Samuel Muscinelli
Assistant Professor
Grossman Center for Quantitative Biology and Human Behavior
The University of Chicago
I am interested in how the anatomy of brain circuits both governs learning and adapts to it.
My current research centers on two main questions: How does neural connectivity give rise to patterns of activity that support learning? What can we say about the plasticity rules that enable the brain to adapt to changes and goals in the environment?
To tackle these questions, I leverage recent advances in our ability to measure synaptic connectivity, and I combine analytical theory, machine learning, and data analysis, working closely with experimental collaborators.
Publications
- 2025 A. P. J. Fink*, S. P. Muscinelli*, S. Wang, M. Hogan, D. English, R. Axel, A. Litwin-Kumar, and C. E. Schoonover*, Experience-dependent reorganization of inhibitory neuron synaptic connectivity. biorXiv.
- 2024 L. Posani*, S. Wang*, S. P. Muscinelli, L. Paninski, and S. Fusi, Rarely categorical, always high-dimensional: how the neural code changes along the cortical hierarchy. bioRxiv.
- 2023 S. P. Muscinelli, M. Wagner, and A. Litwin-Kumar, Optimal routing to cerebellum-like structures. Nature Neuroscience 26 (9) 1630-1641. PDF.
- 2023 M. Xie, S. P. Muscinelli, K. D. Harris, and A. Litwin-Kumar, Task-dependent optimal representations for cerebellar learning. eLife 12 e82914.
- 2021 V. Esmaeili*, K. Tamura*, S. P. Muscinelli, A. Modirshanechi, M. Boscaglia, A. B. Lee, A. Oryshchuk, G. Foustoukos, Y. Liu, S. Crochet, W. Gerstner, and C. C. H. Petersen, Rapid suppression and sustained activation ofdistinct cortical regions for a delayed sensory-triggered motor response. Neuron, 109, 1-19.
- 2019 S. P. Muscinelli, W. Gerstner, and T. Schwalger, How single neuron properties shape chaotic dynamics and signal transmission in random neural networks. PLOS Computational Biology 15(6): e1007122 PDF
- 2019 C. Gastaldi, S. P. Muscinelli, and W. Gerstner, Optimal stimulation protocol in a bistable synaptic consolidation model. Frontiers in Computational Neuroscience 13, 78
- 2017 S. P. Muscinelli, W. Gerstner, and J. Brea, Exponentally long orbits in Hopfield neural networks.
Neural Computation 29(2), 458-484
- 2016 F. Colombo, S. P. Muscinelli, A. Seeholzer, J. Brea, and W. Gerstner. Algorithmic Composition of Melodies with Deep Recurrent Neural Networks1st Conference on Computer Simulation of Musical Creativity,
- 2013 M. Bochicchio and S. P. Muscinelli, Ultraviolet asymptotics of glueball propagators.
Journal of high energy physics 2013 (8), 1-51
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