Abstract

In this work, we present a computing platform named digital twin brain (DTB) that can simulate spiking neuronal networks of the whole human brain scale and more importantly, a personalized biological brain structure. In comparison to most brain simulations with a homogeneous global structure, we highlight that the sparseness, couplingness and heterogeneity in the sMRI, DTI and PET data of the brain has an essential impact on the efficiency of brain simulation, which is proved from the scaling experiments that the DTB of human brain simulation is communication-intensive and memory-access-intensive computing systems rather than computation-intensive. We utilize a number of optimization techniques to balance and integrate the computation loads and communication traffics from the heterogeneous biological structure to the general GPU-based HPC and achieve leading simulation performance for the whole human brain-scaled spiking neuronal networks. On the other hand, the biological structure, equipped with a mesoscopic data assimilation, enables the DTB to investigate brain cognitive function by a reverse-engineering method, which is demonstrated by a digital experiment of visual evaluation on the DTB. Furthermore, we believe that the developing DTB will be a promising powerful platform for a large of research orients including brain-inspired intelligence, rain disease medicine and brain-machine interface.

  • @megaman1970OP
    link
    11 year ago

    The paper is really interesting, even though it looks like it was translated with Google Translate. I’m not sure as to the credibility of this particular institution, but the concept of using BOLD data to initiate the simulation is a really interesting one. I wonder if it would work better using data from the new sub-micron fMRI tech.

    The really fascinating point is that they were able to check the simulation but giving it inputs similar to what a live brain would receive, and get very similar responses. That’s amazing, and I’d like to see if anyone else manages to replicate their results.