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
Computational mechanisms of distributed value representations and mixed learning strategies
S. Farashahi, A. Soltani
Learning appropriate representations of the reward environment is challenging in the real world where there are many options, each with…
Nature CommunicationsNeural optimal feedback control with local learning rules
A major problem in motor control is understanding how the brain plans and executes proper movements in the face of…
NeurIPSBridging the Gap: Point Clouds for Merging Neurons in Connectomics
J. Berman, D. Chklovskii, J. Wu
In the field of Connectomics, a primary problem is that of 3D neuron segmentation. Although deep learning-based methods have achieved…
arXiv:2112.02039
