Artificial neural networks that learn to perform Principal Component Analysis (PCA) and related tasks using strictly local learning rules have…arXiv:1810.06966
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.
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 in 2017 as a member of the neuroscience group at the Center for Computational Biology. 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,…
Cengiz Pehlevan joined Center for Computational Biology’s Neuroscience group in 2015 to build theories of neural computation and to develop methods to analyze large neuroscience datasets in order to test such theories. Prior to joining the foundation, Pehlevan was a postdoctoral associate at the Janelia…