Re-did 3 notebooks

[ArcadeShrimp]

0-Jupyter-Notebook-Introduction

6-Time-Series-Properties: I didn't find much on time series properties so I tried making sections which covered the subpoints discussed during our first meeting

7-Noise-Filter-Band-Misinterpretations: I also didnt find much on noise and filter misrepresentations, heavily referenced 'Parameterizing Neural Power Spectra'

added affiliated files in dat/ img/ utils/

Note: this is in partial fulfillment of #1

[sydney-smith]

0 Jupyter Notebooks

Looks good. Maybe include a link to a general python notebook user guide for keyboard shortcuts, cell types, etc. like this https://www.dataquest.io/blog/jupyter-notebook-tips-tricks-shortcuts/ (just quick example, if you can find a better one, go for it)

6 Time Series Properties

1. I think adding titles and axis labels to your plots would make them a lot easier to understand and keep track of.

2. YAY for citations for noise-generators!

3. I think this tutorial would really benefit from an introduction to power law and colored noise (see https://en.wikipedia.org/wiki/Colors_of_noise). Introducing the power law exponent (β) could be helpful in talking about the slope of the PSD.

4. Many of these definitions assume a signal with components at all frequencies, with a power spectral density per unit of bandwidth proportional to 1/f β and hence they are examples of power-law noise. For instance, the spectral density of white noise is flat (β = 0), while flicker or pink noise has β = 1, and Brownian noise has β = 2.

5. you can disable warnings from MNE using

import warnings
warnings.filterwarnings("ignore")

7 Noise Filter Band Misinterpretations

1. Would it be possible to combine the two age-related backgrounds into a single plot? Or put them in as subplots to make comparison between the two more straightforward.

2. In-text citation for paper should be (Haller 2018) not (Matar 2018)