Extended Data Fig. 3: Identification of the projectome from propriospinal neurons.
Step 1, Acquisition of functional MRI from the spinal cord in response to the recruitment of proprioceptive afferents from specific leg muscles. The muscle spindles are recruited either by stretching the muscles in which they are embedded (the limb is mobilized by a physiotherapist, aided with audio cues), or by applying muscle tendon vibration using MR-compatible pneumatic vibrators (synchronized with MRI triggers). Two runs are acquired for each muscle. Only the right leg muscles are tested. In addition to the functional volume series, T2 anatomical images and physiological (heart rate, respiratory) signals are acquired. Step 2, Raw fMRI volume series are repeatedly acquired every 2.5 s (TR) in functional runs lasting about 7 minutes. Step 3, A two staged motion correction (3D and then 2D slice-by-slice) is applied for each run. First, the volumes are registered to their respective averaged-in-time image using 3D rigid body realignment. Secondly, taking as reference the averaged-in-time corrected volume, a slice-by-slice 2D realignment is applied thus accounting for the nonrigid property of the spinal cord. Step 4, The motion-corrected series are spatially smoothed, volume by volume with 3D gaussian kernel with full width at half maximum (FWHM) of 2×2×6 mm3. Step 5, The motion-corrected series are again averaged through time. The cerebrospinal fluid and white matter are segmented from this mean functional image. Step 6, Physiological signals (heart rate and respiratory) acquired concomitantly to the fMRI volumes are used to model physiological noise (RETROICOR based procedure). If no signals are available, noise regressors are built with component based noise extraction (aCompCor). Step 7, Acquisition timings corresponding to the task-design, pre-processed (motion corrected, smoothed) fMRI volume series and physiological noise regressors are submitted to a specific first level generalized linear model. A second level fixed effects analysis (subject level, task specific) is performed by combining the two runs. Whenever possible, multiple comparison corrections are performed (Z > 2, pcorr < 0.05). Step 8, Spinal segments are identified from high-definition T2-ZOOMit structural images that allow visualization of the dorsal roots. Spinal segments are then reported in the T2 anatomical image acquired in each run. Step 9, Using non-rigid transformations, the mean functional images are co-registered to the T2 anatomical image. Step 10, Thresholded activity patterns resulting from the generalized linear model are coregistered to the anatomical image. The projectome of proprioceptive neurons innervating the mobilized muscles are extracted and mapped to the anatomical model. Step 11, Projectomes from the three participants, and for comparison, averaged myotome distribution measured electrophysiologically in a large population of patients undergoing surgery. The color dots represent the reconstructed projectome from key leg muscles. Vertical color bars represent mean population distribution of muscular motor hotpots. The projectomes differed across the participants. In particular, the projectome identified in P3 revealed an unexpected inversion of the projectome from ankle antagonists. This rostrocaudal inversion was confirmed electrophysiologically.
