Lars Buesing

Currently, I am a research fellow at the Grossman Center for the Statistics of Mind and the Department of Statistics at Columbia University.
My CV is here.

Office Address

Department of Statistics
Columbia University
Office 930
1255 Amsterdam Avenue
New York, NY 10027
Email: lars [at]

Code package for analyzing high-dimensional recordings of neural activity

I've written, together with Jakob Macke, a Matlab toolbox for analyzing high-dimensional recordings of neural activity.
It contains implementations of the following methods:
Here are a couple of example applications for the toolbox:

The git repository can be found here.

Research Interests and Publications

Structured latent variable models for inferring circuit structure from multi-cell activity recordings

Modelling & Analysis of Recordings from Neural Populations

In collaboration with Maneesh Sahani and Jakob Macke, I have been working on probabilistic methods for analyzing simultaneous recordings from multiple neurons such as multi-electrode recordings. I am especially interested in latent variable models as they allow for principled ways of dimensionality reduction and smoothing of recorded data, which is often high-dimensional and apparently noisy.

Functional Models of Neural Mircocircuits

I am also interested in functional, "top-down" models of single neurons and neural microcircuits. This research is driven by the widely acknowledge fact that neural system must "reason", e.g. detect causes of sensory percepts, based on ambiguous and noisy observations of the world. Together with collaborators form TU Graz, I have been exploring the idea that neural microcircuits perform inference computations by sampling from hypotheses that are consistent with the observed data.

Models of Synaptic Plasticity

Learning is believed to rely to great extend on the plasticity of synaptic connections between neurons. Together with colleagues from the LCN at the EPFL in Lausanne I have been working on phenomenological models of synaptic plasticity.