Background: Reactive balance recovery evokes a negative peak of cortical electroencephalography (EEG) activity (N1) that is simultaneous to brainstem-mediated automatic balance-correcting muscle activity. This study follows up on an observation from a previous study, in which N1 responses were larger in individuals who seemed to have greater difficulty responding to support-surface perturbations. Research Question: We hypothesized that people engage more cortical activity when balance recovery is more challenging. We predicted that people with lower balance ability would exhibit larger cortical N1 responses during balance perturbations. Methods: In 20 healthy young adults (11 female, ages 19-38) we measured the amplitude of the cortical N1 response evoked by 48 backward translational support-surface perturbations of unpredictable timing and amplitude. Perturbations included a Small (8 cm) perturbation that was identical across participants, as well as Medium (13-15 cm) and Large (18-22 cm) perturbations scaled to participant height to control for height-related differences in perturbation difficulty. To assess individual differences in balance ability, we measured the distance traversed on a narrow (0.5-inch wide) 12-foot beam across 6 trials. We tested whether the cortical N1 response amplitude was correlated to balance ability across participants. Results: Cortical N1 amplitudes in response to standing balance perturbations (54±18 μV) were inversely correlated to the distance traveled in the difficult beam-walking task (R²=0.20, p=0.029). Further, there was a significant interaction between performance on the beam-walking task and the effect of perturbation magnitude on the cortical N1 response amplitude, whereby individuals who performed worse on the beam-walking task had greater increases in N1 amplitudes with increases in perturbation magnitude. Significance: Cortical N1 response amplitudes may reflect greater cortical involvement in balance recovery when challenged. This increased cortical involvement may reflect cognitive processes such as greater perceived threat or attention to balance, which have the potential to influence subsequent motor control.

Note: This data set has also been appended to include additional data from the same data collection in the same participant cohort associated with the manuscript "Cortical beta oscillatory activity evoked during reactive balance recovery scales with perturbation difficulty and individual balance ability" submitted to NeuroImage

Participants. We recruited 20 young adults (11 female, ages 19-38) for a research study approved by Emory University’s Institutional Review Board. All participants reported no significant history of neurological or musculoskeletal disorders. Participants signed written informed consent before participation. Participants were 26 years old (SD 5), 168 cm tall (SD 8, range 156-185 cm), and 70 kg (SD 14).

Perturbations. Participants were given 48 backward translational support-surface perturbations of unpredictable timing and amplitude while barefoot (Figure 1A). Perturbations were delivered using a custom perturbation platform (Factory Automation Systems, Atlanta, GA). Perturbations were evenly divided between Small, Medium, and Large magnitudes to vary difficulty and maintain unpredictability of magnitude. The Small perturbation (7.7 cm, 16.0 cm/s, 0.23 g) was identical across participants. To control for height-related differences in perturbation difficulty, the Medium (12.6-15.0 cm, 26.6-31.5 cm/s, 0.38-0.45 g) and Large (18.4-21.9 cm, 38.7-42.3 cm/s, 0.54-0.64 g) perturbations were linearly scaled down from an upper bound (Medium: 15.8 cm, 34.1 cm/s, 0.49 g; Large: 23.7 cm, 45.8 cm/s, 0.69 g) by multiplying by the participant’s height divided by 200 cm. The timing and duration of acceleration, velocity, and displacements were identical across perturbation magnitudes for the first 500 ms of perturbation (Figure 2). Participants were asked to execute a stepping response on half of perturbations and to resist stepping on the other half. Stepping and non-stepping responses are combined for analyses, except where explicitly stated for kinematic comparisons.

Electroencephalography (EEG) collection. EEG data were collected during the perturbation series, and recording equipment was removed before the beam-walking task. Thirty-two active EEG electrodes (ActiCAP, Brain Products, Germany) were placed on the scalp according to the international 10-20 system. Electrodes TP9 and TP10 were removed from standard locations and placed on the skin over the mastoid bones behind the ears for offline re-referencing. After the wired electrode cap was placed on the participant, the active electrode sites were prepared with conductive electrode gel (SuperVisc 100 gr. HighViscosity Electrolyte-Gel for active electrodes, Brain Products) using a blunt-tipped needle, which was simultaneously used to rub the scalp to improve electrode impedance. Mastoid sites were additionally scrubbed with an alcohol swab prior to placement. Impedances below 10 kOhm were obtained for Cz and mastoid electrodes before the start of data collection.

