Subjects
Six healthy adult subjects (5 males, 1 female) were recruited from staff and students at the Prince of Wales Hospital, the University of Western Sydney and the University of Melbourne. All were right handed (self-report). All subjects gave written informed consent, and the study was approved by the local ethics committee (South Eastern Sydney Local Health District Human Research Ethics Committee). All procedures were carried out in accordance with the Declaration of Helsinki.
EEG/ECeG Recording
EEG was recorded using a 104 (96 cap + 8 external, EasyCap GmbH) channel custom 10% cerebellar extension montage designed by completing the population of the Iz circle, and then two additional 10% rows below, as described in Heine et al. (2020). ActiveTwo amplifiers (BioSemi, Holland) were used. 102 of the 104 channels were from cephalic electrode sites, including a pair of electrodes were placed infra-ocularly (IO), with the last pair on the sternocleidomastoid (SCM) muscle. The sampling rate was 4096 Hz.
EMG Recording and triggering
For recording finger extension EMG, bipolar electrode pairs (Cleartrace 1700-030, Conmed Corp., USA) were located to the extensor indices (EI) and flexor digitorum muscles from the left and right hands. For foot dorsiflexion EMG bipolar electrode pairs were located over the tibialis anterior (TA) and soleus (SOL) muscles of the left and right legs. EMG signals were amplified (x1000, Medelec AA6, Mark III), band-pass filtered (2 Hz − 1.6 kHz), sampled at 10 kHz using a Power1401 and Signal software (6.1, CED Electronics, UK). Rectified EMG signals from the target muscles (EI, for finger extension, TA for foot dorsiflexion) were thresholded and debounced for the production of a trigger to signal movement onset. The Power1401 digital output in turn sent a 1 ms pulse to the BioSemi trigger box to indicate movement onset.
Movement task, accelerometry and foot displacement measurement
For each subject, recordings were made under five conditions. Initially, subjects were required to sit at rest for 5 minutes with eyes in a fixed neutral position ahead. In four subsequent recording sessions, subjects, after suitable training to minimise EMG/EOG artefact, were required to extend in turn the right or left index fingers, followed by right and left foot dorsiflexion. Additional training with feedback was given to ensure a sufficiently brisk movement at the required rate, about once every 5 seconds, which would reliably produce a trigger. This training session also allowed the adjustment of the threshold to an appropriate level. For each task a unilateral accelerometer (model 3026-200-S, ICSensors, USA) was used to record finger and foot acceleration, amplified (x1000, custom bridge amplifier) and sampled at 10 kHz using the CED Power1401. The accelerometer was secured on the distal phalanx during right and left index finger extension and on the dorsum of the foot during dorsiflexion. For foot dorsiflexion, angular displacement was also recorded by means of a custom adapted sewing machine foot controller (model ES01FC, Shanrya). Subjects were asked to keep their gaze forward throughout. Up to 100 trials were recorded for each condition. Subjects were given a break at 50 trials.
EEG/ECeG screening and averaging.
Using Brain Electrical Source Analysis (BESA (version 7.1, MEGIS Software GmbH, Germany), EEG/ECeG recordings were initially screened for blinks, eye movement and ECG artifacts. For most small eye blink/movement artefacts, the BESA artefact removal algorithm was employed along with the ECG artefact removal algorithm after modelling the ECG by a single dipole in the neck, with the left and right SCM channels used to detect ECG. The EEG/ECeG was then epoched to − 2000 ms to + 2000 ms around the EMG trigger and the baseline correction set to − 2000 ms to − 1500 ms. A high-pass filter of 0.2 Hz was applied with forward phase at 6 dB/octave roll-off. After the individual mean MRPs were produced for each of the subjects, a small number of channels that were noisy due to residual artefact were interpolated.
