, High-resolution MRI images enable clear-cut visualization of spinal tissues, including individual dorsal roots., Elaboration of highly realistic anatomical models from MRI and CT scans., Automatic generation of rootlets based on the identification of the uppermost rootlet in high-resolution MRI acquisitions. Rootlet trajectories are interpolated from this rootlet, using the measured segment length as a reference.
, Applying the transformation matrix depicted in Step 5 allows to convert the predicted recruitment of dorsal roots shown in Step 4 into a prediction of motor pool recruitment., For each position of the lead, the recruitment of the targeted motor pools compared to the non-targeted motor pools is measured to obtain a selectivity index.
Extended Data Fig. 5 Impact of model abstractions to determine the optimal position of the paddle lead., Generalized computational model of the interaction between EES and the spinal cord, including the location of motor neurons from key leg muscles., Personalized computational model of the interaction between EES and the spinal cord for the three participants. The models are aligned with the generalized model depicted in Step 1.
Extended Data Fig. 7 Configurations of frequency-specific EES trains to elicit functional muscular and kinematic activity., Configuration of electrodes to target the hotspots associated with weight acceptance and whole-leg flexion . Example from participant P3. EES bursts are delivered at 20 Hz. and 100 Hz to elicit muscle responses, recorded from the Iliopsoas (
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