DOI: 10.5061/dryad.mw6m90642
title: Functional representation of trigeminal nociceptive input in the human periaqueductal gray

description: The periaqueductal gray (PAG) is located in the mesencephalon in the upper
 part of the brainstem and as part of the descending pain modulation is
 considered a crucial structure for pain control. Its modulatory effect on
 painful sensation is often seen as a systemic function affecting the whole
 body similarly. However, recent animal data suggest some kind of
 somatotopy in the PAG. This would make the PAG capable of
 dermatome-specific analgesic function. We electrically stimulated the
 peripheral dermatomes of the trigemino-cervical complex consisting the
 three branches of the trigeminal nerve and the greater occipital nerve in
 sixty-one humans during optimized brainstem fMRI. We provide evidence for
 a fine-grained and highly specific somatotopic representation of
 nociceptive input in the PAG in humans and a descending functional
 connectivity between the individual representations of the peripheral
 nerves in the PAG and the brainstem nuclei of these nerves. Our data
 suggest that the downstream antinociceptive properties of the PAG may be
 rather specific down to the level of individual dermatomes. This study was
 preregistered at clinicaltrials.gov: NTC03999060 and primary outcomes
 already published elsewhere.
description: Sixty-three healthy, right-handed volunteers participated in our
 study on repetitive, randomize, peripheral, painful electrical stimulation
 of the three trigeminal branches (V1, V2, V3) innervating the facial
 dermatomes and the greater occipital nerve (GON) which innervates the back
 of the head (Figure 1B in the related publication). For the primary
 outcomes, (confirmation of earlier studies showing somatotopic
 representation for the insula, thalamus etc) which are not part of this
 manuscript, we initially measured 25 participants for
 hypothesis-generation. Power calculations revealed that 36 participants
 were needed to reproduce the hypothesized results. As the results in the
 PAG, which we present here, are preregistered as secondary outcome we
 combined both groups for a robust outcome resulting in 63 participants.
 Two volunteers of the second cohort had to be excluded due to technical
 problems, leaving 61 (27 male, age: 28.51 +/- 9.4) for the further
 analysis. All participants were free from psychiatric and neurological
 diseases and neither they nor their first-degree relatives suffered from
 headache disorders. Electrical stimulation was
 delivered with a MR-compatible Digitimer DS7A Current Stimulator
 (Digitimer Ltd., Welwyn Garden City, UK), which was coupled to four WASP
 electrodes (Specialty Developments, Bexley, UK) via a D188 Remote
 Electrode Selector (Digitimer Ltd., Welwyn Garden City, UK) and
 custom-build MR-compatible cables. The cables were build using a published
 <sup>1</sup> and MR-safety tested design to prevent tissue
 damage due to currents induced by electro-magnetic wave coupling. While
 the subject was sitting on the MR-bed, the four electrodes were positioned
 on the left side according to the three branches of the trigeminal nerve
 and the GON (Figure 1B in the related publication). The GON was located by
 palpation according to validated procedures<sup>2</sup> and
 the electrode positioned immediately above. V1 was stimulated by means of
 an electrode placed on an arbitrary vertical line between the medial and
 lateral quarter of the face, corresponding to the middle of the eyebrow
 and approximately 1 cm above. The V2 was stimulated 1 cm lateral of the
 same arbitrary vertical line on the level of a horizontal line through the
 inferior part of left ala of the nose. V3 was stimulated along the same
 vertical line approximately 1 cm caudal from the corner of the mouth.
