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\begin{document}

\title{Neurophysiological oscillatory mechanisms underlying the effect of
mirror visual feedback-induced illusion of hand movements on nociception
and cortical activation}



\author[1]{Marco Rizzo}%
\author[1]{Laura Petrini}%
\author[2]{Claudio Del Percio}%
\author[1]{Lars Arendt-Nielsen}%
\author[3]{Claudio Babiloni}%
\affil[1]{Aalborg University}%
\affil[2]{Universita La Sapienza}%
\affil[3]{University of Foggia}%


\vspace{-1em}



  
  \date{May 07, 2024}


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\selectlanguage{english}
\begin{abstract}
Mirror Visual Feedback (MVF)-induced illusion of hand movements produces
beneficial effects in patients with chronic pain. However,
neurophysiological mechanisms underlying these effects are poorly known.
Here we hypothesized that such an MVF-induced movement illusion may
exert its effects by changing the activity in midline cortical areas of
the pain neural matrix. Electrical stimuli with individually fixed
intensity were applied to the left hand in healthy adults to produce
painful and non-painful sensations during unilateral right-hand
movements with such an MVF illusion and right and bilateral hand
movements without MVF. During these events, electroencephalographic
(EEG) activity was recorded from 64 scalp electrodes. Event-related
desynchronization (ERD) of EEG alpha rhythms (8-12 Hz) indexed the
neurophysiological oscillatory mechanisms inducing cortical activation.
As compared to the painful sensations, the non-painful sensations were
specifically characterized by (1) lower alpha ERD estimated in the
cortical midline, angular gyrus, and lateral parietal regions during the
experimental condition with MVF and (2) higher alpha ERD estimated in
the lateral prefrontal and parietal regions during the control
conditions without MVF. These core results suggest that the MVF-induced
movement illusion may affect nociception and neurophysiological
oscillatory mechanisms reducing the activation in cortical limbic and
default mode regions.%
\end{abstract}%



\sloppy


Neurophysiological oscillatory mechanisms underlying the effect of
mirror visual feedback-induced illusion of hand movements on nociception
and cortical activation

\textsuperscript{1}Rizzo M., \textsuperscript{1}*Petrini
L.,\textsuperscript{2}Del Percio C., \textsuperscript{1,3}Arendt-Nielsen
L., and \textsuperscript{2,4}Babiloni C.

1 Center for Neuroplasticity and Pain (CNAP), SMI\selectlanguage{ngerman}®, Department of Health
Science and Technology, Aalborg

University, Aalborg, Denmark

2 Department of Physiology and Pharmacology ''V. Erspamer'', Sapienza
University of Rome, Rome, Italy

3 Department of Medical Gastroenterology, Mech-Sense, Aalborg University
Hospital, Aalborg, Denmark

4 Hospital San Raffaele Cassino, Cassino (FR), Italy

\textbf{*Corresponding author:} Associate Prof. Laura Petrini

Center for Neuroplasticity and Pain (CNAP)

Department of Health Science and Technology,

The Faculty of Medicine

Aalborg University, Fredrik Bajers Vej 7A/2-201

9220 Aalborg Ø, Denmark

Phone: +45 99 40 98 26

Email: lap@hst.aau.dk

\textbf{Running title:} Neural oscillations during MVF and nociception

\textbf{Keywords:} High-density electroencephalography (HD-EEG), alpha
event-related de/synchronization (ERD/ERS), source analysis, Mirror
Visual Feedback (MVF), sensory-motor interaction

\textbf{Acknowledgements:} The Authors thank Dr. Susanna Lopez for her
assistance. This project has received funding from the European Union's
Horizon 2020 research and innovation programme under the Marie
Sk\selectlanguage{polish}ł\selectlanguage{english}odowska-Curie grant agreement No 754465. The Center for
Neuroplasticity and Pain (CNAP) is supported by the Danish National
Research Foundation (DNRF121).

Abstract

Mirror Visual Feedback (MVF)-induced illusion of hand movements produces
beneficial effects in patients with chronic pain. However,
neurophysiological mechanisms underlying these effects are poorly known.
Here we hypothesized that such an MVF-induced movement illusion may
exert its effects by changing the activity in midline cortical areas of
the pain neural matrix. Electrical stimuli with individually fixed
intensity were applied to the left hand in healthy adults to produce
painful and non-painful sensations during unilateral right-hand
movements with such an MVF illusion and right and bilateral hand
movements without MVF. During these events, electroencephalographic
(EEG) activity was recorded from 64 scalp electrodes. Event-related
desynchronization (ERD) of EEG alpha rhythms (8-12 Hz) indexed the
neurophysiological oscillatory mechanisms inducing cortical activation.
As compared to the painful sensations, the non-painful sensations were
specifically characterized by (1) lower alpha ERD estimated in the
cortical midline, angular gyrus, and lateral parietal regions during the
experimental condition with MVF and (2) higher alpha ERD estimated in
the lateral prefrontal and parietal regions during the control
conditions without MVF. These core results suggest that the MVF-induced
movement illusion may affect nociception and neurophysiological
oscillatory mechanisms reducing the activation in cortical limbic and
default mode regions.

