Moji Shahmohammadi

Research Assistant

Supervisor

Dr Hamid Karimi-Rouzbahani

Current research

My research bridges Artificial Intelligence and cognitive neuroscience, employing machine learning and computational modeling to decode the brain's intricate mechanisms. Building upon a Masters in AI and Robotics, and data analytics experience, I focus on perception and working memory, seeking to generate impactful insights into human cognition. My current work aims to contribute to a deeper understanding of how the brain processes information.

Research interests

Neural Decoding
Brain Imaging
Machine Learning

Publications

Karimi-Rouzbahani, H., Shahmohammadi, M., Vahab, E., Setayeshi, S., & Carlson, T. (2021). Temporal variabilities provide additional category-related information in object category decoding: a systematic comparison of informative EEG features. Neural Computation, 33(11), 3027-3072 https://doi.org/10.1162/neco a 01436

Shahmohammadi, M., Vahab, E., & Karimi-Rouzbahani, H. (2020). Informative Neural Codes to Separate Object Categories. bioRxiv, 2020-12 https://doi.org/10.1101/2020.12.04.409789

Shahmohammadi, M., Setayeshi,S. (2019) What to look at when decoding object category information from Electrical Brain Activations. In 6th Iranian human brain mapping congress (IHBM), Tehran, Iran

Karimi-Rouzbahani, H., Vahab, E., & Shahmohammadi, M. (2018) Fundamental role of prefrontal cortex in target-detection as revealed by decoding and causality analysis of EEG brain patterns. In Australasian Cognitive Neuroscience Society Congress, Melbourne, Australia