Ivilin Peev Stoianov

PublicationsI am a researcher at the National Research Council of Italy (CNR), Institute of Cognitive Sciences and Technologies (ISTC), Padova.My principle research interests include neurocomputational modeling and analysis of human cognition functions, including visual perception, sensorimotor processing, spatial navigation, goal-directed behavior, planning, numerical cognition. Research methods include computational modeling and statistical analysis of behavioral and neurophysiological data.I coordinate the CNR units of two research projects, PACE financed by the PRIN2017 program of the Italian Ministry of University and Research and "MAIA", financed by the European Commission under Horizon2020. Those two projects investigate the computational principles of sensorimotor transformations in the Superior Parietal Cortex. MAIA also aims to develop a decoder of the sensorimotor intentions. In past research projects I investigated visual perception in reading, numerical perception and cognition in general, neural-level analysis.Research highlight:

• Stoianov, I., & Zorzi, M. (2012). Emergence of a “visual number sense” in hierarchical generative models. Nature Neuroscience (15) 194–6. doi:10.1038/nn.2996
• Stoianov, I., Genovesio, A., & Pezzulo, G. (2016). Prefrontal goal-codes emerge as latent states in probabilistic value learning. Journal of Cognitive Neuroscience (28), 140–157. doi:10.1162/jocn_a_00886
• Testolin, A., Stoianov, I., & Zorzi, M. (2017). Letter perception emerges from unsupervised deep learning and recycling of natural image features. Nature Human Behaviour, 1, 657–664. doi:10.1038/s41562-017-0186-2
• Stoianov, I., Pennartz, C., Lansink, C., & Pezzulo, G. (2018). Model-based spatial navigation in the hippocampus-ventral striatum circuit: a computational analysis. Plos Computational Biology, 1–28.
• Jezzini, A., Caruana, F., Stoianov, I., Gallese, V., & Rizzolatti, G. (2012). Functional organization of the insula and inner perisylvian regions. Proceedings of the National Academy of Sciences, 109, 10077–10082. doi:10.1073/pnas.1200143109