Thursday, February 7, 2013

In-silico hypothesis curator

In my earlier post about the big-ticket billion euro human brain project, I drew a laborious analogy between the HBP and the large hadron collider (LHC). I suggested that to maximally take advantage of the proposed mega simulation of the brain, we must ask ourselves what are tens or hundreds of standard models, we need to look for in the properties of the simulator.

For example, a future series of experiments that might involve a little bit of everything: say pharmacological manipulation, functional imaging (fMRI), microscopic of imaging of neural circuits (EM), extracellular electrophysiology, and psychophysics, and that would be hard/impossible to run in a single lab, could be run on the simulated brain. In a potential scenario the in-silico experimentalist could download a single instance of the "live simulated brain" (or even just a single cortical region or slice, depending on the hypothesis), run programs that mimic a pharmacological intervention, and then run other programs that provide infinite-SNR electrophysiology or microscopy data.

I feel that the best way to engage with the HBP would be to curate a transparent, ranked, well-debated, and amendable list of top 100 hypotheses to test in-silico, given the features and limitations of the platform.

I propose a workshop leading to a magazine or a journal special issue, starting with an open call to neuroscientists looking to scale their hypotheses, worded as follows: 

If we could record from all neurons in the brain and know all about its structural connectivity, OR EQUIVALENTLY if we could access molecular/ celluar-scale activity with infinite SNR (from a whole-brain simulator), what kinds of questions would we be asking? How would we scale our hypothesis to match the scaling of technology?

The idea is to source the following classes of talks and articles:

1. Invite supporters of the in-silico platform to submit blue-sky ideas for future great experiments. The set of future great experiments must span a diverse range, from the lowest to the highest levels of brain organization. Questions could include, for example:

    • How do neurons acquire tuning properties and wiring over developmental time scales?
    • How is gene expression in a particular brain area influenced by learning, and how does that in-turn influence long-term memory storage and recall?
    • How are probabilistic computations achieved within and across circuits?
    • How does slow-wave sleep spread from single neurons across the whole brain?
2. Invite contrarians to argue that we can learn all we need to from classic integrative experimental neuroscience.

3. Invite historians of science and simulation-driven scientists from other disciplines—statistical physics comes to mind—to describe the nature of fundamental discoveries have been made from large-scale computer simulations.

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