Picking the Connectome Data Lock by Nicole Hemsoth
From the post:
Back in 2005, researchers at Indiana University and Lausanne University simultaneously (yet independently) spawned a concept and pet term that would become the hot topic in neuroscience for the next several years—connectomics.
The concept itself isn’t necessarily new, even thought the use of “connectomics” in popular science circles is relatively so.
A hybrid between the study of genomics (the biological blueprint) and neural networks (the “connect”) this term quickly caught on, including with large organizations like the National Institutes of Health (NIH) and its Human Connectome Project.
For instance, the NIH is in the midst of a five-year effort (starting in 2009) to map the neural pathways that underlie human brain function. The purpose is to acquire and share data about the structural and functional connectivity of the human brain to advance imaging and analysis capabilities and make strides in understanding brain circuitry and associated disorders.
And talk about data… just to reconstruct the neural and synaptic connections in a mouse retina and primary visual cortex involved a 12 TB data set (which incidentally is now available to all at the Open Connectome Project).
Mapping the connectome requires a complete mapping process of the neural systems on a neuron-by-neuron basis, a task that requires accounting for billions of neurons, at least for most larger, complex mammals. According to Open Connectome Project, the human cerebral cortex alone contains something in the neighborhood of 1010 neurons linked by 1014 synaptic connections.
That number is a bit difficult to digest without context, so how about this: the number of base-pairs in a human genome is 109.
I didn’t want anyone to feel I was neglecting the “big data” side of things, although 12 TB of data will only be “big data” for your home computer. 😉
Moreover, Sebastian Seung, Professor of Computational Neuroscience at MIT and author of the book, Connectome, is quoted as speculating that memories may be represented in the patterns of connections between neurons. Which sounds familiar to anyone who has heard Steve Newcomb talk about the subjects that are implicit in associations.
I wonder if it is possible to represent a summation of the connectome, much in the same way that we accept lower resolution images for some purposes? So that the task isn’t a one-to-one representation of the connectome, which would be a connectome itself (a map equivalent to the territory itself is the territory, one of those philosophy things).
That’s a nice data structure/information theory problem that would not require dimming the lights in your neighborhood when your system boots up. At least until you wanted to run a simulation. 😉
If you are interested in a game to make discoveries about the neural structure of the retina, see: http://www.eyewire.org/.