Updated on 2026/03/20

写真a

 
MARTINEZ TEJADA LAURA ALEJANDRA
 
Organization
School of Computing Assistant Professor
Title
Assistant Professor
External link

Research Interests

  • Human Computer Interface

  • Computational Neuroscience

  • Behavioral Neuroscience

  • Brain Computer Interface

  • Comprehensive Brain Network

  • Emotion Recognition

Research Areas

  • Life Science / Cognitive and brain science

  • Informatics / Perceptual information processing

  • Informatics / Human interface and interaction

  • Manufacturing Technology (Mechanical Engineering, Electrical and Electronic Engineering, Chemical Engineering) / Electron device and electronic equipment

Research History

  • School of Computing, Tokyo Institute of Technology   Department of Computer Science

    2024.10

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    Country：Japan

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  • School of Computing, Institute of Science Tokyo   Department of Computer Science

    2022.8 - 2024.10

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Papers

  • Experimental synchronization between neuroelectrical activity and an elementary electronic chaotic oscillator Reviewed

    Longxiang Fu, Yuri Antonacci, Manyu Zhao, Laura Alejandra Martinez-Tejada, Hiroyuki Ito, Dezhong Yao, Pedro A. Valdes-Sosa, Natsue Yoshimura, Mattia Frasca, Ludovico Minati

    Chaos, Solitons & Fractals   201 ( 3 )   2025.12

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

    DOI： 10.1016/j.chaos.2025.117268

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  • Classification of Autism Spectrum Disorder Subtypes based on Graph Attention Network

    Shan Wang, Laura Alejandra Martinez-Tejada, Natsue Yoshimura

    2025 International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA)   1 - 7   2025.8

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

    DOI： 10.1109/acdsa65407.2025.11166344

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  • Comparison of autism spectrum disorder subtypes based on functional and structural factors Reviewed

    Shan Wang, Zhe Sun, Laura Alejandra Martinez-Tejada, Natsue Yoshimura

    Frontiers in Neuroscience   2024.10

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    Publishing type：Research paper (scientific journal)  

    <jats:p>Autism spectrum disorder (ASD) is a series of neurodevelopmental disorders that may affect a patient’s social, behavioral, and communication abilities. As a typical mental illness, ASD is not a single disorder. ASD is often divided into subtypes, such as autism, Asperger’s, and pervasive developmental disorder-not otherwise specified (PDD-NOS). Studying the differences among brain networks of the subtypes has great significance for the diagnosis and treatment of ASD. To date, many studies have analyzed the brain activity of ASD as a single mental disorder, whereas few have focused on its subtypes. To address this problem, we explored whether indices derived from functional and structural magnetic resonance imaging (MRI) data exhibited significant dissimilarities between subtypes. Utilizing a brain pattern feature extraction method from fMRI based on tensor decomposition, amplitude of low-frequency fluctuation and its fractional values of fMRI, and gray matter volume derived from MRI, impairments of function in the subcortical network and default mode network of autism were found to lead to major differences from the other two subtypes. Our results provide a systematic comparison of the three common ASD subtypes, which may provide evidence for the discrimination between ASD subtypes.</jats:p>

    DOI： 10.3389/fnins.2024.1440222

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MISC

Research Projects

  • AI-Driven Immersive Training for High-Pressure Scenarios: A Cross-Cultural Study

    Grant number：25K06598  2025.4 - 2028.3

    Roy ParthaPratim, Martinez Tejada Laura Alejandra, Masakazu Iwamura

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    Authorship：Coinvestigator(s) 

    Grant amount：\4680000 （ Direct Cost: \3600000 、 Indirect Cost：\1080000 ）

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  • Emotion-regulation brain computer interface based on electroencephalography source localization and an adjustable video game to help in the treatment of depression and anxiety disorders

    Grant number：25K18952  2025.4 - 2028.3

    Martinez Tejada Laura Alejandra

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    Authorship：Principal investigator 

    Grant amount：\4810000 （ Direct Cost: \3700000 、 Indirect Cost：\1110000 ）

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