Our goal is to understand how the brain analyzes large and complex datasets streamed by sensory organs in order to aid efforts at building artificial neural systems and treating mental illness.
We analyze experimental data, assembling connectomes from high-throughput electron microscopy and determining neuronal dynamics from calcium imaging and multi-electrode recordings. In addition, we are developing a novel algorithmic theory of neural computation.
Artificial neural networks that learn to perform Principal Component Analysis (PCA) and related tasks using strictly local learning rules have…arXiv:1810.06966
Temporally precise movement patterns underlie many motor skills and innate actions, yet the flexibility with which the timing of such…Nature Communications
We study the large source asymptotics of the generating functional in quantum field theory using the holographic renormalization group, and…arXiv:1802.05362
Johannes Friedrich joined the Flatiron Institute is an Associate Research Scientist at the Center for Computational Neuroscience. His research focuses on efficient machine-learning and optimization algorithms for statistical analysis of large-scale neural data, as well as on theories of neural computation, such as implementations of…