ArticlePDF Available

Movement related slow cortical potentials in severely paralyzed chronic stroke patients

Frontiers
Frontiers in Human Neuroscience
Authors:
  • University of Tuebingen / TECNALIA, San Sebastian, Spain

Abstract and Figures

Movement-related slow cortical potentials (SCPs) are proposed as reliable and immediate indicators of cortical reorganization in motor learning. SCP amplitude and latency have been reported as markers for the brain's computational effort, attention and movement planning. SCPs have been used as an EEG signature of motor control and as a main feature in Brain-Machine-Interfaces (BMIs). Some reports suggest SCPs are modified following stroke. In this study, we investigated movement-related SCPs in severe chronic stroke patients with no residual paretic hand movements preceding and during paretic (when they try to move) and healthy hand movements. The aim was to identify SCP signatures related to cortex integrity and complete paralysis due to stroke in the chronic stage. Twenty severely impaired (no residual finger extension) chronic stoke patients, of whom ten presented subcortical and ten cortical and subcortical lesions, underwent EEG and EMG recordings during a cue triggered hand movement (open/close) paradigm. SCP onset appeared and peaked significantly earlier during paretic hand movements than during healthy hand movements. Amplitudes were significantly larger over the midline (Cz, Fz) for paretic hand movements while contralateral (C4, F4) and midline (Cz, Fz) amplitudes were significantly larger than ipsilateral activity for healthy hand movements. Dividing the participants into subcortical only and mixed lesioned patient groups, no significant differences observed in SCP amplitude and latency between groups. This suggests lesions in the thalamocortical loop as the main factor in SCP changes after stroke. Furthermore, we demonstrated how, after long-term complete paralysis, post-stroke intention to move a paralyzed hand resulted in longer and larger SCPs originating in the frontal areas. These results suggest SCP are a valuable feature that should be incorporated in the design of new neurofeedback strategies for motor neurorehabilitation.
Content may be subject to copyright.
ORIGINAL RESEARCH ARTICLE
published: 15 January 2015
doi: 10.3389/fnhum.2014.01033
Movement related slow cortical potentials in severely
paralyzed chronic stroke patients
Ozge Yilmaz1,2*, Niels Birbaumer 1,3 and Ander Ramos-Murguialday1,4
1Institute of Medical Psychology and Behavioral Neurobiology, University of Tuebingen, Tuebingen, Germany
2Brain and Mind Studies Lab, Department of Psychology, Bahcesehir University, Istanbul, Turkey
3Ospedale San Camillo, Istituto di Ricovero e Cura a Carattere Scientifico, Lido di Venezia, Italy
4Health Technologies Department, Tecnalia, San Sebastian, Spain
Edited by:
Richard A. P. Roche, The National
University of Ireland Maynooth,
Ireland
Reviewed by:
Patricia Mary Gough, Maynooth
University, Ireland
Sarah J. Casey, Acquired Brain Injury
Ireland, Ireland
*Correspondence:
Ozge Yilmaz, Brain and Mind
Studies Lab, Bahcesehir University,
Ciragan Cad. 2-4 34353 Besiktas,
Istanbul, Turkey
e-mail: ozge_yilmaz@yahoo.com
Movement-related slow cortical potentials (SCPs) are proposed as reliable and immediate
indicators of cortical reorganization in motor learning. SCP amplitude and latency have
been reported as markers for the brains computational effort, attention and movement
planning. SCPs have been used as an EEG signature of motor control and as a main
feature in Brain-Machine-Interfaces (BMIs). Some reports suggest SCPs are modified
following stroke. In this study, we investigated movement-related SCPs in severe chronic
stroke patients with no residual paretic hand movements preceding and during paretic
(when they try to move) and healthy hand movements. The aim was to identify SCP
signatures related to cortex integrity and complete paralysis due to stroke in the chronic
stage. Twenty severely impaired (no residual finger extension) chronic stoke patients,
of whom ten presented subcortical and ten cortical and subcortical lesions, underwent
EEG and EMG recordings during a cue triggered hand movement (open/close) paradigm.
SCP onset appeared and peaked significantly earlier during paretic hand movements than
during healthy hand movements. Amplitudes were significantly larger over the midline (Cz,
Fz) for paretic hand movements while contralateral (C4, F4) and midline (Cz, Fz) amplitudes
were significantly larger than ipsilateral activity for healthy hand movements. Dividing
the participants into subcortical only and mixed lesioned patient groups, no significant
differences observed in SCP amplitude and latency between groups. This suggests lesions
in the thalamocortical loop as the main factor in SCP changes after stroke. Furthermore,
we demonstrated how, after long-term complete paralysis, post-stroke intention to move
a paralyzed hand resulted in longer and larger SCPs originating in the frontal areas. These
results suggest SCP are a valuable feature that should be incorporated in the design of
new neurofeedback strategies for motor neurorehabilitation.
Keywords: stroke, movement related slow cortical potentials, EEG, movement preparation, intention to move
INTRODUCTION
Stroke occurs as a consequence of cardiovascular flow distur-
bances damaging neural networks in the brain. Following stroke,
reorganization of cortical networks occurs (Grefkes et al., 2008;
Ward, 2011). Reorganization consists among other consequences
of enhanced neural activity of the healthy hemisphere (Chollet
et al., 1991; Murase et al., 2004; Bashir et al., 2010).
Movement-related slow cortical potentials (SCPs) recorded
with EEG can be divided into two main components: (a) poten-
tials occurring during intention or anticipation of an upcoming
movement which is also called the Bereitschaftspotential (BP)
for self-paced movements (Barrett et al., 1986), (b) the motor
potential (MP) occurring at the time of the execution (Deecke
et al., 1969). A BP is a bilateral low frequency (0–5 Hz) nega-
tive shift (NS) occurring seconds before the movement onset.
The MP peak rises primarily contralateral to the movement side
around the onset of a voluntary movement (Birbaumer et al.,
1991),whichisalsoreferredtoaspeakNS(Barrett et al., 1986;
Shibasaki and Hallett, 2006). According to the excitation thresh-
old theory, during the preparation of a movement SCPs serve
as regulatory mechanisms that facilitate neuronal firing of the
involved networks (Elbert and Rockstroh, 1987; Birbaumer et al.,
1991).
Cortical activity preceding voluntary movements is well-
documented (Kornhuber and Deecke, 1965). The main cortical
generators of SCPs are the premotor cortices (PMC), supple-
mentary motor areas (SMAs) and cingulate cortices (Deecke,
1987; Cui et al., 1999). There is emerging evidence that subcor-
tical structures, particularly the basal ganglia, also contribute to
movement preparation, execution and control. The thalamus is
connected to cortex and both the basal ganglia and the cerebellar
pathways and the role of these connections in movement prepa-
ration has recently been studied extensively in humans (Rektor,
2002; Paradiso et al., 2004).Alesioninanyofthesestructures
or connections (e.g., corticothalamic loop) could affect move-
ment preparation and planning and should be reflected in SCPs,
Frontiers in Human Neuroscience www.frontiersin.org January 2015 | Volume 8 | Article 1033 |1
HUMAN NEUROSCIENCE
Yilmaz et al. Slow cortical potentials in chronic stroke
especially if motor recovery does not take place and chronic stage
is reached.
It has been shown that the latency of SCP [i.e., the time
between the onset of SCP and the movement onset recorded
with electromyography (EMG)] indicates the preparation time
of the required action, with longer the latencies indicating more
complex is the motor tasks (Tarkka and Hallett, 1990; Lang
et al., 1992). Repetitive simple movements, which do not require
higher order cognitive pre-planning and preparation, are related
to shorter SCP latency and smaller SCP amplitudes (Libetetal.,
1982). It has been suggested that the amplitude of the nega-
tive peak may indicate the brain’s computational demand” to
perform the movement (Libet et al., 1982; Lang et al., 1990;
Simonetta et al., 1991; Libet, 1992).
