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.
Learning appropriate representations of the reward environment is challenging in the real world where there are many options, each with…Nature Communications
A major problem in motor control is understanding how the brain plans and executes proper movements in the face of…arXiv:2111.06920
In the field of Connectomics, a primary problem is that of 3D neuron segmentation. Although deep learning-based methods have achieved…arXiv:2112.02039
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…