nma_cn_flow_state

Neuromatch Academy 2021 Computational Neuroscience analysis of Steinmetz 2019 data.

Data can be found here: https://figshare.com/articles/dataset/Dataset_from_Steinmetz_et_al_2019/9598406

Project guidelines:

1. finding a phenomenon and a question to ask about it What's different about a mouse not looking/correct/incorrect? Is the task difficulty represented in the data, e.g. dimensionality. How is this information reflected between brain areas and the flow between it? What is the underlying structure, and how is it related to different times in the trial/task difficulty?

2. understanding the state of the art PCA, dimensionality reduction, phase synchrony, phase amplitude coupling

3. determining the basic ingredients Timing of when different parts of the trials occur, task difficulty based on contrast levels, spike counts, LFP downsampled to 100 Hz

4. formulating specific, mathematically defined hypotheses Mice make incorrect trials, and there must be some difference in the underlying structure. We believe we can find differences in the underlying structure and flow of information between brain areas based on task diffculty and correct, incorrec, and no go trials

5. Selecting the toolkit

6. Planning / drafting the model

7. Implementing the model

8. Completing the model

9. testing and evaluating the model

10. publishing the model