Statistical Analysis of Neural Data

We develop statistical models and open-source computational tools to extract insights from neural data. We are particularly interested in characterizing flexibility and variability in neural circuits—e.g., how do the dynamics of large neural ensembles change over the course of learning a new skill, during periods of high attention or task engagement, or during development and aging.

Summarizing these processes even on a descriptive level is a difficult and unsolved challenge in need of new analysis tools.

Laboratory for Neural Statistics website

Publications

June 29, 2026

The Squealer: Sensification of model exploration and model misfit

A. Gelman, Andrew H. Jaffe, Eliot Carlson, P. Greengard

We introduce a method for visual and auditory feedback when exploring the fit of a model to data. Starting with…

arXiv:2606.29842

June 22, 2026

Similarity of Neural Network Representations in Superposition

Sunny Liu, Habon Issa, André Longon, Liv Gorton, Meenakshi Khosla, A. Williams, David Klindt

Comparing internal representations is a central goal in neuroscience and machine learning, but standard linear alignment metrics (Representational Similarity Analysis,…

arXiv:2604.00208

May 14, 2026

How Data Augmentation Shapes Neural Representations

Tianxiao He, A. Williams, S. Harvey

Data augmentation is widely recognized for improving generalization in deep networks, yet its impact on the geometry of learned representations…

arXiv:2605.15306

Group Leader

Alex Williams, Ph.D.

Associate Research Scientist, Statistical Analysis of Neural Data

Alex is jointly appointed as an Assistant Professor in the Center for Neural Science at NYU and an Associate Research Scientist / Project Leader at the Flatiron Institute.

Hanna Dettki

Research Analyst, Statistical Analysis of Neural Data and NeuroRSE

Hanna is a Research Analyst at the Center for Computational Neuroscience.

Philip Greengard, Ph.D.

Associate Research Scientist, Statistical Analysis of Neural Data

Philip is an Associate Research Scientist in Flatiron’s Center for Computational Neuroscience.

Sarah Harvey, Ph.D.

Flatiron Research Fellow, Statistical Analysis of Neural Data

Sarah Harvey is a Flatiron Research Fellow in the Statistical Analysis of Neural Data at the Center for Computational Neuroscience.

Kushal Kolar

Predoctoral Researcher, Statistical Analysis of Neural Data

Kushal Kolar is a Ph.D. student at NYU in Biomedical Engineering.

Andrew Mah, Ph.D.

Flatiron Research Fellow, Statistical Analysis of Neural Data

Andrew Mah joined the Flatiron Institute’s Center for Computational Neuroscience in 2025 as a Flatiron Research Fellow.

Arina Medvedeva

Research Analyst, Statistical Analysis of Neural Data

Arina Medvedeva joined the Center for Computational Neuroscience in 2024 as a research analyst in the Statistical Analysis of Neural Data group led by Alex Williams.

Joshua Pughe-Sanford, Ph.D.

Flatiron Research Fellow, Statistical Analysis of Neural Data

Joshua Pughe-Sanford is a Flatiron Research Fellow in the Center for Computational Neuroscience.

Aramis Tanelus

Guest Researcher, Statistical Analysis of Neural Data

Aramis Tanelus is a guest researcher at the Flatiron Institute researching artificial neural networks for sound source localization in collaboration with Alex Williams.

Sarah Jo Venditto, Ph.D.

Associate Research Scientist, NeuroRSE and Statistical Analysis of Neural Data

Starting in 2024, Sarah Jo is an Associate Research Scientist for the Center for Computational Neuroscience, where she supports and develops open-source software for the center and with the Statistical Analysis of Neural Data group.