Preliminary investigation of Brain Network Activation (BNA) and its clinical utility in sport-related concussion

Abstract

Background: The clinical diagnosis and management of patients with sport-related concussion is largely dependent on subjectively reported symptoms, clinical examinations, cognitive, balance, vestibular and oculomotor testing. Consequently, there is an unmet need for objective assessment tools that can identify the injury from a physiological perspective and add an important layer of information to the clinician’s decision-making process. Objective: The goal of the study was to evaluate the clinical utility of the EEG-based tool named Brain Network Activation (BNA) as a longitudinal assessment method of brain function in the management of young athletes with concussion. Methods: Athletes with concussion (n = 86) and age-matched controls (n = 81) were evaluated at four time points with symptom questionnaires and BNA. BNA scores were calculated by comparing functional networks to a previously defined normative reference brain network model to the same cognitive task. Results: Subjects above 16 years of age exhibited a significant decrease in BNA scores immediately following injury, as well as notable changes in functional network activity, relative to the controls. Three representative case studies of the tested population are discussed in detail, to demonstrate the clinical utility of BNA. Conclusion: The data support the utility of BNA to augment clinical examinations, symptoms and additional tests by providing an effective method for evaluating objective electrophysiological changes associated with sport-related concussions.

Theta-Band Functional Connectivity and Single-Trial Cognitive Control in Sports-Related Concussion: Demonstration of Proof-of-Concept for a Potential Biomarker of Concussion

“…Specifically, mTBI participants frequently demonstrate evoked potentials that are delayed and weaker compared to peers (Broglio, Pontifex, O’Connor, & Hillman, 2009; Duncan, Kosmidis, & Mirsky, 2003; Larson, Farrer, & Clayson, 2011). Yet only a few reports have examined group differences in response-locked functional connectivity, for example, during set-shifting (Pang, Dunkley, Doesburg, da Costa, & Taylor, 2016), target detection (Reches et al, 2017), working memory (Bailey et al, 2017; Kumar, Rao, Chandramouli, & Pillai, 2009), and learning tasks (Tsirka et al, 2011).…”

In-clinic event related potentials after sports concussion: A 4-year study

“…ERP's are typically labeled by their polarity (P for positive or N for negative) and their time of occurrence after the stimulus in milliseconds (e.g., P300). Numerous studies have reported ERP-related differences between mTBI and control groups, even as some of these found no differences using neuropsychological measures [19][20][21][22][23][24][25][26][27][28][29].…”

Objective Classification of mTBI Using Machine Learning on a Combination of Frontopolar Electroencephalography Measurements and Self-reported Symptoms

“…According to Haneef et al [21], the acute, subacute, and chronic mTBI stages can be mapped out using qEEG measurements, suggesting that this technique could be used for diagnosis and monitoring recovery. Although analysis for unique EEG components in a mTBI is showing a lot of potential, it still requires the use of a large number of electrodes [22], making rapid measurements problematic.…”