Saturday, February 24, 2007 featured on the cover of NeuroImage

- Shawn Mikula was featured on the March 15, 2007, cover of NeuroImage for the article entitled, "Internet-Enabled High-Resolution Brain Mapping and Virtual Microscopy".

This is only the beginning. is far more than a cool online high resolution brain atlas, it is also a research tool. When used in conjunction with tools like BrainMaps Analyze, it is possible to download image data from and apply image analysis routines. It is also possible to do 3D reconstructions and morphological analyses. Expect to see upcoming publications emphasizing this point.

Google Earth for the Brain

- Shawn Mikula

Users of have often described it as a Google Maps for the Brain, which is interesting because we have taken Google Maps as an inspiration and a guide for what mapping the brain should be like. In line with this, one of the developers at, Issac Trotts, has released a veritable Google Earth for the Brain, called StackVis. In a nutshell, StackVis is a 3D viewer of neuroanatomical sections. But it is revolutionary in the sense that it permits rapid interactive viewing of arbitrarily large images.

Conventional microscopy, electron microscopy, and imaging techniques such as MRI and PET commonly generate large stacks of images of the sectioned brain. In other domains, such as neurophysiology, variables such as space or time are also varied along a stack axis. Digital image sizes have been progressively increasing and in virtual microscopy, it is now common to work with individual image sizes that are several hundred megapixels and several gigabytes in size. The interactive visualization of these high-resolution, multiresolution images in 3D has not been possible, until now. StackVis is a tool for interactive visualization of multiresolution image stacks in 3D.

The method, characterized as quad-tree based multiresolution image stack interactive visualization using a texel projection based criterion, relies on accessing and projecting image tiles from multiresolution image stacks in such a way that, from the observer's perspective, image tiles all appear approximately the same size even though they are accessed from different tiers within the images comprising the stack. This method enables efficient navigation of high-resolution image stacks. We implement this method in StackVis, which is a Windows-based, interactive 3D multiresolution image stack visualization system written in C++ and using OpenGL. It is freely available at

About this Blog

Side view of my brain based on MRI. It's not really blue

Since Blogger does not allow HTML in the 'About Me' section, I thought it good to make a separate post, to let readers know a little about one of the people behind I do realize that this is self-indulgent, but this is the only personal post on this blog, so feel free to stop reading now and skip to other posts.

I was born on the eastern coast of Spain, of Hungarian and Spanish descent, moved to NJ, and then to TX, then to MD for graduate school in neuroscience at Johns Hopkins, and am now in sunny CA at the Univ of Calif, where hopefully I'll remain for awhile.

I work in computational neuroscience and neuroanatomy. I am involved with the BrainMaps Project at the University of California, which involves online high resolution brain mapping.

Here are a few publications to give an idea about my work:

  • Mikula S, Manger PR, Jones EG (2007) The Thalamus of the Monotremes: Cyto- and Myeloarchitecture and Chemical Neuroanatomy. Phil. Trans. R. Soc. B. PMID 17229579

  • Mikula S, Trotts I, Stone J, Jones EG (2007) Internet-Enabled High-Resolution Brain Mapping and Virtual Microscopy."NeuroImage" 35(1):9-15 PMID 17229579

  • Trotts I, Mikula S, Jones EG (2007) Interactive Visualization of Multiresolution Image Stacks in 3D."NeuroImage" PMID 17336095

  • Mikula S, Niebur E (2007) Exact Solutions for Rate and Synchrony in Recurrent Networks.

  • Mikula S, Fontoura-Costa L, Liu X-B, Jones EG (2007) Particle and Cell Segmentation for Light and Electron Microscopy Using Mathematical Morphology.

  • Mikula S, Niebur E (2006) A Novel Method for Visualizing Functional Connectivity using Principal Component Analysis."Int J Neurosci" 116(4):419-29 PMID 16574580

  • Mikula S, Niebur E (2005) Rate and Synchrony in Feedforward Networks of Coincidence Detectors: Analytical Solution."Neural Computation" 17(4):881-902 PMID 15829093

  • Mikula S, Niebur E (2004) Correlated Inhibitory and Excitatory Inputs to the Coincidence Detector: Analytical Solution."IEEE Transactions on Neural Networks" 15(5):957-62 PMID 15484872

  • Mikula S, Niebur E (2003) Synaptic Depression leads to Nonmonotonic Frequency Dependence in the Coincidence Detector."Neural Computation" 15(10):2339-58 PMID 14511524

  • Mikula S, Niebur E (2003) The Effects of Input Rate and Synchrony on a Coincidence Detector: Analytical Solution."Neural Computation" 15(3):539-47 PMID 12625330