3D Models by NASA

nasa_3d_models

For all 3D and space enthusiast, this might be very interesting. NASA offers 3D models for many of their spaceships, satellites and devices they used in the past (e.g. the opportunity rover, the Apollo lunar module) as free download on their website. Most models are in 3ds or obj-format which should be readable by most 3d-tools. Some of them are even in Blender.

Neural network visualization

Calender_neuron

Recently, I was asked to create an abstract illustration of my current project. This is what I came up with. I work on an artificial neural network model of the cortex-hippocampus-loop in the brain. In particular, I am interested in the transformation of population activity into a spatio-temporal spiking pattern that results from converging connections from the cortex to the hippocampal loop. Spike-timing and heterogenous conduction delays between neurons are crucial properties in this model.

neuron_blender

The picture was created in Blender and rendered in Cycles.

Allen Brain Atlas as SVG

allen_brainJust discovered that you can download single images of the Allen Brain Atlas as SVG-files. This tutorial explains how to download the vector files. The simplest way is to use this URL in your browser

http://api.brain-map.org/api/v2/svg_download/plane_id?groups=28

Where plane_id is the id of the plane you want to download, e.g.

http://api.brain-map.org/api/v2/svg_download/100960084?groups=28

Very cool, that they share all the data in an open source vector format.

Neural Networks: What should we borrow from biology?

This is a nice (and freely available) article by Oliver Coleman:

Models of  the brain: What Should We Borrow From Biology?

It was presented on the AAAI Symposium How Should Intelligence Be Abstracted in AI  Research and reviews several basic properties of neural networks that are possibly of critical importance for their functioning but mostly neglected in artificial neural networks. This is a great article for every computer scientist interested in neural networks and in the neuroscientific perspective on neural networks. It is hopefully a source of inspiration for new and more complete models.