The swc-importer for neural reconstructions is also now on Github. I used this opportunity to embed the key function into an importer class for Blender.
I find it fascinating that the complexity of any biological structure, and the brain in particular, is the result of a low-dimensional encoding, simple developmental mechanisms and external input. This visualization of abstract growing structures gives a pretty good idea of how we can think of this process. Apart from that, these structures look absolutely stunning.
I was not satisfied with the available abstract depictions of the hippocampal formation and I didn’t want to worry about copyrights or citation obligations when I use them in scientific publications and presentations. Therefore, I thought it would be a great if there would be a free template figure in vector format that everybody can use, improve and share with others. Luckily, master student Stefanie Bothe, who makes an internship in our lab right now, created exactly this:
I opened a repository, called NeuroSVG, where you can download this figure and send pull request, if you would like to improve it. For your own usage, you can modify this figure and use it freely wherever you like. Maybe, others like to contribute further neuroscientific illustrations in SVG format in this repository.
Recently, I was wondering how long the rat hippocampus on the septal-temporal axis actually is. With my 3d model of the rat hippocampus and the Measure Panel Addon for Blender this is easy to measure. Simply select an edge loop within one of the planes and compute the path length.
I was pretty surprised when I saw that the dentate gyrus in my model is about 9.7mm long! First, I couldn’t believe that but when I looked into the original data by Kjonigsen et al. 2011, it became clear that this seems to be really the length of the rat hippocampus when it is unfolded in 2D.
Given the thin unmyelinated fibers in CA3 which have pretty long conduction times, signal processing within the hippocampal loop suddenly appears to be very slow. 😉
In the last few months, PAM received a major update. Most importantly, mappings between different layers can now be configured within the Blender user interface and they are also saved in the blend-file. Now, a 3d network can be generated within a minute and it is not necessary anymore to learn new python commands for the network definition.
The newest episode of Neuro.TV features memory formation, reconsolidation, retrieval.
Buchanan and Mellor show in their article, that context-dependent STDP rules can be found in the hippocampus that deviate from the classical STDP rule applied in computational models.
at Frontiers in Synaptic Neuroscience