How does the brain extract relevant visual features from the rich, dynamic visual input that typifies active exploration, and how does the neural representation of these features support visual navigation?
Marius Schneider
(he/him)
Postdoctoral Researcher
Institute for Collaborative Biotechnologies
University of California, Santa Barbara
Marius Schneider is a Postdoctoral Researcher at the Institute for Collaborative Biotechnologies. He completed his doctoral research in Systems Neuroscience at the Ernst Strüngmann Institute in Frankfurt, in affiliation with the International Max Planck Research School (IMPRS) for Neural Circuits at the Max Planck Institute for Brain Research. Marius defended his PhD with highest honors at Radboud University Nijmegen in May 2024.
Marius’s research aims to uncover how the brain achieves flexible information processing. He focuses on understanding how different cell types and brain regions integrate sensory information to drive behavior. To address these questions, he combines detailed biophysical modeling and state-of-the-art machine learning techniques with large-scale, multi-areal electrophysiological recordings.
Outside the lab, Marius enjoys running, working out at the gym, spending time at the beach, traveling, and listening to music.
- 3205 BioEngineering
- marius_schneider@ucsb.edu
Honors & Awards
- EBBS Young Investigator Award (2024)
- Travel Grant for CNS 2019, Barcelona, Spain
- Travel Grant for Neural Dynamics Summer School 2018, Bristol, UK
Education
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PhD in Neurophysics, 2024
Radboud University, Nijmegen, Netherlands
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MS in Physics, 2019
Goethe University, Frankfurt am Main, Germany
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BS in Physics, 2016
Goethe University, Frankfurt am Main, Germany
Project Lead
Publications
Beyond neural activity prediction: Probing latent representations in mouse V1 digital twins
We introduce a multi-level evaluation framework for digital twins of mouse V1 that links neural-prediction accuracy to probe decodability, latent-unit tuning, and hidden-population geometry.
Adriano Lima, Yuchen Hou, Michael Beyeler, Marius Schneider arXiv
Visual robustness and neural alignment in a shared foraging task: The Mouse vs. AI benchmark
We introduce Mouse vs. AI, a public benchmark suite that unifies visual robustness, embodied foraging behavior, and neural alignment by evaluating artificial agents and mice in the same naturalistic 3D task.
Marius Schneider, Joe S. Canzano, Yuchen Hou, Jing Peng, Anjali Deepu, Utsab Karan, Phu-Hoa Pham, Tran Chi Nguyen, Dao Sy Duy Minh, Phu Quy Nguyen Lam, Trung-Kiet Huynh, Simone Azeglio, Spencer LaVere Smith, Michael Beyeler arXiv