Alireza Modirshanechi
EPFL IC IINFCOM LCN1
SV 2805 (Bâtiment SV)
Station 19
CH-1015 Lausanne
Web site: Web site: https://lcn.epfl.ch/
Fields of expertise
Computational and Theoretical Neuroscience
Reinforcement Learning
Statistical Learning and Bayesian Inference
Reinforcement Learning
Statistical Learning and Bayesian Inference
Biography
I am a computer science Ph.D. student in the Laboratory of Computational Neuroscience at EPFL where I work on computational models of learning and decision-making in the brain - under the supervision of Prof. Wulfram Gerstner. My main track of research focuses on (i) mathematical definitions of surprise and novelty, (ii) their influence on human behavior, and (iii) their manifestation in physiological measurements. I use statistical inference, information theory, and reinforcement learning to develop theoretical models which I test against behavioral and physiological data. I have worked with EEG, MEG, fMRI, and single neuron recordings.Prior to joining EPFL, I received my B.Sc. in Electrical Engineering from the Sharif University of Technology, Tehran. During the last two years of my study, I did a few research projects in the Augmented Intelligence Research Lab (AIR Lab) under the supervision of Prof. Hamid Aghajan. My projects were mainly on (i) studying biomarkers of surprise in EEG signals, (ii) decoding surprise using these biomarkers, and (iii) fMRI-based classification of visual and auditory stimuli.
You can find my random scientific notes and educational articles here in my Medium account, and more information about me on my personal website.
Publications
Selected publications
A. Modirshanechi, J. Brea, W. Gerstner Preprint on bioRxiv, 2021 |
Surprise: a unified theory and experimental predictions |
H.A. Xu*, A. Modirshanechi*, M.P. Lehmann, W. Gerstner, M.H. Herzog PLoS Computational Biology, 2021 |
Novelty is not Surprise: Human exploratory and adaptive behavior in sequential decision-making |
V. Liakoni*, A. Modirshanechi*, W. Gerstner, J. Brea Neural Computation, 2021 |
Learning in Volatile Environments with the Bayes Factor Surprise |
A. Modirshanechi, M.M. Kiani, H. Aghajan NeuroImage, 2019 |
Trial-by-trial surprise-decoding model for visual and auditory binary oddball tasks |
Full list of publications - |
Click here |
Posts on Medium - |
Click here |