Several groups have demonstrated altered SCP features after
a brain disease or injury (Sasaki and Gemba, 1984; Cunnington
et al., 1999). Kitamura et al. (1996), in a study involving two sub-
cortical stroke patients performing synergistic movements of the
paretic arm, report that the early SCP component remained bilat-
eral as in healthy participants. However, MP was also distributed
bilaterally as opposed to its dominant contralateral distribu-
tion in healthy individuals, indicating a stronger involvement of
the healthy hemisphere during the movements of paretic side.
Additionally, stroke patients’ recovering motor function spon-
taneously shows an increase in fMRI BOLD activity toward the
non-lesioned hemisphere when executing paretic hand move-
ments. These are shifted back to ipsilesional areas once recovery
takes place, reaching a “normal” bilateral activation with a peak
at hand movement’s contralateral hemisphere (Rossini et al.,
2003; Murphy and Corbett, 2009). Green et al. (1999) offer sup-
port for these findings using multimodal neuroimaging methods
with EEG and fMRI demonstrating that the intact hemisphere
becomes more active after stroke in participants with varying
degrees of recovery. Similar findings regarding contralesional acti-
vation were observed by other groups (Lang et al., 1988; Verleger
et al., 2003; Jankelowitz and Colebatch, 2005).Ithasalsorecently
been shown sensorimotor-rhythm (SMR) based EEG Brain-
Machine-Interfaces (BMIs) can be used to recover motor function
in chronic severely paretic stroke patients (Ramos-Murguialday
et al., 2013). Furthermore, SCPs have been extensively used as
features for neurofeedback and BMI control (Birbaumer et al.,
1999).
In this study, we investigated the effects of cortex integrity
and stroke severity on SCPs (i.e., neural reorganization in par-
ticipants with severe hand weakness in the chronic stage). The
final goal is to identify relevant features that can be used and
optimized (e.g., toward normal potentials’ characteristics) in SCP
based BMI neurofeedback therapy for motor rehabilitation in
paralyzed chronic stroke patients. We studied SCPs of 20 severely
impaired chronic stroke patients, who suffered from subcortical
and mixed (cortical and subcortical) lesions, during paretic and
healthy hand movements. The aim was to investigate changes in
SCPs in severe chronic stroke comparing the SCP amplitudes and
latencies induced by the subcortical vs. cortical lesions and paretic
vs. healthy hand movements. We used the healthy hand move-
ment related SCPs as reference because it is related to healthy
motor output. Although brain activity might not be the same as in
a healthy person, the motor output is normal. Due to the severity
of motor impairment in our participants, we expected to observe
widespread (i.e., bilateral) SCP activity and earlier SCP onset in
paretic compared to the healthy hand movements (compensatory
movement planning). An ipsilateral over-activation (i.e., higher
negative amplitudes) and a contralateral lower activation were
expected during motor preparation of the paretic compared to
healthy hand movements (maladaptive higher involvement of the
intact hemisphere). Furthermore, we hypothesized that frontal
and premotor areas in the participants presenting mixed lesions
(subcortical and cortical) would show higher levels of activa-
tion, due to increased compensatory efforts of the secondary
motor areas, compared to the participants with subcortical
lesions.
MATERIALS AND METHODS
PARTICIPANTS
Twenty hemiparetic (none of the participants had bilateral
lesions) participants 51.4 ±11.1 years old and 5.9 ±5.5 years
since stroke participated in the study. Ten participants (5 male, 5
female) presented subcortical lesions (Sub-L) only and 10 par-
ticipants (7 male, 3 female) presented mixed lesions (Mix-L)
(subcortical and cortical areas). Selection criteria were no residual
finger extension and time since stroke of at least 12 months. The
degree of functional severity was measured using a modified ver-
sion of the Fugl-Meyer Assessment (FMA) scale. (for participant
information and detailed selection criteria see the Supplementary
Information). The study was conducted at the University of
Tuebingen, Germany. Informed consent was obtained from all
participants involved. The study was approved by the ethics com-
mittee of the Faculty of Medicine of the University of Tuebingen
(Germany).
DATA ACQUISITION
Participants underwent a 16-channel EEG recording (Acticap,
BrainProducts GmbH, Germany) session [Fp1, Fp2, F3, Fz, F4,
T7, C3, Cz, C4, T8, CP3, CP4, P3, Pz, P4, Oz, AFz (Ground) and
FCz (Reference)]. Surface electromyographic (EMG) activity was
recorded from both arms using eight bipolar Ag/AgCl electrodes
from Myotronics-Noromed (Tukwila, WA, USA) on four differ-
ent muscle groups (extensor carpi ulnaris, extensor digitorum,
external head of the biceps and external head of the triceps) in
order to detect movement onset and involuntary muscle contrac-
tions. Electrooculography (EOG) recordings were also carried out
forocularcorrections.
Participants performed an audiovisual task. The imperative
cue was visual (an arrow pointing right or left appearing on the
screen for 5 s) and auditory (a sound indicating right or left) given
concurrently. This protocol was tried to resemble movements
during a standard rehabilitation session. Participants either exe-
cuted a hand opening and closing movement with their healthy
hand (HM) or tried to open and close the paretic hand (PM)
at a comfortable personal pace for 5 s according to the audio-
visual imperative cues. Participants were trained and instructed
to avoid compensatory movements during the intention to open
and close the paretic hand. The inter-trial-interval was random-
ized between 3 and 4 s and a fixation cross appeared on the screen
Frontiers in Human Neuroscience www.frontiersin.org January 2015 | Volume 8 | Article 1033 |2
Yilmaz et al. Slow cortical potentials in chronic stroke
during this inter-trial resting interval. The data acquired in one
session, which was lasted around 30 min.
DATA ANALYSIS
Data were analyzed using Brain Vision Analyzer 2.0 signal pro-
cessing software (BrainProducts GmbH, Germany). During the
EEG preprocessing a 50 Hz notch filter was applied. Data were
separated from ocular artifacts using the Gratton and Coles
method (Gratton et al., 1983). Participants performed 68 trials
per condition (resting, healthy and paretic hand movements).
After the artifact eliminations the mean number of epochs aver-
aged was 58 and 46, for the healthy hand and paretic hand,
respectively.
We used current source density (CSD) to analyze reference free
data. Although 16 channels might not be sufficient to accurately
estimate the CSD, we assume that the configuration used in this
study permitted the CSD calculation in the channels used in the
analysis (C3, F3, Cz, Fz, C4, F4: for more on CSD method see
the Supplementary Information). EEG data were filtered between
0.1 and 2.5 Hz to detect SCPs. Data were segmented from 2500
to 2000 ms, aligned to the EMG onset and to the cue onset sep-
arately. The first 500ms of each segment were used for baseline
correction.
Left- and right-sided lateralized scalp sites were swapped in
the participants with the right hemispheric lesion, in order to be
able to make statistical comparisons between all patients’ lesioned
hemisphere and intact hemisphere data (e.g., F3 for the left lesions
and F4 for the right lesion were pooled) (Rosahl and Knight,
1995). Thus, in this text, when we mention paretic movements,
this refers to right hand movement and when we mention healthy
hand movements, this refers to left hand movements. For paretic
hand movement condition, F3 and C3 will be contralateral and
F4 and C4 will be ipsilateral to the movement and for healthy
hand condition F3 and C3 will be ipsilateral and F4 and C4 will
be contralateral (Ta ble 1 ).
Six frontal and central electrodes were used for statistical
analysis (F3, Fz, F4, C3, Cz, C4) because the activity of fronto-
central cortices is the major source for SCPs (Deecke et al., 1969;
Libet et al., 1982). SCP onset time (Onset) and peak amplitude
(Peak-Amp) features were extracted, while lesion (subcortical
and mixed) location and hand movement condition (paretic and
healthy) were independent variables. One-Way ANOVA for group
comparisons and repeated measures ANOVA with paired t-test
Table 1 | Referred channels according to the conditions.
Healthy hand
movement (HM)
Paret ic hand
movement (PM)
(Left hand) (Right hand)
Contralateral (Intact/right hemisphere)
C4
F4
(Lesioned/left hemisphere)
C3
F3
Ipsilateral (Lesioned/left hemisphere)
C3
F3
(Intact/right hemisphere)
C4
F4
post-hoc analysis were carried out (for more on statistical analysis
see the Supplementary Information).
