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neural activity in mouse visual cortex predicted by eye movements versus orofacial movements

Orofacial behaviors, not eye movements, govern neural activity in mouse visual cortex

Vision

Thousands of neurons

Behavior

Machine learning

Orofacial movements predict the majority of neural activity in mouse visual cortex related to behavior.

Atika Syeda, Miguel Angel Núñez-Ochoa, Lin Zhong,Marius Pachitariu^†, Carsen Stringer^†

predictive coding surprise response in visual cortex

Spatial predictive coding in visual cortical neurons

Vision

Thousands of neurons

Behavior

Image novelty, not temporal novelty, drives mismatch responses in visual cortex.

Qingqing Zhang, Sverre Grødem, Alexa Gracias, Kristian K Lensjø, Marianne Fyhn, Carsen Stringer^†, Marius Pachitariu^†

A simplified minimodel of visual cortical neurons

Vision

Thousands of neurons

Machine learning

Simplified and interpretable “minimodels” are sufficient to explain complex visual responses in mouse and monkey V1.

Fengtong Du, Miguel Angel Núñez-Ochoa, Marius Pachitariu^†, Carsen Stringer^†

Unsupervised pretraining in biological neural networks

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^†

image restoration of various cellular images

Cellpose3: one-click image restoration for improved cellular segmentation

Segmentation

Machine learning

Tools

Software for image restoration that works across many cell types and imaging modalities.

Carsen Stringer, Marius Pachitariu

schematic of neural recordings from mouse V1, whole-brain, and hippocampus; neural activity traces from the population, showing more correlated activity in V1 and whole-brain recordings versus more decorrelated activity in hippocampus

A critical initialization for biological neural networks

Thousands of neurons

Neural modeling

Neural recordings resemble linear dynamical systems governed by a symmetric connectivity matrix.

Marius Pachitariu, Lin Zhong, Alexa Gracias, Amanda Minisi, Crystall Lopez, 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

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

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^†

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^†

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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