2.1 Participants
In sum, 33 healthy young adults (20 women and 13 men) aged between 18 and 35 years (M = 25.03, SD = 4.40) volunteered to participate in the study. They had no history of psychiatric, neurological, respiratory, or swallowing disorders and were all suitable for NIRS measurements (no wounds on the scalp, no hyper sensibility of the skin, etc.). Participants were included in the study regardless of their self-reported handedness (29 right-handed and 4 left-handed). Recruitment of participants was conducted via social media, email distribution and personal contacts. Except of one subject, all participants had graduated from high school (Matura) or had achieved an even higher level of education.
Due to COVID-19, the study took place under strict safety regulations. To reduce times of personal contact, part of the study was conducted via online survey. In Addition, participants received documents for written informed consent, information about the
procedure and the safety guidelines, including a symptom checklist for COVID-19 symptoms prior to the laboratory measurements via email. The measurements took place in a laboratory room at the University of Graz in consideration of hygienic guidelines (e.g., usage of hand sanitizer, wearing an FFP-2 mask all the time, usage of gloves and additional facial shield during positioning of the NIRS equipment, cleaning of the laboratory and used equipment after each participant).
All participants gave written informed consent and were free of COVID-19 symptoms for at least seven days prior to the measurement. Psychology students received course credits for their participation in the study. The study procedures were approved by the ethics
commission of the University of Graz and data privacy was ensured in line with the European General Data Protection Regulation (DSGVO).
2.2 Material
2.2.1 Edinburgh Handedness Inventory – Short Form
The Edinburgh-Handedness-Inventory – Short Form (EHI short form; Veale, 2014) is a well-established tool to assess handedness, which asks on a five-point scale for the
preferably used hand for four different activities and objects (writing, throwing, toothbrush,
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spoon). A laterality quotient is calculated from the mean of the responses, ranging from -100 (fully left-handed) to 100 (fully right-handed). Scores between -60 and 60 are considered as mixed handed.
2.2.2 Short Questionnaire to Assess Body Awareness (KEKS)
The short questionnaire to assess body awareness (original: Kurzer Fragebogen zur Eigenwahrnehmung des Körpers, KEKS; Pöhlmann, Berger, von Jarnim & Joraschky, 2009) was used to assess body awareness of the participants. The KEKS is based on the dimensions of body awareness used in functional relaxation (original: funktionelle Entspannung, FE;
(Fuchs, 1997). The authors report construct validity assessed via factor analysis and good reliability of the KEKS (Cronbach’s ⍺ = .71 - .93). Further, medium convergent validity is assumed as it correlates (r = .42) with another questionnaire measuring self-attention (SAM;
Filipp & Freudenberg, 1989). Regarding discriminant validity, the KEKS showed to
differentiate between Hatha Yoga practitioners (which are assumed to have high awareness of their body) and non-yoga practitioners. The questionnaire consists of three scales (parts of skeleton, body cavities and skin) and two control items. Examples for included body parts are tongue (body cavities), shoulder blades (skeleton), eyelids (skin), or cerebellum (control).
Participants rate on a scale from “1” (no awareness) to “5” (detailed awareness) how distinct they can feel 20 different parts of their body at that moment. In this study the mean score for body awareness was used but scores for the scales can be calculated as well. As the KEKS aims to measure body awareness at the time of implementation, it was used before the ME/MI task and afterwards (see section 2.4).
2.2.3 Vividness of Movement Imagery Questionaire 2
The Vividness of movement imagery questionnaire-2 (VMIQ-2; Roberts, Callow, Hardy, Markland, & Bringer, 2008) in its German version (Dahm, Bart, Pithan, & Rieger, 2020) was used to assess motor imagery ability. The VMIQ-2 is a commonly used
questionnaire measuring vividness of MI for the three imagery modalities (external visual imagery, internal visual imagery, and kinesthetic imagery), which were all included in this study. The authors report high internal consistency (Cronbachs ⍺ = .90 - .91) and a test-retest reliability between rtt = .64 and rtt = .69. The factorial validity is comparable to the English version of the questionnaire, as are the intercorrelation between the separate scales (r = .44 -
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.59) with exception for internal and external visual imagery, which scored higher than the original. The VMIQ-2 consists of 36 items, participants are asked to imagine twelve different movements for each of the three imagery strategies and rate their imagination on a scale from
“1” (perfectly clear and vivid) to “5” (no image at all, you only know that you are “thinking”
of the skill). A score below three means that the movement could not be imagined
successfully. A mean score, calculated for each scale separately, was used for further analysis.
