Inception Loops

machine learning and neuroscience
inception loops

We are using highly predictive deep learning models as in silico avatars of neural populations in visual cortex and analyse their nonlinear properties. Our goal is to find interpretable and experimentally verifiable computational principles of biological vision. We do this by synthesizing new stimuli for neuroscientific experiments in silico and verifying them in vivo with our collaboration partners. We call this cycle “Inception Loops”.

dasilva walker altendorf willeke elumalai ma qiu

Publications

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2022

Erick Cobos, Taliah Muhammad, Paul G Fahey, Zhiwei Ding, Zhuokun Ding, Jacob Reimer, Fabian H. Sinz, Andreas Tolias It takes neurons to understand neurons: Digital twins of visual cortex synthesize neural metamers biorXiv preprint · system identification inception loops · biorXiv
Katrin Franke¹, Konstantin F. Willeke¹, Kayla Ponder, Mario Galdamez, Taliah Muhammad, Saumil Patel, Emmanouil Froudarakis, Jacob Reimer, Fabian H. Sinz, Andreas S. Tolias State-dependent pupil dilation rapidly shifts visual feature selectivity Nature , equal contribution: ¹ journal paper · inception loops neuroscience · nature twitter biorXiv data code
Jiakun Fu, Konstantin F. Willeke, Pawel A. Pierzchlewicz, Taliah Muhammad, George H. Denfield, Fabian H. Sinz, Andreas S. Tolias Hetereogenous orientation tuning across sub-regions of receptive fields of V1 neurons in mice Cell Press Sneak Preview preprint · inception loops neuroscience · cell press

2019

Edgar Y. Walker¹, Fabian H. Sinz¹, Erick Cobos, Taliah Muhammad, Emmanouil Froudarakis, Paul G. Fahey, Alexander S. Ecker, Jacob Reimer, Xaq Pitkow, Andreas S. Tolias Inception loops discover what excites neurons most using deep predictive models Nature Neuroscience , equal contribution: ¹ journal paper · inception loops · bioRxiv Nature Neuroscience github