 Figure 1B in the related publication sketches the location of the
 electrodes. Electrode 3 stimulating the third branch of the trigeminal
 nerve proved to be the most painful of all 3 trigeminal dermatomes. To
 make sure that all four sites received robust but bearable pain with the
 same standardized input, we used this site as orientation for the stimulus
 intensity. After fixing the electrodes, the subjects
 were moved into the scanner and the electrical detection thresholds (EDT)
 by means of the QUEST-procedure <sup>3</sup> at all electrode
 sites were determined. The final current was set to 10 times the EDT of
 the electrode above V3 for both experiments but was not allowed to exceed
 5 mA nor a pain rating above 50 (with levels from 0 to 100) for a single
 pulse. The actual stimulation consisted of a small train of three pulses
 separated by 100 ms each with 400 V and 2 ms duration. Each stimulus was
 followed by a break of 3 s (jittered between 2 and 4 seconds), a pain
 intensity rating on a visual analogue scale (VAS) with levels between 0
 and 100 using a button box with the right hand, and another break before
 the next trial started. For technical reasons, the VAS rating are only
 available for the second cohort, i..e. 36 participants. The inter-trial
 interval was set to 15 s (jittered between 12 and 18 s). The stimulation
 site was randomized and each site was repeated 10 times per session. The
 volunteers participated in 3 sessions resulting in 30 trials per
 stimulation site and subject during approximately 30 minutes of fMRI
 scanning. The experimental design is sketched in Figure 1A in the related
 publication. All MR data was recorded with a Siemens 3T
 PRISMA scanner (Siemens, Erlangen) using a 64-channel head coil. During
 the actual experiment we recorded 3 sessions with 230 images each using an
 EPI protocol (repetition time 2.93 s, echo time 33 ms,
 1.3x1.3x2.0 m<sup>3</sup> spatial resolution, GRAPPA
 acceleration, flip angle 80°, 72 slices with a multiband factor of 2, FOV
 215 mm, no gap, flow rephasing) with a field of view covering the
 brainstem as low as C2/3, cerebellum, midbrain and the insula cortices. In
 each session the first five images were removed to avoid scanner
 saturation effect. Afterwards we recorded fieldmaps (repetition time
 0.792 s, echo times 5.51 and 7.97 ms, 3x3x2 mm<sup>3</sup>
 spatial resolution, flip angle 20°, 72 slices, FOV 222 mm, no gap)
 covering the same volume as the EPIs to attenuate the inhomogeneity of the
 magnetic field. Pulse and breathing were recorded simultaneously to
 attenuate extra-cerebral (i.e. cardio-vascular) artifacts. Last we
 acquired high resolution (1 mm<sup>3</sup>) anatomical images
 (MPRAGE, repetition time 2.3 s, echo time 2.98 ms, flip angle 9°, 240
 slices, FOV 256 mm). All MRI data was first filtered
 using the spatially adaptive non-local means filter implemented in the
 CAT12 toolbox. The fMRI data was then corrected for movements and for
 distortions of the homogeneity of the magnetic field (fieldmaps) using the
 realign and unwarp algorithm as implemented in SPM12. Additionally, slice
 time correction was performed using the onsets of the single slices as
 suited for our multiband protocol. We then calculated a subject-wise GLM
 including condition-wise onsets of each stimulus as stick functions, which
 were then convolved with a hemodynamic response function (HRF). The button
 box responses as well as the onset and duration of the visual analogue
 scale were modelled as regressors of no interest. Additional regressors of
 no interest were included to correct for (uncorrelated) movement,
 cardiovascular influence, using the algorithms proposed by Deckers and
 colleagues <sup>4</sup>, and changes in the spinal fluid
 extracted from the 4<sup>th</sup> ventricle. The co-registered
 structural images were segmented with the unified segmentation approach
 algorithm implemented in SPM12 but using the templates provided by
 Blaiotta <sup>5</sup>, which are optimized for the brainstem
 and spinal cord, to gain deformation fields used to warp the contrast
 images of the subject-wise GLM into MNI space. Each step was carefully
 controlled by visual inspection. We further calculated a group template,
 and gray and white matter masks from the warped structural
 images. Group statistics were calculated by a one-way
 within subject ANOVA. Results from the effect of the individual
 stimulation locations were masked with a PAG mask stemming from Faull and
 colleagues <sup>6</sup> and had to pass a statistical
 threshold of
 p<sub>FWE</sub>&lt;10<sup>-4</sup> (voxel-wise
 family wise error (FWE) corrected, T&gt;6.5, n=61, df=180). This
 resulted in four statistical parametric maps, one for each stimulation
 site, including their voxel-wise t-values. For each voxel within this PAG
 mask (Figure 1C in the related publication), we then searched for the
 stimulation site with the maximal t-value which resulted in clusters
 specific for the individual stimulation site within the PAG.
