Yukie Nagai, Ph.D.
Principal Investigator
Computation
Project Professor
Understanding and assisting human intelligence through cognitive developmental robotics
Research
Human infants acquire various cognitive capabilities during their first few years of life. While the behavioral dynamics of this developmental process have been closely analyzed, the underlying mechanisms remain largely unknown. Our research aims to understand the neural basis of cognitive development using computational approaches grounded in the neuroscience theory of predictive processing. This theory posits that the brain minimizes prediction errors between top-down predictions and bottom-up sensations by updating its internal models or altering the environment through active inference. We design computational neural networks based on this theory and implement them in robots to explore how it can explain the continuity and diversity of cognitive development. Inspired by these computational studies, we also develop assistive systems for developmental disorders. These systems, based on predictive processing, help individuals with developmental disorders gain a better understanding of themselves, thereby contributing to the design of an inclusive society.
Publications
Daikoku, T., Kumagaya, S., Ayaya, S., and Nagai, Y. Non-autistic persons modulate their speech rhythm while talking to autistic individuals. PLoS ONE, 18(9):e0285591, 2023.
Tsujita, M., Homma, M., Kumagaya, S., and Nagai, Y. Comprehensive intervention for reducing stigma of autism spectrum disorders: Incorporating the experience of simulated autistic perception and social contact. PLoS ONE, 18(8):e0288586, 2023.
Philippsen, A., Tsuji, S., and Nagai, Y. Quantifying developmental and individual differences in spontaneous drawing completion among children. Frontiers in Psychology, 13:783446, 2022.
Philippsen, A., Tsuji, S., and Nagai, Y. Simulating Developmental and Individual Differences of Drawing Behavior in Children Using a Predictive Coding Model. Frontiers in Neurorobotics, 16:856184, 2022.
Seker, M. Y., Ahmetoglu, A., Nagai, Y., Asada, M., Oztop, E., and Ugur, E. Imitation and mirror systems in robots through Deep Modality Blending Networks. Neural Networks, 146:22-35, 2022.
Friston, K., Moran, R. J., Nagai, Y., Taniguchi, T., Gomi, H., and Tenenbaum, J. World model learning and inference. Neural Networks, 144:573-590, 2021.
Lanillos, P., Oliva, D., Philippsen, A., Yamashita, Y., Nagai, Y., and Cheng, G. A review on neural network models of schizophrenia and autism spectrum disorder. Neural Networks, 122:338-363, 2020.
Nagai, Y. Predictive learning: its key role in early cognitive development. Philosophical Transactions of the Royal Society B: Biological Sciences, 374(1771):20180030, 2019.
Horii, T., Nagai, Y., and Asada, M. Modeling Development of Multimodal Emotion Perception Guided by Tactile Dominance and Perceptual Improvement. IEEE Transactions on Cognitive and Developmental Systems, 10(3):762-775, 2018.
Baraglia, J., Nagai, Y., and Asada, M. Emergence of Altruistic Behavior Through the Minimization of Prediction Error. IEEE Transactions on Cognitive and Developmental Systems, 8(3):141-151, 2016.
Nagai Y. and Rohlfing, K. J. Computational Analysis of Motionese Toward Scaffolding Robot Action Learning. IEEE Transactions on Autonomous Mental Development, 1(1):44-54, 2009.
Nagai, Y., Hosoda, K., Morita, A., and Asada, M. A constructive model for the development of joint attention. Connection Science, 15(4):211-229, 2003.
Biography
Yukie Nagai obtained her Ph.D. in Engineering from Osaka University in 2004. Following her doctoral studies, she worked at the National Institute of Information and Communications Technology, Bielefeld University, and Osaka University. Since 2019, she has been a Project Professor at the International Research Center for Neurointelligence at the University of Tokyo, where she leads the Cognitive Developmental Robotics Laboratory. Her research delves into the developmental principles of human social cognition through computational approaches. In acknowledgment of her work, she was named one of the “World’s 50 Most Renowned Women in Robotics” in 2020 and one of the “35 Women in Robotics Engineering and Science” in 2022, among other recognitions. She also serves as the principal investigator of the JST CREST projects “Cognitive Mirroring” and “Cognitive Feeling” since 2016 and 2021, respectively. Her concurrent positions include Project Professor at the Next Generation Artificial Intelligence Research Center and the Center for Coproduction of Inclusion, Diversity, and Equity at the University of Tokyo, Visiting Professor at the Center for Human Nature, Artificial Intelligence, and Neuroscience at Hokkaido University, and Associate Member of the Science Council of Japan.
