Simulation of brain neurons in real-time using biophysically meaningful models is a prerequisite for comprehensive understanding of how neurons process information and communicate with each other, in effect efficiently complementing in-vivo experiments. State-of-the-art neuron simulators are, however, capable of simulating at most few tens/hundreds of biophysically accurate neurons in real-time due to the exponential growth in the interneuron communication costs with the number of simulated neurons. In this paper, we propose a real-time, reconfigurable, multichip system architecture based on localized communication, which effectively reduces the communication cost to a linear growth. All parts of the system are generated automatically, based on the neuron connectivity scheme. Experimental results indicate that the proposed system architecture allows the capacity of over 3000 to 19 200 (depending on the connectivity scheme) biophysically accurate neurons over multiple chips.

Additional Metadata
Keywords Axons, Biological system modeling, Biophysically accurate neuron simulation, Computational modeling, Field programmable gate arrays, Junctions, Mathematical model, multi-chip data-flow architecture, neuron network
Persistent URL dx.doi.org/10.1109/TBCAS.2017.2780287, hdl.handle.net/1765/104455
Journal IEEE Transactions on Biomedical Circuits and Systems
Rights no subscription
Citation
Zjajo, A, Hofmann, J. (Jaco), Christiaanse, G.J. (Gerrit Jan), Van Eijk, M, Smaragdos, G, Strydis, C, … Leuken, R.V. (Rene van). (2018). A Real-Time Reconfigurable Multichip Architecture for Large-Scale Biophysically Accurate Neuron Simulation. IEEE Transactions on Biomedical Circuits and Systems. doi:10.1109/TBCAS.2017.2780287