Figure 2.

Detailed configuration of the motor nervous system on neuromorphic hardware. The components are implemented separately for the flexor and extensor, which simultaneously drive the joint modeled as a beam freely rotating around the endpoint (simulated in software outside FPGAs). For each muscle (flexor or extensor), the muscle force is calculated from a Hill-type muscle model activated by 6 motoneuron pools with 6 different motoneuron sizes, each pool comprising of 128 identical motoneurons modeled by Izhikevich (Izhikevich, 2003). The motoneuron pools receive excitatory input from both the spinal loop and transcortical loop. In the spinal loop, the sensory feedback is provided by muscle spindles implemented as Mileusnic and colleagues did (Mileusnic et al., 2006), which include both the Primary (Ia) and Secondary (II) afferents to provide the dynamic and static proprioceptive information about the muscle. A total of 128 spindles are implemented for each muscle, thus providing 256 independently spiking afferents. In the transcortical loop, the spindle afferents synapse on a population of 128 cortical neurons representing the primary sensory and motor cortex. The cortical part is clearly an oversimplification of the cortex but it enables an additional 32ms conduction delay in the proprioceptive feedback loop, which is the main focus of this study rather than modeling a full cortex. In the cortex, spindle afferents may join additional inputs modeling the voluntary motor command. The TONIC model is implemented by adding to the cortical drive a tonic component that is independent from the voluntary drive or the sensory feedback. The HI-GAIN model is implemented by increasing the synaptic gain of the spindle afferents prior to activating the cortical neuron pool. Due to the limited capacity of each FPGA unit, the system must be distributed on multiple FPGAs as indicated by the blocks. The entire system uses 6 FPGA boards enabling 2 muscles with 2,304 neurons. Only half of the system (flexor) is shown.