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Functional and anatomical basis for brain plasticity in facial palsy rehabilitation using the masseteric nerve
Accepted Manuscript Functional and anatomical basis for brain plasticity in facial palsy rehabilitation using the masseteric nerve Javier Buendia, MD, Francis R. Loayza, PhD, Elkin O. Luis, MSc, Marta Celorrio, Maria A. Pastor, MD, PhD, Bernardo Hontanilla, MD, PhD PII:
S1748-6815(15)00517-3
DOI:
10.1016/j.bjps.2015.10.033
Reference:
PRAS 4808
To appear in:
Journal of Plastic, Reconstructive & Aesthetic Surgery
Received Date: 19 May 2015 Revised Date:
7 September 2015
Accepted Date: 21 October 2015
Please cite this article as: Buendia J, Loayza FR, Luis EO, Celorrio M, Pastor MA, Hontanilla B, Functional and anatomical basis for brain plasticity in facial palsy rehabilitation using the masseteric nerve, British Journal of Plastic Surgery (2015), doi: 10.1016/j.bjps.2015.10.033. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Functional and anatomical basis for brain plasticity in facial palsy rehabilitation using the masseteric nerve
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List of Authors: Javier Buendia MDa* Francis R. Loayza, PhDbc§*
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Elkin O. Luis MScb,c Marta Celorriob,c
Bernardo Hontanilla MD, PhDa ** a
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Maria A. Pastor, MD, PhDb,c**
Plastic and Reconstructive Surgery Department, Clinica Universidad de Navarra, University of Navarra, 31008 Pamplona, Spain
b
Functional Neuroimaging Laboratory, Division of Neurosciences, Center for Applied Medical Research (CIMA), University of
Navarra, 31008 Pamplona, Spain. c
CIBERNED, Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, Instituto de Salud Carlos III, Spain
§
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F. Loayza actual affiliation: Neuroimaging and Bioengineering Laboratory, Faculty of Mechanical Engineering, Littoral Polytechnic University (ESPOL), EC090112, Guayaquil, Ecuador.
*Both authors contributed equally to this article.
** Both authors are considered corresponding authors.
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Corresponding Authors:
Bernardo Hontanilla MD, PhD
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Plastic Surgery Department, Clinica Universidad de Navarra, University of Navarra. C/Pío XII 36, 31008 Pamplona, Spain. [email protected]
Maria A. Pastor MD, PhD Functional Neuroimaging Laboratory, Center for Applied Medical Research (CIMA), University of Navarra, 31008 Pamplona, Spain. [email protected]
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ACCEPTED MANUSCRIPT SUMMARY
Several techniques have been described for smile restoration after facial nerve paralysis. When a nerve other than the contralateral facial nerve is used to restore the smile, some
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controversy appears because of the non-physiological mechanism of smile recovering. Different authors have reported natural results with the masseter nerve. The physiological pathways which determine whether this is achieved remain unclear.
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Brain activation pattern measuring Blood-Oxygen-Level-Dependent (BOLD) signal during smiling and jaw-clenching was recorded in a group of 24 healthy subjects (11
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females) using functional magnetic resonance imaging. Effective connectivity of premotor regions was also compared in both tasks.
The brain activation pattern was similar for smile and jaw-clenching tasks. Smile activations showed topographic overlap though more extended for smile than clenching.
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Gender comparisons during facial movements, according to kinematics and BOLD signal, did not reveal significant differences. Effective connectivity results of Psycophysiological interaction (PPI) from the same seeds located in bilateral facial
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premotor regions showed significant task and gender differences (p<0.001). The hypothesis of brain plasticity between the facial nerve area and masseter nerve area
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is supported by the broad cortical overlap in the representation of facial and masseter muscles.
Keywords: Facial; Masseter; Cortical representation; functional magnetic resonance imaging; BOLD; facial palsy.
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ACCEPTED MANUSCRIPT INTRODUCTION
Several techniques have been described for smile restoration after facial nerve paralysis. Depending on the origin of the facial palsy and its evolution over time, the patient may
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require a muscle transfer, either free or transposition, a nerve graft/transposition, or both.
Traditionally the best donor nerve for restoring the smile is the contralateral facial
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nerve. This cross-nerve grafting provides a physiological result, achieving spontaneous smile, but requires nerve grafting and occasionally a two-stage procedure. Using this
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technique, when the patient smiles with the healthy side of the face, the crossed innervation provides contralateral movement. Despite its initial attraction, the risk of injuring the healthy side must be considered, and some authors prefer to use of other donor nerves regardless of the good results achieved with this technique. During recent
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years the masseter nerve has become more popular because it provides a large axonal load resulting in powerful muscle contraction in a one stage procedure, demonstrating advantages compared to hypoglossal or contralateral facial cross-nerve, with objective
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methods of measurement 1,2.
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Different scores have been reported to grade the degree of nerve damage in facial palsy or to assess the results of surgery. These methods include qualitative assessment, as in House-Brackmann, Burres-Fisch and Sunnybrook
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or quantitative assessment with
automatic 3D motion capture systems as in facial CLIMA
2,4
. Thus, better results have
been demonstrated for surgical rehabilitation of short-term facial palsy with the masseter nerve in comparison to cross-facial nerve graft neurotization, with excellent symmetry and a higher degree of recovery 5.
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ACCEPTED MANUSCRIPT Several studies have reported natural smile results with masseter nerve facial rehabilitation, but the physiological pathways remain unclear. Brain plasticity is thought to be the mechanism responsible for masseter nerve efficiency when it is used for dynamic rehabilitation of the smile 1. This is especially interesting considering reports
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that patients can dissociate smiling from jaw-clenching when a trigeminal branch is used for smile restoration. In addition, spontaneous smiling has been described with the use of masseter nerve 6. The question arises when some patients develop spontaneous
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smiles and others do not. It has been reported that some people naturally contract the masseter muscle during a normal smile and it could be a possible explanation of this
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phenomena 7.
The muscles responsible for the smile are innervated by the facial nerve, and chewing muscles are innervated by the third branch of the trigeminal nerve. These two muscular
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groups are closely represented in the somesthetic and motor cortex. The cortical somatotopic organization of the primary motor cortex has been extensively investigated by invasive imaging techniques, such as electrical stimulation of the cortical surface,
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carried out as exploratory maneuvers 8. Recently, using functional magnetic resonance
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imaging (fMRI), a non-invasive method with superior spatial resolution has proved useful for the study of the functional organization of the human brain, with the possibility of creating individual brain maps 9–12.
The purpose of the present study is to define the activation of the facial somatomotor area during smiling and jaw-clenching in healthy volunteers. The maps obtained provide the basis to understand functional changes in cortical plasticity after injury or neuro-reconstructive surgery of facial paralysis
13–19
. We hypothesize, based on clinical
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ACCEPTED MANUSCRIPT findings (dissociated and spontaneous smiles after facial palsy surgery) that facial muscles, recruited for smiling, and the masseter group share cortical representation. We aim to determine the possible interactions between these two neuronal populations in an
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attempt to explain the potential implications for facial palsy surgery.
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ACCEPTED MANUSCRIPT PATIENTS AND METHODS
Participants We recruited 24 healthy volunteers (11 women), mean age= 28.6 (range 21 to 58 years).
