A large update to Cerebrii has been submitted to the app store.

• New anatomical layers from high definition fiber tracking data
• Updated engine fixes the rendering issues found on the 3GS iPhones
• Speed increase on both old and new hardware

In collaboration with Walter Schneider and Sudhir Pathak at Pitt, we are able to include high definition fiber tracking data. White matter tracts spanning various regions of the brain are visualized in high-color according to principal fiber direction.

Finally, We are happy to announce that Cerebrii will be available for free through the app store until the end of November. While the update has yet to be approved, this release was originally timed to coincide with the start of the SFN conference in Chicago.

If you find cerebrii useful please consider making a small donation to Autism Speaks by clicking here. No minimum donation required - every small amount helps!

Follow the below above.

Read the rest of this entry »

I have some extra shirts (n=6, assorted sizes) from the 2008 SFN Conference in Wash. D.C. Full design can be found on here.

The short sleeve and long sleeves are silk-screen’d American Apparel; hoodies are silk-screen’d Gildans. Email stoner at cerebrii.com if your interested. Price 20/25/30 + S&H - First come first serve. Limited quantities and sizes available.

Let’s see how this works

I am going to post pdf’s from articles I  share via Google reader to this page. Due to limitations with copyright and republication, I may not be able to keep the files online indefinitely.

Publication Date: 2009 Jan 27 PMID: 19172386

Authors: Kellems, A. R. - Roos, D. - Xiao, N. - Cox, S. J.

Journal: J Comput Neurosci

The accurate simulation of a neuron's ability to integrate distributed synaptic input typically requires the simultaneous solution of tens of thousands of ordinary differential equations. For, in order to understand how a cell distinguishes between input patterns we apparently need a model that is biophysically accurate down to the space scale of a single spine, i.e., 1 mum. We argue here that one can retain this highly detailed input structure while dramatically reducing the overall system dimension if one is content to accurately reproduce the associated membrane potential at a small number of places, e.g., at the site of action potential initiation, under subthreshold stimulation. The latter hypothesis permits us to approximate the active cell model with an associated quasi-active model, which in turn we reduce by both time-domain (Balanced Truncation) and frequency-domain ([Formula: see text] approximation of the transfer function) methods. We apply and contrast these methods on a suite of typical cells, achieving up to four orders of magnitude in dimension reduction and an associated speed-up in the simulation of dendritic democratization and resonance. We also append a threshold mechanism and indicate that this reduction has the potential to deliver an accurate quasi-integrate and fire model.

On staying with the theme of subthreshold membrane voltages (see my previous shares if you missed them) - This is the type of work that needs to be done if we're to make anything out of the almost infinite complexity of the analog world.... Comp neuro is a wonderful thing.

Update: See this page for a detailed FAQ re: memristors from HP

Since 1972, scientists have known there are four basic circuit components, but if you've spent any time in an electrical engineering classroom, you probably only have experience with three: capacitor, inductor, and resistor. The fourth basic component, the memristor, had remained stuck in the domain of theory--a nice idea that even the theorists thought had few practical uses. Last year, scientists at Hewlett-Packard (HP) demonstrated the first functional solid-state memristor, made from thin films of TiO₂, and discovered it had an abundance of unique and highly promising properties. A study released Monday by The Proceedings of the National Academy of Sciences shows that these same TiO₂ memristors can be fabricated into functional and reprogrammable integrated circuits. Scientists at HP combined a crossbar architecture of memristors with field effect transistors (FETs) to produce a convincing proof-of-concept device that includes circuits that can dynamically reprogram themselves, acting a bit like a solid-state nerve cell-like operation--a holy grail of electrical engineering. Click here to read the rest of this article