NEURO tv is a monthly online conversation between neuroscientists, psychologists and philosophers who try to understand the brain and the mind.
Jep, and this is great! Jean-Francois Gariépy uploaded already 11 episodes of his Neuro.TV series, each of them roughly an hour long. He organizes online video meetings with researchers discussing latest opinions and research directions in neurosience.
Scaling Brain Size, Keeping Timing: Evolutionary Preservation of Brain Rhythms by György Buzsáki, Nikos Logothetis and Wolf Singer
In this paper, they report changes of frequency of several rhythms as a function of brain weight. What I found interesting was Fig. 2 showing that most rhythms are invariant to brain weight (or equally size) except theta, suggesting that spatial properties of the hippocampus (e.g. its overall size) indeed constrain the range in which theta rhythm emerges.
I am proud to announce the start of a new long term project that begins with a paper that came out recently.
PAM is the foundation for studying generic and specific coding principles of neural networks. The idea is to create artificial neural networks whose connectivity properties and connection lengths result from reconstructed anatomical data. Using a 3d environment to model and describe real neural networks, we can describe complex relationships between layers of neurons. With PAM, we can account for connectivity properties that are influenced by global and local anatomical axes, non-linear relationships between distances of neurons and their connection lengths, and we can incorporate many experimental data, like images from tracer studies, directly into our model.
In the long run, I hope that PAM can help to understand how the structure but also how self-organizing principles (like diverse forms of plasticity) contribute to the topology and thereby also to the function of the network. In particular, we are interested in the functioning of the hippocampus.
The project website is hosted on Bitbucket Github.
Updated on 26.05.2015:
Replaced link to Bitbuckt by link to Github.
If you, like me, work on the hippocampus, you know that it is incredibly hard to understand how the hippocampal formation actually looks like in 3D. Dentate Gyrus and CA3-CA1 lie in the rat along the dorsal-ventral axis but also traverse the medial-lateral and anterior-posterior axis.
Now you can order a 3d print of the hippocampus at Shapeways which helps a lot to understand how the neural layers look like and how they are interwoven.
This TED talks shows some impressive visualizations of molecular reactions. In particular the emergence of this football-like shape (at around 1:16) is astonishing.
The software they use, called molecular flipbook, has been developed by a team around Janet Iwasa and is based on Blender. This is another great example of Blender becoming more and more a helpful tool for scientists.
The Pigeon Brain Atlas
Recently, a 3d atlas of the ascending sensory and the descending motor systems in the pigeon brain has been presented, that is freely available. This is one important step towards a database that allows comparisons of network structures and their functions across species.
I think the hippocampal formation is one of the hardest regions to understand with regard to its overall shape and connection patterns. In the rodent it crosses all three axes in the brain and the orientation of its convoluted layers changes across its septal-temporal axis. Therefore, I am happy to share with you a video that I produced recently, in which I show how the hippocampal formation looks like in 3d. For me it was also a good exercise to produce a video for Youtube, as I am going to produce more in the next weeks.
This video is fascinating and frustrating (from a computational modeling point of view) at the same time. Jeff Lichtman shows in this video (above) the complexity of a tiny little fraction of the mouse brain scanned on a nanometer scale using serial electron microscopy. At 16:00 and the following minutes he shows the relation between the nanometer scale, the complexity that can be observed on this level and the large scale view on the brain. Absolutely impressive.
Functional connectivity of the entorhinal-hippocampal space circuit by Sheng-Jia Zhang and colleagues from the Kavli Institute for Systems Neuroscience in Trondheim.
They used light-evoked discharges of grid- and other cells to determine whether these cells have direct hippocampal projections. What I find interesting about this study is that principle cells in MEC need between <5-30ms to fire, depending on the current they receive.
New and Distinct Hippocampal Place Codes Are Generated in a New Environment during Septal Inactivation by Mark Brandon and colleagues from the Center for Functional Connectomics in Seoul.
In this paper they show that septal inactivation leads to reduced theta power and grid cell activity. In a novel environment place fields emerged which suggests (according to their interpretation) that neurons can generate place fields without grid cell activity.
The Allen Brain Atlas provides most of their tracked brain data as 3d-files in the VTK-format. I found it difficult to find a converter for this format that would give me e.g. an obj-file. I came across the Graph Toolbox for Matlab which can read vtk-files and write obj-files. However, their importer did not work for that particular version of the vtk-format. Here is read_Allen_vtk.m, an m-file that I derived from read_vtk.m, which is able to extract all vertices and face-data from the vtk-files. You can then save them using write_obj() and open them in the 3d-tool of your choice. In the upper image you see the hippocampus and entorhinal cortex of the mouse in Blender.