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None of the subjects had a history of neurological (including facial palsy) or psychiatric disease. Exclusion criteria were clinical depression and specific MRI safety considerations. All participants were right-handed, as assessed by the Edinburgh
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Handedness Inventory. Prior to scanning, all subjects gave written informed consent,
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and the University of Navarra Ethics Research Committee approved the study.
fMRI study
Prior to the scanning session, all subjects underwent a training session outside the scanner to ensure the correct understanding and familiarity with the task. Volunteers
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were asked to perform 3 simple orders: slight smile, jaw-clench and rest. To be able to study non-emotional expressions of mimicry and to avoid imitating expressions that could lead us to emotional cerebral activation, we designed the experiment in blocks
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with a simple emoticon per task (Figure 1). The tasks were voluntary and repetitive movements, visually guided by emoticons, in blocks of 20s duration consisting in 20
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repetitive visual instructions to move at a frequency of 1Hz. The baseline control task was rest with similar visual input. All tasks were presented in a pseudo-random design during the 11-minute scanning session.
PUT HERE FIGURE 1
Subjects completed the tasks in two scanning sessions. The eye-tracker system was used
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ACCEPTED MANUSCRIPT to control for attention and sleepiness.
To reduce the MRI artifacts produced by movements inside the magnetic field, the subjects were requested to minimize all movements during each task. Thus, for the
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smile task, subjects were instructed to perform a slight contraction of zygomaticus muscles without opening the mouth while minimizing the jaw movement and trying to follow frequency of the visual presentation. Similarly, for the jaw-clenching task,
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subjects were instructed to perform a slight contraction of masseter muscles without opening the mouth, making a jaw-pressure-minimizing jaw movement, following the
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frequency of the visual presentation. For the control task, we requested that the subjects fix their attention on the visual input keeping their facial muscles as relaxed as possible. Thus, subtraction of the control task minimized the effect of the visual input.
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Bold Signal
The change from diamagnetic oxyhemoglobin to paramagnetic deoxyhemoglobin that takes place with brain activation results in decreased signal intensity on MRI, it has
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been named Blood Oxygen Level Dependent (BOLD) signal. It was described in 1990 by Ogawa20. Increases in neuronal activity elevate neuronal demand on oxygen and
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glucose which are delivered via blood stream. This response occurs faster in activated neurons compared to inactive ones. This results in a surplus of oxyhemoglobin localized to the active area, giving rise to a measureable change in the local ratio of oxy-todeoxyhemoglobin, thus providing a localizable marker of activity for MRI.
Scanning protocol Imaging was performed using a 3-Tesla scanner (Siemens Trio TIM, Erlangen,
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ACCEPTED MANUSCRIPT Germany) equipped with a 12-channel head array coil. Each subject underwent two fMRI scan sessions. The presentation of the stimuli was designed using Matlab v7.9 (MathWorks, Natick, MA). A T2-weighted echo planar imaging sequence sensitive to BOLD contrast was used to acquire 220 volumes per session over 11 min. Each volume
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comprised 48 transverse slices with 15% gap, covering the entire brain. Other imaging parameters were as follows: resolution=3mm isotropic, echo time (TE) =30 ms and repetition time (TR) =3.0 s. The first three volumes of each session were discarded and
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not included in the analysis. Anatomical images were also acquired with a high
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resolution MPRAGE sequence.
Imaging data analysis
We used voxel-based Statistical Parametric Mapping (SPM8) software for image processing and analysis (http://www.fil.ion.ucl.ac.uk/spm) implemented in Matlab 7.9.
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For preprocessing the fMRI data, we used the Diffeomorphic Anatomical Registration through Exponentiated Lie algebra toolbox (Dartel) 21. The DARTEL toolbox provided a high-dimensional normalization protocol expected to increase registration accuracy,
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thereby increasing sensitivity and improving localization in our comparisons. In the first preprocessing step, anatomical images for all subjects were segmented into
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gray matter (GM), white matter (WM), and cerebrospinal fluid using the unified segmentation tool
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provided in SPM8. The GM and WM segments were entered into
the DARTEL toolbox in order to create a customized template. DARTEL then registered the individual tissue segments to the template in order to obtain the individual nonlinear deformation fields. After inter-subject registration, all the GM and WM maps were further transformed into the Montreal Neurological Institute (MNI) space, modulated to compensate for spatial normalization effects.
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For the second step, the 440 volumes of the two sessions were realigned to the first volume, corrected for bias field inhomogeneities and co-registered to the anatomical image. Subsequently, fMRI volumes were brain extracted using custom scripts in
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Matlab. Next, the individual tissue deformations obtained were then used to warp and modulate each participant’s fMRI data for nonlinear effects. Finally, the modulated fMRI volumes were smoothed with a 6 mm3 FWHM Gaussian kernel and filtered over
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time using a high-pass filter of 128s.
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Subsequent statistical analyses were performed using a general linear model to estimate the effects at each voxel of the brain 23. At the first level, the time series of each subject was analyzed by combining the two sessions. We modeled the three tasks (smile, jawclenching and rest) as block design, convolving each block with a canonical double
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gamma as a hemodynamic response function (HRF). At this level, we estimated the following contrasts of interest for each subject: smile vs. rest and jaw-clenching vs. rest.
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Contrasts were obtained independently for each session.
At the second level, we used a random effects analysis
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and tested for the contrast
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difference between smile and jaw-clenching tasks and for the hypothetical difference for facial movements between male and female volunteers. We used a two-way Analisys of the variance (ANOVA) with factors: gender and task, each factor containing two levels. Common regions to both tasks were found using conjunction analysis 25.
Additionally, we performed a Psycophysiological Interaction analysis (PPI)
26
with the
objective to assess variations in functional effective connectivity of bilateral motor
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ACCEPTED MANUSCRIPT regions during jaw-clenching and smile. We also tested for gender differences at this level. For the PPI analysis, we used the procedure described by Stephan 27 selecting the coordinates of two seeds 4mm radius using the local maxima of bilateral primary motor area (MI) obtained from the conjunction analysis: one for the left hemisphere and one
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for the right. For each seed and subject, we extracted the temporal series and its first principal component. The PPI term was estimated as the element by element product of the extracted time series (seeds): a) Seeds x Smile vs. rest, and b) Seeds x Jaw-
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clenching vs. rest. The PPI term was included as regressor in a first level analysis. Individual t-contrasts were computed as 1 for the PPI regressor and 0 elsewhere. At the
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second level, we performed a two-way ANOVA with factors: gender and task. Threshold was set as p<0.001 False discovery rate (FDR) cluster-wise corrected.
Facial Kinematics
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To ensure that volunteers were following the tasks properly we asked for a test prior to the scanning as we mentioned before. Although that is a good way for adhesion of the procedure we wanted to ensure that facial movements were segregated. Outside the
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scanner we performed an automatic quantitative analysis of facial expressions with the “facial CLIMA” system. This automatic 3D motion capture system uses infrared
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cameras to detect 18 reflecting-spheres placed on the volunteer´s face. This previously validated system is a highly accurate and operator-independent method of movement evaluation with a reliability of up to 99% in healthy subjects 4.
The subjects were requested to perform the same movements as inside the scanner with the same visual inputs. The sequences of movements were registered with the facial CLIMA equipment. We selected two parameters as controls of facial movements
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ACCEPTED MANUSCRIPT performed in the scanner: commissural excursion and velocity of commissural excursion.. In this fashion we could check if there were any movements during jawclenching or smiling that can artifact results. Data from “facial CLIMA” were analyzed with a Mann-Whitney test comparing differences in commissural excursion (mm) and
PRISM 5.0 (GraphPad Software Inc.)
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RESULTS
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excursion velocity (mm/s) between men and women processed with SPSS 16.0.1 and
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Imaging data
The imaging results showed a similar pattern of brain activity, with significant overlap for smile and jaw-clenching tasks, recruiting mainly bilateral premotor cortex, primary motor area (MI) of the face and primary somatosensory cortex (SI) in the pre and post
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central gyrus and bilateral superior temporal gyrus. Subcortical areas were bilateral basal ganglia: the anterior putamen and prefrontal thalamus and bilateral cerebellum: lobule VI and VIII (Figure 1 Left panel depicts overlapping areas, Right Panel
tasks.