EMG ANALYSIS
EMG data were processed and used to detect muscle contraction
and to align segmented EEG data to muscle activity (for details
see the Supplementary Information).
RESULTS
In order to test our different hypotheses we performed separate
statistical analyses having; (A) all participants together in one
group and (B) dividing them in two groups depending on the
lesion location (subcortical and mixed). These analyses were per-
formed using two features extracted from SCPs (peak amplitude
and onset time) (Tabl e 2 ).
ALL PARTICIPANTS
We detected the two components of SCP (BP and MP) as one
transient response occurring as a negative slope and a following
peak. Figure 1 shows the grand averages of PM (paretic “right
hand) and HM (healthy “left” hand) aligned to the EMG onset
and cue onset (time 0) separately. Mean EMG onset for PM was
1380.6 ±453.3 ms and for HM was 615.7 ±147.6 ms after the
cue onset. In order to avoid this reaction time delay between PM
and HM, which may influence the SCP analysis, we analyzed fur-
ther EEG data aligned to the EMG onset only, not to the cue
onset.
Additionally, a positive peak was clearly observed after the
cue onset as a P300 potential (Polich, 2007) reflecting orient-
ing to the stimuli (Figure 1). However, we did not include this
P300 response into our analysis and we did not compare the
results aligned to the cue onset, because data aligned to the
cue onset would have resulted in biased SCP amplitude and
latencies.
Peak amplitude
The repeated measures ANOVA analysis on peak amplitude
showed a significant hand effect (PM vs. HM) [F(1,19) =10.19,
p<0.01], laterality effect [F(1,19) =18.41, p<0.001], hand ×
laterality interaction [F(1,19) =3.28, p<0.05], hand ×fronto-
central distribution interaction [F(1,19) =15.55, p<0.001], lat-
erality ×frontocentral distribution interaction [F(1,19) =9.50,
p<0.01] and hand ×laterality ×frontocentral interaction
[F(1,19) =8.27, p<0.01].
In between conditions (PM vs. HM), post-hoc paired t-test
analysis showed no significant difference for peak amplitude com-
paring contralateral potentials during HM and PM. However,
over the midline electrodes peak amplitudes were signifi-
cantly larger during PM compared to HM {Fz paretic vs. Fz
healthy [t(20) =−2.16, p<0.05];Czpareticvs.Czhealthy
[t(20) =−11.33, p<0.001]}. Comparing ipsilateral activities
during PM and HM, peak amplitude was significantly larger
on central electrode site during PM {C4 paretic vs. C3 healthy,
[t(20) =−3.89, p<0.001]} (Figure 2).
When comparing laterality factor (contralateral, midline, ipsi-
lateral activity) within the hand movement conditions (PM and
HM) we observed that in PM, Cz amplitude was significantly
Frontiers in Human Neuroscience www.frontiersin.org January 2015 | Volume 8 | Article 1033 |3
Yilmaz et al. Slow cortical potentials in chronic stroke
Table 2 | Mean of SCP onset time in ms and peak amplitude in µV for subcortical and mixed lesioned participants are presented.
Features Healthy hand movements (HM) Paretic hand movements (PM)
C3 F3 Cz Fz C4 F4 C3 F3 Cz Fz C4 F4
Sub-L
Onset
111 267 127 327 222 347 754 921 74 7 889 710 898
Sub-L
PeakAmp
4.5 8.8 9.4 12.7 9.4 12.1 12. 9 12.6 16. 5 15.1 11. 1 10. 6
Mix-L
Onset
166 200 187 185 172 197 722 805 692 74 8 724 752
Mix-L
PeakAmp
5.8 9.3 9.3 12.3 8.3 11. 4 8.9 10 15.9 15.6 13.7 14 .6
FIGURE 1 | SCPs of severe chronic stroke patients averaged and aligned to EMG onset (A, C) and to cue onset (B, D). The Y-axis represents SCP
amplitude (µV/m2) and the X-axis represents time (ms). An additional Y-axis bar (25 µV) at the right side represents the EMG amplitudes.
larger than C3 and C4 {Cz vs. C3 [t(20) =−6.08, p<0.001]; Cz
vs. C4 [t(20) =−5.89, p<0.001]} and C3 and C4 amplitudes
were not significantly different from each other [t(20) =−0.9, ns].
The same pattern of activity was observed at frontal electrodes. Fz
showed significantly larger amplitudes than F3 and F4 {Fz vs. F3
[t(20) =−5.51, p<0.001]; Fz vs. F4 [t(20) =−4.06, p<0.001]}.
There was no significant difference between F3 and F4 [t(20) =
0.71, ns]. This result indicates no clear laterality in PM. On the
other hand, during HM (left hand) a clear lateralization toward
contralateral and midline regions was observed, as expected. C4
an Cz showed significantly larger amplitude than C3 {C3 vs. C4
[t(20) =3.17, p<0.01]; C3 vs. Cz [t(20) =5.43, p<0.001]} and
there was no significant difference between Cz and C4 (t(20) =
0.5, ns). Similarly, F4 and Fz also showed significantly larger
Frontiers in Human Neuroscience www.frontiersin.org January 2015 | Volume 8 | Article 1033 |4
Yilmaz et al. Slow cortical potentials in chronic stroke
FIGURE 2 | The laterality effects on peak amplitudes in µV for both
paretic (in blue) and healthy (in red) hand movements. X axis represents
frontal contralateral (F contra), frontal midline (F mid), frontal ipsilateral (F ipsi)
and central contralateral (C contra), central midline (C mid), central ipsilateral
(C ipsi) channels. (p=0.05; ∗∗p=0.01; ∗∗∗ p=0.001) (Error bars represent
the standard error).
amplitudethanF3{F3vs.F4[t(20) =2.64, p<0.05]; F3 vs. Fz
[t(20) =5.86, p<0.001]} and there was no significant difference
between Fz and F4 [t(20) =−1.14, ns] (Figure 2).
The frontocentral distribution revealed that during HM (left
hand) all frontal locations presented larger amplitudes compared
to central locations {F3 vs. C3 [t(20) =−3.88, p<0.001]; Fz
vs. Cz. [t(20) =−2.68, p<0.05]; F4 vs. C4 [t(20) =−2.71, p<
0.05]} while during PM (right hand) there was no significant
frontocentral distribution difference (Figure 2).
Onset time
The repeated measures ANOVA analysis on SCP onset time
revealed a significant hand effect [F(1,19) =45.48, p<0.001].
Further post-hoc analyses were applied to test the hypothesis that
before PM there will be a longer preparation time comparing HM.
Post-hoc paired t-test comparisons of laterality (contralateral
and ipsilateral) of SCP onset between hand movement condi-
tions (paretic and healthy) showed that in PM, all locations’
(contralateral, midline, ipsilateral) SCP onsets were significantly
earlier (i.e., SCP negativity started earlier relative to the EMG
onset) than in HM {F3 paretic vs. F4 healthy [t(20) =−5.94,
p<0.001]; Fz paretic vs. Fz healthy [t(20) =−5.91, p<0.001];
Cz paretic vs. Cz healthy [t(20) =−6.15, p<0.001]; C3 paretic
vs. C4 healthy [t(20) =−5.82, p<0.001]; F4 paretic vs. F3
healthy [t(20) =−6.52, p<0.001]; C4 paretic vs. C3 healthy
[t(20) =−6.75, p<0.001]}.
Post-hoc paired t-tests revealed that the laterality effect on
onset time was not significant during HM within the condition,
(i.e., the activity started bilaterally and was widespread). However,
during PM, onset was significantly earlier at electrode F3 only
(contralateral to the movement, over the lesioned hemisphere)
when compared to Fz [t(20) =−2.27, p<0.05].
Post-hoc analysis of fronto-central distribution of onset time
revealed that during HM, similar to what was obtained in the
peak amplitude analysis (larger amplitudes for frontal regions),
F3 and Fz showed also significantly earlier onset of SCP than C3
and Cz, respectively {F3 vs. C3 [t(20) =−2.77, p<0.05]; Fz vs.