\textbf{1 \emph{INTRODUCTION}}

The illusory phenomenon whereby the mirrored movement of one limb is
perceived as the simultaneous movement of the opposite limb is known as
Mirror Visual Feedback (MVF) (Ortiz-Catalan et al., 2016; Rjosk et al.,
2016). MVF technique entails placing a mirror perpendicularly to the
observer's body midline. While watching the limb reflected in the
mirror, the observer experiences the misperception of looking at his/her
true limb (Ding et al., 2019; Ramachandran \& Rodgers-Ramachandran,
1996; Ramachandran, Rogers-Ramachandran, \& Cobb, 1995). Several
investigations in cohorts of patients with chronic pain or motor
deficits demonstrated neuroplasticity processes associated with MVF
sensory-motor experience (Arya, 2016; Deconinck et al., 2015).
Therefore, MVF-based neurorehabilitation strategies were developed to
treat chronic pain conditions, such as phantom limb pain (PLP) syndrome
(Finn et al., 2017; Ramachandran et al., 1995; Th\selectlanguage{ngerman}øgersen et al., 2020),
post-stroke hemiparesis (Bae, Jeong, \& Kim, 2012; Bartur, Pratt,
Frenkel-Toledo, \& Soroker, 2018; Dohle et al., 2009), and complex
regional pain syndrome (McCabe et al., 2003; Tichelaar, Geertzen,
Keizer, \& Paul Van Wilgen, 2007). These strategies were also successful
to facilitate upper-extremities motor recovery (Bullock, Won, Bailenson,
\& Friedman, 2020; Zhang \& Fong, 2019).

Neuroimaging studies in healthy individuals used functional magnetic
resonance imaging (fMRI) (Merians, Tunik, Fluet, Qiu, \& Adamovich,
2009; Numata, Murayama, Takasugi, Monma, \& Oga, 2013; Shinoura et al.,
2008), near infrared spectrometry (Imai, Takeda, Shiomi, Taniguchi, \&
Kato, 2008; Inagaki et al., 2019), and transcranial magnetic stimulation
(TMS) (Aziz-Zadeh, Maeda, Zaidel, Mazziotta, \& Iacoboni, 2002;
Fukumura, Sugawara, Tanabe, Ushiba, \& Tomita, 2007; Garry, Loftus, \&
Summers, 2005) to investigate the brain neural basis of the effects by
the MVF procedure. Results showed an MVF-related increase in cortical
excitability or activation in premotor, primary motor (M1), and primary
somatosensory (S1) cortical areas ipsilateral to the moving hand. Other
fMRI and TMS studies extended the focus of the investigation to the
whole brain, showing the involvement of the visual and parietal
posterior cortical areas -- strongly connected with the central
sensory-motor regions -- as responsible for visuomotor transformation
processes occurring during MVF-induced illusory experience (Bartur et
al., 2018; Fritzsch et al., 2014; Fukumura et al., 2007; Garry et al.,
2005; Hamzei et al., 2012; Matthys et al., 2009; Numata et al., 2013).
In this regard, an fMRI study investigated the effects of MVF training
in low amputees. After 12 sessions of MVF therapy, patients showed a
significant reduction of PLP and increased activity in the bilateral
orbitofrontal cortex in response to phantom ankle ``imaginary'' movement
(Seidel et al., 2011). Interestingly, the phantom ankle movements alone
induced activation in the premotor and parietal associative cortical
areas rather than the primary sensory-motor cortex (Seidel et al.,
2011).

The above neuroimaging results had the advantage of a high spatial
resolution but were limited in describing the temporal evolution of the
MVF-related cortical activation. For this purpose,
electroencephalography (EEG) can probe the cortical activity related to
motor and sensory events with less spatial resolution but enhanced
temporal resolution (milliseconds) (Kim \& Lee, 2015; Light et al.,
2011). Previous EEG investigations measured lateralized related
potentials (as an index of M1 activity) during unilateral hand movement
tasks performed with MVF illusion. Those potentials showed clear
activation of the M1 contralateral to the hand reflected in the mirror
and perceived as moving (indeed immobile) (Debnath \& Franz, 2016;
Touzalin-Chretien \& Dufour, 2008; Touzalin-Chretien, Ehrler, \& Dufour,
2010).

Other EEG studies used the so-called event-related desynchronization
(ERD) of the cortical EEG alpha (8-12 Hz) rhythms to investigate the
neurophysiological oscillatory mechanisms regulating the excitability of
the cerebral cortex during sensory and motor events in humans (Neuper,
Wörtz, \& Pfurtscheller, 2006; Pfurtscheller \& Aranibar, 1979;
Pfurtscheller \& Lopes Da Silva, 1999). Specifically, ample
resting-state EEG alpha rhythms reflect the cortical inhibition in the
central and posterior sensory-motor areas during a wakefulness state of
psychophysical relaxation (Pfurtscheller \& Lopes Da Silva, 1999;
Pfurtscheller \& Neuper, 1994; Babiloni et al., 2020). These alpha
rhythms reduce in amplitude (alpha ERD) as a sign of cortical activation
during the preparation and execution of voluntary movements (Babiloni et
al., 1999, 2014; Neuper et al., 2006; Pfurtscheller \& Lopes Da Silva,
1999). Furthermore, central alpha ERD was associated with nociception
and sensorimotor interactions (gating) between voluntary hand movements
and painful stimuli (Babiloni et al., 2003; 2008, 2010, 2014; Del Percio
et al., 2006), while other EEG studies showed consistent alpha ERD
overlying frontal and parietal areas during the MVF-induced movement
illusion (Bartur et al., 2015; Lee, Li, \& Fan, 2015; Rizzo et al.,
2022). Altered activity in the frontal and parietal cortical areas was
also linked to dysesthesia (i.e., abnormal limb perceptions and emotions
associated with pathological pain like PLP) due to MVF-induced
sensorimotor incongruence provoked by a mismatch between motor intention
and sensory feedback (Foell, Bekrater-Bodmann, Mccabe, \& Flor, 2013;
Katayama, Osumi, Kodama, \& Morioka, 2016; McCabe, Haigh, Halligan, \&
Blake, 2005). For example, EEG investigations in healthy subjects
reported stronger alpha and beta ERD in the bilateral frontal premotor
and anterior-posterior cingulate areas when they experienced dysesthesia
(Katayama et al., 2019, 2016) and discomfort sensations (Nishigami et
al., 2014) induced by the sensorimotor incongruence. Notably,
dysesthesia is an interesting experimental model as it is characterized
by a discomfort like that reported in people with pathological chronic
pain (Daenen et al., 2012; Mccabe, Cohen, \& Blake, 2007).