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depicts conjunction analysis). However, there were significant differences between
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PUT HERE FIGURE 2 PUT HERE TABLE 1
During smiling bilateral MI (with left hemisphere predominance), Pre-Supplementary motor areas and insular regions (both anterior insula and temporoparietal junction), showed greater activation. During jaw-clenching, increased activity was recorded in dorsal and dorso-lateral prefrontal cortex and cingulate cortex extended to caudate
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ACCEPTED MANUSCRIPT (p<0.001 FDR cluster-wise corrected). Gender comparisons did not reveal any significant differences in BOLD signal during facial movements. PUT HERE FIGURE 3
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PUT HERE TABLE 3
Connectivity results (PPI) from seeds located in bilateral facial MI showed significant task and gender differences: The main effect of the task showed that facial MI had
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increased connectivity during smiling with the inferior frontal cortex and superior temporal gyrus with left predominance. During the jaw-clenching task, we found
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increased connectivity from bilateral facial MI seeds with the middle frontal gyrus with right predominance (Figure 3 Upper row). There were significant effect of gender in connectivity from bilateral facial MI, emerging periacueductal gray, in collicular
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PUT HERE TABLE 3
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regions and bilateral thalamic nuclei (Figure 3 Lower row).
Facial Kinematics
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Kinematics of facial movements did not reveal any significant gender differences. We obtained a mean excursion distance of 3.6mm in men and 3.7mm in women (p=0.884), and a mean velocity of 27.45mm/s in men and 26.33mm/s (p=0.505) in women while smiling. During the jaw-clenching phase we obtained almost no movement regarding these parameters, which confirms segregation of movements during the task and avoids possible interactions for the fMRI imaging. PUT HERE FIGURE 5
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PUT HERE VIDEOS 1 AND 2
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ACCEPTED MANUSCRIPT DISCUSSION
Several techniques for facial reanimation have been described. In all dynamic techniques the smiling movement can be restored with different methods such as direct
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neurotization, nerve grafting or free muscle transfer, taking the contralateral facial, hypoglossal or masseter as donor nerves. Results with these techniques can vary, and many surgeons are keen to determine which one may achieve a better result. The
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technique choice is made considering the cause of the paralysis, age, general condition,
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and expectations of the patient.
When the use of the masseter nerve was introduced it was found to be an easy and reliable donor nerve but was considered by some unable to result into a spontaneous smile or dissociated from chewing. Further studies, however, postulated a dissociated
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and even spontaneous smile using this nerve after years of training, which can be achieved by neuronal plasticity6,28. Cortical reorganization of facial movements is not well established, but by studying the cortical representation of the movements produced
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by the masseter and facial nerves, we can define the anatomical basis for this
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phenomenon (figure 5).
When structural injury occurs, several changes start to develop within the neuronal tissue with the goal of functional adaptation. The way this happens or the reason it fails is not well established. This adaptation can be traced by fMRI to determine the anatomical basis for the neuronal plasticity observed in the rehabilitation of facial paralysis.
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ACCEPTED MANUSCRIPT We found overlapping patterns of activation for smiling and jaw-clenching with a more extended activation pattern for smiling movements. As expected, both voluntary repetitive movements activated primary motor and premotor cortex, somatosensory cortex, cerebellum and basal ganglia. It is important to emphasize that in our design,
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movements during the fMRI were repetitive, controlled in number and without emotional load.
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The result of wide overlapping of cortical representation during the recruitment of the facial muscles and masseter is consistent with the concept that a cranial nerve that
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shares the same cortical areas may be the best candidate to replace the damaged function of the other. It is believed that neuronal plasticity is developed either by the reactivation of inactive preexisting connections or the creation of new ones
29,30
, and
this process is easier the closer these areas are. For this reason, the similar cortical
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representation shown in our experiment may support the possibility to develop a dissociated and a spontaneous smile when masseter nerve is used in smile rehabilitation.
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We can define a dissociated smile when a patient can voluntary smile without contracting chewing muscles, or in other words while opening the mouth. A
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spontaneous smile happens unintentionally and may be provoked by emotions, humor or as an imitating expression. Expression of laughter seems to depend on two partially independent neuronal pathways as seen in the anterior opercular syndrome, where patients manifest only a partial face, jaw and pharynx paralysis, affecting only voluntary movements, while can still smile spontaneously. This supports the idea of different pathways for voluntary and involuntary movements for smiling and clenching. Whether a patient will develop a spontaneous smile or not is still unpredictable when
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ACCEPTED MANUSCRIPT using the masseter nerve. Some structures responsible for emotions may be implicated. Despite a spontaneous smile can be easily provoked in the clinical setting, a reproducible and reliable series of spontaneous smile under fMRI experimental
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conditions would be difficult to record.
The question of why some people can develop a spontaneous smile may be explained by different hypotheses. Both jaw-clenching and smile are consciously self-initiated
the basal ganglia and the cerebellum
31,32
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motor functions under the control of premotor frontal opercular areas, SMA, face MI, . Each orofacial muscle is represented in
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multiple microzones in the face area of MI that are intermingled and often overlap with other orofacial microzones as well as neighboring microzones representing the limbs and neck. It has been suggested that face MI characteristics of bilateral overlapping motor representation are consistent with the idea that the MI is organized into efferent
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microzones to control movements involving the coordinated activation of more than one muscle, rather than the activation of individual muscles. According to this idea, each of the motor-output microzones may control one of the many contextual functions in
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which that muscle participates31,33–35.
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Neuroimaging fMRI studies have shown that voluntary elemental orofacial movements (e.g., jaw, lip or tongue movements) are associated with activation of facial MI. This activation is part of a distributed network that may include other cortical and subcortical regions such as the SI, SMA, CMA/swallow cortex, thalamus, globus pallidus, caudate nucleus and putamen. Many of the orofacial movements have bilateral representation with considerable overlap of jaw and tongue motor representations within MI 31,36.
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ACCEPTED MANUSCRIPT Some subjects naturally contract masseter muscle while performing a complete smile measured with electromyography (EMG)7. This result suggests that spontaneous smile could be achieved by those who previously smiled with masseter contraction supporting the results of the present study that reflect overlapping of motor cortical activity of
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smile and jaw-clenching. Conversely, the finding of overlapping muscle representation areas does not reflected directly a co-contraction since many muscle groups share similar motor areas (For a review see Michael S. A. Graziano, Cortical Action
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Representations Published In: Brain Mapping: An Encyclopedic Reference. Toga AW, Poldrack RA (Eds) Amsterdam: Elsevier, 2015). In fact our study was specifically
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designed to avoid contaminated movements by performing slight smiling. On the other hand, jaw-clenching may recruit other muscles as the temporalis, which are controlled by the same cortical area leading to a possible higher activation pattern, but we also tried to avoid this making a delicate clench. Thus, as previously reported, that some
whereas others not6, 28.
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subjects, tend to have a natural facility to develop a dissociated and spontaneous smile
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The distinct activation of cerebral cortex while smiling and jaw-clenching has recently been described by fMRI studies
37,38
. A study in facial palsy patients operated using
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Lengthening Temporalis Myoplasty, which innervation is provided by the trigeminal nerve as in the masseter nerve, showed that activation areas for smiling and jawclenching become one after smile restoration 38.
A recent study, not aiming to compare directly smiling and jaw-clenching, found two different activation patterns with minimal overlap for the masseter and facial nerves cortical representation using repetitive facial and masseter movements in healthy
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37
. However, the introduction of tapping as a control task in this study may
have distorted the cortical representation of the facial and masseter area due to the proximity of the cortical somatomotor hand area. In our setting these areas showed a high overlap pattern that is more consistent with reproducible clinical findings after 1,5,6,28,38,39
. The finding that these two areas share the same activation patterns
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surgery
better explains the phenomenon of a dissociated or spontaneous smile after surgery in
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most patients using the masseteric nerve as donor nerve 1,38,40.