Cz [t(20) =−2.35, p<0.05]}. There was no significant difference
between F4 and C4 (on the contralateral (healthy) hemisphere
during HM [t(20) =−1.76, ns]. These results indicate that in HM,
SCP started significantly earlier in frontal regions compared to
central locations over the midline and ipsilateral (lesioned) hemi-
sphere. Additionally, all frontal regions presented significantly
earlier SCP onset compared to central regions during PM {Fz vs.
Cz [t(20) =−2.17, p<0.05]; F3 vs. C3 [t(20) =−3.13, p<0.01];
F4 vs. C4 [t(20) =−2.78, p<0.05]}.
SUBCORTICAL vs. MIXED LESIONED PARTICIPANTS
FMA score difference between subcortical and mixed lesion
groups was not significant [F(1,19) =3.39, ns]. One-Way ANOVA
analysis did not show any difference between Sub-L and Mix-
L group of participants for any of the extracted SCP features
(Peak-Amp and Onset), neither in PM nor in HM (Figure 3).
DISCUSSION
The two SCP components (BP and MP) concatenated as a NS
peaking around movement onset. During PM we observed the
negative peak before the EMG onset and during HM after the
EMG onset. The NS started around 1 s before the EMG onset (i.e.,
SCP mean onset was 822 ±338 ms) and the peak was observed
around 120 ms after the EMG onset for PM. For HM the NS
started around the time of the EMG onset (i.e., SCP mean onset
was 212 ±236 ms) and the peak was observed around 500 ms
after the EMG onset. Although we believe our EMG onset calcula-
tion is robust, one limitation of our study could be the EMG onset
difference between groups. Six out of the 10 patients belonging
to the subcortical group presented no EMG onset in the paretic
hand and our extrapolation method, using a constant calculated
Frontiers in Human Neuroscience www.frontiersin.org January 2015 | Volume 8 | Article 1033 |5
Yilmaz et al. Slow cortical potentials in chronic stroke
FIGURE 3 | Grand average SCPs of the participants with mixed
(subcortical and cortical) lesion (A, C) and with subcortical lesion (A,
D). Contralateral (green), midline (black) and ipsilateral (red) electrodes
were shown for each movement condition. EMG activity is in blue. An
additional Y-axis bar (25 µV) at the right side represents the EMG
amplitudes.
on all patients from both groups presenting EMG onset, may be
inappropriate.
The SCP NS started significantly earlier and lasted longer in
preparation for PM than HM and negligible preparation time
was detected before HM, indicating a significantly longer move-
ment preparatory phase during PM. We assume earlier SCP onset
represents a longer neural computational effort to evoke the nec-
essary brain excitation to induce a motor top-down command
during PM. This result supports previous findings suggesting that
the time between the onset of the SCP and the EMG onset may
indicate extended preparation (Tarkka and Hallett, 1990)—the
brain starts exciting motor networks (facilitating the neural fir-
ing) for a significantly longer time before an EMG onset can be
produced on the paretic side compared to healthy hand motor
actions.
Longer planning time was needed for PM. Individuals with
severe paralysis lack contingencies between volitional actions
and consequences. Such contingencies cannot therefore be
used to drive reorganization within functional brain networks.
Consequently, such individuals are prone to devolution toward
a maladaptive state indicative of learned disuse (Taub et al.,
1999; Krakauer, 2006; Pomeroy et al., 2011). Therefore, motor
intention contingency delivered by a BMI driven orthosis may
explain the positive results of Ramos-Murguialday et al. work
andshouldreducethetimelapsebetweenSCPpeakandEMG
onset. Furthermore, a combination of SMR and SCP feed-
back could improve BMI feedback optimizing the rehabilitation
intervention.
Due to the severity of motor impairment in our partici-
pants we expected to observe compensatory over-activation (i.e.,
larger peak amplitudes) during motor preparation for execution
attempts of PM compared to HM generated SCPs. The peak
amplitude of SCP was significantly larger during PM over the
midline (Fz, Cz) and ipsilateral central (C4) locations than dur-
ing HM. It has been previously suggested that the amplitude of the
negativity indicates the brain’s computational demand to perform
the movement (Jankelowitz and Colebatch, 2005). Therefore, our
results denote a higher effort during PM. However, this higher
activity occurs over ipsilateral central areas and medial-fronto-
central areas, which may be due to maladaptive (since participants
Frontiers in Human Neuroscience www.frontiersin.org January 2015 | Volume 8 | Article 1033 |6
Yilmaz et al. Slow cortical potentials in chronic stroke
did not recover) over-activation of the healthy hemisphere and/or
to the lack of cross-hemispheric inhibition from lesioned to
non-lesioned hemisphere.
On the other hand, between conditions we did not observe
any significant difference in SCP amplitude at the electrodes con-
tralateral to the movement during PM (C3) compared to HM
(C4). We expected a decrease in amplitude of SCPs due to the
lesion in the contralateral (ipsilesional) hemisphere during PM
but this was not the case. Cortical generators of SCP might not
be compromised and the recorded SCP amplitude during PM
could remain at similar levels if the SCP generated in subcorti-
cal structures does not contribute significantly (due to volume
conduction) to the activity recorded with the EEG electrodes.
We observed that preparation of movement comes from
frontal and not from central areas. The larger response on the
healthy side could reflect the non-use or atrophy of the lesioned
side or it may indicate a compensatory over-activation on the
healthy side.
Following previous findings (Kitamura et al., 1996)wedid
not find any difference in peak amplitude between contralateral
(ipsilesional) and ipsilateral (contralesional) hemispheres dur-
ing PM, while during HM the amplitude was significantly larger
in contralateral compared to ipsilateral electrodes (Green et al.,
1999). Since peak amplitude has been related with the computa-
tional demand, one could expect either an increase in the peak
amplitude on the ipsilesional side if cortex is intact (subcortical
lesion), which is what happened in all participants, or a decrease
in peak amplitude in primary motor areas and an increase in
other non-lesioned secondary motor areas if cortex is lesioned
(mixed lesion). We hypothesized that frontal and premotor areas
in participants presenting mixed lesions (subcortical and corti-
cal) would be more activated, due to the compensatory role of
the secondary motor areas to overcome the loss of primary motor
cortical structures in the participants presenting cortical lesions.
However, we did not observe any significant difference between
Sub-L and Mix-L groups, neither in the peak amplitude nor in
SCP onset during PM or HM. This may be due to the fact that
in participants presenting mixed lesions, the cortex was not heav-
ily affected and peri-lesional areas could induce similar SCP peak
amplitudes. However, since the top-down control of the motor
neurons is not efficient and there is no afferent return confirm-
ing the delivery of the efferent signal, other areas of the cortex
(medial and ipsilateral) are excited (facilitation of neural firing)
to exploit their connection to the motor neurons of the affected
muscles, resulting in significantly higher SCPs amplitudes and in
maladaptive compensatory functional brain changes.
CONCLUSION
We describe SCP changes in chronic severe stroke patients.
Paralyzed participants showed significantly longer movement
planning time and significantly larger SCP peak amplitudes in
medial and ipsilateral sites during PM, indicating larger compu-
tational demand during paretic hand intention to move. Non-
use of the paretic hand induces over-activation of the healthy
hemisphere with larger SCP amplitudes and, probably, stronger
maladaptive inhibition of the lesioned side impeding cortical
reorganization and motor rehabilitation. These changes were
independent of cortex integrity. SCP latency and peak amplitude
in both hemispheres appear to be appropriate features to be used
and optimized in BMI-like neurorehabilitation interventions.
ACKNOWLEDGMENTS
We would like to thank our participants and the Stroke team. This
work was funded by the European Research Council (ERC) Grant
227632, the Werner Reichardt Centre of Integrative Neuroscience
(CIN), by the German Federal Ministry of Education and
Research (BMBF, Förderzeichen 01GQ0831) as well as the
Deutsche Forschungsgemeinschaft (DFG), DAAD (Deutscher
Akademischer Austauschdienst) and the Baden-Wuerttemberg
Stiftung (ROB-1), Baden-Württemberg Stiftung (ROB-1), the
Indian-European collaborative research and technological devel-
opment projects (INDIGO-DTB2-051), the Natural Science
Fundation of China (NSFC 31450110072).