Spectral Power and Coherence
After recording EMG/EEG/ECeG and epoching, we performed spectral power analyses on all channels over the 4 s epoch using the continuous wavelet transform (CWT) as implemented in the MATLAB toolbox (R2019b, Mathworks, Natick, CA). To eliminate the effects of mains contamination, a narrow band-stop filter at 50 Hz and all harmonics to 650 Hz was applied prior to performance of the CWT. In the present analysis a Morlet wavelet was employed at a density of 24 voices per octave over 9 octaves. The CWTs were further transformed to scaleograms (time-frequency images) from the absolute value of the CWT and rescaled to be in dB per Hz re 1 µV2. Scaleograms were computed for all trials, then further split into eight frequency bands; delta (δ: 1.5 Hz – 3 Hz), theta (θ: 3–6 Hz), alpha (α: 6–12 Hz), beta (β: 13–30 Hz), gamma (γ: 30–80 Hz), ultra-gamma (u-γ: 80–160 Hz), very high frequency (VHF: 160–320 Hz) and ultra-high frequency (UHF: 320–640 kHz). These were then further segmented into 16 equal time segments to allow for ANOVA testing of movement related changes. Wavelet coherence was also computed using the same MATLAB toolbox. Coherograms were computed for all trials, then further split into the same eight frequency bands and segmented for statistical analysis.
Statistical analysis
Statistical analyses of the segmented power and coherence was conducted by means of repeated measures analysis of variance (ANOVA) based on a 7 (“X”, lateral) by 3 (“Y”, anteroposterior) grid centred on either Cz (“cerebral”) or SIz (“cerebellar”). For power (Table 1) and midline coherence (Table 2) within-subjects factors were LIMB (Foot vs Hand), SIDE (Left vs Right), “X” (1 to 7), “Y” (1 to 3) and SEGMENT (1 to16). Due to temporalis muscle EMG in some subjects, the X-factor for the Cz power was reduced to five levels to exclude T7 and T8 electrodes for the high-frequency (gamma and above) bands. For lateralised coherence within-subjects factors were SEED (C1/C2 or PO11/12), SIDE (Left vs Right), “X” (1 to 7), “Y” (1 to 3) and SEGMENT (1 to16).
Table 1
ANOVA of power for SIz versus Cz grids
SIz GRID
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Band
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δ
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θ
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α
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β
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γ
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u-γ
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VHF
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UHF
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Factor
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LIMB
|
|
|
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|
|
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SIDE
|
|
|
|
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< .05
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< .05
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= .05
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|
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X
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|
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< .1
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< .1
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|
|
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Y
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< .005
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< .001
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< .05
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< .05
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|
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SEGMENT
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< .001
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< .1
|
< .1
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< .05
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|
|
|
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X*Y
|
|
|
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< .05
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< .1
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= .1
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< .05
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|
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SI*SEG
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< .1
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|
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|
|
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LI*SEG
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< .1
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Cz GRID
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Band
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δ
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θ
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α
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β
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γ
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u-γ
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VHF
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UHF
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Factor
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|
|
|
|
|
|
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LIMB
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= .1
|
= .1
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|
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SIDE
|
|
|
|
|
|
|
|
|
|
X
|
|
= .001
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< .001
|
< .001
|
|
= .1
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< .05
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< .1
|
|
Y
|
|
|
|
< .1
|
|
|
|
|
|
SEGMENT
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< .005
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< .05
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< .05
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< .005
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< .05
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|
|
|
SI*SEG
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|
< .05
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|
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< .1
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|
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X*SEG
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< .05
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< .005
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Y*SEG
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< .05
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|
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Table 2
ANOVA of midline coherence for SIz versus Cz seeds
SIz seed
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Band
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δ
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θ
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α
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β
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γ
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u-γ
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VHF
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UHF
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Factor
|
|
|
|
|
|
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LIMB
|
|
|
|
|
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|
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< .1
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SIDE
|
|
|
|
|
|
|
|
|
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X
|
|
= .001
|
= .001
|
= .001
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< .001
|
< .05
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|
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Y
|
|
< .005
|
< .01
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|
|
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< .05
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< .05
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SEGMENT
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< .05
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|
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X*Y
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< .1
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< .005
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< .1
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|
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SI*SEG
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LI*SEG
|
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< .05
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|
Cz seed
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Band
|
δ
|
θ
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α
|
β
|
γ
|
u-γ
|
VHF
|
UHF
|
Factor
|
|
|
|
|
|
|
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|
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LIMB
|
|
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< .05
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|
|
|
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SIDE
|
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|
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|
|
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X
|
|
|
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< .1
|
|
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< .1
|
|
|
Y
|
|
< .005
|
< .01
|
< .05
|
= .005
|
< .01
|
< .1
|
|
|
SEGMENT
|
|
< .05
|
|
|
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< .1
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SI*SEG
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< .1
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