An overlapped activation pattern between movements of smiling and jaw-clenching
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suggest that the two movements share the motor and somesthetic representation in the cerebral and cerebellar cortex. The larger activation while smiling compared to jawclenching may explain a more complex action, in spite of being discrete movements, and the need to perform constant and long-term training to achieve neuronal plasticity.
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The repetitive movement network and visual input recruited to produce timed small movements that are visually guided would be cancelled out when comparing the two different conditions because of the common visual clue frequency in both conditions.
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Furthermore, despite the fact that both tasks share motor, premotor, cerebellar and basal ganglia structures, PPI results showed different patterns of effective connectivity of
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facial MI during smile and jaw-clenching tasks. Since both hemispheres contribute to both kinds of processes, we found that the connectivity of the MI was lateralized to the prefrontal left hemisphere during smile and to the prefrontal right hemisphere during jaw-clenching. These findings, that need further consideration, are in line with the generally accepted idea that the hemispheres exhibits asymmetry in both structure and function6,27,28,40,41.
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ACCEPTED MANUSCRIPT Additionally, we found different patterns of effective connectivity related to gender. Males tended to have increased connectivity mainly between facial MI and basal ganglia, thalamic and mesencephalic structures. The periaqueductal gray circuits to facial and trigeminal motor nuclei bear striking similarities and regulate both sensory
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processes and control of motor output42,43. It is known that better outcomes using the masseter nerve are achieved after patients undergo long-term training 1, and in patients with a higher level of education. It has also been proposed that these results may be
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influenced by gender 39. Although further studies are clearly needed, these findings may have crucial importance in the treatment of facial paralysis, which might be supported
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by the different connectivity patterns shown between the two tasks (smile and jawclenching), and between males and females in the present study.
CONCLUSIONS
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In light of clinical results, a natural smile can be achieved when using the masseter nerve in facial palsy rehabilitation. The hypothesis of brain plasticity between the facial nerve area and masseter nerve area is supported by the broad cortical overlap in the
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representation of facial and masseter muscles. Further studies are needed to assess why
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some people tend to develop dissociation and spontaneous smile and why other patients do not when using the masseteric nerve as donor nerve in the management of facial paralisis.
CONFLICT OF INTEREST The authors declare that there is no conflict of interests regarding the publication of this paper.
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AKNOWLEDGMENTS This work was supported by Foundation for Applied Medical Research, University of Navarra (FIMA), and Foundation Mutua Madrileña (FMMA). FRL was supported by
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the Senescyt through the Prometheus Program of the Ecuadorian Government.
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ACCEPTED MANUSCRIPT FIGURE LEGENDS Figure 1. Explanation of two emoticons in the control condition. Figure 2. Image shows the significant activity overlapped on an inflated brain. Left
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panel: Smile > control in hot color; Jaw-Clenching > control in cold colors. Green shows the overlapping regions between both tasks. The right panel depicts common areas in the conjunction analysis between both tasks. P<0.001 FDR cluster-wise
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corrected.
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Figure 3. Shows the significant differences between Smile and Jaw-Clenching tasks. Hot colors represent significant areas greater in the contrast Smile > Jaw-Clenching and Cold colors for significant areas greater in the contrast Jaw Clenching > Smile. p<0.001 FDR cluster-wise corrected.
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Figure 4. Upper row depicts changes in connectivity from bilateral seeds (in blue) located on facial MI. Violet color represents t-test with increases in connectivity during jaw-clenching compared to resting task, and green for smile compared to rest. Second
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row depicts t-test of brain regions with gender differences in effective connectivity from seeds located on facial MI during smile and jaw-clenching tasks together p<0.001 FDR
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cluster-wise corrected in both analyses. Figure 5. Results from facial kinematics for speed contraction and commissural excursion while smiling among men and women. Figure 6. A 27 years old patient with a left complete facial paralysis after neurofibroma resection in the facial nerve one year ago. A. Preop of the patient when smiling after nerve transference with the masseteric nerve to the facial nerve. B. Postop of the patient when smiling. This woman can smile with the mouth opened and have a spontaneously
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smile.
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ACCEPTED MANUSCRIPT VIDEO LEGENDS Video 1. Preop. of patient of Fig. 5.
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Video 1. Postop. of patient of Fig. 5.
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TABLES Table 1. Main effect of task - Smile and Jaw-clenching
MNI Coordinates
Stats.
Cluster
X
t value
size
Y
Z
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Region
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Main effect of task - Smile and Jaw-clenching (Post-hoc comparisons)
Smile > Jaw-clenching -44
11
-9
4.67
1232
39
7
8
4.84
634
-56
-9
43
7.28
816
53
-9
42
5.52
811
Left Middle Temporal gyrus
-53
-52
7
4.35
411
Right Middle Temporal gyrus
57
50
11
4.42
835
Cerebellar vermis
-2
-60
-5
4.27
624
0
3
54
5.00
-9
5.11
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Left Insula lobe extended to IFG BA44 Right Insula lobe extended to IFG BA44 Left Postcentral gyrus
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Right Precentral gyrus
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Supplementary Motor Area
347
Jaw-clenching > Smile
Bilateral ACC extended to Orbital and -11
32
1541
Caudate nucleus Right Middle Frontal Gyrus
1200 42
48
6
4.63
32
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Table 2. Conjunction analysis between the two conditions Smile and Jaw-clenching.
Region
MNI Coordinates
Stats.
Cluster
X
t value
size
Y
Bilateral Cerebellum:
Bilateral Basal Ganglia:
-58
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Z
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Smile - Jaw-clenching
Lobule VI and VIII
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Overlapped regions - Smile and Jaw-clenching (Conjunction analysis)
-23
13.16
23442
-23
-4
9
7.59
-26
-4
-8
8.09
-54
-7
43
11.37
5060
Right Postcentral gyrus (facial MI)
57
-7
42
7.95
2892
Supplementary Motor Area
-2
-1
60
9.25
2858
Left Superior Temporal Gyrus
-48
-34
21
7.64
1759
Right Superior Temporal Gyrus
47
-33
21
4.67
338
Thalamus and Putamen Bilateral Amygdala
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Left Postcentral gyrus (facial MI)
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Effective connectivity PPI results Changes in connectivity from seed located on facial MI MNI Coordinates
Stats.
Cluster
X
t value
size
Y
Z
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Region
Increases in connectivity during Jaw-clenching compared to Smile Right Inferior Frontal (p. Triangularis)
41
30
35
38
4.93
18
4.46
655
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Right Middle Frontal
13
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Increases in connectivity during Smile compared to Jaw-clenching Left Inferior Frontal (p. Orbitalis)
-51
32
-6
4.48 389
Left Inferior Frontal (p. Triangularis)
26
6
3.99
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-56
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Gender differences in effective connectivity during Smile and Jaw-Clenching tasks
Bilateral periacueductal grey
6
-24
-11 6.14
-22
-12
Left Thalamus prefrontal
-12
-7
12
5.41
Left Thalamus parietal
-21
-10
19
4.73
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-3
752
643 Left Thalamus Temporal
-11
-24
12
4.66
Left Thalamus premotor
-17
-13
4
3.47
Right Thalamus prefrontal
20
-10
16
5.58
489
34
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S1748-6815(15)00517-3
DOI:
10.1016/j.bjps.2015.10.033
Reference:
PRAS 4808
To appear in:
Journal of Plastic, Reconstructive & Aesthetic Surgery
Received Date: 19 May 2015 Revised Date:
7 September 2015
Accepted Date: 21 October 2015
Please cite this article as: Buendia J, Loayza FR, Luis EO, Celorrio M, Pastor MA, Hontanilla B, Functional and anatomical basis for brain plasticity in facial palsy rehabilitation using the masseteric nerve, British Journal of Plastic Surgery (2015), doi: 10.1016/j.bjps.2015.10.033. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Functional and anatomical basis for brain plasticity in facial palsy rehabilitation using the masseteric nerve
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List of Authors: Javier Buendia MDa* Francis R. Loayza, PhDbc§*
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Elkin O. Luis MScb,c Marta Celorriob,c
Bernardo Hontanilla MD, PhDa ** a
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Maria A. Pastor, MD, PhDb,c**
Plastic and Reconstructive Surgery Department, Clinica Universidad de Navarra, University of Navarra, 31008 Pamplona, Spain
b
Functional Neuroimaging Laboratory, Division of Neurosciences, Center for Applied Medical Research (CIMA), University of
Navarra, 31008 Pamplona, Spain. c
CIBERNED, Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, Instituto de Salud Carlos III, Spain
§
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F. Loayza actual affiliation: Neuroimaging and Bioengineering Laboratory, Faculty of Mechanical Engineering, Littoral Polytechnic University (ESPOL), EC090112, Guayaquil, Ecuador.
