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