Connectomic reconstruction of the inner plexiform layer in the mouse retina

Helmstaedter, M., Briggman, K. L., Turaga, S.C., Jain, V., Seung, H. S., Denk, W. (2013). Connectomic reconstruction of the inner plexiform layer in the mouse retina. Nature 500

So this is Kevin's retina data, but with extensive annotations from 224 undergrads (who did the skeletons), and then an algorithm to fill the volume and link to the skeletons.

They first classify the reconstructed cells into types, mainly based on the layer-branching pattern.

They further go on to show that some cells can be classified based on the connectivity patterns. CBC5 have been seen before, and thought to contain several true classes of ganglion cells. They show that there is a connectivity feature that separates CBC5A from the rest. They show that CBC5A is a "true type" because it tiles the retina.

Finally they look at the circuitry of some of the cells.

The BRAIN grid

Ok, so this is an extension of the famous multiple levels figure of Churchland and Sejnowski. I like the idea of it being 7x7, but I've changed the spatial levels slightly. The original has 7, but I've consolidated the original "Systems, Maps, Networks" into "Maps and Circuits", and then added "Compartments" as a level that sits between neurons and synapses. Compartments is supposed to be information about the sub-cellular structure, but I could also merge compartments with synapses (these are both sub-cellular structures) if a separation at the larger areas are more important.

Here are just some general thoughts about the temporal scales:
Milliseconds: Spikes, instant state of the brain
Seconds: Plasticity, working memory
Hours: Long-term storage
Days: Sleep, consolidation
Years:
Lifetime: Development

Ok, so the goal is to just put everything we know about neuroscience into these 49 squares and link them all together with computational theory. Here is just some ideas:

Molecules
At this level we are mainly focused on the computational machine that is the DNA-protein network. Experience and the environment feed all the way down to the genetic level.

Milliseconds: Channels, Chemical Reactions
Seconds: Feedback signals,
Hours: Protein synthesis
Days: Gene activation, genes on sleep vs. awake
Years:
Lifetime: Genetic programs development
Evolution: DNA evolutionary dynamics

Synapses
I like synapses as their own level because they are so important and so varied.
Milliseconds: Potentials, vesicle release, Macro-channel dynamics, gap-junctions
Seconds: Calcium, excitability, g-protein receptors, neuromodulators, STP
Hours: Hormones, neuromodulators, LTP, synaptogenisis
Days: Consolidation, stabilization, synaptogensis, elimination
Years: regeneration
Lifetime: circuit formation, development
Evolution: evolution of synapse

Compartments
The sub-cellular compartments of a neuron are extremely important
Milliseconds: Spike-initiation zone, Multi-layer perceptron integration, Shunting Inhibition
Seconds: Calcium spikes, neuromodulators, bursting
Hours: Dendritic plasticity, Apical-basal interations in learning
Days:
Years:
Lifetime: Layers
Evolution: Simple 1-compartment neuron to many many compartmental pyramidal cells

Neurons
Neurons I like in the middle. This is the foundation of the brain.
Milliseconds: Spikes
Seconds: Up-Down states, modulators
Hours:
Days: Consolidation
Years: Neurogenesis
Lifetime: Types, Layers
Evolution:

Circuits
The basic building blocks of computation
Milliseconds: Firing-rate space, instantaneous state
Seconds: Gamma, working memory, neuromodulation, evidence accumulation
Hours: memory, learning
Days: sleep consolidation,
Years: learning
Lifetime: Cortical development
Evolution: 3-layer to 6-layer, basic building blocks

Maps
Maps for large networks. I like maps because of how well a map corresponds to a brain region (the visual fields have retinotopic maps, auditory maps). A Map processes a modality of information.
Milliseconds: Sharp-wave ripples, Attention
Seconds: Theta (within map), Alpha (between maps), decisions
Hours: Memory
Days: Consolidation
Lifetime: Within map, between map development
Evolution: Cortex, sensory/motor systems,

Brains
The whole brain network.
Milliseconds: qualia, consciousness
Seconds: Attention,
Hours;
Days: Sleep-wake cycle
Lifetime: large-scale development
Evolution: The evolution of the brain

So, a lot of ideas span across several spots in the grid -- like neuromodulators.