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Neuromatch Computational Neuroscience- Final Project

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Dataset

The Stringer dataset contains simultaneous recordings of 10,000 or 20,000 neurons from a mouse's visual cortex either during the presentation of gratings or during spontaneous behaviours like running, whisking and sniffing.

Main Motivation

  • Predict the pupil area changes over time from the neural activity obtained from a V1 neuronal population from a mouse in a dark environment.
  • Evaluate different linear and non-linear decoder models for accuracy

Model Evaluations

Linear Models

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Non-Linear Models

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Decoding Pupil Area over Time

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References

[1] Stringer, C., Pachitariu, M., Steinmetz, N., Reddy, C. B., Carandini, M., & Harris, K. D. (2019). Spontaneous behaviors drive multidimensional, brainwide activity. Science. https://doi.org/aav7893

[2] He, K., Zhang, X., Ren, S., & Sun, J. (2015). Deep Residual Learning for Image Recognition. ArXiv. /abs/1512.03385

[3] Chen, T., & Guestrin, C. (2016). XGBoost: A Scalable Tree Boosting System. ArXiv. https://doi.org/10.1145/2939672.2939785

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Project for neuromatch academy coursework

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