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Analysis of the dimensionality of neuronal population dynamics as a function of neuron number

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📈 scaling_analysis 📈

Estimating the "reliable" dimensionality of neuronal population dynamics, and how it scales with the number of recorded neurons

Source code accompanying the article:

Manley, J., Lu, S., Barber, K., Demas, J., Kim, H., Meyer, D., Martínez Traub, F., & Vaziri, A. (2024). Simultaneous, cortex-wide dynamics of up to 1 million neurons reveal unbounded scaling of dimensionality with neuron number. Neuron. https://doi.org/10.1016/j.neuron.2024.02.011.

This codebase is split into two packages: PopulationCoding and scaling_analysis.

PopulationCoding

Documentation Status

PopulationCoding includes some more general purpose functions for dimensionality reduction and other analysis of neurobehavioral data. Check out the full API in the documentation.

scaling_analysis

Documentation Status

scaling_analysis enables estimation of the reliable dimensionality of neuronal population dynamics and its scaling as a function of the number of sampled neurons, as described by Manley et al. Neuron 2024. Check out the demo for examples!

Example data

Interested in large-scale neuronal population dynamics? Example datasets are freely available at https://doi.org/10.5281/zenodo.10403684.

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Analysis of the dimensionality of neuronal population dynamics as a function of neuron number

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