2020: A Moderately Bemused Review of the Year in Neuroscience
By: Mark Humphries
Tags: Artificial Intelligence, Neuroscience, Science, Psychology

The world moved online, and neuroscience was no different. The Neuromatch conferences led the way, kicking off in early May with a computational neuroscience meeting, and graduating to a full-on replica of the (cancelled) SfN Annual Meeting in late October, right down to the titles of its “Themes”. WorldWideNeuro set up a one-stop shop for all the one-off seminars and talks happening online around the world. Much debate about whether these were better or worse than doing stuff in person. They are both, of course: better access for a more diverse audience; worse for actually meeting people and doing the kinds of things that create bonds between people. But there’s little doubt that how we disseminate our science will be changed forever, with online, virtual events proving their worth.

The Neuromatch Academy, an online summer school for computational neuroscience, was truly an awesome achievement. The sheer scale and quality of the content was breathtaking — and still is: you can access it all, for free. As was the sheer scale of the number of faculty involved. My involvement was peripheral, a mentor for two groups working fiercely hard on their projects, but was still a lovely little vignette of how the Academy opened up the world, me in the UK mentoring one group in China and one split between Australia and New Zealand. Would be wonderful to see it again next year, if any of the organisers remain capable of seeing the words “Neuromatch Academy” without their eye involuntarily twitching.

Fascinating neuroscience research kept appearing print, oblivious to the world outside. Special mention for the paper from Simon Peron and colleagues in Karel Svoboda’s on the local circuits in cortex, for two remarkable things. For one, being a proper, straight-up test of causality in systems neuroscience by identifying single neurons with strong coding of the outside world, and then specifically killing each of them to see if they really were carrying the code for the population. And for another, the computational model driving the research is Figure 1 of the paper! This was one of the few neuroscience papers I’ve ever read that looked like hard science as we aspire to do it: derive predictions from a model, and causally test them in experiments. Special mention too for Srdjan Ostojic, his lab, and their collaborators (including Omri Barak) who seemingly overnight unleashed on us an entire research programme on when, how, and why networks of neurons will have low-dimensional structure, giving compelling answers to some of the deep questions of systems neuroscience.

Some chilling papers appeared too. The NARPS paper showed us how seventy teams of analysts looking at the same set of fMRI data agreed on almost nothing about which hypotheses those data supported. As I wrote earlier this year, nothing about the failures in this paper were specific to fMRI research — the authors were showing us how any area of science with complex data processing and analysis pipelines could have teams of brilliant, smart people end up at polar opposite conclusions from the exact same data.

And a stuff-of-nightmares paper for any modeller showed that a widely-used model for estimating the dynamics of the evolution of existing species could produce an infinite number of evolutionary trees consistent with collected data. So any inferences made from that model are garbage. Cue a bonfire of papers, and computational people from all other disciplines muttering “there but for the grace of god go I” under their breath.

COVID-19 research didn’t have sole claim to a tranche of wonderfully terrible and over-hyped papers this year, of course — the lure of scientific fame and glory still brings out the overreachers and the just plain bonkers, and neuroscience was no exception. We learnt that crows have consciousness apparently, just because when they report seeing a faint grey square we can detect that imminent report in their neural activity. Which amounts to “brain has memory of seeing a thing”. Which we already knew ought to be in their brains, because if that activity wasn’t somewhere in their brains then they wouldn’t make that decision. Unless crows use their spleens to make choices. Now that would be worth publishing in Science.

And fittingly for a year spent for many of us in a state of repose, it was a good year for reading about neuroscience. Matthew Cobb’s “The Idea of the Brain” kicked the year off with its deep scholarship of the history of neuroscience worn lightly and entertainingly, and ended the year as The Times (of London) book of the year in Ideas & Philosophy. Serious brain books doing seriously well. Ashley Juavinett’s “So You Want To Be A Neuroscientist” debuted in November, and its lucid, lovely guidance should be immediately gifted to anyone you know who is already a neuroscientist, desperately wants to be one, or once remarked in passing that brains are kinda cool. And your parents, so they can find out what it is you do for a living.