Keeping in mind the above findings, we believe that a methodological
approach based on high-resolution EEG and estimation of alpha ERD
cortical sources may shed light on the effects of MVF-induced movement
illusion on nociception and the activation in the cortical midline
(limbic) regions belonging to the so-called pain neural matrix. These
cortical midline (limbic) regions including medial prefrontal, anterior
and posterior cingulate, and precuneus cortices may underpin human pain
experience in relation to the affective sense-of-self, body
representation, and interoceptive signals (Araujo, Kaplan, \& Damasio,
2013; Babiloni et al., 2003; Cavanna \& Trimble, 2006; Goffaux,
Girard-Tremblay, Marchand, Daigle, \& Whittingstall, 2014; Northoff \&
Bermpohl, 2004; Northoff et al., 2006). In this line, here we tested the
hypothesis that in healthy adults, the MVF-related illusion of hand
movements may affect the nociception and the activation in the midline
cortical areas, as revealed by the alpha ERD. To test this hypothesis,
electrical stimuli were applied to the left hand to produce painful or
non-painful sensations during unilateral right-hand movements with MVF.
As control conditions, the same electrical stimuli were applied during
unilateral right-hand and bilateral hand movements without MVF. The
alpha ERD was estimated within mathematical sources modelled in the
cortical midline and control regions.

\textbf{2 \emph{MATERIALS AND METHODS}}

\textbf{2.1 Subjects}

Thirteen healthy adult volunteers were recruited for the study (mean age
= 26.2, SD = ±4.7). The main exclusion criteria included the presence of
chronic pain, nerve pain, neurological diseases, current medical
treatments, and participation in other studies involving pain
stimulation in the past four weeks. The Edinburgh Handedness Inventory
(EHI, Oldfield, 1971) confirmed that all the subjects were right-handed.
Remarkably, ten subjects participated in our previous MVF study (Rizzo
et al., 2022). All experiments were conducted at the Aalborg University
(Denmark). The study was approved by the Scientific Ethical Committee of
Region Nordjylland (N-20190008) and all participants signed the informed
consent according to the Declaration of Helsinki.

\textbf{2.2 Experimental procedure}

The participants were comfortably seated on a chair with their arms
lying symmetrically ahead on a table. Auditory cues of 70 dB, 1000 Hz,
and 50 ms of duration (Kida et al., 2006) were used to trigger right
index finger movements. Three different conditions (80 trials each) were
randomized across the participants. In the experimental condition
(Unilateral with Mirror, or UM+) the mirror was placed on the desk,
perpendicularly to the subjects' midsagittal plane with the reflecting
face on the right side (Figure 1). Subjects were instructed to move the
right index finger in response to the auditory cue while watching the
image of the reflected moving hand in the mirror to give the illusion of
the simultaneous left index finger movement. The position of the left
hand behind the mirror corresponded to the image of the left hand
reflected in the mirror. In the control conditions, the mirror was
removed from the experimental setting and the left hand was directly
visible to the participants. In one control condition (Unilateral
without Mirror, UM-), subjects were asked to perform the same unilateral
right index finger movements. In the other control condition (Bilateral
without Mirror, BM-), subjects had to perform synchronous movements of
both index fingers. The movements consisted of a double extension of the
index finger with a slow release toward the bottom (approx. 1 s). All
the participants received a brief training to perform the movement
correctly and keep the left hand as still as possible during the
unilateral conditions. In each condition, an electrical stimulus was
delivered on the tip of the left index finger 100 ms after the auditory
cue to induce cortical sensory-motor interaction (Figure 2). The
interval between the stimuli was fixed at 10 s, a sufficient period to
reset the desynchronization of the alpha rhythms (Babiloni et al.,
2008). A fixed interval also allowed to produce a sort of predictability
of the upcoming auditory and electrical stimuli, optimal to study the
anticipatory alpha ERD/ERS responses. However, subjects were not
informed of this fixed interval to avoid any counting strategies.

\textbf{2.3 Electrical stimulations and pain threshold detection}

Electrical stimulations were provided by a voltage-controlled current
stimulator (NoxiSTIM; JNI Biomedical; Aalborg, Denmark). Stimuli were
delivered on the tip of the left finger using an electrode with a gold
pin cathode and a ring anode (Figure 1). An inactive electrode (sham)
was placed on the right index finger to achieve a congruent mirror
visual feedback (Figure 1). A multi-channel data acquisition module
(NI-6221, National Instruments Corp., Austin, TX, USA) was used to
synchronize the electrical stimuli to the auditory cues.