*Both authors contributed equally to this article.
** Both authors are considered corresponding authors.
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Corresponding Authors:
Bernardo Hontanilla MD, PhD
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Plastic Surgery Department, Clinica Universidad de Navarra, University of Navarra. C/Pío XII 36, 31008 Pamplona, Spain. [email protected]
Maria A. Pastor MD, PhD Functional Neuroimaging Laboratory, Center for Applied Medical Research (CIMA), University of Navarra, 31008 Pamplona, Spain. [email protected]
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ACCEPTED MANUSCRIPT SUMMARY
Several techniques have been described for smile restoration after facial nerve paralysis. When a nerve other than the contralateral facial nerve is used to restore the smile, some
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controversy appears because of the non-physiological mechanism of smile recovering. Different authors have reported natural results with the masseter nerve. The physiological pathways which determine whether this is achieved remain unclear.
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Brain activation pattern measuring Blood-Oxygen-Level-Dependent (BOLD) signal during smiling and jaw-clenching was recorded in a group of 24 healthy subjects (11
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females) using functional magnetic resonance imaging. Effective connectivity of premotor regions was also compared in both tasks.
The brain activation pattern was similar for smile and jaw-clenching tasks. Smile activations showed topographic overlap though more extended for smile than clenching.
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Gender comparisons during facial movements, according to kinematics and BOLD signal, did not reveal significant differences. Effective connectivity results of Psycophysiological interaction (PPI) from the same seeds located in bilateral facial
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premotor regions showed significant task and gender differences (p<0.001). The hypothesis of brain plasticity between the facial nerve area and masseter nerve area
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is supported by the broad cortical overlap in the representation of facial and masseter muscles.
Keywords: Facial; Masseter; Cortical representation; functional magnetic resonance imaging; BOLD; facial palsy.
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ACCEPTED MANUSCRIPT INTRODUCTION
Several techniques have been described for smile restoration after facial nerve paralysis. Depending on the origin of the facial palsy and its evolution over time, the patient may
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require a muscle transfer, either free or transposition, a nerve graft/transposition, or both.
Traditionally the best donor nerve for restoring the smile is the contralateral facial
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nerve. This cross-nerve grafting provides a physiological result, achieving spontaneous smile, but requires nerve grafting and occasionally a two-stage procedure. Using this
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technique, when the patient smiles with the healthy side of the face, the crossed innervation provides contralateral movement. Despite its initial attraction, the risk of injuring the healthy side must be considered, and some authors prefer to use of other donor nerves regardless of the good results achieved with this technique. During recent
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years the masseter nerve has become more popular because it provides a large axonal load resulting in powerful muscle contraction in a one stage procedure, demonstrating advantages compared to hypoglossal or contralateral facial cross-nerve, with objective
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methods of measurement 1,2.
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Different scores have been reported to grade the degree of nerve damage in facial palsy or to assess the results of surgery. These methods include qualitative assessment, as in House-Brackmann, Burres-Fisch and Sunnybrook
3
or quantitative assessment with
automatic 3D motion capture systems as in facial CLIMA
2,4
. Thus, better results have
been demonstrated for surgical rehabilitation of short-term facial palsy with the masseter nerve in comparison to cross-facial nerve graft neurotization, with excellent symmetry and a higher degree of recovery 5.
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ACCEPTED MANUSCRIPT Several studies have reported natural smile results with masseter nerve facial rehabilitation, but the physiological pathways remain unclear. Brain plasticity is thought to be the mechanism responsible for masseter nerve efficiency when it is used for dynamic rehabilitation of the smile 1. This is especially interesting considering reports
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that patients can dissociate smiling from jaw-clenching when a trigeminal branch is used for smile restoration. In addition, spontaneous smiling has been described with the use of masseter nerve 6. The question arises when some patients develop spontaneous
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smiles and others do not. It has been reported that some people naturally contract the masseter muscle during a normal smile and it could be a possible explanation of this
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phenomena 7.
The muscles responsible for the smile are innervated by the facial nerve, and chewing muscles are innervated by the third branch of the trigeminal nerve. These two muscular
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groups are closely represented in the somesthetic and motor cortex. The cortical somatotopic organization of the primary motor cortex has been extensively investigated by invasive imaging techniques, such as electrical stimulation of the cortical surface,
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carried out as exploratory maneuvers 8. Recently, using functional magnetic resonance
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imaging (fMRI), a non-invasive method with superior spatial resolution has proved useful for the study of the functional organization of the human brain, with the possibility of creating individual brain maps 9–12.
The purpose of the present study is to define the activation of the facial somatomotor area during smiling and jaw-clenching in healthy volunteers. The maps obtained provide the basis to understand functional changes in cortical plasticity after injury or neuro-reconstructive surgery of facial paralysis
13–19
. We hypothesize, based on clinical
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ACCEPTED MANUSCRIPT findings (dissociated and spontaneous smiles after facial palsy surgery) that facial muscles, recruited for smiling, and the masseter group share cortical representation. We aim to determine the possible interactions between these two neuronal populations in an
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attempt to explain the potential implications for facial palsy surgery.
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ACCEPTED MANUSCRIPT PATIENTS AND METHODS
Participants We recruited 24 healthy volunteers (11 women), mean age= 28.6 (range 21 to 58 years).
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None of the subjects had a history of neurological (including facial palsy) or psychiatric disease. Exclusion criteria were clinical depression and specific MRI safety considerations. All participants were right-handed, as assessed by the Edinburgh
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Handedness Inventory. Prior to scanning, all subjects gave written informed consent,
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and the University of Navarra Ethics Research Committee approved the study.
fMRI study
Prior to the scanning session, all subjects underwent a training session outside the scanner to ensure the correct understanding and familiarity with the task. Volunteers
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were asked to perform 3 simple orders: slight smile, jaw-clench and rest. To be able to study non-emotional expressions of mimicry and to avoid imitating expressions that could lead us to emotional cerebral activation, we designed the experiment in blocks
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with a simple emoticon per task (Figure 1). The tasks were voluntary and repetitive movements, visually guided by emoticons, in blocks of 20s duration consisting in 20
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repetitive visual instructions to move at a frequency of 1Hz. The baseline control task was rest with similar visual input. All tasks were presented in a pseudo-random design during the 11-minute scanning session.