SUPPLEMENTARY MATERIAL
The Supplementary Material for this article can be found
online at: http://www.frontiersin.org/journal/10.3389/fnhum.
2014.01033/abstract
REFERENCES
Barrett, G., Shibasaki, H., and Neshige, R. (1986). Cortical potentials pre-
ceding voluntary movement: evidence for three periods of preparation in
man. Electroencephalogr. Clin. Neurophysiol. 63, 327–339. doi: 10.1016/0013-
4694(86)90017-9
Bashir, S., Mizrahi, I., Weaver, K., Fregni, F., and Pascual-Leone, A. (2010).
Assessment and modulation of neural plasticity in rehabilitation with transcra-
nial magnetic stimulation. PM &R2, 253–268. doi: 10.1016/j.pmrj.2010.10.015
Birbaumer, N., Elbert, T., Canavan, A. G., and Rockstroh, B. (1991). Slow potentials
of the cerebral cortex and behavior. Physiol. Rev. 70, 1–41.
Birbaumer, N., Ghanayim, N., Hinterberger, T., Iversen, I., Kotchoubey, B., Kübler,
A., et al. (1999). A spelling device for the paralysed. Nature 398, 297–298. doi:
10.1038/18581
Chollet, F., DiPiero, V., Wise, R. J., Brooks, D. J., Dolan, R. J., and Frackowiak, R.
S. (1991). The functional anatomy of motor recovery after stroke in humans:
a study with positron emission tomography. Ann. Neurol. 29, 63–71. doi:
10.1002/ana.410290112
Cui, R. Q., Huter, D., Lang, W., and Deecke, L. (1999). Neuroimage of voluntary
movement: topography of the Bereitschaftspotential, a 64-channel DC current
source density study. Neuroim age 1, 124–134. doi: 10.1006/nimg.1998.0388
Cunnington, R., Iansek, R., and Bradshaw, J. L. (1999). Movement-related poten-
tials in Parkinson’s disease: external cues and attentional strategies. Mov. Disord.
14, 63–68.
Deecke, L. (1987). Bereitschaftspotential as an indicator of movement prepara-
tion in supplementary motor area and motor cortex. Ciba Found. Symp. 132,
231–250.
Deecke, L., Scheid, P., and Kornhuber, H. H. (1969). Distribution of readiness
potential, pre-motion positivity, and motor potential of the human cerebral
cortex preceding voluntary finger movements. Exp. Brain Res. 7, 158–168. doi:
10.1007/BF00235441
Elbert, T., and Rockstroh, B. (1987). Threshold regulation- a key to understanding
of the combined dynamics of EEG and event-related potentials. J. Psychophysiol.
4, 317–333.
Gratton, G., Coles, M. G., and Donchin, E. (1983). A new method for off-line
removal of ocular artifact. Electroencephalogr. Clin. Neurophysiol. 55, 468–484.
doi: 10.1016/0013-4694(83)90135-9
Green, J. B., Bialy, Y., Sora, E., and Ricamato, A. (1999). High-resolution EEG in
poststroke hemiparesis can identify ipsilateral generators during motor tasks.
Stroke 30, 2659–2665. doi: 10.1161/01.STR.30.12.2659
Grefkes, C., Nowak, D. A., Eickhoff, S. B., Dafotakis, M., Küst, J., Karbe, H., et al.
(2008). Cortical connectivity after subcortical stroke assessed with functional
magnetic resonance imaging. Ann. Neurol. 63, 236–246. doi: 10.1002/ana.21228
Frontiers in Human Neuroscience www.frontiersin.org January 2015 | Volume 8 | Article 1033 |7
Yilmaz et al. Slow cortical potentials in chronic stroke
Jankelowitz, S. K., and Colebatch, J. K. (2005). Movement related potentials
in acutely induced weakness and stroke. Exp. Brain Res. 161, 104–113. doi:
10.1007/s00221-004-2051-6
Kitamura, J., Shibasaki, H., and Takeuchi, T. (1996). Cortical potentials preceding
voluntary elbow movement in recovered hemiparesis. Electroencephalogr. Clin.
Neuro physiol. 98, 149–156. doi: 10.1016/0013-4694(95)00218-9
Kornhuber, H. H., and Deecke, L. (1965). Hirnpotentialeanderungen bei
Willkuerbewegungen und passiven Bewegungen des Menschen: bere-
itschaftspotential und reafferente Potentiale. Pfluegers Arch. 284, 1–17.
doi: 10.1007/BF00412364
Krakauer, J. W. (2006). Motor learning: its relevance to stroke recovery and neu-
rorehabilitation. Curr. Opin. Neurol. 19, 84–90. doi: 10.1097/01.wco.00002005
44.29915.cc
Lang, W., Beisteiner, R., Lindinger, G., and Deecke, L. (1992). Changes of cortical
activity when executing learned motor sequences. Exp. Brain Res. 89, 435–440.
doi: 10.1007/BF00228259
Lang, W., Lang, M., Podreka, I., Steiner, M., Uhl, F., Suess, E., et al. (1988).
DC-potential shifts and regional cerebral blood flow reveal frontal cortex
involvement in human visuomotor learning. Exp. Brain Res. 71, 353–364. doi:
10.1007/BF00247495
Lang, W., Obrig, H., Lindinger, G., Cheyne, D., and Deecke, L. (1990).
Supplementary motor area activation while tapping bimanually different
rhythms in musicians. Exp. Brain Res. 79, 504–514. doi: 10.1007/BF00229320
Libet, B. (1992). Voluntary acts and readiness potentials. Electroencephalogr. Clin.
Neuro physiol. 82, 85–86. doi: 10.1016/0013-4694(92)90186-L
Libet, B., Wright, E. W., and Gleason, C. A. (1982). Readiness-potentials preceding
unrestricted ‘spontaneous’ vs. pre-planned voluntary acts. Electroencephalogr.
Clin. Neurophysiol. 54, 322–335. doi: 10.1016/0013-4694(82)90181-X
Murase, N., Duque, J., Mazzocchio, R., and Cohen, L. G. (2004). Influence of inter-
hemispheric interactions on motor function in chronic stroke. Annu. Neurol.
55, 400–409. doi: 10.1002/ana.10848
Murphy, T. H., and Corbett, D. (2009). Plasticity during stroke recovery: from
synapse to behavior. Nat. Rev. Neurosci. 10, 861–872. doi: 10.1038/nrn2735
Paradiso, G., Cunic, D., Saint-Cyr, J. A., Hoque, T., Lozano, A. M., Lang, A. E.,
et al. (2004). Involvement of human thalamus in the preparation of self-paced
movement. Brain 127, 2717–2731. doi: 10.1093/brain/awh288
Polich, J. (2007). Updating P300: an integrative theory of P3a and P3b. Clin.
Neuro physiol. 118, 2128–2148. doi: 10.1016/j.clinph.2007.04.019
Pomeroy, V., Aglioti, S. M., Mark, V. W., McFarland, D., Stinear, C., Wolf, S.
L., et al. (2011). Neurological principles and rehabilitation of action disor-
ders: rehabilitation interventions. Neurorehabil. Neural Repair. 25, 33–43. doi:
10.1177/1545968311410942
Ramos-Murguialday, A., Broetz, D., Rea, M., Läer, L., Yilmaz, Ö., Brasil, F. L., et al.