2.2.4 Visual Analog Scale
Visual analog scales (VAS) were used to assess subjective ratings of the success of motor execution and imagination, as well as motivation, swallowing difficulties or sensed pain (see Appendix A.4). VAS are assumed to be reliable and valid (Reips & Funke, 2008).
Each item consists out of a horizontal line (10 cm) whose ends represent two extremes of a continuum. Participants are asked to mark the point on the line, which represents their position. The answers are measured in millimeters, whereas 1 indicates full agreement with the left-sided and 100 with the right-sided extreme of the item.
2.2.5 Motor Imagery Strategies
Additionally, participants were asked to describe the strategies they used during MI of swallowing and if those strategies where successful for the imagination (Appendix A.5).
2.3 Motor Execution and Imagery Task
A similar ME/MI task as in Kober & Wood (2014) was used in the present study, with saliva instead of water swallowing. During the task, participants had to swallow their own saliva (ME) and imagine how it feels to swallow it (MI). The task consisted out of 20 ME and 20 MI trials presented in a randomized order, with each one lasting for 15 seconds. A
computer script using PsychoPy3 (Peirce et al., 2019) was programmed to indicate
participants on a computer screen whether they should execute or imagine swallowing and to set triggers in the signal, referring to each task on- and offset. As shown in Figure 1, the letter
“A” indicated ME and the letter “V” indicated MI. Participants were asked to swallow between five and six times during each ME trial in a comfortable pace. During MI
participants were instructed to imagine swallowing in the same pace as during ME and to use a kinesthetic approach. In between the tasks a fixation cross was presented on the screen for a
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variable length of 28 to 32 seconds and participants were asked to avoid active swallowing as much as possible. Before the actual task all participants were briefly trained.
Figure 1. Schematic representation of the ME/MI task. ME (A) and MI (V) trials were presented in a randomized order.
2.4 NIRS Recordings
A NIRSport 2 system (NIRx Medizintechnik, GmbH, Berlin, Germany) was used to record the hemodynamic respond of participants during the ME/MI task. It is a continuous wave system with LED sources, emmiting light at wavelengths of 760 and 850 nm, and detectors measuring oxy- (HbO), deoxy- (HbR) and total hemoglobin changes in the cortex.
The probe-setup consisted of eight source- and eight detector-optodes which were mounted on EEG-caps with holders ensuring a distance of 30 mm between each source-detector pair (long-distance channels). Caps were available in different sizes (54, 56 and 58 cm), to guarantee a proper fitting for each participant. Additionally, to long-distance probes, eight short-distance detector probes were placed about 8 mm apart from the sources (short-distance channels). Therefore, one long-distance detector had to be sacrificed to serve as an optode for them. The sampling rate was set to 10.2 Hz. Two standard software packages provided by NIRx were used for channel configuration (NIRSSite 2.0) and recording (Aurora fNIRS 1.4).
The probe-setup depicted in Figure 2 was positioned above the IFG bilaterally,
according to previous NIRS studies investigating ME/MI of swallowing (Kober, Bauernfeind, et al., 2015; Kober & Wood, 2014) and further included dorsolateral prefrontal cortex,
premotor and supplementary motor cortex, frontal eye fields, middle and superior temporal gyrus, subcentral area, primary somatosensory cortex, supramarginal and angular gyrus (Wernicke) and the somatosensory association cortex (see also Table 1).
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AtlasViewer (Aasted et al., 2015), a free software package based on MATLAB (MathWorks, Natick, MA, USA), was used to generate visualizations of the probe-setup located above the cortex and the recorded NIRS data.
Figure 2. NIRS probe-setup over the left (LH) and right (RH) hemisphere and placement according to 10-20 system, displayed with Aurora (right) and AtlasViewer (left). Red points indicate source probes, blue points indicate long- and short-distance detector probes. Yellow lines show corrsponding source-detector pairs.