Subjects were asked to evaluate the intensity of electrical stimuli
using a Numerical Scale Rating (NRS) from 0 to 10, where 0 represents
the absence of any sensory perception, whereas 10 is the ``worst
imaginable pain''. Before the pain threshold measurement, 15 stimuli at
random intensities were delivered in a familiarization phase. The method
of limits was used to determine the pain threshold for each subject.
Starting from 0.5 milliamperes (mA), the current intensity was
progressively increased until a rating of 5 out of 10, namely the
minimum current intensity producing a painful sensation (Hu, Cai, Xiao,
Luo, \& Iannetti, 2014). The fixed individual pain threshold was used
during the three conditions (mean mA = 5.5; SD = ± 3.1). During the
experiment, subjects were asked to provide a numerical value (decimals
included) of the average pain intensity of the last 5 trials. Since each
condition consisted of 80 trials, 16 values per condition were
considered in the analysis. Due to the fluctuant subjective perception
of fixed stimuli, painful (NRS \textgreater{} 5) and non-painful (NRS
\textless{} 5) responses were obtained for each condition. If one
condition did not show that fluctuation in the perceived pain intensity,
the single dataset was removed from the analysis. Therefore, the final
samples considered in the statistical analysis were: UM+ = 8 subjects,
UM- = 13 subjects, and BM- = 12 subjects. Of interest, the painful
epochs (NRS \textgreater{} 5) were 36.5\% in the UM- condition, 58.5\%
in the BM- condition, and 53.9\% in the UM+ condition.

\textbf{2.3 EEG recording and analysis}

The EEG activity was recorded from scalp electrodes by an active
64-channels system (g.HIamp amplifier, g.tec medical engineering GmbH,
Austria) according to the 10-10 international system. Ground and
reference electrodes were placed on the forehead and ear lobes,
respectively. The electrode impedance was kept under 5 k\selectlanguage{english} and the
sampling rate was 1200 Hz. Eye movements and blinking activity was
controlled by Fp1 and Fp2 channels (Zeng et al., 2013). The offline data
analysis was performed using the EEGLAB 2021.1 (Delorme \& Makeig, 2004)
freeware toolbox for MatLab R2018b (MathWorks, Inc., Natick, MA, USA).
After visual inspection, data were filtered with a zero-phase basic FIR
filter (0.3-40 Hz), resampled to 256 Hz, re-referenced, and epoched in
80-time windows of 9 s each. Artefacts, such as blinking, muscular
movements, 50 Hz noise, etc., were recognized and removed using the
Infomax independent component analysis (ICA) algorithm (Bell \&
Sejnowski, 1995). On percentage, 7.9\% of artefact epochs and 7.3\% of
artefact components were removed from the EEG datasets. Finally, to
quantify the alpha ERD/ERS from the artefact-free EEG epochs, the global
EEG spectrum was computed using an FFT-based method. The outcomes were
used to select the individual alpha frequency peak (IAFp) from the EEG
power spectra. IAFp was defined as the frequency showing the highest
peak within the alpha band (8-12 Hz) (Klimesch, 1999). Thus, the EEG
data were individually filtered at the alpha frequency band depending on
the IAFp, namely from IAFp-2 Hz to IAFp+2 Hz (mean IAFp = 10.1; SD = +-
1.0).

\textbf{2.4 Cortical sources estimation}

The freeware tool ``exact Low-Resolution Brain Electromagnetic
Tomography'' (eLORETA) (Pascual-Marqui, 2007) used artifact-free EEG
data as input for the cortical source estimation. The eLORETA freeware
is a functional imaging technique belonging to a family of standardized
linear inverse solution procedures modelling the 3D distributions of the
EEG sources within a head volume conductor model comparted in the scalp,
skull, and brain (Pascual-Marqui, Esslen, Kochi, \& Lehmann, 2002;
Pascual-Marqui et al., 1999). eLORETA solves the EEG inverse problem by
estimating the current density values at the voxel level and provides a
brain source space restricted to the cortical grey matter of 6,239
voxels (5 mm resolution, with each voxel containing an equivalent
current dipole), as based on the Montreal Neurological Institute
template (MNI152). For each voxel, eLORETA provides information about
the MNI coordinates, the lobe, and the Brodmann area (BA). The input for
the source estimation was the spectral power density computed by 62
scalp electrodes as eLORETA source analysis is a free-reference method
(W. Peng, Hu, Mao, \& Babiloni, 2015), (i.e., the two reference
electrodes were not considered in the analysis). Due to the low spatial
resolution characteristic of the EEG techniques, adjacent Brodmann areas
were clusterized. The clusters included BAs 1-2-3 together with BA 4
(sensory-motor area), BA 24 together with BA 32 (anterior cingulate
cortex), BA 44 with BA 45 (inferior frontal gyrus), and BA 9 with BA 46
(superior frontal gyrus or dorsolateral prefrontal cortex).

\textbf{2.5 Alpha ERD/ERS calculation}

Standard quantification of the alpha ERD/ERS was performed for the
anticipation and execution stages of the movements (Babiloni et al.,
2010; Pfurtscheller \& Aranibar, 1979; Pfurtscheller \& Lopes Da Silva,
1999; Pfurtscheller \& Neuper, 1994; Pfurtscheller et al., 1997). The
alpha ERD/ERS was calculated by the following formula: ERD/ERS\% =
(E-R)/R*100, where E and R represent the power density at the ``Event''
(1 s) and ``Rest'' (1 s) periods. The ``Rest'' was defined as the period
from 5 s to 4 s before the auditory cues triggering the movement. The
anticipation ``Event'' was defined as the period of 1 s before the
auditory cues. Finally, the execution ``Event'' was defined as the
period of 1 s from 250 ms to 1250 ms after the auditory cues and the
alpha ERD peak within this interval was considered in the analysis. The
first 250 ms after the auditory cues were intentionally removed to
exclude the auditory-evoked potentials (N1-P2 complex) (Lightfoot, 2016)
and the pain-evoked potentials (N2-P2 complex) (Babiloni et al., 2008;
Fabrizi et al., 2016; Mouraux, Iannetti, \& Plaghki, 2010). The
resulting negative percentage values represented the alpha ERD, as a
reflection of cortical activity. On the contrary, positive percentage
values represented the alpha ERS as a reflection of cortical inhibition
(Pfurtscheller \& Lopes Da Silva, 1999; Pfurtscheller et al., 1997). For
the scalp analysis, clusters of electrodes were considered for each
hemisphere at frontal (F3 and FC3; F4 and FC4) and centro-parietal (C3,
CP3, and P3; C4, CP4, and P4) levels. On the other hand, the eLORETA
solutions were used to compute the cortical voxel-level ERD/ERS in the
alpha frequency band.

