volta_sensor_decoding_v_12_best__159e9 v1.0.0

LINK ---> https://byltly.com/2tklhr

example signals during brain control of grasp. average smr modulation across 150 brain-controlled grasp trials in one sensorimotor sensor for subject s03. this sensor is highlighted in red on a top-down view of the meg helmet on the right of this figure. at time zero the participant is cued to close the virtual hand by decreasing their smr, i.e. desynchronization shown as blue. trials began after an iti, followed by a hand initialization stage.


additionally, we are working on a new open source platform called volta.ai [ 11 ]. volta provides the ability to run small or large networks of neural networks in parallel on the same gpu. once deployed, the latency of the server can be as low as 50 ms. volta also provides full dataflow interfaces for real-time processing, streaming, and real-time decoding of brain activity. volta is designed for running models across multiple gpus and multiple servers in real time.


xilinx’s upcoming zynq ultrascale+ mpsoc will incorporate the above hardware. the software stack on these platforms is evolving rapidly and is not yet fully supported by craniux. the hardware above is targeted at volta.ai applications but can also be used in other applications.


example signals during brain control of grasp. average smr modulation across 150 brain-controlled grasp trials in one sensorimotor sensor for subject s01. this sensor is highlighted in red on a top-down view of the meg helmet on the right of this figure. at time zero the participant is cued to close the virtual hand by decreasing their smr, i.e. desynchronization shown as blue. trials began after an iti, followed by a hand initialization stage. modulation is the percent change relative to the smr activity during the iti 84d34552a1