2.5 Procedure
First, participants completed an online survey, generated with LimeSurvey
(LimeSurvey GmbH, Hamburg, Germany), comprised out of the EHI, the KEKS (pre-test) and the VMIQ-2. Participants received a personalized invitation link to the survey via email to prevent repeated completions of the questionnaires. The completion of the survey took about 20 minutes. Afterwards participants booked a timeslot for the laboratory session in an online calendar (Doodle AG, Zurich, Switzerland) and received further information and safety instructions (as described in section 2.2) via email.
Before entering the laboratory, participants gave written informed consent and handed over the COVID-19 symptom-checklists. In the laboratory participants were seated in a cabin
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in front of a computer screen, which allowed to darken the surrounding completely during NIRS measurements. The session started with participants filling out social-demographic data and a brief introduction to the NIRS system. Afterwards, a suitable cap containing the probes was mounted on participants’ heads and instructions for the ME/MI task were given including a short training session with one ME and one MI trial. During this training, participants were observed to ensure that they had understood the instructions and were following them. Then the lights in the cabin were switched off and the ME/MI paradigm as well as NIRS
measurements were started from a laboratory PC located outside the cabin. After completion of the task, participants were freed from the cap and filled out questionnaires regarding used strategies, VAS and the KEKS (post-test). The whole procedure in the laboratory took between 50 and 60 minutes.
2.6 Data Preprocessing
For NIRS data preprocessing the MATLAB (MathWorks, Natick, MA, USA) based program Homer2 (Huppert, Diamond, Franceschini, & Boas, 2009) was used. Four different processing pathways were used to compare artifact correction methods. An overview of the exact processing steps for each method is shown in Figure 3.
Raw optical density data was converted into changes in optical density (OD) for all techniques using the Homer2 function hmrIntensity2OD. Next, the enPruneChannels function was applied, to discard channels with extremely low OD. Then, data was either filtered with a wavelet transformation (Wav and Wav + SD) using the function hmrMotionCorrectWavelet (iqr = 0.1), or visually checked and manually corrected for motion artifacts (manual and manual + SD).
For four participants wavelet filtering was additionally performed with different settings for iqr (0.8 and 1.5), to exemplary investigate its impact on NIRS data during ME of swallowing (see Appendix B.3). Subsequently, the same settings as for Wav+SD were used.
The functions hmrMotionArtifact (STDEVthresh = 15.0; AMPthresh = 0.30) and enStimRejection (tRange = -10.0 – 10.0 seconds) were operated on processing options Wav and Wav + SD, to automatically detect and exclude trials, still containing motion artifacts after correction. A high-pass (0.01 Hz) and a low-pass filter (0.50 Hz) were then applied in all processing pathways via the function hmrBandpassFilt, to filter out physiological noise. Next, and again for all pathways, hmrOD2Conc (ppf = 6.0/6.0) was executed to convert the signal into HbO and HbR concentration changes. For pathways that should include SD-channel
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regression, the hmrDeconvHRF_DriftSS function (trange = -5.0 – 40.0; glmSolveMethod = 1;
idxBasis = 2; paramsBasis = 0.1/3.0/10.0/1.8/3.0/10.0; rhoSD_ssThresh = 15.0; flagSSmethod
= 0; driftOrder = 3; flagMotionCorrect = 0) was used to regress out general hemodynamic drift from the signal. In all pathways, HbO and HbR concentration changes during the tasks were referred to a baseline interval, 5 seconds prior to the stimulus onset (seconds -5 to 0).
Block averages where then calculated via hmrBlockAvg for seconds -5 to 40 around stimulus onset. After visual inspection of the resulting signal, two participants had to be excluded, due to poor data quality resulting in exclusion of almost all trials. The data for the remaining 31 participants were then exported and averaged for a time interval of seconds 5 to 15 (Task period) and seconds 15 to 25 (Pause period) after task onset, for ME and MI separately.
Averages were automatically calculated using Homer’s Export Mean Results function.