PUT HERE FIGURE 1
Subjects completed the tasks in two scanning sessions. The eye-tracker system was used
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To reduce the MRI artifacts produced by movements inside the magnetic field, the subjects were requested to minimize all movements during each task. Thus, for the
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smile task, subjects were instructed to perform a slight contraction of zygomaticus muscles without opening the mouth while minimizing the jaw movement and trying to follow frequency of the visual presentation. Similarly, for the jaw-clenching task,
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subjects were instructed to perform a slight contraction of masseter muscles without opening the mouth, making a jaw-pressure-minimizing jaw movement, following the
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frequency of the visual presentation. For the control task, we requested that the subjects fix their attention on the visual input keeping their facial muscles as relaxed as possible. Thus, subtraction of the control task minimized the effect of the visual input.
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Bold Signal
The change from diamagnetic oxyhemoglobin to paramagnetic deoxyhemoglobin that takes place with brain activation results in decreased signal intensity on MRI, it has
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been named Blood Oxygen Level Dependent (BOLD) signal. It was described in 1990 by Ogawa20. Increases in neuronal activity elevate neuronal demand on oxygen and
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glucose which are delivered via blood stream. This response occurs faster in activated neurons compared to inactive ones. This results in a surplus of oxyhemoglobin localized to the active area, giving rise to a measureable change in the local ratio of oxy-todeoxyhemoglobin, thus providing a localizable marker of activity for MRI.
Scanning protocol Imaging was performed using a 3-Tesla scanner (Siemens Trio TIM, Erlangen,
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ACCEPTED MANUSCRIPT Germany) equipped with a 12-channel head array coil. Each subject underwent two fMRI scan sessions. The presentation of the stimuli was designed using Matlab v7.9 (MathWorks, Natick, MA). A T2-weighted echo planar imaging sequence sensitive to BOLD contrast was used to acquire 220 volumes per session over 11 min. Each volume
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comprised 48 transverse slices with 15% gap, covering the entire brain. Other imaging parameters were as follows: resolution=3mm isotropic, echo time (TE) =30 ms and repetition time (TR) =3.0 s. The first three volumes of each session were discarded and
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not included in the analysis. Anatomical images were also acquired with a high
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resolution MPRAGE sequence.
Imaging data analysis
We used voxel-based Statistical Parametric Mapping (SPM8) software for image processing and analysis (http://www.fil.ion.ucl.ac.uk/spm) implemented in Matlab 7.9.
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For preprocessing the fMRI data, we used the Diffeomorphic Anatomical Registration through Exponentiated Lie algebra toolbox (Dartel) 21. The DARTEL toolbox provided a high-dimensional normalization protocol expected to increase registration accuracy,
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thereby increasing sensitivity and improving localization in our comparisons. In the first preprocessing step, anatomical images for all subjects were segmented into
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gray matter (GM), white matter (WM), and cerebrospinal fluid using the unified segmentation tool
22
provided in SPM8. The GM and WM segments were entered into
the DARTEL toolbox in order to create a customized template. DARTEL then registered the individual tissue segments to the template in order to obtain the individual nonlinear deformation fields. After inter-subject registration, all the GM and WM maps were further transformed into the Montreal Neurological Institute (MNI) space, modulated to compensate for spatial normalization effects.
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For the second step, the 440 volumes of the two sessions were realigned to the first volume, corrected for bias field inhomogeneities and co-registered to the anatomical image. Subsequently, fMRI volumes were brain extracted using custom scripts in
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Matlab. Next, the individual tissue deformations obtained were then used to warp and modulate each participant’s fMRI data for nonlinear effects. Finally, the modulated fMRI volumes were smoothed with a 6 mm3 FWHM Gaussian kernel and filtered over
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time using a high-pass filter of 128s.
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Subsequent statistical analyses were performed using a general linear model to estimate the effects at each voxel of the brain 23. At the first level, the time series of each subject was analyzed by combining the two sessions. We modeled the three tasks (smile, jawclenching and rest) as block design, convolving each block with a canonical double
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gamma as a hemodynamic response function (HRF). At this level, we estimated the following contrasts of interest for each subject: smile vs. rest and jaw-clenching vs. rest.
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Contrasts were obtained independently for each session.
At the second level, we used a random effects analysis
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and tested for the contrast
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difference between smile and jaw-clenching tasks and for the hypothetical difference for facial movements between male and female volunteers. We used a two-way Analisys of the variance (ANOVA) with factors: gender and task, each factor containing two levels. Common regions to both tasks were found using conjunction analysis 25.
Additionally, we performed a Psycophysiological Interaction analysis (PPI)
26
with the
objective to assess variations in functional effective connectivity of bilateral motor
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ACCEPTED MANUSCRIPT regions during jaw-clenching and smile. We also tested for gender differences at this level. For the PPI analysis, we used the procedure described by Stephan 27 selecting the coordinates of two seeds 4mm radius using the local maxima of bilateral primary motor area (MI) obtained from the conjunction analysis: one for the left hemisphere and one
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for the right. For each seed and subject, we extracted the temporal series and its first principal component. The PPI term was estimated as the element by element product of the extracted time series (seeds): a) Seeds x Smile vs. rest, and b) Seeds x Jaw-
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clenching vs. rest. The PPI term was included as regressor in a first level analysis. Individual t-contrasts were computed as 1 for the PPI regressor and 0 elsewhere. At the
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second level, we performed a two-way ANOVA with factors: gender and task. Threshold was set as p<0.001 False discovery rate (FDR) cluster-wise corrected.
Facial Kinematics
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To ensure that volunteers were following the tasks properly we asked for a test prior to the scanning as we mentioned before. Although that is a good way for adhesion of the procedure we wanted to ensure that facial movements were segregated. Outside the
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scanner we performed an automatic quantitative analysis of facial expressions with the “facial CLIMA” system. This automatic 3D motion capture system uses infrared
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cameras to detect 18 reflecting-spheres placed on the volunteer´s face. This previously validated system is a highly accurate and operator-independent method of movement evaluation with a reliability of up to 99% in healthy subjects 4.
The subjects were requested to perform the same movements as inside the scanner with the same visual inputs. The sequences of movements were registered with the facial CLIMA equipment. We selected two parameters as controls of facial movements
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ACCEPTED MANUSCRIPT performed in the scanner: commissural excursion and velocity of commissural excursion.. In this fashion we could check if there were any movements during jawclenching or smiling that can artifact results. Data from “facial CLIMA” were analyzed with a Mann-Whitney test comparing differences in commissural excursion (mm) and
PRISM 5.0 (GraphPad Software Inc.)
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RESULTS
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excursion velocity (mm/s) between men and women processed with SPSS 16.0.1 and
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Imaging data
The imaging results showed a similar pattern of brain activity, with significant overlap for smile and jaw-clenching tasks, recruiting mainly bilateral premotor cortex, primary motor area (MI) of the face and primary somatosensory cortex (SI) in the pre and post
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central gyrus and bilateral superior temporal gyrus. Subcortical areas were bilateral basal ganglia: the anterior putamen and prefrontal thalamus and bilateral cerebellum: lobule VI and VIII (Figure 1 Left panel depicts overlapping areas, Right Panel
tasks.
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depicts conjunction analysis). However, there were significant differences between
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PUT HERE FIGURE 2 PUT HERE TABLE 1
During smiling bilateral MI (with left hemisphere predominance), Pre-Supplementary motor areas and insular regions (both anterior insula and temporoparietal junction), showed greater activation. During jaw-clenching, increased activity was recorded in dorsal and dorso-lateral prefrontal cortex and cingulate cortex extended to caudate
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ACCEPTED MANUSCRIPT (p<0.001 FDR cluster-wise corrected). Gender comparisons did not reveal any significant differences in BOLD signal during facial movements. PUT HERE FIGURE 3
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PUT HERE TABLE 3
Connectivity results (PPI) from seeds located in bilateral facial MI showed significant task and gender differences: The main effect of the task showed that facial MI had
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increased connectivity during smiling with the inferior frontal cortex and superior temporal gyrus with left predominance. During the jaw-clenching task, we found
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increased connectivity from bilateral facial MI seeds with the middle frontal gyrus with right predominance (Figure 3 Upper row). There were significant effect of gender in connectivity from bilateral facial MI, emerging periacueductal gray, in collicular
PUT HERE FIGURE 4
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PUT HERE TABLE 3
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regions and bilateral thalamic nuclei (Figure 3 Lower row).
