Anatomical modeling at the SFN 2015

I noted that there is a bunch of other people using in one way or another anatomical modeling to learn something about the brain. Here is a list of posters and companies I found at the SFN that present work based on anatomical models. This list will be updated throughout the conference:

17th Oct. Saturday afternoon:

[Board BB27] Life after streamlines: Describing structural connectivity with Reeb graphs

Matthew Cieslak

[Board BB32] Critical role of topography in determining spatio-temporal network dynamics in a large-scale model of hippocampus

Phillip Hendrickson

[Board BB37] Exploring the effects of spatial constraints on cell network formation in the dentate gyrus

Adam Mergenthal

[Board BB38] Computational study of local field potentials in a heterogeneous 3D model of rat hippocampus

Kyle Loizos

[Board BB93] Virtual slice in 3D: constructing and cutting a full-scale computational model of the dentate gyrus

Ivan Raikov

19th Oct. Sunday:

[Board DD46] Visualizing, editing and simulating neuronal models with the Open Source Brain 3D explorer

Padraig Gleeson

[Board DD47] Informatics tools for mapping brain connectivity at meso- and micro-scale

Linqing Feng

[Board DD52] Web visualization of massive neuroscience datasets using the open connectome project

Alexander Baden
openconnectome project

[Board K15] Large scale imaging and 3d visualization of long-range circuits in clarity-treated primate visual cortex

Cameron Christensen

[Board DD52] Open connectome project: Lowering the barrier to entry big data neuroscience

Joshua Vogelstein

[Board DD62] A platform for brain-wide imaging and reconstruction of individual neurons

Michael Economo

[Board Q1] Data-driven construction of mouse whole-brain models

Csaba Eroe

Data-driven construction of mouse whole-brain models


[711] Arivis

Neuronal layers have volume

Transversal view of the hippocampus
Transversal view of the hippocampus: red: dentate gyrus; blue shades: CA3-CA1; yellow: subiculum; green shades: entorhinal cortex layer 2 & 3

The next release version of the PAM version of the Waxholm Rat Atlas is already under development. The neural layers (at least stratum pyramidale and granule layer) have volume which makes the neuron distribution a bit more realistic. Computing neuron positions and rendering them at full scale is already possible on average desktop machines. And also the mappings for EC2/3 to DG and CA3/1 works with the volume data.

These renderings show just 5% of all excitatory neurons in the hippocampal formation and for only 20 neurons in EC2 and EC3 their projections to the hippocampus. The axon diameter is at realistic scale (0.75um).

Realistic numbers of excitatory neurons


This is just a „small“ test render of the layered version of the Waxholm Rat Atlas. Each main neural layer in the hippocampal formation contains a realistic number of neurons (little pyramids in this case). DG: 1,200,000 neurons; CA3: 250,000; CA2: 30,000; CA1: 360,000. This yielded about 10 Mio. Vertices and it took Blender a couple of minutes to render an image, but overall it was pretty straight forward. A visualization of a full scale model of the rat hippocampus is coming into reach.

The right image also depicts a basal dendritic tree of one single neuron. Now imagine, every neuron has such a dendritic tree. Must be a pretty dense structure.

Single dendrite compared with the entire rat hippocampus

While I am converting the Waxholm Rat Atlas into a PAM model, I thought it would be fun to see how a single dendrite at realistic scale looks within the entire rat hippocampus. So I imported a model of a dendrite taken from this paper (thanks Corrado) into Blender. As it is impossible in the normal 3d mode to see the entire rat model and the dendrite at the same time, I created a little video, in which I zoom into the dendrite and back. The next step would be to create whole dendritic trees at a realistic scale with the TREEs module.

Waxholm Space atlas of the rat brain hippocampal region


Only disovered now, that there is a new (February 2015) great resource out there for reconstructing the rat hippocampus as parametric anatomical model. The Waxholm Space Atlas for the rat (and this is the paper about the atlas). The Waxholm Space Atlas contains volume data of the rat brain. Mesh data of the volumes can be obtained from this website. The image above was created based on the mesh data.

Tracing in PAM

Screenshot from 2015-09-16 17:07:22

With PAM, you can simulate anterograde and retrograde injection-based tracings. Simply position the cursor onto an injection side, select antero- or retrograde tracing in the tracing-panel of PAM modeling, chose an injection radius and then press „Perform tracing“. PAM will mark all post-synaptic (or pre-synaptic) neurons that are affected by the tracer.

Screenshot from 2015-09-16 17:07:50

Tracing simulation is implemented in a very rudimentary way right now but it already can help to validate the model definition with experimental data. The tracing-feature is already in the master branch.

Axonal conduction delays, part II

Yesterday, I wrote about a nice Scholarpedia article dealing with axonal conduction delays. The plot of the diameter-to-velocity function is from a paper from 1980 by Waxman. I found it confusing that for an unmyelinated axon with an average diameter of 0.1μm the conduction velocity is predicted to be ~0.7m/s, while experimental evidence indicates that conduction velocity is only about ~0.3m/s.

After some literature search I found that Wen and Chklovskii in 2010 examined this issue and came up with new parameters for the Waxman model of axonal conduction delay.

Screenshot from 2015-08-27 15:52:38The most important part is that the coefficient for thin unmyelinated fibers is not ~2.3 as given in the Waxman paper but rather 1.06, in order to explain the experimental data. When it comes to modeling thin unmyelinated fibers (e.g. in the hippocampus), this makes a considerable difference!