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How a happy moment for neuroscience is a sad moment for science

Systems neuroscience is celebrating a landmark, but one that shows the way we do science is broken.

Mark Humphries
Aug 1, 2016 · 4 min read
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The Allen Institute for Brain Science released a landmark set of data in June. Entitled the “Allen Brain Observatory”, it contains a vast array of recordings from the bit of cortex that deals with vision, while the eyes attached to that bit of cortex were looking at patterns. Not too exciting, you say. In some respects you’d be right: some mouse brain cells became active when shown some frankly boring pictures. Experimental neuroscience is eternally lucky that mice have a very high boredom threshold.

The release of this data took a privately funded institute. It could not have come from a publicly-funded scientist. It is a striking case-study in how modern science is worryingly broken, because it prioritises private achievement over the public good.

You see, it’s not the what, but the how. These data are the first complete set of neural activity recordings released before publication. No papers preceded it; not even a report. Nothing. Just: here you go guys, the fruits of the joint labour of around 100 people over 4 years.

And all available to anyone, for free. Anyone at all. You, in fact – if you fancy being a neuroscientist for a day, go take a look at it. I’ll just wait here.

What did you find? If you found something new to science, or replicated some older work, go ahead and write it up for publication. The Allen Institute claim no jurisdiction over the data at all. It gives you that warm, fuzzy feeling inside.

Most scientists would never even contemplate such a manoeuvre. Research needs grants to fund it, and grants need papers. Promotion needs papers. Tenure need papers. Postdoc positions need papers. Even PhD studentships need papers now, God help us all. Everything needs bloody papers. (Which works well for people like me who enjoy writing; but is a distinct disadvantage for talented scientists who don’t.)

(Last semester, we even got a Faculty-wide email encouraging us to write up our Master’s students’ project work for publication. Because what science needs right now is more unfinished crap.)

Data makes papers. Data makes grants. Who would ever release data without first writing up a paper? Who would fund grants to work on data that you’ve already released? Which committees recognise “releasing data” as a principal output when looking for a new job candidate or a promotion? Or assessing the research quality of a university?

This all means I’m feeling rather ambivalent about the “Brain Observatory” data. On the one hand, I deeply admire that the philanthropic principles of the Allen Institute extend to giving away their data for free. On the other hand, I’m deeply sad that it takes a billionaire software designer’s philanthropy to make such a thing happen. The Allen Institute is supported by Paul Allen, erstwhile founding partner of Microsoft with Bill Gates, making it an entirely private, self-sufficient research institution. Which brings with it a more corporate approach to science: dedicated teams of specialists solving technical issues, or collecting specific types of data. Their performance targets are tight deadlines for reaching project milestones, rigour of the methods, and quality of the resulting science.

Their targets are not papers. Nor money.

So, landmark moment for neuroscience that it is, the Allen Institute’s “Brain Observatory” is also a case study in how modern science’s incentives are all wrong. If we only measure the quality of someone’s science by the amount of money they accrue and the number of “impactful” papers they produce, then by definition we are not measuring the quality and rigour of the science itself. It is sad that an entirely private research institute can show up so starkly the issues of publicly-funded science.

But this also offers a case study in the solutions to science’s incentive problem. The Allen Institute have shown repeatedly that quality and rigor of science can be prioritised over quantity of output and money as measures of “success”. Others have also shown how dedicating many resources to long term projects can produce deep insights and highly beneficial tools for neuroscience. For example, Jeremy Freeman’s team producing a suite of neuroscience analysis tools for high performance computing platforms; or Christian Machens’ team developing their general neuron population analysis framework, and applying it a vast range of datasets.

What all these have in common is their origin in dedicated, privately funded research institutes. These researchers are somewhat immune to the science incentive problem that pervades universities. This is because universities drive the quest for money. Research grants pay a lot towards universities’ infrastructure, services, and administrative people. So universities want grants. And papers, as noted above, play a key role in getting grants: so they want papers too. (In the UK we also have the direct equation that papers = money, thanks to the REF).

A solution is thus that universities should adopt the private institute model: stop pressurising researchers to obtain grants and papers. Instead they could spend their own money sustaining the research programmes of their own researchers (rather than on, say, yet more bloody buildings , or administrators). This would remove the pressure to get short term grants, but leave open the need for high value grants for major programmes of work. Reward quality and rigour, not output. Reward the work effort, not the luck of the draw in where the paper finally came out.

There, solved. Next week: how nuclear disarmament can be achieved with a teaspoon and an angry badger.

(Read Vox’s great piece on the problems facing science here)

Want more? Follow us at The Spike

Twitter: @markdhumphries

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