(2013). Brain–machine interface in chronic stroke rehabilitation: a controlled
study. Ann. Neurol. 74, 100–108. doi: 10.1002/ana.23879
Rektor, I. (2002). Scalp-recorded Bereitschaftspotential is the result of the activ-
ity of cortical and subcortical generators–a hypothesis. Clin. Neurophysiol. 113,
1998–2005. doi: 10.1016/S1388-2457(02)00286-9
Rosahl, S. K., and Knight, R. T. (1995). Role of prefrontal cortex in generation of
thecontingentnegativevariation.Cereb. Cortex 5, 123–134. doi: 10.1093/cer-
cor/5.2.123
Rossini, P. M., Calautti, C., Pauri, F., and Baron, J. C. (2003). Post-stroke
plastic reorganisation in the adult brain. Lancet Neurol. 2, 493–502. doi:
10.1016/S1474-4422(03)00485-X
Sasaki, K., and Gemba, H. (1984). Compensatory motor function of the
somatosensory cortex for the motor cortex temporarily impaired by cooling in
the monkey. Exp. Brain Res. 55, 60–68. doi: 10.1007/BF00240498
Shibasaki, H., and Hallett, M. (2006). What is the Bereitschaftspotential?. Clin.
Neuro physiol. 117, 2341–2356. doi: 10.1016/j.clinph.2006.04.025
Simonetta, M., Clanet, M., and Rascol, O. (1991). Bereitschaftspotential in a
simple movement or in a motor sequence starting with the same simple move-
ment. Electroencephalogr. Clin. Neurophysiol. 81, 129–134. doi: 10.1016/0168-
5597(91)90006-J
Tarkka, I. M., and Hallett, M. (1990). Cortical topography of premotor and
motor potentials preceding self-paced, voluntary movement of dominant and
non-dominant hands. Electroencephalogr. Clin. Neurophysiol. 75, 36–43. doi:
10.1016/0013-4694(90)90150-I
Taub, E., Uswatte, G., and Pidikiti, R. (1999). Constraint-Induced
Movement Therapy: a new family of techniques with broad applica-
tion to physical rehabilitation–a clinical review. J. Rehabil. Res. Dev. 36,
237–251.
Verleger, R., Adam, S., Rose, M., Vollmer, C., Wauschkuhn, B., and Kömpf,
D. (2003). Control of hand movements after striatocapsular stroke:
high-resolution temporal analysis of the function of ipsilateral activa-
tion. Clin. Neurophysiol. 114, 1468–1476. doi: 10.1016/S1388-2457(03)
00125-1
Ward, N. S. (2011). Assessment of cortical reorganisation for hand func-
tion after stroke. J. Physiol. 589, 5625–5632. doi: 10.1113/jphysiol.2011.
220939
Conflict of Interest Statement: The authors declare that the research was con-
ducted in the absence of any commercial or financial relationships that could be
construed as a potential conflict of interest.
Received: 16 October 2014; accepted: 09 December 2014; published online: 15 January
2015.
Citation: Yilmaz O, Birbaumer N and Ramos-Murguialday A (2015) Movement
related slow cortical potentials in severely paralyzed chronic stroke patients. Front.
Hum. Neu rosci . 8:1033. doi: 10.3389/fnhum.2014.01033
This article was submitted to the journal Frontiers in Human Neuroscience.
Copyright © 2015 Yilmaz, Birbaumer and Ramos-Murguialday. This is an open-
access article distributed under the terms of the Creative Commons Attribution License
(CC BY). The use, distribution or reproduction in other forums is permitted, provided
the original author(s) or licensor are credited and that the original publication in this
journal is cited, in accordance with accepted academic practice. No use, distribution or
reproduction is permitted which does not comply with these terms.
Frontiers in Human Neuroscience www.frontiersin.org January 2015 | Volume 8 | Article 1033 |8
... Each of them is optimally elicited via ad-hoc paradigms and encodes slightly different neurophysiological information. Sensorimotor rhythms are oscillations in the EEG occurring in the alpha (8)(9)(10)(11)(12) and beta (13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30) bands and can be recorded over the sensorimotor areas, whose amplitude typically decreases (i.e. desynchronizes) during movement execution. ...
... Finally, cortico-muscular coherence (CMC) is a measure of synchronization between central and peripheral activations, and it can be considered a simple form of hybrid functional connectivity measuring the spectral coherence between EEG and EMG signals [10]. All of these brain and brainmuscles correlates of movement have been described in post-stroke populations, showing deviations from the healthy condition sometimes related to the degree of motor impairment [6,[16][17][18][19]. ...
... The computation was repeated for all the 7 windows of task trials and the only one window of rest trials. Power spectrum values were averaged in two frequency bands of interest, normally associated with brain correlates of voluntary movements [7]: alpha (8-12 Hz) and beta (13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30) bands. ...
Article
Full-text available
Objective. Brain–Computer Interfaces targeting post-stroke recovery of the upper limb employ mainly electroencephalography to decode movement-related brain activation. Recently hybrid systems including muscular activity were introduced. We compared the motor task discrimination abilities of three different features, namely event-related desynchronization/synchronization (ERD/ERS) and movement-related cortical potential (MRCP) as brain-derived features and cortico-muscular coherence (CMC) as a hybrid brain-muscle derived feature, elicited in 13 healthy subjects and 13 stroke patients during the execution/attempt of two simple hand motor tasks (finger extension and grasping) commonly employed in upper limb rehabilitation protocols. Approach. We employed a three-way statistical design to investigate whether their ability to discriminate the two movements follows a specific temporal evolution along the movement execution and is eventually different among the three features and between the two groups. We also investigated the differences in performance at the single-subject level. Main results. The ERD/ERS and the CMC-based classification showed similar temporal evolutions of the performance with a significant increase in accuracy during the execution phase while MRCP-based accuracy peaked at movement onset. Such temporal dynamics were similar but slower in stroke patients when the movements were attempted with the affected hand (AH). Moreover, CMC outperformed the two brain features in healthy subjects and stroke patients when performing the task with their unaffected hand, whereas a higher variability across subjects was observed in patients performing the tasks with their AH. Interestingly, brain features performed better in this latter condition with respect to healthy subjects. Significance. Our results provide hints to improve the design of Brain–Computer Interfaces for post-stroke rehabilitation, emphasizing the need for personalized approaches tailored to patients’ characteristics and to the intended rehabilitative target.
... The electrophysiological process that is associated with motor anticipation and whether changes in motor anticipation are associated with functional improvement are unclear in patients with stroke [22]. Existing studies indicated that a loss of frequency alpha band on the ipsilesional hemisphere was related to poor motor recovery outcome [23]. ...
... Contingent negative variation (CNV) is a slow negative event-related potential (ERP) that can reflect the cognitive process of event-related motor preparation [27][28][29]. It is considered a reliable index for observ-ing cortical excitability of motor anticipatory [22] and can be used to assess the cortical excitability during motor anticipation in stroke patients [30]. Study on source analysis indicated that CNV is generated from multiple sources, including cortical and subcortical generators of the anterior cingulate cortex, supplementary motor area, and primary motor area [27,31,32]. ...
... The F3, F4, and Fz lie over the premotor cortex, and the C3, C4, and Cz lie over the primary motor cortex. For the purpose of statistical comparison, the left and right side hemispheres were flipped right to left in the participant with a right hemispheric lesion so that the "left" hemisphere was always the lesioned hemisphere [22]. ...
Article
Full-text available
Background: Impaired cognitive ability to anticipate the required control for an upcoming task in patients with stroke may affect rehabilitation outcome. The cortical excitability of task-related motor anticipation for upper limb movement induced by virtual reality (VR) training remains unclear. Aims: To investigate the effect of VR training on the cortical excitability of motor anticipation when executing upper limb movement in patients with subacute stroke. Methods: A total of thirty-six stroke survivors with upper limb hemiparesis resulting from the first occurrence of stroke within 1 to 3 months were recruited. Participants were randomly allocated to the VR intervention group or conventional therapy group. Event-related potentials (ERPs) and electromyography (EMG) were used to simultaneously record the cortical excitability and muscle activities during palmar grasp motion. Outcome measures of the contingent negative variation (CNV) latency and amplitude, EMG reaction time, Upper Limb Fugl-Meyer Assessment (UL-FMA), Action Research Arm Test (ARAT), and National Institutes of Health Stroke Scale (NIHSS) were recorded pre- and postintervention. The between-group difference was analysed by mixed model ANOVA. Results: The EMG onset time of the paretic hand in the VR group was earlier than that observed in the control group (t = 2.174, p = 0.039) postintervention. CNV latency reduction postintervention was larger in the VR group than in the control group (t = 2.411, p = 0.021) during paretic hand movement. The reduction in CNV amplitude in the VR group was larger in the VR group than in the control group (p < 0.001 for all electrodes except for C3) when executing paretic hand movement. ARAT and UL-FMA scores were significantly higher in the VR group than in the control group (p = 0.019 and p = 0.037, respectively) postintervention. No significant difference in the reduction in NIHSS was found between the VR and control groups (p = 0.072). Conclusions: VR intervention is superior to conventional therapy to improve the cognitive neural process of motor anticipation and reduce the excessive compensatory activation of the contralesional hemisphere. The improvements observed in the cognitive neural process corroborated with the improvements in hand function.