Facial Kinematics
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Kinematics of facial movements did not reveal any significant gender differences. We obtained a mean excursion distance of 3.6mm in men and 3.7mm in women (p=0.884), and a mean velocity of 27.45mm/s in men and 26.33mm/s (p=0.505) in women while smiling. During the jaw-clenching phase we obtained almost no movement regarding these parameters, which confirms segregation of movements during the task and avoids possible interactions for the fMRI imaging. PUT HERE FIGURE 5
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ACCEPTED MANUSCRIPT PUT HERE FIGURE 6
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PUT HERE VIDEOS 1 AND 2
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ACCEPTED MANUSCRIPT DISCUSSION
Several techniques for facial reanimation have been described. In all dynamic techniques the smiling movement can be restored with different methods such as direct
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neurotization, nerve grafting or free muscle transfer, taking the contralateral facial, hypoglossal or masseter as donor nerves. Results with these techniques can vary, and many surgeons are keen to determine which one may achieve a better result. The
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technique choice is made considering the cause of the paralysis, age, general condition,
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and expectations of the patient.
When the use of the masseter nerve was introduced it was found to be an easy and reliable donor nerve but was considered by some unable to result into a spontaneous smile or dissociated from chewing. Further studies, however, postulated a dissociated
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and even spontaneous smile using this nerve after years of training, which can be achieved by neuronal plasticity6,28. Cortical reorganization of facial movements is not well established, but by studying the cortical representation of the movements produced
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by the masseter and facial nerves, we can define the anatomical basis for this
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phenomenon (figure 5).
When structural injury occurs, several changes start to develop within the neuronal tissue with the goal of functional adaptation. The way this happens or the reason it fails is not well established. This adaptation can be traced by fMRI to determine the anatomical basis for the neuronal plasticity observed in the rehabilitation of facial paralysis.
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ACCEPTED MANUSCRIPT We found overlapping patterns of activation for smiling and jaw-clenching with a more extended activation pattern for smiling movements. As expected, both voluntary repetitive movements activated primary motor and premotor cortex, somatosensory cortex, cerebellum and basal ganglia. It is important to emphasize that in our design,
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movements during the fMRI were repetitive, controlled in number and without emotional load.
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The result of wide overlapping of cortical representation during the recruitment of the facial muscles and masseter is consistent with the concept that a cranial nerve that
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shares the same cortical areas may be the best candidate to replace the damaged function of the other. It is believed that neuronal plasticity is developed either by the reactivation of inactive preexisting connections or the creation of new ones
29,30
, and
this process is easier the closer these areas are. For this reason, the similar cortical
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representation shown in our experiment may support the possibility to develop a dissociated and a spontaneous smile when masseter nerve is used in smile rehabilitation.
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We can define a dissociated smile when a patient can voluntary smile without contracting chewing muscles, or in other words while opening the mouth. A
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spontaneous smile happens unintentionally and may be provoked by emotions, humor or as an imitating expression. Expression of laughter seems to depend on two partially independent neuronal pathways as seen in the anterior opercular syndrome, where patients manifest only a partial face, jaw and pharynx paralysis, affecting only voluntary movements, while can still smile spontaneously. This supports the idea of different pathways for voluntary and involuntary movements for smiling and clenching. Whether a patient will develop a spontaneous smile or not is still unpredictable when
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ACCEPTED MANUSCRIPT using the masseter nerve. Some structures responsible for emotions may be implicated. Despite a spontaneous smile can be easily provoked in the clinical setting, a reproducible and reliable series of spontaneous smile under fMRI experimental
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conditions would be difficult to record.
The question of why some people can develop a spontaneous smile may be explained by different hypotheses. Both jaw-clenching and smile are consciously self-initiated
the basal ganglia and the cerebellum
31,32
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motor functions under the control of premotor frontal opercular areas, SMA, face MI, . Each orofacial muscle is represented in
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multiple microzones in the face area of MI that are intermingled and often overlap with other orofacial microzones as well as neighboring microzones representing the limbs and neck. It has been suggested that face MI characteristics of bilateral overlapping motor representation are consistent with the idea that the MI is organized into efferent
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microzones to control movements involving the coordinated activation of more than one muscle, rather than the activation of individual muscles. According to this idea, each of the motor-output microzones may control one of the many contextual functions in
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which that muscle participates31,33–35.
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Neuroimaging fMRI studies have shown that voluntary elemental orofacial movements (e.g., jaw, lip or tongue movements) are associated with activation of facial MI. This activation is part of a distributed network that may include other cortical and subcortical regions such as the SI, SMA, CMA/swallow cortex, thalamus, globus pallidus, caudate nucleus and putamen. Many of the orofacial movements have bilateral representation with considerable overlap of jaw and tongue motor representations within MI 31,36.
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ACCEPTED MANUSCRIPT Some subjects naturally contract masseter muscle while performing a complete smile measured with electromyography (EMG)7. This result suggests that spontaneous smile could be achieved by those who previously smiled with masseter contraction supporting the results of the present study that reflect overlapping of motor cortical activity of
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smile and jaw-clenching. Conversely, the finding of overlapping muscle representation areas does not reflected directly a co-contraction since many muscle groups share similar motor areas (For a review see Michael S. A. Graziano, Cortical Action
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Representations Published In: Brain Mapping: An Encyclopedic Reference. Toga AW, Poldrack RA (Eds) Amsterdam: Elsevier, 2015). In fact our study was specifically
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designed to avoid contaminated movements by performing slight smiling. On the other hand, jaw-clenching may recruit other muscles as the temporalis, which are controlled by the same cortical area leading to a possible higher activation pattern, but we also tried to avoid this making a delicate clench. Thus, as previously reported, that some
whereas others not6, 28.
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subjects, tend to have a natural facility to develop a dissociated and spontaneous smile
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The distinct activation of cerebral cortex while smiling and jaw-clenching has recently been described by fMRI studies
37,38
. A study in facial palsy patients operated using
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Lengthening Temporalis Myoplasty, which innervation is provided by the trigeminal nerve as in the masseter nerve, showed that activation areas for smiling and jawclenching become one after smile restoration 38.
A recent study, not aiming to compare directly smiling and jaw-clenching, found two different activation patterns with minimal overlap for the masseter and facial nerves cortical representation using repetitive facial and masseter movements in healthy
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ACCEPTED MANUSCRIPT subjects
37
. However, the introduction of tapping as a control task in this study may
have distorted the cortical representation of the facial and masseter area due to the proximity of the cortical somatomotor hand area. In our setting these areas showed a high overlap pattern that is more consistent with reproducible clinical findings after 1,5,6,28,38,39
. The finding that these two areas share the same activation patterns
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surgery
better explains the phenomenon of a dissociated or spontaneous smile after surgery in
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most patients using the masseteric nerve as donor nerve 1,38,40.
An overlapped activation pattern between movements of smiling and jaw-clenching
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suggest that the two movements share the motor and somesthetic representation in the cerebral and cerebellar cortex. The larger activation while smiling compared to jawclenching may explain a more complex action, in spite of being discrete movements, and the need to perform constant and long-term training to achieve neuronal plasticity.
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The repetitive movement network and visual input recruited to produce timed small movements that are visually guided would be cancelled out when comparing the two different conditions because of the common visual clue frequency in both conditions.
