Canon PowerShot SD700 IS
ƒ/2.8
5.8 mm
1/60

3D computer models of neural growth and patterns of firing (modeling a cortical column for synthetic olfaction). Implemented on $2K of NVIDIA GPUs from Fry’s Electronics — a DIY supercomputer.

Left Brain: dendrites grow along chemical gradients, densely filling all available space, and exploring approximately 500 possible connections for each ultimate synapse formation.

Right Brain: neural model with detailed modeling of the computation that occurs in the dendrites. Earlier, simplistic neural network models assumed that the cell body was the aggregating locus of computation.

9 responses to “Brainstorm”

  1. a brain running on windows oh my god! 😉

  2. Cool graphics!

    I used to work in the fiield of Neural Networks – I wish I had access to the computing power people have today!


    Seen on your photo stream. (?)

  3. Neat! Just steps away from being able to record people’s dreams in hi-def!

  4. Nice modelling tool! 😉

    As it happens, I’m an admin for a group called Computer Simulations, and we would all love to have your photo added to the group, as I think it is a perfect match.

    Of course, if you have computer snapshots of the images in the monitors, all the better!

  5. Looks like two 23" cinema displays. What are they hooked up to?

  6. Rows of NVIDIA chips. DIY supercomputer

  7. the math behind the model:

    Mental Model

    The voltage spike will propagate, with gain, along the dendrite, from one finite element region to the neighbor, not as a free flow of electrons, but as a bucket brigade of opening and closing ion channels, like fingers cascading down a very long flute.

    The dendrite with myriad branches is a fundamental locus of computation, not just the neuron cell body.

  8. Now that GPUs have revolutionized the efficacy of neural networks, Evolved Machines CEO Paul Rhodes reflects: "The GPU impact on compute is beautiful. We had CUDA 0.1, and one of the first cards (it was called the G-80), handed to us in a bag, pre commercial availability. I will never forget the 80x speedup we got on our neuron simulations when we ported to that platform. It is so native for neural computation."

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