Table 1. List of channels (source [Src] - detector [Det] pairs; see also Figure 2) of right (RH) and left (LH) hemispheres and corresponding projections onto the brain surface. First number represents sources, second number detectors.
1-2 - 6 Pre-motor and supplementary motor cortex
1-3 5-6 9 Dorsolateral prefrontal cortex 2-1 6-5 46 Dorsolateral prefrontal cortex
2-3 6-6 9, 45 Dorsolateral prefrontal cortex, Pars triangularis (part of IFG and Broca's area)
2-4 6-7 45, 46 Pars triangularis (part of IFG and Broca's area), Dorsolateral prefrontal cortex
3-2 - 6 Pre-motor and supplementary motor cortex
3-3 7-6 6 Pre-motor and supplementary motor cortex 4-3 8-6 44 Pars opercularis (part of IFG an Broca's area) 4-4 8-7 45 Pars triangularis, Pars orbitalis (both part of IFG)
Note: Broadman areas and descriptions were adapted from Kober et al.(2015), as the same probe setup was used in the present study.
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Figure 3. Signal processing steps for wavelet filtering (orange) and manual rejection (green).
2.7 Statistical Analyses
To estimate the topographical distribution of significantly activated brain areas, t-tests were performed between the activation interval (seconds 5 to 25) and the baseline (seconds -5 to 0) for each channel, each condition (ME and MI) and HbO/HbR separately. Significant concentration changes were identified using the FDR-method (Singh & Dan, 2006). For further calculations, the same ROI’s as in Kober et al. (2015) were used to ensure comparability of the results with previous studies. ROI’s were defined for channels corresponding with left detector pairs: 2-4, 4-3, and 4-4) and right IFG (source-detector pairs: 6-7, 8-6, 8-7; see Table 1 and Figure 2).
In accordance with Kober and Wood (2014) and to analyze changes in HbO and HbR during ME and MI, two separate 2x2x2 ANOVA’s for repeated measures were conducted with the within-subjects factors Task (ME vs. MI), Time (Task vs. Pause) and Hemi (left vs.
right) were conducted. The dependent variables for each ANOVA were HbO- and HbR-Concentration Change, respectively. For this analysis only data processed with wavelet filtering and SD-channels was used, to validate if earlier findings were due to motion artifacts.
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To compare motion artifact correction methods, two 2x2 ANOVA’s for repeated measures with the within-subject factors Correction Method (Wavelet transformation vs.
Manual rejection) and SD-Channel-Regression (yes vs. no) were conducted. As motion artifacts should occur especially during active swallowing, and therefore the greatest difference between correction methods is expected, HbO- and HbR-Concentration Change during METask (seconds 5 to 15) were used as dependent variables. In regard of the different scaling of the HRF for the diverse correction methods, HbO and HbR values were
standardized via z-transformation over all four methods within the subjects.
To investigate correlates of brain activation patterns elicited by MI of swallowing, bivariate correlations (Pearson) were calculated between HbO- and HbR-Concentration Changes during MI (pause period: 15-25s; correction method: Wav+SD) and the results from several questionnaires: Kinesthetic Imagery Ability (KMI subscale from VMIQ-2), Body Awareness (KEKSPre and KEKSPost), Motivation (motivation during MI; VAS subscale) and Quality (subjectively rated quality of imagined swallows; VAS subscale). The pause period after MI was chosen over the task period, as a prolonged time course for MI of swallowing has been indicated by previous studies (Kober & Wood, 2014; see section 1.2.1). As this hypothesis was of explorative nature, no correction for multiple comparisons was carried out.
All statistical calculations were performed using IBM SPSS Statistics 26 (IBM Corp., Armonk, NY, USA). All dependent variables were checked for extreme outliers through visual inspections of the boxplots, by checking for normal distribution of the Shapiro-Wilk-Test and by visual inspection of Q-Q plots. One participant was detected as an extreme outlier in almost all HbO- and HbR-concentration changes. As the participant had further consumed coffee and cigarettes less than an hour before the NIRS-measurements and his data could therefore been distorted, he was excluded from further analysis. Therefore, only 30
participants were included in all further analyses (see also exclusions after data processing, section 2.5). The level of significance was set to ⍺ = .05 (two-tailed).
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