... According to the literature, the MRCP signals can be generated during voluntary movements of hands and feet [1][2][3][4]. These include some components in different frequency bands: a slow 0-5Hz [75,76] readiness potential and an early desynchronization in the 10-12Hz frequency band (before movement onset), and a late synchronization of 20-30Hz activity approximately 1 s after movement execution (after movement onset), and also at movement onset (a slow motor potential [76,77]). Our results show that using MRCP signals, the hand Table 9 Results for windowing technique on modified EEGNet, TSCR-Net, and TSCIR-Net models. ...
... According to the literature, the MRCP signals can be generated during voluntary movements of hands and feet [1][2][3][4]. These include some components in different frequency bands: a slow 0-5Hz [75,76] readiness potential and an early desynchronization in the 10-12Hz frequency band (before movement onset), and a late synchronization of 20-30Hz activity approximately 1 s after movement execution (after movement onset), and also at movement onset (a slow motor potential [76,77]). Our results show that using MRCP signals, the hand Table 9 Results for windowing technique on modified EEGNet, TSCR-Net, and TSCIR-Net models. ...
Article
Brain Computer Interface (BCI) offers a promising approach to restoring hand functionality for people with cervical spinal cord injury (SCI). A reliable classification of brain activities based on appropriate flexibility in feature extraction could enhance BCI systems performance. In the present study, based on convolutional layers with temporal-spatial, Separable and Depthwise structures, we develop Temporal-Spatial Convolutional Residual Network)TSCR-Net(and Temporal-Spatial Convolutional Iterative Residual Network)TSCIR-Net(structures to classify electroencephalogram (EEG) signals. Using EEG signals in five different hand movement classes of SCI people, we compare the effectiveness of TSCIR-Net and TSCR-Net models with some competitive methods. We use the bayesian hyperparameter optimization algorithm to tune the hyperparameters of compact convolutional neural networks. In order to show the high generalizability of the proposed models, we compare the results of the models in different frequency ranges. Our proposed models decoded distinctive characteristics of different movement efforts and obtained higher classification accuracy than previous deep neural networks. Our findings indicate that TSCIR-Net and TSCR-Net models fulfills a better classification accuracy of 71.11%, and 64.55% for EEG_All and 57.74%, and 67.87% for EEG_Low frequency data sets than the compared methods in the literature.
... Green et al 1999 showed similar findings using EEG and fMRI (Green et al., 1999). And also an interesting study demonstrated that in chronic stroke, non-use of the paretic hand is accompanied by over activation of intact hemisphere indicating maladaptive inhibition of the lesioned side (Yilmaz et al., 2015). ...
... Finally, it has been said that "by choosing stimulation parameters at random, no information would be gained on the mechanism of action. This would offer little insight into how to improve a protocol or predict for which applications it is optimal" (Yilmaz et al., 2015). Thus, further research is needed to verify if the technique mentioned in our study could be used to guide customize NIBS protocols tailoring the optimal site and parameters for each patient. ...
Article
Background: Event related cortical potentials related to motor action are referred to as movement related cortical potentials. The late component of which is the readiness potential (RP) and its polarity is more negative in the hemisphere responsible for planning of motor action. This lateralized nature of RP during unilateral hand movement is studied as lateralized readiness potential (LRP) by calculating the contralateral-minus-ipsilateral difference wave for each hand. Objective: The aim was to identify the hemisphere contributing to motor recovery in acute and chronic stroke patients through recording LRPs. Methods: Twenty-nine cases with cerebrovascular stroke (15 acute and 14 chronic) were included in the study. EEG was recorded in response to self-cued button presses by the paretic side to obtain the averaged LRP amplitude. The hemisphere with greater negativity was considered the side of recovery. Functional recovery was assessed by Fugl Meyer test. Results: In acute cases, recovery was more related to LRP activity in the contralesional hemisphere (73%), whereas lateralization was equal in chronic cases; 50% in either group. LRP amplitude was higher in the contralesional hemisphere (p = 0.02). Functional recovery assessed by the Fugl Meyer test (FM) was similar whether recovery was ipsi- or contralesional. Conclusions: Early after stroke, motor recovery is more likely to involve compensatory activity in the contralesional hemisphere, while in the chronic phase, the ipsilesional hemisphere may recover its function and become more active. Further research is needed to verify if the technique mentioned in our study could be used to guide customized NIBS protocols tailoring the optimal site and parameters for each patient.
... Electroencephalographic studies have shown that movement on the paralyzed side is accompanied by greater cortical activity in the contralesional hemisphere due to disinhibition from reduced inhibitory output from the ipsilesional hemisphere [31,32], resulting in imbalanced activity and insufficient motor output. By applying 1 Hz rTMS to the contralesional MI, this transhemispheric inhibition can be suppressed, thereby facilitating motor output from the damaged hemisphere [33]. ...
Article
Full-text available
Recovery of motor function following stroke requires interventions to enhance ipsilesional cortical activity. To improve finger motor function following stroke, we developed a movement task with visuomotor feedback and measured changes in motor cortex activity by electroencephalography. Stroke patients performed two types of movement task on separate days using the paretic fingers: a visuomotor tracking task requiring the patient to match a target muscle force pattern with ongoing feedback and a simple finger flexion/extension task without feedback. Movement-related cortical potentials (MRCPs) were recorded before and after the two motor interventions. The amplitudes of MRCPs measured from the ipsilesional hemisphere were significantly enhanced after the visuomotor tracking task but were unchanged by the simple manual movement task. Increased MRCP amplitude preceding movement onset revealed that the control of manual movement using visual feedback acted on the preparatory stage from motor planning to execution. A visuomotor tracking task can enhance motor cortex activity following a brief motor intervention, suggesting efficient induction of use-dependent cortical plasticity in stroke.
Article
Full-text available
More than 85% of stroke survivors suffer from different degrees of disability for the rest of their lives. They will require support that can vary from occasional to full time assistance. These conditions are also associated to an enormous economic impact for their families and health care systems. Current rehabilitation treatments have limited efficacy and their long-term effect is controversial. Here we review different challenges related to the design and development of neural interfaces for rehabilitative purposes. We analyze current bibliographic evidence of the effect of neuro-feedback in functional motor rehabilitation of stroke patients. We highlight the potential of these systems to reconnect brain and muscles. We also describe all aspects that should be taken into account to restore motor control. Our aim with this work is to help researchers designing interfaces that demonstrate and validate neuromodulation strategies to enforce a contingent and functional neural linkage between the central and the peripheral nervous system. We thus give clues to design systems that can improve or/and re-activate neuroplastic mechanisms and open a new recovery window for stroke patients.
Chapter
Stroke is the leading cause of sensorimotor disability worldwide. Recently, neurorehabilitation therapies based on neural interfaces have paved the way toward new effective rehabilitation strategies exploiting neural plasticity mechanisms and have produced promising results even in extremely compromised patients. In this chapter, we review and discuss several aspects of the design and use of neural interfaces coupled with upper limb actuators (robotics and functional electrical stimulation (FES)) for motor rehabilitation after stroke. We first describe the burden of stroke and the limitations of currently used rehabilitation strategies. Secondly, we analyze different neural interfacing methods to reinforce the brain-to-muscle link leveraging previous neuroscientific findings on motor learning and functional neuroplasticity. We review current clinical trials using this technology and analyze its effect on the sensorimotor function of stroke patients, reported as clinical and neurophysiological parameters. Thirdly, we provide several guidelines for the optimal design of these systems to boost motor recovery. We conclude with some recommendations and thoughts for future development of this technology in stroke rehabilitation.
