Electrocortical dynamics differentiate athletes exhibiting low- and high- ACL injury risk biomechanics

Abstract

Anterior cruciate ligament (ACL) injuries are physically and emotionally debilitating for athletes,while motor and biomechanical deficits that contribute to ACL injury have been identified, limited knowledge about the relationship between the central nervous system (CNS) and biomechanical patterns of motion has impeded approaches to optimize ACL injury risk reduction strategies. In the current study it was hypothesized that high-risk athletes would exhibit altered temporal dynamics in their resting state electrocortical activity when compared to low-risk athletes. Thirty-eight female athletes performed a drop vertical jump (DVJ) to assess their biomechanical risk factors related to an ACL injury. The athletes' electrocortical activity was also recorded during resting state in the same visit as the DVJ assessment. Athletes were divided into low- and high-risk groups based on their performance of the DVJ. Recurrence quantification analysis was used to quantify the temporal dynamics of two frequency bands previously shown to relate to sensorimotor and attentional control. Results revealed that high-risk participants showed more deterministic electrocortical behavior than the low-risk group in the frontal theta and central/parietal alpha-2 frequency bands. The more deterministic resting state electrocortical dynamics for the high-risk group may reflect maladaptive neural behavior-excessively stable deterministic patterning that makes transitioning among functional task-specific networks more difficult-related to attentional control and sensorimotor processing neural regions.

Keywords: anterior cruciate ligament; drop vertical jump; electrocortical dynamics; electroencephalogram; recurrence quantification analysis.

Conflict of interest statement

CONFLICT OF INTEREST

The authors report no conflicts of interest.

© 2020 Society for Psychophysiological Research.

Figures

FIGURE 1

The DVJ is shown in the left of the figure. The peak knee abduction moment is calculated at the position of the black stick figure. Based on that value, the participants were assigned to their respective groups using the cutoffs displayed in the middle panel. Finally, the electrode positions are displayed on the right side of the figure. The light gray circles indicate the locations of the frontal theta frequency band electrodes. In order from left to right they are F3, FZ, and F4. The black circles indicate the locations of the parietal, central, and occipital alpha-2 frequency band electrodes. Starting from the top-left midline electrode they are C3, P3, O1, O2, P4, and C4 in counterclockwise order

FIGURE 2

Displayed above is the analysis process. First, in plot (a), 2 s of example raw and unfiltered EEG data from the Fz electrode is presented. The data were then filtered to retain only the theta frequency band (displayed in plot b) and the alpha-2 frequency band (displayed in plot c). Both plots (b) and (c) originated from the data presented in plot (a) and display the same 2 s of data (i.e., 500 samples). The last step, after downsampling, was to create the recurrence plots for each of the electrodes' two specific frequency-band time series. The recurrence plot displayed in (d) is of the theta frequency band and the approximately 120 data points equates to roughly two seconds of EEG data. In order to highlight the structure of the plots, only two seconds of the whole recurrence plots are shown because the whole plots are too large to easily observe the intricate structure within. The same procedure is displayed in plot (e), but with the alpha-2 frequency band data