# Sitemap

A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

Published:

Published:

## CV

This is a page not in th emain menu

## Blogging with Jupyter Notebooks and Jekyll using nbconvert templates

Published:

Here’s a quick (and hopefully helpful) post for those wishing to blog in Jekyll using Jupyter notebooks. As some of you may know, nbconvert can easily convert your .ipynb files to markdown, which Jekyll can easily turn into blog posts for you.

## An academic scientist goes to DevOps Days

Published:

Last week I took a few days to attend DevOpsDays Silicon Valley. My goal was to learn a bit about how the DevOps culture works, what are the things people are excited about and discuss in this community. I’m also interested in learning a thing or two that could be brought back into the scientific / academic world. Here are a couple of thoughts from the experience.

## Combining dates with analysis visualization in python

Published:

Sometimes you want to do two things:

## Dates in python

Published:

As a part of setting up the website for the Docathon I’ve had to re-learn all of my date string formatting rules. It’s one of those little problems you don’t really think about - turning an arbitrary string into something structured like a date - until you’ve actually got to do it.

## Matplotlib Cyclers are Great

Published:

Every now and then I come across a nifty feature in Matplotlib that I wish I’d known about earlier. The MPL documentation can be a beast to get through, and as a result you miss some cool stuff sometimes.

## Brainy Jingle Bells

Published:

This is a quick demo of how I created this video. Check it out below, or read on to see the code that made it!

## The bleeding edge of publishing, Scraping publication amounts at biorxiv

Published:

Per a recent request somebody posted on Twitter, I thought it’d be fun to write a quick scraper for the biorxiv, an excellent new tool for posting pre-prints of articles before they’re locked down with a publisher embargo.

Published:

## 5 things I learned at SciPy

Published:

I’ve finally decompressed after my first go-around with Scipy. For those who haven’t heard of this conference before, Scipy is an annual meeting where members of scientific community get together to discuss their love of Python, scientific programming, and open science. It spans both academics and people from industry, making it a unique place in terms of how software interfaces with scientific research. (if you’re interested the full set of Scipy conferences, check out here.

## Could Brexit have happened by chance?

Published:

As a scientist, watching the Brexit vote was a little bit painful. Though probably not for the reason you’re thinking. No, it wasn’t the politics that bothered me, but the method for making such an incredibly important decision. Let me explain…

## The beauty of computational efficiency

Published:

When we discuss “computational efficiency”, you often hear people throw around phrases like $O(n^2)$ or $O(nlogn)$. We talk about them in the abstract, and it can be hard to appreciate what these distinctions mean and how important they are. So let’s take a quick look at what computational efficiency looks like in the context of a very famous algorithm: The Fourier Transform.

Published:

# NIH Fellowship Success Rates

As I’m entering the final years of graduate school, I’ve been applying for a few typical “pre-doc” fellowships. One of these is the NRSA, which is notorious for requiring you to wade through forests of beaurocratic documents (seriously, their “guidelines” for writing an NRSA are over 100 pages!). Doing so ends up taking a LOT of time.

Published:

## Using Craigslist to compare prices in the Bay Area

In the last post I showed how to use a simple python bot to scrape data from Criagslist. This is a quick follow-up to take a peek at the data.

Published:

## Overview

In this notebook, I’ll show you how to make a simple query on Craigslist using some nifty python modules. You can take advantage of all the structure data that exists on webpages to collect interesting datasets.

## Coherence correlation

Published:

Note - you can find the nbviewer of this post here

## MNE Python

<img class="image" src=https://martinos.org/mne/stable/_static/mne_logo.png alt="Feature Image" style="height: 75px"/>

Neuro electrophysiology visualization and analysis in Python!

## The Docathon

<img class="image" src=https://docathon.github.io/docathon/images/logo.svg alt="Feature Image" style="height: 75px"/>

A week-long global sprint to improve documentation in the open-source community.

## Binder

<img class="image" src=https://mybinder.org/static/logo.svg?v=f9f0d927b67cc9dc99d788c822ca21c0 alt="Feature Image" style="height: 75px"/>

A tool to create interactive and sharable code repositories.

