# Harnessing plasticity

Author’s note: This was an old journal entry from August 3, 2014.

An interesting article made it to the front page of the /r/techonology subreddit today about using vagal nerve stimulation (VNS) for the treatment of tinnitus. There seems to be a lot of redditors suffering from tinnitus, considering the top comment to for the practically every hearing-related submission to /r/science seems to be about tinnitus (see 1, 2, 3, and 4). I don’t know if this is from a preponderance of tinnitus sufferers on reddit, or whether redditors with tinnitus are just really vocal. Perhaps both.

Back to the more interesting issue. How crazy is it that VNS can potentially alleviate symptoms of tinnitus!? I read a bit about the proposed mechanism, namely modulating cortical plasticity via cholinergic projections from the nucleus basalis, which receive some input from the solitary nucleus. This certainly seems plausible, but it just seems crazy that stimulating the vagus nerve can have an effect at all on tuning in the auditory cortex, as shown in this paper. The treatment in that study involved pairing the VNS with tones, so it seems like there needs to some sort of interaction of bottom-up and top-down mechanisms to induce plastic changes. I find this interesting for two reasons:

1. A method as crude as electrically stimulating the entire vagus nerve manages to successfully invoke the diffuse cholinergic projections to cortex, considering the vagus nerve performs so many different functions, and
2. Activation of these very diffuse projections can have such a specific effect on one part of the brain.

Now this raises a lot of interesting questions. What other effects does VNS have? From the list of other uses on Wikipedia, potentially a lot. If the whole neocortex is made more plastic, are there system-wide changes going on, or does there need to be the bottom up input as well? Are the normal functions of the vagus nerve disrupted in any way? I think these types of questions are indicative of how much more we have to understand about the brain. You might argue (and I might agree) that perhaps it shouldn’t matter as long as it helps people and the negative side effects we observe are minimal. But that’s just it. How are we supposed to observe all (or at least an acceptable number) of the possible side effects if we have such a minimal understanding of the system?

There’s an interesting Latin maxim: ignoramus et ignorabimus (“we do not know and will not know”), credited to the 19th century German physiologist Emil du Bois-Reymond in Über die Grenzen des Naturerkennens (“On the limits of our understanding of nature”). This saying seems pretty defeatist, but sometimes I feel this applies to neuroscience, even if I don’t like especially like it. I tend to prefer David Hilbert’s retort: “Wir müssen wissen — wir werden wissen!” (“We must know — we will know!”). Of course, Hilbert also wanted to find a complete and consistent set of axioms for mathematics, which we now know is impossible (thanks Gödel!). Perhaps we could revise it to: “We really want to know, and we’ll probably know more in the future than now!” Not as catchy though.

# Word Clouds!

Author’s note: This is an old journal entry from July 29, 2014 that I never did anything with, so now it’s going to become my first blog post.

I recently discovered Wordle, a site which allows you to create beautiful word clouds, a type of graphic consisting of words where the font size is proportional to how often the word appears in a given body of text. I thought it would be fun trying to use Wordle to analyze some abstract books from scientific conferences, but that may have been a bit overambitious. Who knew you could crash Chrome by trying to copy and paste 15,000+ pages of text?

Undeterred (i.e. too much time on my hands), I decided to write some Matlab code to make my own. This allowed me to analyze very large bodies of text and also have more control in the final graphic creation. I had to learn some regular expressions as well as use Matlab’s Computer Vision Toolbox in a manner in which it certainly wasn’t designed, but hey, it works. Below are two word clouds, showing the most common 200 words in the ARO 2014 and SfN 2013 abstract books, respectively. ARO stands for the Association of Research in Otolaryngology, and it’s definitely the largest conference devoted to hearing research. It pales in size, however, compared to the annual SfN meeting (Society for Neuroscience), which draws in about 30,000 people.

Word cloud from ARO 2014

Word cloud from SfN 2013

To make the word clouds, I simply counted word frequencies like Wordle, but in addition to ignoring common English words (“the”, “and”, etc.), I also removed nonspecific scientific words like “abstract” and “methods.” The result certainly isn’t as pretty as those from Wordle, but look, a brain! and sort of a cochlea! The clouds from Wordle have much nicer inter-word spacing due to the way they handle collision detection, but I had to be more flexible since I wanted the words to fit into an arbitrary shape.

Observations so far? Despite obtaining the #3 spot on the ARO cloud, the word “auditory” barely made it into the SfN cloud, achieving spot #196 and losing terribly to “visual” at #47. Oh well, at least the sensory neuroscientists can be bitter together, since they were beaten by other systems, namely #19 “memory” and #21 “motor.” In case you were wondering, the word “neurons” was used 17,452 times in the SfN abstract book, an order of magnitude increase from the #1 word in the ARO cloud: “cells,” which was used 1,846 times. This isn’t all that surprising given the huge size of SfN relative to ARO.

Lastly, for a summary of the data, here are some basic counts on the text analysis.