To enable subtraction of eye movement and blink artifacts, electrooculography (EOG) data were collected with bipolar passive electrodes (E220x, Brain Products) vertically bisecting the right pupil with a reference electrode on the forehead. Before electrode placement, the skin was scrubbed with an alcohol swab, and electrodes were prepared with high-chloride abrasive gel (ABRALYT HiCl 250 gr., High-chloride-10% abrasive electrolyte gel, Brain Products). EEG and EOG data were amplified on an ActiCHamp amplifier (Brain Products) sampling at 1000 Hz, with a 24-bit A/D converter and an online 20 kHz anti-aliasing low-pass filter.

EEG data preprocessing. Raw EEG data were high-pass filtered offline at 1 Hz with a third-order zero-lag Butterworth filter, mean-subtracted within channels, and then low-pass filtered at 25 Hz. Cz data were re-referenced to mastoids and epoched into 2.4 s segments beginning 400 ms before perturbation onset. Vertical EOG data were similarly filtered and segmented without re-referencing. Blinks and vertical eye movement artifacts were subtracted from the epoched data at Cz using the algorithm developed by Gratton and Coles, as described in Payne et al.. Single-trial epochs of Cz data were then baseline-corrected by subtracting the mean between 50-150 ms prior to perturbation onset.

EEG quantification. Epoched cortical responses were averaged within each participant across trials, both within and across perturbation magnitudes. Cortical N1 peak response amplitudes (μV) and latencies (ms) were then measured between 100-200 ms after perturbation onset in the averaged cortical responses.

Center of mass (CoM) position and trunk angle. A 10-camera Vicon Nexus 2 motion capture system recorded body motion at 100 Hz during perturbations. Participants wore a reflective 25-marker set that enabled Vicon’s Plug-in Gait model to calculate positions and masses of the following body segments: head-arms-trunk, and bilateral thigh and shank-foot. CoM position was then calculated as a weighted sum of body segment positions and masses. CoM positions were baseline subtracted (-50 to 150 ms baseline) to obtain CoM displacements. Trunk angles relative to the vertical were calculated using a vector from the average position of hip markers to the average position of shoulder markers. One participant was excluded from CoM position and trunk angle calculations due to a missing marker that prevented calculation of one of the body segments (N=19).

            Quantification of CoM displacement. CoM displacement along the axis of platform motion was averaged across non-stepping responses to Small perturbations and quantified as peak amplitude between 1-2 s after perturbation for each participant.

            Quantification of trunk angle. Trunk angles were averaged across non-stepping responses to Large perturbations and quantified as the peak between 0.5-1 s after perturbation.

Beam-walking task. Balance ability was assessed after completion of the perturbation series. Participants were given 6 attempts to walk across a narrow beam (12 feet long, 0.5 inch wide, 1 inch high) while wearing standardized shoes and keeping their arms crossed (Figure 1B). Participants were not given instructions regarding speed or step length. Each trial ended when the participant (1) reached the end of the beam, (2) stepped off the beam, or (3) uncrossed their arms. Distance traversed was measured as the parallel distance from the start of the beam to the back of the heel on the forward foot when the trial ended. Balance ability is reported as the normalized distance traveled, with a maximum possible score of 1 if the end of the beam was reached on all 6 trials.

This is a matlab dataset. Matrix "Cz" contains the filtered single trial data from all subjects. Each row corresponds to a different trial. The "Flags" matrix has the same number of rows and contains the information relevant to each trial. The labels describing the columns of the "Flags" matrix are in the variable "FlagNames." Specifically, column 1 of "Flags" indicates the subject number for each trial, column 2 has the value 0 for trials in which subjects were asked not to step and the value 1 for trials in which subjects were asked to step, column 3 contains the value 270 for all trials (describing the backward motion of the moving platform), column 4 has values 1, 2, or 3, corresponding to the different perturbation magnitudes, column 5 contains the value 1 on trials in which a step was taken, based on vertical forces on either force plate going below 5N within 1000ms of the onset of platform motion. The "time_erps" vector contains the time (in seconds) relative to the onset of platform motion for all trials. The vector "Y" is from an accelerometer placed on the platform and connected to the EEG recording system to identify the timing of platform motion, but the units are meaningless. Acceleration traces reported in the paper were collected separately, directly from the moving platform. Other subject measures mentioned in the paper are included in the matrix "Subject_data" with corresponding labels in "Subject_data_names".

Additional data for the submission to NeuroImage include an additional column to the Flags matrix labeling steps within 2000ms of platform onset, and variables beta (single trial beta traces), MG and TA (single trial emg data), and their associated time vectors time_beta and time_emg.