 References 1.           Schmidt K, Forkmann K,
 Sinke C, Gratz M, Bitz A, Bingel U. The differential effect of trigeminal
 vs. peripheral pain stimulation on visual processing and memory encoding
 is influenced by pain-related fear. <em>Neuroimage</em>.
 2016;134:386-395. doi:10.1016/j.neuroimage.2016.03.026
 2.           Loukas M, El-Sedfy A, Tubbs RS, et al.
 Identification of greater occipital nerve landmarks for the treatment of
 occipital neuralgia. <em>Folia Morphol (Warsz)</em>.
 2006;65(4):337-342. 3.           Taesler P, Rose M.
 Psychophysically-anchored, Robust Thresholding in Studying Pain-related
 Lateralization of Oscillatory Prestimulus Activity. <em>J Vis
 Exp</em>. 2017;(119). doi:10.3791/55228
 4.           Deckers RHR, van Gelderen P, Ries M, et al. An
 adaptive filter for suppression of cardiac and respiratory noise in MRI
 time series data. <em>NeuroImage</em>. 2006;33(4):1072-1081.
 doi:10.1016/j.neuroimage.2006.08.006 5.          
 Blaiotta C, Freund P, Cardoso MJ, Ashburner J. Generative diffeomorphic
 modelling of large MRI data sets for probabilistic template construction.
 <em>Neuroimage</em>. 2018;166:117-134.
 doi:10.1016/j.neuroimage.2017.10.060 6.           Faull
 OK, Jenkinson M, Clare S, Pattinson KTS. Functional subdivision of the
 human periaqueductal grey in respiratory control using 7 tesla fMRI.
 <em>NeuroImage</em>. 2015;113:356-364.
 doi:10.1016/j.neuroimage.2015.02.026
description: # Functional representation of trigeminal nociceptive input in the human
 periaqueductal gray
 [https://doi.org/10.5061/dryad.mw6m90642](https://doi.org/10.5061/dryad.mw6m90642) ## Description of the data and file structure This dataset consists of processed images from functional magnetic resonance imaging (fMRI) in NIFTI-format readable by common MRI viewing and analyzing software like Mango ([https://mangoviewer.com/](https://mangoviewer.com/), MRIcron ([https://www.nitrc.org/projects/mricron](https://www.nitrc.org/projects/mricron) or SPM12 ([https://www.fil.ion.ucl.ac.uk/spm/software/spm12/](https://www.fil.ion.ucl.ac.uk/spm/software/spm12/)). The images of this dataset were created using the SPM12 toolbox. For each of the 61 subjects there is a folder containing 8 images: ·        con0003.nii refers to neuronal activity occurring in the brain by stimulating the first trigeminal branch (V1), ·        con0004.nii refers to neuronal activity occurring in the brain by stimulating the second trigeminal branch (V2),, ·        con0005.nii refers to neuronal activity occurring in the brain by stimulating the third trigeminal branch (V3), ·        con0006.nii refers to neuronal activity occurring in the brain by stimulating the greater occipital nerve (GON). These four images are additionally uploaded in a masked version, where the periaqueductal grey (PAG) is masked, with the suffix ‘_masked’. As the dataset stems from two independent cohorts, the naming convention of the folders differs. We initially measured 25 participants for hypothesis generation. These are the folders include the phrase ’PRISMA’. Power calculations revealed that 36 participants were needed to reproduce the hypothesized results generated with the first cohort. Folders from this cohort start with the phrase ‘subject’. For the results in the PAG, we combined both groups for a robust outcome resulting in 61 participants. Missing numbers in the series stem from either pilots or dropouts due to technical problems during imaging. These images were used for the group statistics. We used a one-way repeated-measure ANOVA implemented in aforementioned software package SPM12.