Neural Circuits and Algorithms

A complex diagram incorporating representations of neurons.

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

Connectomics Read More

Digital illustration of a Hebbian and anti-Hebbian network

Theory Read More

Automatic detection of neurons and neuronal processes contained in the data streams generated by brains of test subjects. Here, the pink and yellow objects are active neurons or neuronal processes detected in the brain of a mouse engaged in a behavioral task

Calcium Imaging Data Analysis Read More

Publications

June 15, 2026

Stochastic Thermodynamics of Score Matching in Diffusion Models

X. Ding, H. T. Quan, Y. Tu

Score-based diffusion models are a powerful class of generative AI systems capable of sampling from complex, high-dimensional probability distributions. Their…

arXiv:2606.17252

May 29, 2026

Diffusion models learn underlying trends in actomyosin networks and predict behavior at unseen filament turnover

Elisabeth Rennert, A. K. Behera, Yuqing Qiu, Suriyanarayanan Vaikuntanathan

Generative diffusion models have demonstrated an ability to produce novel images sampled from the learned underlying data distribution. These models…

bioRxiv:2026.05.26.727950

April 20, 2026

Reproducibility and model-selection stability in connectome-constrained circuit modeling

Christos Karaneen, E. Schomburg, D. Chklovskii

Connectome-constrained neural network models aim to link anatomical connectivity with functional computation by training networks whose architectures reflect biological circuits.…

bioRxiv: 2026.04. 18.717873

News & Announcements

Biological Brains Inspire a New Building Block for Artificial Neural Networks

An artist's illustration of a digital hand and a human hand each drawing the other.

New Computational Model of Real Neurons Could Lead to Better AI Rachel Tompa

Researchers Create First-Ever Map of a Single Animal’s Early Visual System By Thomas Sumner

Software

CaImAn Python

Computational toolbox for large scale Calcium Imaging Analysis, including movie handling, motion correction, source extraction, spike deconvolution and result visualization.

CaImAn-MATLAB

Complete Matlab pipeline for large scale calcium imaging data analysis.

Group Members

Dmitri ‘Mitya’ Chklovskii, Ph.D.

Group Leader, Neural Circuits and Algorithms

The goal of Mitya Chklovskii’s research is to reverse engineer the brain on the algorithmic level. Informed by anatomical and physiological neuroscience data, his group develops algorithms that model brain computation and solve machine learning tasks.

Agnish Kumar Behera, Ph.D.

Flatiron Research Fellow, Neural Circuits and Algorithms

Agnish Kumar Behera is a Flatiron Research Fellow in the Center for Computational Neuroscience.

Nourah Boujaber-Diederichs

Associate Research Analyst, Neural Circuits and Algorithms

Nourah Boujaber-Diederichs joined the foundation in January 2025 as an Associate Research Analyst.

Xuehao Ding, Ph.D.

Flatiron Research Fellow, Neural Circuits and Algorithms

Xuehao Ding joined the Simons Foundation in April 2025 as a Flatiron Research Fellow.

Amy Hong

Associate Research Analyst, Neural Circuits and Algorithms

Amy is an Associate Research Analyst at CCN.

Philip Kidd, Ph.D.

Flatiron Research Fellow, Neural Circuits and Algorithms

Philip Kidd is a Flatiron Research Fellow in the Neural Circuits and Algorithms group at the Center for Computational Neuroscience.

Aviv Ratzon, Ph.D.

Flatiron Research Fellow, Neural Circuits and Algorithms and Statistical Biophysics

Aviv Ratzon is a Flatiron Research Fellow at the Center for Computational Neuroscience.

Erik Schomburg, Ph.D.

Research Scientist, Neural Circuits and Algorithms

Erik Schomburg joined the Flatiron Institute as a Research Scientist to develop and maintain software for the Center for Computational Neuroscience.

Ruo-Yu Shang, Ph.D.

Flatiron Research Fellow, Neural Circuits and Algorithms

Ruo-Yu Shang is a Flatiron Research Fellow in the Center for Computational Neuroscience.

Aya Shinomiya

Research Analyst, Neural Circuits and Algorithms, CCN

Aya Shinomiya joined the Flatiron institute as a Research Analyst in August 2021.

Kazunori Shinomiya, Ph.D.

Research Scientist, Neural Circuits and Algorithms, CCN

Kazunori Shinomiya is a Research Scientist in the Neural Circuits and Algorithms group working on the wasp brain connectome project.