Research

We design experiments and tools to understand large-scale neural computations.

spikes colored by amplitude along probe

Spike sorting with Kilosort4

Machine learning
Tools
Analysis tool for accurate spike sorting, which is the computational process of extracting the firing times of single neurons from recordings of local electrical fields.

Marius Pachitariu, Shaswat Sridhar, Jacob Pennington, Carsen Stringer

unsupervised and supervised learning

Distinct streams for supervised and unsupervised learning in the visual cortex

Vision
Thousands of neurons
Behavior
Unsupervised learning - exposure to stimuli without rewards - drives large changes in neural activity in visual cortex, particularly in higher order medial visual areas.

Lin Zhong, Scott Baptista, Rachel Gattoni, Jon Arnold, Daniel Flickinger, Carsen Stringer, Marius Pachitariu

facemap

Facemap: a framework for modeling neural activity based on orofacial tracking

Behavior
Thousands of neurons
Machine learning
Tools
Analysis tool for tracking mouse face keypoints and relating them to large-scale neural activity, using convolutional neural networks.

Atika Syeda, Lin Zhong, Renee Tung, Will Long, Marius Pachitariu†, Carsen Stringer†

rastermap visualization of neural activity during a virtual reality task

Rastermap: A Discovery Method for Neural Population Recordings

Thousands of neurons
Machine learning
Tools
Analysis tool for large-scale neural data which allows users to explore dynamical and spatial relationships among neurons.

Carsen Stringer, Lin Zhong, Atika Syeda, Fengtong Du, Maria Kesa, Marius Pachitariu

retrained network vs original cellpose network on fluorescence and live cell image.

Cellpose 2.0: how to train your own model

Segmentation
Machine learning
Tools
Software for users to quickly and easily create accurate segmentation models for their own data.

Marius Pachitariu, Carsen Stringer

dimensionality of spontaneous activity increases across development, becomes more related to neural activity, and orthogonal to stimulus-driven activity.

Not so spontaneous: Multi-dimensional representations of behaviors and context in sensory areas

Thousands of neurons
Behavior
Spontaneous activity across species is related to motor movements. These motor-driven patterns emerge during development, diverging from sensory-driven activity.

Lilach Avitan, Carsen Stringer

highly precise encoding of visual stimuli

High precision coding in visual cortex

Vision
Thousands of neurons
Visual cortex encodes stimuli highly precisely, far surpassing behavioral precision in mice and humans. In a task, visual cortex does not contribute to behavioral variability.

Carsen Stringer, Michalis Michaelos, Dmitri Tsyboulski, Sarah E. Lindo, Marius Pachitariu

Cellpose: a generalist algorithm for cellular segmentation

Segmentation
Machine learning
Tools
Accurate deep learning-based cellular segmentation tool that works for a wide variety of images, and includes an easy to use GUI.

Carsen Stringer, Tim Wang, Michalis Michaelos, Marius Pachitariu

neural activity reconstructed from subsets of principal components, and sorted by rastermap

High-dimensional geometry of population responses in visual cortex

Vision
Thousands of neurons
Neural population activity in response to natural images is high-dimensional, and the activity correlations obey a power law of 1/n.

Carsen Stringer*, Marius Pachitariu*, Nicholas Steinmetz, Matteo Carandini†, Kenneth D Harris†

neural activity predicted from the principal components of mouse face motion

Spontaneous behaviors drive multidimensional, brainwide activity

Thousands of neurons
Behavior
Machine learning
Ongoing neural activity is high-dimensional and driven by the mouse’s behavior. These behavioral representations are orthogonal to stimulus-driven responses.

Carsen Stringer*, Marius Pachitariu*, Nicholas Steinmetz, Charu Bai Reddy, Matteo Carandini†, Kenneth D Harris†

neuron traces and masks

Suite2p: beyond 10,000 neurons with standard two-photon microscopy

Thousands of neurons
Segmentation
Machine learning
Tools
Suite2p enables fast and accurate processing of large-scale neural recordings.

Marius Pachitariu, Carsen Stringer, Sylvia Schröder, Mario Dipoppa, L. Federico Rossi, Matteo Carandini, Kenneth D. Harris

neuronal network simulations fit to neural population activity

Inhibitory control of correlated intrinsic variability in cortical networks

Neural modeling
Behavior
Cortical networks exhibit large-scale fluctuations which creates noise correlations that impact sensory coding. Modeling and data analysis show that inhibition can control these fluctuations.

Carsen Stringer*, Marius Pachitariu*, Nicholas Steinmetz, Michael Okun, Peter Bartho, Kenneth D Harris, Maneesh Sahani, Nicholas Lesica
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