Article
Background and Objective :How to learn robust representations from brain activities and to improve algorithm performance are the most significant issues for brain-computer interface systems. Methods : This study introduces a long short-term memory recurrent neural network to decode the multichannel electroencephalogram or electrocorticogram for implementing an effective motor imagery-based brain-computer interface system. The unique information processing mechanism of the long short-term memory network characterizes spatio-temporal dynamics in time sequences. This study evaluates the proposed method using publically available electroencephalogram/electrocorticogram datasets. Results : The decoded features coupled with a gradient boosting classifier could obtain high recognition accuracies of 99% for electroencephalogram and 100% for electrocorticogram, respectively. Conclusions :The results demonstrated that the proposed model can estimate robust spatial-temporal features and obtain significant performance improvement for motor imagery-based brain-computer interface systems. Further, the proposed method is of low computational complexity.
Article
Full-text available
Objective: Chronic stroke patients with severe hand weakness respond poorly to rehabilitation efforts. Here, we evaluated efficacy of daily brain-machine interface (BMI) training to increase the hypothesized beneficial effects of physiotherapy alone in patients with severe paresis in a double-blind sham-controlled design proof of concept study. Methods: Thirty-two chronic stroke patients with severe hand weakness were randomly assigned to 2 matched groups and participated in 17.8 ± 1.4 days of training rewarding desynchronization of ipsilesional oscillatory sensorimotor rhythms with contingent online movements of hand and arm orthoses (experimental group, n = 16). In the control group (sham group, n = 16), movements of the orthoses occurred randomly. Both groups received identical behavioral physiotherapy immediately following BMI training or the control intervention. Upper limb motor function scores, electromyography from arm and hand muscles, placebo-expectancy effects, and functional magnetic resonance imaging (fMRI) blood oxygenation level-dependent activity were assessed before and after intervention. Results: A significant group × time interaction in upper limb (combined hand and modified arm) Fugl-Meyer assessment (cFMA) motor scores was found. cFMA scores improved more in the experimental than in the control group, presenting a significant improvement of cFMA scores (3.41 ± 0.563-point difference, p = 0.018) reflecting a clinically meaningful change from no activity to some in paretic muscles. cFMA improvements in the experimental group correlated with changes in fMRI laterality index and with paretic hand electromyography activity. Placebo-expectancy scores were comparable for both groups. Interpretation: The addition of BMI training to behaviorally oriented physiotherapy can be used to induce functional improvements in motor function in chronic stroke patients without residual finger movements and may open a new door in stroke neurorehabilitation.
Article
Full-text available
Describes a model based on the biocybernetical ideas of V. Braitenberg (1977, 1978, 1984), which suggest that threshold regulation of neural activity is the basis of neural processing. It is posited that regulatory circuits exhibit features of deterministic chaos and may contribute to the generation of electrical activity in the cortex. The information about the amount of ongoing cortical activity may be projected via the basal ganglia to the thalamus, in turn projecting back to the apical dendrites. It is concluded that in one mode of brain functioning the EEG reflects brain functioning under the control of the medio-thalamic/frontocortical system. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Article
Full-text available
A method of chronological data storage and reverse computation is described by which bio-electrical phenomena preceding “spontaneous” events within the nervous system can be analysed if these events appear repeatedly and are capable of triggering a computer. Slow brain potentials accompanying voluntary and passive movements of the limbs were analysed by this method. These potentials were recorded from different points of the scalp from 12 healthy subjects in 94 experiments with more than 100 movements in each record. At times artifacts were superimposed upon cerebral potentials. The former were identified, and, as far as was possible, eliminated. Voluntary hand or foot movements are preceded by a slowly increasing surfacenegative cortical potential of 10–15 μV, called readiness potential. This potential is maximal over the contralateral precentral region, but shows bilateral spread and is larger over the frontal than over the occipital areas. The readiness potential increases with intentional engagement and is reduced by mental indifference of the subject. Voluntary movements are followed by a complex potential with an early positive phase that begins 30–90 msec after the onset of movement. The late potentials following voluntary movements are similar to those after passive movements. Both resemble the late bilateral components of the evoked potentials after electrical stimulation of peripheral nerves. Some variable differences between the early components of the potentials after the onset of active and passive movements require further investigation. No relation between the onset of voluntary movements and the phase of the alpha rhythm could be detected.
Article
Full-text available
This third chapter discusses the evidence for the rehabilitation of the most common movement disorders of the upper extremity. The authors also present a framework, building on the computation, anatomy, and physiology (CAP) model, for incorporating some of the principles discussed in the 2 previous chapters by Frey et al and Sathian et al in the practice of rehabilitation and for discussing potentially helpful interventions based on emergent neuroscience principles.
Article
Full-text available
Reductions in blood flow to the brain of sufficient duration and extent lead to stroke, which results in damage to neuronal networks and the impairment of sensation, movement or cognition. Evidence from animal models suggests that a time-limited window of neuroplasticity opens following a stroke, during which the greatest gains in recovery occur. Plasticity mechanisms include activity-dependent rewiring and synapse strengthening. The challenge for improving stroke recovery is to understand how to optimally engage and modify surviving neuronal networks, to provide new response strategies that compensate for tissue lost to injury.
Article
Deecke L: Bereitschaftspotential as an indicator of movement preparation in supple-mentary motor area and motor cortex. In: Porter R, (Chairman): Motor areas of the cerebral cortex. Chichester, Wiley (Ciba Found. Symp. 132), pp 231-250 (1987) Abstract Topographical studies in humans of the Bereitschaftspotential (BP or readiness potential, as averaged from the electroencephalogram) and the Bereitschaftsmagnetfeld (BM, or readiness magnetic field, as averaged from the magnetoencephalogram) revealed a widespread ditribution of Motor preparation over both hemispheres even before unilateral movement ....
Article
Potentials recorded from the scalp of human subjects preceding voluntary finger movements may be devided into 3 components:1. a slowly increasing surface negative readiness potential which starts about 850 msec before movement and is bilaterally symmetrical over the pre- and post-central region with a maximum at the vertex; 2. a pre-motion positivity which is also bilaterally symmetrical and starts about 86 msec before the onset of EMG; 3. a surface negative motor potential which starts about 56 msec before the onset of movement in the EMG and has its maximum over the contralateral precentral hand area.
Article
Stroke often leads to impairment of hand function. Over the following months a variable amount of recovery can be seen. The evidence from animal and human studies suggests that reorganization rather than repair is the key. Surviving neural networks are important for recovery of function and non-invasive techniques such as functional magnetic resonance imaging allow us to study them in humans. For example, initial attempts to move a paretic limb following stroke are associated with widespread activity within the distributed motor system in both cerebral hemispheres, more so in patients with greater impairment. Disruption of activity in premotor areas using transcranial magnetic stimulation prior to movement can impair motor performance in stroke patients but not in controls suggesting that these new patterns of brain activity can support recovered function. In other words, this reorganisation is functionally relevant. More recently, research has been directed at understanding how surviving brain regions influence one another during movement. This opens the way for functional brain imaging to become a clinically useful tool in rehabilitation. Understanding the dynamic process of systems level reorganization will allow greater understanding of the mechanisms of recovery and potentially improve our ability to deliver effective restorative therapy.
Article
Despite intensive efforts to improve outcomes after acquired brain injury, functional recovery is often limited. One reason for this limitation is the challenge in assessing and guiding plasticity after brain injury. In this context, transcranial magnetic stimulation (TMS), a noninvasive tool of brain stimulation, could play a major role. TMS has been shown to be a reliable tool for measuring plastic changes in the motor cortex associated with interventions in the motor system, such as motor training and motor cortex stimulation. In addition, as illustrated by the experience in promoting recovery from stroke, TMS is a promising therapeutic tool to minimize motor, speech, cognitive, and mood deficits. In this review, we will focus on stroke to discuss how TMS can provide insights into the mechanisms of neurologic recovery and how it can be used for measurement and modulation of plasticity after an acquired brain insult.