\textbf{2.6 Statistical analysis for the ERD/ERS scalp distribution}

Linear mixed model for repeated measures was used to assess whether the
subjective perception of the stimulus intensity was depending on the
MVF. The fixed factors were \emph{Condition} (UM+, UM-, and BM-)
and\emph{Stimulus} (pain and no-pain), whereas the random factor was the
number of subjects in each group. The models were fitted separately in
the left and right hemispheres for the frontal (F3-FC3 and F4-FC4) and
centro-parietal (C3-CP3-P3 and C4-CP4-P4) clusters of electrodes as well
as for the anticipation and execution phases of the event. The linear
mixed model statistical analysis was carried out using IBM SPSS
Statistics 27 (IBM, New York, USA).

\textbf{2.7 Statistical analysis for the alpha ERD/ERS cortical sources}

To investigate the differences in the cortical activation between
stimuli perceived as painful and non-painful, statistical nonparametric
mapping voxel-based wise randomization tests (5000 permutations) were
applied for the alpha ERD/ERS eLORETA solutions for each condition (UM+,
UM-, and BM-) and stage of the event (Anticipation and Execution). The
outcomes obtained through this statistical approach are equivalent to
statistical parametric methods with multiple comparison corrections
(Nichols \& Holmes 2001). This nonparametric permutation is particularly
useful when analyzing small sample sizes with low degrees of freedom
(Bian et al., 2019; Nichols \& Holmes, 2001). The results are displayed
as voxel-by-voxel T statistics maps with a corrected P \textless{} 0.05
(randomization tests correction) (Nichols \& Holmes, 2001). To weaken
the type II error (risk of false negatives), an uncorrected significance
threshold of a more severe P \textless{} 0.001 was also considered in
the analysis. Only cortical areas with a minimum number of 5 voxels were
considered in the analysis. These statistical analyses were performed
using eLORETA statistical toolbox (Pascual-Marqui, 2007).

\textbf{2.8 Control analysis}

Event-related potentials (ERPs) in response to the auditory cues and
electrical stimuli were extracted from the Cz electrode. Successively,
the waveforms resulting from painful and non-painful blocks were
averaged across the subjects for each condition and paired samples
t-tests were used for statistical comparison. The ERPs considered were
the N1-P2 (auditory), P2-N2 complex (electrical stimulus), and P3
(attentional). Furthermore, the randomness of the painful and
non-painful epochs was tested by performing the RUNS test for each
subject and condition. Finally, NRS values were compared in order to
control differences in the subjective perception of the stimulus
intensity for each condition. All the statistical analyses were
performed using IBM SPSS Statistics 27 (IBM, New York, USA).

\textbf{3 \emph{RESULTS}}

\textbf{3.1 Scalp topography}

Figure 3 shows the scalp distribution of the alpha ERD/ERS for the three
conditions (UM-, BM-, and UM+) at the anticipation (1000 ms before the
auditory cue) and execution (peak within 1250 ms after the auditory cue)
of the event. The cortical activity patterns resulting from the blocks
perceived as painful (NRS \textgreater{} 5) and non-painful (NRS
\textless{} 5) are thus compared. In the control conditions without MVF
(UM- and BM-), results indicate similar centrally-distributed alpha ERD
in the anticipation phase of the event. When considering the execution
phase, the alpha ERD is stronger and more widespread in the non-painful
than painful blocks in both conditions. In the experimental MVF
condition, the alpha ERD shows an opposite activity pattern, i.e.,
stronger in the painful than non-painful blocks. Moreover, it shows a
prominent parieto-central distribution. Even in the MVF condition, the
alpha ERD is stronger and more widespread during the execution phase of
the event.

However, the linear mixed model analyses performed to assess the
interaction between the stimulus intensities and the conditions did not
indicate any statistically significant effect neither for the frontal
nor central brain regions (p \textgreater{} 0.05).

\textbf{3.2 Control conditions without MVF}

This section of the results considers the differences between painful
and non-painful blocks for the control conditions without the MVF
illusion (i.e., UM- and BM-). The spatial distribution of the p values
related to the Student's t-tests (parametric statistical maps) for the
eLORETA solutions of the alpha ERD/ERS is illustrated in Figure 4 (first
and second rows). The significant T values with the relative voxel
cluster size and locations are listed in Table 1.

For both conditions, the anticipation and execution phases of the event
are characterized by a stronger activation (alpha ERD) in the
non-painful than painful blocks. In particular, the UM- condition shows
this pattern in the left anterior cingulate (BA 32; peak value: T =
4.36; p \textless{} 0.05 corrected) and inferior parietal cortex (BA 40;
peak value: T = 3.95; p \textless{} 0.05 corrected) in the anticipatory
phase, and no significant differences in the execution phase. In the BM-
conditions, the differences appear in the bilateral sensory-motor (BAs
1-2-3, 4; peak value: 4.61; p \textless{} 0.05 corrected), inferior
parietal (BA 40; peak value: T = 4.46; p \textless{} 0.05) cortical
areas, and bilateral inferior frontal gyrus (BAs 44-35; peak value: T =
3.36; p \textless{} 0.001 uncorrected), for the anticipation phase.
Furthermore, the execution phase of the event shows those differences in
the right superior (BAs 9-46; peak value: T = 4.11; p \textless{} 0.05
corrected) and inferior (BAs 44-45; peak value: T = 3.79; p \textless{}
0.001 uncorrected) frontal gyri as well as right anterior cingulate
cortex (BA 32; peak value: T = 3.67; p \textless{} 0.001 uncorrected).

