Studying the brain at the mesoscale

It i snot entirely clear that we are going about studying the brain in the right way. Zachary Mainen, Michael Häusser and Alexandre Pouget have an alternative to our current focus on (relatively) small groups of researchers focusing on their own idiosyncratic questions:

We propose an alternative strategy: grass-roots collaborations involving researchers who may be distributed around the globe, but who are already working on the same problems. Such self-motivated groups could start small and expand gradually over time. But they would essentially be built from the ground up, with those involved encouraged to follow their own shared interests rather than responding to the strictures of funding sources or external directives…

Some sceptics point to the teething problems of existing brain initiatives as evidence that neuroscience lacks well-defined objectives, unlike high-energy physics, mathematics, astronomy or genetics. In our view, brain science, especially systems neuroscience (which tries to link the activity of sets of neurons to behaviour) does not want for bold, concrete goals. Yet large-scale initiatives have tended to set objectives that are too vague and not realistic, even on a ten-year timescale.

Here are the concrete steps they suggest in order to from a successful ‘mesoscale’ project:

  1. Focus on a single brain function.
  2. Combine experimentalists and theorists.
  3. Standardize tools and methods.
  4. Share data.
  5. Assign credit in new ways.

Obviously, I am comfortable living on the internet a little more than the average person. But with the tools that are starting to proliferate for collaborations – Slack, github, and Skype being the most frequently used right now – there is really very little reason for collaborations to extend beyond neighboring labs.

The real difficulties are two-fold. First, you must actually meet your collaborators at some point! Generating new ideas for a collaboration rarely happens without the kind of spontaneous discussions that arise when physically meeting people. When communities are physically spread out or do not meet in a single location, this can happen less than you would want. If nothing else, this proposal seems like a call for attending more conferences!

Second is the ad-hoc way data is collected. Calls for standardized datasets have been around about as long as there has been science to collaborate on and it does not seem like the problem is being solved any time soon. And even when datasets have been standardized, the questions that they had been used for may be too specific to be of much utility to even closely-related researchers. This is why I left the realm of pure theory and became an experimentalist as well. Theorists are rarely able to convince experimentalists to take the time out of their experiments to test some wild new theory.

But these mesoscale projects really are the future. They are a way for scientists to be more than the sum of their parts, and to be part of an exciting community that is larger than one or two labs! Perhaps a solid step in this direction would be to utilize the tools that are available to initiate conversations within the community. Twitter does this a little, but where are the foraging Slack chats? Or amygdala, PFC, or evidence-accumulation communities?

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