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. 2016;30(9):1075-81.
doi: 10.3109/02699052.2016.1160152. Epub 2016 May 31.

Stability of an ERP-based measure of brain network activation (BNA) in athletes: A new electrophysiological assessment tool for concussion

James T Eckner  1   2 , Ashley Rettmann  2   3   4 , Naveen Narisetty  5 , Jacob Greer  2 , Brandon Moore  2 , Susan Brimacombe  2 , Xuming He  5 , Steven P Broglio  2   3   4   6
Affiliations

Stability of an ERP-based measure of brain network activation (BNA) in athletes: A new electrophysiological assessment tool for concussion

James T Eckner et al. Brain Inj. 2016.

Abstract

Primary objective: To determine test-re-test reliabilities of novel Evoked Response Potential (ERP)-based Brain Network Activation (BNA) scores in healthy athletes.

Research design: Observational, repeated-measures study.

Methods and design: Forty-two healthy male and female high school and collegiate athletes completed auditory oddball and go/no-go ERP assessments at baseline, 1 week, 6 weeks and 1 year. The BNA algorithm was applied to the ERP data, considering electrode location, frequency band, peak latency and normalized amplitude to generate seven unique BNA scores for each testing session.

Main outcomes and results: Mean BNA scores, intra-class correlation coefficient (ICC) values and reliable change (RC) values were calculated for each of the seven BNA networks. BNA scores ranged from 46.3 ± 34.9 to 69.9 ± 22.8, ICC values ranged from 0.46-0.65 and 95% RC values ranged from 38.3-68.1 across the seven networks.

Conclusions: The wide range of BNA scores observed in this population of healthy athletes suggests that a single BNA score or set of BNA scores from a single after-injury test session may be difficult to interpret in isolation without knowledge of the athlete's own baseline BNA score(s) and/or the results of serial tests performed at additional time points. The stability of each BNA network should be considered when interpreting test-re-test BNA score changes.

Keywords: Athlete; brain network activation; concussion; electroencephalography; event-related potential; reliability.

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Conflict of interest statement

DECLARATION OF INTEREST STATEMENT: This research was funded by ElMindA, LTD. Dr. Eckner’s effort on this project was partially supported by career development awards from the Rehabilitation Medicine Scientist Training Program (5 K12 HD001097) and the National Institutes of Health (1 K23 HD078502).

Dr. Eckner has received research support from ElMindA, LTD. His active research funding includes the National Institutes of Health (1 K23 HD078502), the National Collegiate Athletics Association, the United States Department of Defense (14132004), the University of Michigan Injury Center, and the Foundation for Physical Medicine and Rehabilitation. Ms. Rettmann has received research support from ElMindA, LTD. Mr. Greer has received research support from ElMindA, LTD. Mr. Moore has received research support from ElMindA, LTD. Ms. Brimacombe has received research support from ElMindA, LTD. Dr. He has received research support from ElMindA, LTD. Dr. Broglio has received research support from ElMindA, LTD. His active research funding includes the National Institutes of Health (1R15NS081691-01, 3R15NS081691-01S1), the National Collegiate Athletic Association, the United States Department of Defense (14132004), and the University of Michigan Injury Center. Mr. Narisetty reports no declarations of interest.

Figures

Figure 1
Figure 1
Distribution of BNA scores at each time point for the 7 BNA networks. S1–S4 = Session 1- Session 4. Horizontal lines = median values; Squares = mean values; Boxes = Inter-quartile ranges; Whiskers = 1.5 x inter-quartile ranges; Diamonds = outlier values. * = between session differences compared to S1 (p < 0.05).
Figure 2
Figure 2
Participant-level between-session BNA change scores for each BNA network. Individual participants are represented by vertical lines, and are organized by sex and age group: HM = high school males; HF = high school females; CM = collegiate males; CF = collegiate females; S1–S4 = Session 1- Session 4.
Figure 3
Figure 3
Bland-Altman plots of between-session BNA score differences vs. average BNA scores for all 7 BNA networks. S1-S4 = Session 1- Session 4.
Figure 4
Figure 4
Absolute change in BNA scores between session 1 and each subsequent session vs. average data quality score.
Figure 5
Figure 5
Sample averaged ERP waveform associated for the frequent stimulus of the auditory oddball task illustrating the P100 and N200 peaks from which the OB-F2 biomarker is derived (top). Pictorial illustration of the OB-F2 biomarker demonstrating its central theta predominance (bottom).
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