\textbf{3.3 Experimental condition with MVF}

The results from the voxel-by-voxel comparisons between painful and
non-painful blocks in the experimental MVF (UM+) condition are hereby
reported. The spatial distribution of the P values related to the
Student's t-tests is illustrated in Figure 4 (bottom). All the
significant T values with the relative voxels cluster size and
localizations are summarized in Table 1.

Unlike the control conditions, in the UM+ condition, the alpha ERD
observed in the painful blocks was stronger than the alpha ERD in the
non-painful blocks. During the anticipation phase, the main differences
are observed in the right posterior cingulate (BA 30; peak value: T =
-4.16; p \textless{} 0.05 corrected) and the inferior posterior parietal
cortex (BA 40; peak value: T = -4.73; p \textless{} 0.05 corrected).
During the execution phase, these differences are widespread in the
frontal and posterior areas. In particular, results showed significant
differences in the right polar frontal (BA 10; peak value: T = -4.31; p
\textless{} 0.05 corrected) and inferior posterior parietal (BA 40; peal
value: T = -4.67; p \textless{} 0.05 corrected) cortical areas. The same
was true in the right middle temporal gyrus (BA 39; peak value: T =
-4.75; p \textless{} 0.05 corrected) and precuneus (BA 19; peak value: T
= -3.87; p \textless{} 0.001 uncorrected) as well as in the bilateral
anterior cingulate (BAs 24-32; peak value: T = -4.66; p \textless{} 0.05
corrected).

\textbf{3.4 Control analysis}

The ERP waveforms are plotted in Fig. 5. Results indicate as the
negative peaks (N1 and N2) present higher amplitude in the painful (red
line) than non-painful (black line) blocks. This was true at a
statistical level for the N1 in the UM+ condition (p \textless{} 0.05)
as well as for the N2 in the UM- condition (p \textless{} 0.05).
Moreover, the P2 peak showed higher amplitude in the painful than
non-painful blocks in the UM+ condition (p \textless{} 0.05).
Interestingly, no differences were observed for the attentional P3 ERP.
No statistically significant differences were found in the latency
measures.

The RUNS test's results for the experimental condition (UM+) showed no
significant differences (average number of Runs = 6.8; SD = +- 1.6; p
\textgreater{} 0.05) (Figure 6), indicating that the order of the blocks
in which the subjects perceived the electrical stimuli as painful or
non-painful presents a random distribution (i.e., the variability in the
individual perceived intensity was not due to habituation or
sensitization effects).

Finally, paired samples t-tests showed that NRS values relative to
painful blocks are significantly higher than values in the non-painful
blocks for each condition (p \textless{} 0.001 for all comparisons)
(Figure 7).

4 DISCUSSION

In the present exploratory study, we hypothesized that the MVF-induced
illusion of hand movements may affect the nociception and the activation
in the cortical midline areas of the pain neural matrix. For this
purpose, we used an original methodological approach. Electrical stimuli
at about the pain threshold were applied to the left hand to produce
painful or non-painful sensations during unilateral right-hand movements
with the MVF and, as control conditions, during unilateral right and
bilateral hand movements without the MVF. The eLORETA freeware estimated
the EEG source activity, and the alpha ERD (as a sign of cortical
activation) reflected the neurophysiological oscillatory mechanisms
underlying the painful and non-painful sensations associated with the
MVF-related movement illusion.

The results of a control analysis showed that the vertex N1-P2 and/or N2
peaks of the sensory evoked potentials exhibited higher amplitude in
relation to the painful over the non-painful sensations during both MVF
and noMVF conditions. These results corroborate the reliability of the
participants' subjective sensations, in line with previous studies
demonstrating that those sensory-evoked potentials can be considered
trustworthy neurophysiological signatures of enhanced cortical arousal
and pain experience in humans (Fabrizi et al., 2016; Lightfoot, 2016;
Mouraux et al., 2010).

The core results of the present study showed that as compared to the
painful sensations, the non-painful sensations during the MVF condition
were specifically characterized by lower alpha ERD (cortical activation)
estimated in the right cortical midline regions (i.e., medial
prefrontal, anterior and posterior cingulate, parietal cortex, and
precuneus), angular gyrus, and inferior parietal lobule contralateral to
the electric hand stimulation and ipsilateral to the hand movements. In
contrast, the non-painful sensations during the control noMVF conditions
were specifically characterized by stronger alpha ERD estimated in the
left lateral prefrontal and inferior parietal lobule regions ipsilateral
to the electric hand stimulation and contralateral to the hand
movements. The functional meaning of these results is discussed in the
following sections.

\textbf{4.1 The effects of the MVF-induced movement illusion on the
cortical activity and pain}

During the MVF condition, the non-painful over painful sensations were
specifically related to lower alpha ERD in the right cortical midline
regions of the limbic and default mode network, in the right angular
gyrus of the default mode network, and the right inferior parietal
lobule of the ventral attention network. In contrast, the non-painful
sensations in the noMVF conditions were characterized by higher alpha
ERD in the left lateral prefrontal and inferior parietal lobule of the
ventral attention networks.

