I think someone at UCLA did something similar for lobsters. This was
used as material for an SF story ("Lobsters", Charles Stross[sp?])
Jan Mattsson wrote:
Has this approach been successful for any "lesser" animals? E.g.; has anyone
simulated an insect brain system connected to a simulated insect body in a virtual
environment? Starting with a mouse brain seems a bit ambitious.
Since I haven't posted on the list before I guess I should introduce myself: I'm Jan Mattsson in
Stockholm, Sweden. A software developer by profession, I first became interested in AI when I read
"Gödel Escher Bach - an Eternal Golden Braid" many years ago (actually switched from
physics to computer science because of it). More recently I read Kurzweil's "The Singularity
is near", that brought me here.
/JanM
-----Ursprungligt meddelande-----
Från: J. Storrs Hall, PhD. [mailto:[EMAIL PROTECTED]
Skickat: lö 2007-04-28 19:15
Till: [email protected]
Ämne: [agi] mouse uploading
In case anyone is interested, some folks at IBM Almaden have run a
one-hemisphere mouse-brain simulation at the neuron level on a Blue Gene (in
0.1 real time):
http://news.bbc.co.uk/2/hi/technology/6600965.stm
http://ieet.org/index.php/IEET/more/cascio20070425/
http://www.modha.org/papers/rj10404.pdf which reads in gist:
Neurobiologically realistic, large-scale cortical and sub-cortical simulations
are bound to play a key role in computational neuroscience and its
applications to cognitive computing. One hemisphere of the mouse cortex has
roughly 8,000,000 neurons and 8,000 synapses per neuron. Modeling at this
scale imposes tremendous constraints on computation, communication, and
memory capacity of any computing platform.
We have designed and implemented a massively parallel cortical simulator with
(a) phenomenological spiking neuron models; (b) spike-timing dependent
plasticity; and (c) axonal delays.
We deployed the simulator on a 4096-processor BlueGene/L supercomputer with
256 MB per CPU. We were able to represent 8,000,000 neurons (80% excitatory)
and 6,300 synapses per neuron in the 1 TB main memory of the system. Using a
synthetic pattern of neuronal interconnections, at a 1 ms resolution and an
average firing rate of 1 Hz, we were able to run 1s of model time in 10s of
real time!
Josh
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