Neural Circuits and Algorithms
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.
Chklovskii Lab
Projects
Research Highlights
High-fidelity Image Restoration of Large 3D Electron Microscopy Volume
Yuri Kreinin, P. Gunn, D. Chklovskii, J. Wu
Volume electron microscopy (VEM) is an essential tool for studying biological structures. Due to the challenges of sample preparation and…
Microscopy and MicroanalysisThe neuron as a direct data-driven controller
J. Moore, A. Genkin, Magnus Tournoy, J. Pughe-Sanford, Rob R. de Ruyter van Steveninck, D. Chklovskii
Building upon the efficient coding and predictive information theories, we present a perspective that neurons not only predict but may…
Proceedings of the National Academy of Sciences of the United States of AmericaWASPSYN: A Challenge for Domain Adaptive Synapse Detection in Microwasp Brain Connectomes
Yicong Li, Wanhua Li, Qi chen, Wei Huang, Yuda Zou, Xin Xiao, K. Shinomiya, P. Gunn, Nishika Gupta, Alexey Polilov, Yongchao Xu, Yueyi Zhang, Zhiwei Xiong, Hanspeter Pfister, Donglai Wei, J. Wu
The size of image volumes in connectomics studies now reaches terabyte and often petabyte scales with a great diversity of…
IEEE Transactions on Medical Imaging
