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"Can a Neuroscientist Understand a Microprocessor?" argues several points (and is quite an enjoyable read!): 1. Current analytic approaches don't reveal much in
by SapphireSun 10y ago
"Can a Neuroscientist Understand a Microprocessor?" argues several points (and is quite an enjoyable read!):
1. Current analytic approaches don't reveal much insight.
2. The authors advocate for using computer architectures as a synthetic model system for developing new analytic techniques.
3. They aren't arguing that the connectome is useless, in fact they needed the connectome to even begin their analysis.
I think the Wired title is a little overblown. I work in a connectomics lab (software, I'm not a scientist yet so take what I say with a grain of salt), and we've been having enjoyable debates about the paper. It's hardly a "war".
What's kind of interesting about the field of connectomics is that the engineering challenges have been massive enough that it's been hard for many labs to do science with their datasets until recently. Several papers have come out (e.g. a fly visual circuit, two dual mouse visual circuits, a few others), but they generally are findings on relatively small volumes. Thanks to a big grant that created a multi-lab consortium, we are getting closer to doing science with a big volume. We're one year into a five year process which will result in a petabyte size open dataset for the world to use.
Because so few datasets have been adequately reconstructed, and most labs have been obsessed with the reconstruction process, I think in the future, as we do more science, we'll discover better ways to glean insight from the neuroanatomy and physiology traces. It's a new field, so I don't think it's unreasonable to expect that there are new methods to learn. I'm happy to talk about what goes into the reconstruction process. :)
- neuromantik8086 10y agoOut of curiosity, what imaging modality(or modalities) are you using? From your remark it appears that you're working at a very fine level and I'm unfamiliar with the techniques used at the scale (although I have heard mumblings about optogenetics from time to time).
- SapphireSun 10y agoMy lab is one of the reconstruction specialists. We're using electron microscopy (as referenced in the Wired article) to map the ultrastructure of the tissues. I've seen datasets with XY plane (the EM scanning plane) voxels as small as 5nm x 5nm and Z resolution as small as 23nm (though not on the same datasets). Other labs at different phases of the pipeline are working with various kinds of physiological indicators including taking movies of GCaMP (https://en.wikipedia.org/wiki/GCaMP https://en.wikipedia.org/wiki/GCaMP) (a calcium activity indicator) expressing neurons under various behavioral conditions. A glut of calcium ions provide evidence for recent firing of a neuron as calcium is involved in triggering the release of neurotransmitters. If you're interested in methods, here's a paper describing a dataset we focused pretty heavily on (that's not related to the consortium dataset, but paved the way with developing techniques): Briggman, et al. "Wiring specificity in the direction-selectivity circuit of the retina" (http://www.nature.com/nature/journal/v471/n7337/full/nature09818.html http://www.nature.com/nature/journal/v471/n7337/full/nature0...) We later did some science with it ;) JS Kim, et al. "Space–time wiring specificity supports direction selectivity in the retina" http://www.nature.com/nature/journal/v509/n7500/full/nature13240.html http://www.nature.com/nature/journal/v509/n7500/full/nature1... The pipeline has evolved considerably since those papers came out. We're living in exciting times. :)