The present results emphasize the role of brain neurophysiological
oscillatory mechanisms operating at alpha frequencies for modulating the
de -activation of the above cortical regions relevant to human
nociception. In this regard, they complement the following previous
neuroimaging findings obtained in humans: (1) the involvement of medial
prefrontal and anterior-posterior cingulate cortices in processing the
affective component of pain (Peng, Steele, Becerra, \& Borsook, 2018;
Tolomeo et al., 2016); (2) the activation of cortical midline regions in
association with the unpleasantness sensations induced by painful
stimuli (De Ridder \& Vanneste, 2016; Kulkarni et al., 2005; Price,
2000); and (3) the activation of a posterior cortical subnetwork
encompassing inferior parietal lobe, posterior cingulate cortex, and
precuneus related to affective and cognitive components (i.e., the
expectation of pain and self-awareness) of the pain experience (Fauchon
et al., 2019). Moreover, the present results complement previous
evidence showing that experimental sensorimotor incongruence in healthy
individuals may induce alteration in limb perceptions and emotions
(dysesthesia) (Foell, Bekrater-Bodmann, Mccabe, \& Flor, 2013; Katayama,
Osumi, Kodama, \& Morioka, 2016; McCabe, Haigh, Halligan, \& Blake,
2005; Nishigami et al., 2014). In these studies, dysesthesia was linked
to abnormal EEG alpha and beta rhythms desynchronization estimated in
parietal, midline premotor, and cingulate cortical areas (Katayama et
al., 2019, 2016; Nishigami et al., 2014). Notably, such discomfort is
similar to that reported in people with pathological chronic pain
(Daenen et al., 2012; Mccabe et al., 2007).

Taken together, the present and the aforementioned neuroimaging findings
inspired the following speculation. In the present MVF condition, the
reduced alpha ERD in the right cortical midline limbic regions may be
related to non-painful sensations concerning attenuated affective
sense-of-self and internal body perception (Araujo et al., 2013;
Katayama et al., 2016; Nishigami et al., 2014; Northoff \& Bermpohl,
2004; Northoff et al., 2006). Furthermore, the reduced alpha ERD in the
right default mode network regions may be associated with attenuated
body-related (interoceptive) internal representations (Broyd et al.,
2009; Gusnard \& Raichle, 2001; Raichle et al., 2001). In contrast, in
the present noMVF conditions, the increased alpha ERD in the left
lateral prefrontal and inferior parietal lobule may be related to
non-painful sensations in relation to a significant allocation of the
attention and cognitive states on the true moving hand(s) for ``body
gnosis,'' with interferential effects on the neural signals induced by
the electric hand stimulation (Rusconi, Pinel, Dehaene, \& Kleinschmidt,
2010; Rusconi, Walsh, \& Butterworth, 2005). Unfortunately, EEG
techniques do not have the fine spatial resolution necessary to
disentangle the different subcomponents of a given midline cortical
region belonging to either the limbic or default mode network.

During the present MVF condition, the participants may experience the
self-oriented attentional and cognitive states associated with the
illusory sense of ownership (``the illusory moving hand belongs to my
body'') and agency (``I am moving the hand reflected in the mirror'')
for the moving hand reflected in the mirror. According to previous alpha
ERD evidence from our group (Rizzo et al., 2022), these states may be
related to the activation of lateral prefrontal, premotor, and parietal
cortical regions in the hemisphere ipsilateral to the true unilateral
hand movements and contralateral to the moving hand reflected in the
mirror. Notably, in the present experiments, the only region of that
cortical network showing an effect related to pain was the left inferior
parietal lobule. Specifically, the non-painful over painful sensations
during the MVF condition were associated with lower alpha ERD in the
right inferior parietal lobule, as opposed to the higher alpha ERD in
the left inferior parietal lobule during the noMVF conditions. It can be
speculated that during the MVF condition, the non-painful sensations
were also related to a low activation in the right lateral parietal area
integrating the visual-somato(nociceptive)-motor information regarding
the electrically stimulated left hand.

Future multimodal EEG-fMRI studies should shed light on the effects of
the MVF-related movement illusion on the nociception and the functional
connectivity between all cortical and subcortical (e.g.,
amygdala-hypothalamus, amygdala-septum, hippocampus-mammillary bodies,
etc.) components of the limbic system. A modulation in this connectivity
is expected to impact the integration of primary needs, the emotional
value of the painful stimuli, and interoceptive signals related to the
persons' experience in relation to the wellness-illness axis during
painful stimulations (Cavanna \& Trimble, 2006; Goffaux et al., 2014;
Northoff \& Bermpohl, 2004). Furthermore, future studies may investigate
the functional connectivity between the limbic and the default mode
networks in connection with the MVF effects on nociception.

5 CONCLUSIONS

Here we hypothesized that in healthy adults, an MVF-induced movement
illusion may exert its effects changing the activation in midline
cortical areas of the pain neural matrix through neurophysiological
oscillatory mechanisms revealed by EEG alpha rhythms.

As compared to the painful sensations, the non-painful sensations were
specifically characterized by (1) lower alpha ERD (mathematically)
estimated in the cortical midline, angular gyrus, and lateral parietal
regions during the experimental condition with MVF and (2) higher alpha
ERD estimated in the lateral prefrontal and parietal regions during the
control conditions without MVF.

These core results suggest that the MVF-induced movement illusion may
affect nociception and neurophysiological oscillatory mechanisms
reducing the activation in cortical limbic and default mode regions that
may attenuate the affective sense-of-self, internal body perception,
body-related (interoceptive) internal representations, and attention to
signals triggered by the electrically stimulated left hand.

Conflicts of interest

The authors have no conflicts of interest to declare.

Data availability statement

The data that support the findings of this study are available on
request from the corresponding author, MR. The data are not publicly
available due to their confidential contents that could compromise the
privacy of research participants.



