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
Publications
A Network of Biologically Inspired Rectified Spectral Units (ReSUs) Learns Hierarchical Features Without Error Backpropagation
We introduce a biologically inspired, multilayer neural architecture composed of Rectified Spectral Units (ReSUs). Each ReSU projects a recent window…
arXiv:2512.23146Neurons as Detectors of Coherent Sets in Sensory Dynamics
We model sensory streams as observations from high-dimensional stochastic dynamical systems and conceptualize sensory neurons as self-supervised learners of compact…
arXiv:2510.26955Correcting Non-Uniform Milling in FIB-SEM Images with Unsupervised Cross-Plane Image-to-Image Translation
Motivation Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) is an advanced Volume Electron Microscopy technology with growing applications, featuring thinner…
bioRxiv:2025.09. 29.679411