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Furthermore, despite the fact that both tasks share motor, premotor, cerebellar and basal ganglia structures, PPI results showed different patterns of effective connectivity of
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facial MI during smile and jaw-clenching tasks. Since both hemispheres contribute to both kinds of processes, we found that the connectivity of the MI was lateralized to the prefrontal left hemisphere during smile and to the prefrontal right hemisphere during jaw-clenching. These findings, that need further consideration, are in line with the generally accepted idea that the hemispheres exhibits asymmetry in both structure and function6,27,28,40,41.
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ACCEPTED MANUSCRIPT Additionally, we found different patterns of effective connectivity related to gender. Males tended to have increased connectivity mainly between facial MI and basal ganglia, thalamic and mesencephalic structures. The periaqueductal gray circuits to facial and trigeminal motor nuclei bear striking similarities and regulate both sensory
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processes and control of motor output42,43. It is known that better outcomes using the masseter nerve are achieved after patients undergo long-term training 1, and in patients with a higher level of education. It has also been proposed that these results may be
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influenced by gender 39. Although further studies are clearly needed, these findings may have crucial importance in the treatment of facial paralysis, which might be supported
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by the different connectivity patterns shown between the two tasks (smile and jawclenching), and between males and females in the present study.
CONCLUSIONS
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In light of clinical results, a natural smile can be achieved when using the masseter nerve in facial palsy rehabilitation. The hypothesis of brain plasticity between the facial nerve area and masseter nerve area is supported by the broad cortical overlap in the
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representation of facial and masseter muscles. Further studies are needed to assess why
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some people tend to develop dissociation and spontaneous smile and why other patients do not when using the masseteric nerve as donor nerve in the management of facial paralisis.
CONFLICT OF INTEREST The authors declare that there is no conflict of interests regarding the publication of this paper.
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AKNOWLEDGMENTS This work was supported by Foundation for Applied Medical Research, University of Navarra (FIMA), and Foundation Mutua Madrileña (FMMA). FRL was supported by
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the Senescyt through the Prometheus Program of the Ecuadorian Government.
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ACCEPTED MANUSCRIPT FIGURE LEGENDS Figure 1. Explanation of two emoticons in the control condition. Figure 2. Image shows the significant activity overlapped on an inflated brain. Left
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panel: Smile > control in hot color; Jaw-Clenching > control in cold colors. Green shows the overlapping regions between both tasks. The right panel depicts common areas in the conjunction analysis between both tasks. P<0.001 FDR cluster-wise
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corrected.
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Figure 3. Shows the significant differences between Smile and Jaw-Clenching tasks. Hot colors represent significant areas greater in the contrast Smile > Jaw-Clenching and Cold colors for significant areas greater in the contrast Jaw Clenching > Smile. p<0.001 FDR cluster-wise corrected.
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Figure 4. Upper row depicts changes in connectivity from bilateral seeds (in blue) located on facial MI. Violet color represents t-test with increases in connectivity during jaw-clenching compared to resting task, and green for smile compared to rest. Second
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row depicts t-test of brain regions with gender differences in effective connectivity from seeds located on facial MI during smile and jaw-clenching tasks together p<0.001 FDR
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cluster-wise corrected in both analyses. Figure 5. Results from facial kinematics for speed contraction and commissural excursion while smiling among men and women. Figure 6. A 27 years old patient with a left complete facial paralysis after neurofibroma resection in the facial nerve one year ago. A. Preop of the patient when smiling after nerve transference with the masseteric nerve to the facial nerve. B. Postop of the patient when smiling. This woman can smile with the mouth opened and have a spontaneously
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smile.
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ACCEPTED MANUSCRIPT VIDEO LEGENDS Video 1. Preop. of patient of Fig. 5.
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Video 1. Postop. of patient of Fig. 5.
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Gotts SJ, Jo HJ, Wallace GL, Saad ZS, Cox RW, Martin A. Two distinct forms of functional lateralization in the human brain. Proc Natl Acad Sci U S A [Internet].
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2013 Sep 3 [cited 2014 Mar 20];110(36):E3435–44. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3767540&tool=pmce ntrez&rendertype=abstract
Fay RA, Norgren R. Identification of rat brainstem multisynaptic connections to
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the oral motor nuclei in the rat using pseudorabies virus. II. Facial muscle motor
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systems. Brain Res Brain Res Rev [Internet]. 1997 Dec [cited 2014 Jul Available
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Fay RA, Norgren R. Identification of rat brainstem multisynaptic connections to
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the oral motor nuclei using pseudorabies virus I. Masticatory muscle motor systems. Brain Research Reviews. 1997. p. 255–75.
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Michael S. A. Graziano, Cortical Action Representations Published In: Brain Mapping: An Encyclopedic Reference. Toga AW, Poldrack RA (Eds) Amsterdam: Elsevier, 2015
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TABLES Table 1. Main effect of task - Smile and Jaw-clenching
MNI Coordinates
Stats.
Cluster
X
t value
size
Y
Z
SC
Region
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Main effect of task - Smile and Jaw-clenching (Post-hoc comparisons)
Smile > Jaw-clenching -44
11
-9
4.67
1232
39
7
8
4.84
634
-56
-9
43
7.28
816
53
-9
42
5.52
811
Left Middle Temporal gyrus
-53
-52
7
4.35
411
Right Middle Temporal gyrus
57
50
11
4.42
835
Cerebellar vermis
-2
-60
-5
4.27
624
0
3
54
5.00
-9
5.11
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Left Insula lobe extended to IFG BA44 Right Insula lobe extended to IFG BA44 Left Postcentral gyrus
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Right Precentral gyrus
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Supplementary Motor Area
347
Jaw-clenching > Smile
Bilateral ACC extended to Orbital and -11
32
1541
Caudate nucleus Right Middle Frontal Gyrus
1200 42
48
6
4.63
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Table 2. Conjunction analysis between the two conditions Smile and Jaw-clenching.
Region
MNI Coordinates
Stats.
Cluster
X
t value
size
Y
Bilateral Cerebellum:
Bilateral Basal Ganglia:
-58
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Z
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Smile - Jaw-clenching
Lobule VI and VIII
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Overlapped regions - Smile and Jaw-clenching (Conjunction analysis)
-23
13.16
23442
-23
-4
9
7.59
-26
-4
-8
8.09
-54
-7
43
11.37
5060
Right Postcentral gyrus (facial MI)
57
-7
42
7.95
2892
Supplementary Motor Area
-2
-1
60
9.25
2858
Left Superior Temporal Gyrus
-48
-34
21
7.64
1759
Right Superior Temporal Gyrus
47
-33
21
4.67
338
Thalamus and Putamen Bilateral Amygdala
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Left Postcentral gyrus (facial MI)
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Effective connectivity PPI results Changes in connectivity from seed located on facial MI MNI Coordinates
Stats.
Cluster
X
t value
size
Y
Z
RI PT
Region
Increases in connectivity during Jaw-clenching compared to Smile Right Inferior Frontal (p. Triangularis)
41
30
35
38
4.93
18
4.46
655
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Right Middle Frontal
13
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Increases in connectivity during Smile compared to Jaw-clenching Left Inferior Frontal (p. Orbitalis)
-51
32
-6
4.48 389
Left Inferior Frontal (p. Triangularis)
26
6
3.99
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-56
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Gender differences in effective connectivity during Smile and Jaw-Clenching tasks
Bilateral periacueductal grey
6
-24
-11 6.14
-22
-12
Left Thalamus prefrontal
-12
-7
12
5.41
Left Thalamus parietal
-21
-10
19
4.73
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-3
752
643 Left Thalamus Temporal
-11
-24
12
4.66
Left Thalamus premotor
-17
-13
4
3.47
Right Thalamus prefrontal
20
-10
16
5.58
489
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