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\textbf{Figure 1}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

\textbf{Figure 1}

Experimental setup during the Mirror Visual Feedback (MVF) procedure
(Unilateral Mirror or UM+ condition). The mirror is placed in the
subjects' midsagittal plane to give the illusion of ownership of the
left hand. A sham electrode was placed on the right index finger to
strengthen the illusory feeling. Movements consisted of double extension
(1 s approx.) with a slow release toward the table.

\textbf{Figure 2}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

\textbf{Figure 2}

The figure illustrates the sequence of one trial of the experimental
paradigm. In the experiment, a fixed 10 s intertrial interval was
applied. During the offline analysis, 9 s epochs were extracted (from 7
s before the auditory cue to 2 s after the cue). In the figure, the time
is expressed in milliseconds (ms). The 0 (zero) time corresponds to the
auditory cue triggering the right index finger movement (blue line). In
each trial, electrical painful stimuli were delivered on the left index
finger after 100 ms from the auditory cue (red line). The anticipation
(ANT) event period was defined as the time interval of 1000 ms before
the 0, whereas the execution (EXE) period was defined as the time
interval between 250 and 1250 ms after the 0. The alpha event-related
de/synchronization (ERD/ERS) was calculated for the ANT and EXE periods
in relation to a baseline period represented by the yellow box between
5000 and 4000 ms before the 0.

\textbf{Figure 3}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

\textbf{Figure 3}

Across subjects mean 2-D maps of the alpha ERD/ERS distribution over the
scalp for each condition (Unilateral No Mirror, Bilateral No Mirror, and
Unilateral Mirror), phase of the event (Anticipation and Execution), and
subjective perceived intensity of the stimulus (pain, no-pain). In the
maps, the alpha event-related desynchronization (ERD) and
synchronization (ERS) are represented with red and blue colours,
respectively. Four 250 ms time windows before the auditory cue are
averaged for the anticipation phase (ANT). The 250 ms time windows
showing the highest peak of the alpha ERD after the auditory cue are
averaged for the execution phase (EXE).

\textbf{Table 1}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

\end{center}
\end{figure}

\textbf{Table 1}

Voxel-based Student's t-test analysis for the eLORETA sources of the
alpha ERD at the Brodmann areas (BAs) level. **Significance threshold of
p \textless{} 0.05 corrected for multiple comparisons; *significance
threshold of p \textless{} 0.001 uncorrected. The cluster size
represents the number of voxels significant for the multiple
comparisons' threshold (along with the number of voxels significant for
the uncorrected threshold). The most statistically significant voxel is
indicated by the Montreal Neurological Institute (MNI) coordinates. The
alpha ERD is a negative percentage value indicating the reduction of
power density at the event period with reference to the baseline. In the
comparison between the painful vs non-painful epochs, a negative T value
indicates that the alpha ERD is greater in the painful than non-painful
epochs, whereas positive T values indicate that the alpha ERD is greater
in the non-painful than painful epochs.

\textbf{Figure 4}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image5/image5}

\end{center}
\end{figure}

\textbf{Figure 4}

Spatial distribution of the voxel-by-voxel significant p values relative
to the Student's t-test for the alpha ERD/ERS eLORETA solutions. The
figure illustrates the comparisons between pain and no-pain blocks for
each condition (UM-, BM-, and UM+) at the anticipation and execution
phase of the event. The axial, sagittal, and coronal sections are
represented. The t values corresponding to the uncorrected significance
threshold of p \textless{} 0.001 are shown on the right side for each
condition (the t values change as the sample sizes are different among
the groups). In the maps, the red voxels show the areas where the alpha
ERD is significantly stronger in the painful than in no-painful blocks.
Conversely, the blue voxels show the areas where the alpha ERD is
significantly stronger in the no-pain than pain blocks.

\textbf{Figure 5}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image6/image6}

\end{center}
\end{figure}

\textbf{Figure 5}

The figure illustrates the mean event-related potentials (ERPs)
generated in response to auditory cues and electrical sensory stimuli at
the Cz electrode. The difference between painful (red line) and
non-painful (black line) blocks are represented for each condition (UM-,
BM-, and UM+). Statistical analysis (which one? T-test?) showed
significant differences in the N2 peak for the UM- condition as well as
in the N1 and P2 peaks for the experimental UM+ condition (*p
\textless{} 0.05).

\textbf{Figure 6}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image7/image7}

\end{center}
\end{figure}

\textbf{Figure 6}

The graph shows the distribution of the blocks where each subject
(Y-axis) perceived the stimuli as painful (NRS \textgreater{} 5, red
blocks) or non-painful (NRS \textless{} 5, green blocks) in the
experimental Unilateral Mirror (UM+) condition. Each block consisted of
5 trials. Therefore, a total of 16 blocks are shown on the X-axis. The
RUNS test showed as the red and green blocks are randomly distributed
for each subject (p \textless{} 0.05).

\textbf{Figure 7}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image8/image8}

\end{center}
\end{figure}

\textbf{Figure 7}

Histograms of the average of the Numerical Rating Scale (NRS) values
provided by the subjects during each condition (a). The ratings were
separated into painful (NRS \textgreater{} 5, red) and non-painful (NRS
\textless{} 5, green). Paired samples t-tests controlled that the
painful and non-painful ratings were significantly different in each
condition (p \textless{} 0.001). The table below (b) shows the mean and
the standard error (SE) for each condition and perceived intensity.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Fig/Fig}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Fih/Fih}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Fii/Fii}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Fij/Fij}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-5---ERPs/Figure-5---ERPs}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Fig-6---RUNS/Fig-6---RUNS}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Fik/Fik}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Table-1---Table-voxel-by-voxel-comparisons/Table-1---Table-voxel-by-voxel-comparisons}

\end{center}
\end{figure}

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