It’s an incredible time to be a guitarist who doesn’t want to own a bunch of $2,000 amps and an expensive pedalboard of gear. Amp and pedal simulators, which have been around for decades, have in the last few years finally come into their own as nearly indistinguishable sonic replacements. Even John Mayer is now willing to ditch his beloved tube amps for digital models.
I certainly don’t have Mayer’s chops or gear budget, but I do love messing with this sort of tech and have purchased everything from NeuralDSP‘s Archetypes series to Amplitube and Guitar Rig. Last week, as part of an early Black Friday sale, I picked up two amp/effects suites from British developer Polychrome DSP—Nunchuck (Marshall amps) and Lumos (clean through mid-gain tones). They are both excellent.
Any reasonable person should be satisfied with this tech stack, which models gear that collectively costs as much as my house. After my Polychrome DSP purchases, I reminded myself that I am a reasonable person, and that I could therefore ignore any further amp sims that might tempt my wandering eye.
This color-coded representation of a mouse cortex simulates the activity of brain cells. (Video via Allen Institute)
Creating a virtual brain may sound like a science-fiction nightmare, but for neuroscientists in Japan and at Seattle’s Allen Institute, it’s a big step toward a long-held dream.
They say their mouse-cortex simulation, run on one of the world’s fastest supercomputers, could eventually open the way to understanding the mechanisms behind maladies such as Alzheimer’s disease and epilepsy — and perhaps unraveling the mysteries of consciousness.
“This shows the door is open,” Allen Institute investigator Anton Arkhipov said today in a news release. “It’s a technical milestone giving us confidence that much larger models are not only possible, but achievable with precision and scale.”
The massive data set was translated into a 3-D model using the Allen Institute’s Brain Modeling ToolKit. A simulation program called Neulite brought the data to life as virtual neurons that interact with each other like living brain cells.
Scientists ran the program in different scenarios, including an experiment that used the full-scale Fugaku configuration to model the entire mouse cortex.
“In our simulation, each neuron is modeled as a large tree of interacting compartments — hundreds of compartments per neuron,” Arkhipov said in comments emailed to GeekWire. “That is, we are capturing some sub-cellular structures and dynamics within each neuron.”
During the full-scale simulation, it took no more than 32 seconds to simulate one second of real-time activity in a living mouse brain. “This level of performance — 32 times slower than real time — is quite impressive for a system of this size and complexity,” Arkhipov said. “It is not uncommon to see a factor of thousands of times slower for such very detailed simulations (even much smaller than ours).”
The researchers acknowledge that much more work is needed to turn their simulation into a model capable of tracing the progress of a neurological disease. For example, the model doesn’t reflect brain plasticity — that is, the brain’s ability to rewire its own connections.
“If we want to mention something specific besides plasticity, then one aspect that is missing is the effects of neuromodulators, and the other is that we currently do not have a very detailed representation of sensory inputs in our whole-cortex simulations,” Arkhipov said. “For all of these, we need much more data than currently available to make much better models, although some approximations or hypotheses could be implemented and tested now that we have a working whole-cortex simulation.”
Arkhipov said the project’s long-term goal is to simulate an entire brain, not just the cortex. “There’s a distinction between whole-cortex and whole-brain,” he pointed out. “The mouse cortex (and our model of it) contains about 10 million neurons, whereas the whole mouse brain contains about 70 million neurons.”
A human-brain simulation would require an even greater leap. The human cortex alone contains not just 10 million neurons, but 21 billion.
The good news is that a sufficiently powerful supercomputer might be up to the task. “Our work shows that very detailed microscopic-level simulations of larger brains may be possible sooner than previously expected,” Arkhipov said. “The results suggest that a simulation of the whole monkey brain (such as that of a macaque monkey with 6 billion neurons) can fit on the full-scale Fugaku system.”
Arkhipov said it was important to point out that creating a brain model on a supercomputer “does not mean that such a model is complete or accurate.”
“Here we are talking about technical feasibility of simulations, and it looks like such simulations even at the scale of the monkey brain are now within reach,” he said. “But to make such simulations biologically realistic, much more experimental data production and model building work would need to happen.”
Rin Kuriyama and Kaaya Akira of the University of Electro-Communications in Tokyo are the principal authors of the paper presented at SC25, titled “Microscopic-Level Mouse Whole Cortex Simulation Composed of 9 Million Biophysical Neurons and 26 Billion Synapses on the Supercomputer Fugaku.” In addition to Arkhipov, authors from the Allen Institute include Laura Green, Beatriz Herrera and Kael Dai. The study’s other authors are Tadashi Yamazaki and Mari Iura of the University of Electro-Communications; Gilles Gouaillardet and Asako Terasawa of the Research Organization for Information Science and Technology in Hyogo, Japan; Taira Kobayashi of Yamaguchi University; and Jun Igarashi of the RIKEN Center for Computational Science.
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