Where does the time go? Another year, another look at my favorite conference: Cosyne. Cosyne is a Computational and Systems Neuroscience conference, this year held in Denver. I think it’s useful to use it each year to assess where the field is and where it may be heading.
First is who is the most active – and this year it is Ken Harris who I dub this year’s Hierarch of Cosyne. The most active in previous years are:
- 2004: L. Abbott/M. Meister
- 2005: A. Zador
- 2006: P. Dayan
- 2007: L. Paninski
- 2008: L. Paninski
- 2009: J. Victor
- 2010: A. Zador
- 2011: L. Paninski
- 2012: E. Simoncelli
- 2013: J. Pillow/L. Abbott/L. Paninski
- 2014: W. Gerstner
- 2015: C. Brody
- 2016: X. Wang
- 2017: J. Pillow
If you look at the most across all of Cosyne’s history, well nothing ever changes.
Plotting the network of the whole history of Cosyne is a mess – there are too many dense connections. Here are three other ways of looking at it. First, only plotting the superusers (people who have 20+ abstracts across Cosyne’s history, click for PDF):
Or alternately, the regulars (10+ abstracts across Cosyne’s history, click for PDF):
And, finally, the regulars + everyone they have collaborated with (click for PDF):
I’d say the long-term structure looks something like the New York Gang (green), the European Crew (purple), the High-Dimensional Deities (blue), the Ecstasy of Entropy (magenta), and some others that I can’t come up with good names for (comments welcome).
Memming asked whether the central cluster was getting more dispersed or less cliquey with time. This is kind of a hard question to answer. If you just look at how large the central connected group is over time the answer is a resounding no. The community is more cohesive and is more connected than ever before.
On the other hand, we can look within that central cluster. How tightly connected is it? If you look at mean path length – how long it takes to get from one author to another, like degrees of Kevin Bacon or an Erdos number (a Paninski number?) – then the largest cluster is becoming more dispersed. Dan Marinazzo suggested looking at the network efficiency as a metric that is more robust to size. Network efficiency is kind of the inverse of path length, where one would mean you can get from one author to another in a single step and 0 means it takes forever.
I now also have two years of segmented abstracts (both accepted and rejected). What are the most popular topics at Cosyne? I used doc2vec, a method that can take a document and embed it in a high-dimensional space that represents the semantic topics that are being used, and then visualized it with t-SNE. The Cosyne Island that you see above is the density of abstracts at each given point. I’ve given the different islands names that represent the abstracts in each of them.
If you look at the words that you see more in 2018’s accepted abstracts they are “movements”, “uncertainty”, “motion”; looks like behavior!
The rejected abstracts are “orientation”, “techniques”, “highdimensional”,”retinal”, “spontaneous” 😦
We can also look at words that are more likely to be accepted in 2018 than 2017 (which are the big gainers):
And the big losers this year versus last year: