP6916527号
  3. Patent, JP6590411, 2019/09/27
  4. Patent, 6731718, 2020/07/09
  5. Patent, 6742628, 2020/07/31

External Funds

Acceptance Results of Competitive Funds

  1. Moonshot Research and Development Program, Moonshot Goal 9 "Realization of a mentally healthy and dynamic society by increasing peace of mind and vitality by 2050" Innovation for "Mental Capital" by Awareness Music, 2022, 2026
  2. [Fundamental Study for KANSEI communication by visualization of KANSEI information: Establishment of KANSEI quantification for patients with Autistic Spectrum Disorder], 2021/.4, 2022/.3
  3. COI Young Investigator Collaborative Research Fund–Digital Collaboration Research, Development of AI Cloud Platform for Neurophysiological Information, 2020, 2022

Social Activities

Organizing Academic Conferences, etc.

  1. Individual differences in perception, cognition and personality, Organizer, 2010/, 2010/
    Permalink

Other Social Contributions

  1. 2022-2023 Seminars of Department of Computer Science and Engineering Technology at the University of Houston – Downtown, Making a bridge over the valley of death in applied neuroscience: Challenges in Establishing Mental Well-Being through Collection of EEG Big Data, University of Houston – Downtown, 2022/11/14, Virtual, Lecturer, Seminar or workshop, Researchesrs
  2. [42nd Hiroshima Prefecture MRI Workshop], [Measuring your brain power!], Lecturer, Lecture, Researchesrs

History as Peer Reviews of Academic Papers

  1. Attention, Perception, & Psychophysics, Others
  2. Brain and Cognition, Others
  3. Brain Stimulation, Others
  4. Frontiers in Psychology, Others
  5. International Journal of Psychology, Others
  6. Journal of Cognitive Neuroscience, Others
  7. Journal of Neurophysiology, Others
  8. Journal of Neuroscience, Others
  9. NeuroImage, Others
  10. Neuropsychologia, Others