## Zero to JupyterHub for Kubernetes

<img class="image" src=https://zero-to-jupyterhub.readthedocs.io/en/latest/_static/logo.png alt="Feature Image" style="height: 75px"/>

A step-by-step guide to deploying JupyterHub in the cloud.

## Combined process automation for large-scale EEG analysis

Published in Computers in Biology and Medicine, 2012 (paper link)

Introducing a method for analyzing neural oscillations in rat LFP.

Recommended citation: Sfondouris, J. L., Quebedeaux, T. M., Holdgraf, C. R., & Musto, A. E. (2012). Combined process automation for large-scale EEG analysis. Computers in Biology and Medicine, 42(1), 129–34. http://doi.org/10.1016/j.compbiomed.2011.10.017 /files/papers/sfondouris_2012_combined.pdf

## Decoding spectrotemporal features of overt and covert speech from the human cortex

Published in Frontiers in Neuroengineering, 2014 (paper link)

Using machine learning and predictive models to study how the brain uses experience to understand noisy speech.

Recommended citation: Martin, S., Brunner, P., Holdgraf, C. R., Heinze, H.-J., Crone, N. E., Rieger, J. W., … Pasley, B. N. (2014). Decoding spectrotemporal features of overt and covert speech from the human cortex. Frontiers in Neuroengineering, 7(May), 14. http://doi.org/10.3389/fneng.2014.00014 https://www.frontiersin.org/articles/10.3389/fneng.2014.00014/full

## Rapid tuning shifts in human auditory cortex enhance speech intelligibility

Published in Nature Communications, 2016 (paper link)

Using machine learning and predictive models to study how the brain uses experience to understand noisy speech.

Recommended citation: Holdgraf, C. R., de Heer, W., Pasley, B. N., Rieger, J. W., Crone, N., Lin, J. J., … Theunissen, F. E. (2016). Rapid tuning shifts in human auditory cortex enhance speech intelligibility. Nature Communications, 7(May), 13654. http://doi.org/10.1038/ncomms13654 https://www.nature.com/articles/ncomms13654

## Portable learning environments for hands-on computational instruction using container-and cloud-based technology to teach data science.

Published in ACM International Conference Proceeding Series, 2017 (paper link)

This paper covers recent work at UC Berkeley using cloud resources and open-source tools for teaching data analytics.

Recommended citation: Holdgraf, C. R., Culich, A., Rokem, A., Deniz, F., Alegro, M., & Ushizima, D. (2017). Portable learning environments for hands-on computational instruction using container-and cloud-based technology to teach data science. In ACM International Conference Proceeding Series (Vol. Part F1287). https://arxiv.org/pdf/1703.04900.pdf

## Encoding and Decoding Models in Cognitive Electrophysiology

Published in Frontiers in Systems Neuroscience, 2017 (paper link)

A practical methods paper for fitting predictive models of the brain.

Recommended citation: Holdgraf, C. R., Rieger, J. W., Micheli, C., Martin, S., Knight, R. T., & Theunissen, F. E. (2017). Encoding and decoding models in cognitive electrophysiology. Frontiers in Systems Neuroscience, 11. http://doi.org/10.3389/fnsys.2017.00061 https://www.frontiersin.org/articles/10.3389/fnsys.2017.00061/full

## From your laptop to the cloud

Published:

How open-source technologies such as Kubernetes and JupyterHub are making it possible to move analytics workflows from a single laptop to shared computational resources. This opens up possibilities in research, education, and publication. The talk discusses several of these pieces of technology, and covers many interesting case-studies in how it has been used.

## Visualizing the brain with open source tools

Published:

How open-source tools make it possible to visualize the human brain from many different perspectives. I discuss challenges in visualizing something as complicated as the brain, and cover many modern-day open source tools that make this possible, discussing the lessons we’ve learned along the way.

## Zero to JupyterHub on Kubernetes

Published:

A day-long tutorial covering the basics of managing cloud resources, Docker, Kubernetes, and deploying/maintaining a JupyterHub using these tools.