EEG or qEEG as a diagnostic tool for concussions?

A look into the literature

Electroencephalography (EEG) is a visual representation of the electric activity of the brain (Arciniegas, 2011). Conventional EEG involves scalp electrodes that follow a standardized placement method and requires a trained electroencephalographer to interpret the tracings (Arciniegas, 2011). Quantitative electroencephalography (qEEG) applies mathematics to EEG, through software-assisted data analysis (Arciniegas, 2011). This can be useful in deriving measures, conducting data transforms and determining small shifts in the patterns of the electrical activity (Arciniegas, 2011).    

EEG is typically employed in the initial neurocritical care assessment and treatment of moderate to severe traumatic brain injuries but is not as common in the initial assessment for minor traumatic brain injuries (mTBIs) (Arciniegas, 2011). When recorded, changes are often minimal and vary greatly between individuals, due to a number of variables: age, sex, loss of consciousness or not, complications with mTBI, period post-injury when EEG was taken and more (Arciniegas, 2011). Occasionally, generalized or focal slowing and attenuated posterior alpha can be seen within the first few hours following mTBI, with a greater likelihood of EEG abnormalities among individuals who have lost consciousness for more than 2 minutes (Arciniegas, 2011). However, other research has demonstrated that it is more likely attributed to anxiety than head trauma itself (Nuwer et al., 2005). No direct connection has been found between other mTBI clinical symptoms and EEG abnormalities post-concussion (Arciniegas, 2011). Given this and other findings, conventional EEG is not recommended as an assessment tool for mTBI diagnosis (Arciniegas, 2011; Nuwer et al., 2005). Although it is not appropriate for mTBI evaluation, it is considered effective in the assessment of individuals suspected of posttraumatic epilepsy, keeping in mind that an EEG free of abnormalities does not rule out posttraumatic epilepsy (Arciniegas, 2011).    

When using qEEG to examine mTBI and persistent concussive symptoms, frequency analyses and coherence are the most pertinent measures (Arciniegas, 2011). The frequency of the electrical energy created by groups of cortical neurons changes with 1) numbers (typically lowers as neurons are lost, therefore so does amplitude and power) 2) integrity of the thalamocortical circuits which they are part of (injury to the circuits leads to slower frequencies) 3) influence of bottom-up activation from the reticular system (increases in activity of this system result in higher frequencies and vice versa) (Arciniegas, 2011). Coherence examines the correlation of EEG activity between scalp electrodes, therefore it is thought to be a good marker of neural network connectivity and dynamics (Arciniegas, 2011). As seen with conventional EEG, results of qEEG demonstrate considerable variance, yet the most common findings include decreased mean alpha frequency, increased theta activity or increased theta-alpha ratios, decreased differences in alpha and beta power between anterior and posterior cortical areas, decreased alpha power posteriorly and increased coherence and reduced phase between frontal and temporal regions (Arciniegas, 2011).    

A substantial amount of research has been put into developing a qEEG assessment tool for mTBI diagnosis, with particular focus on developing qEEG-based discriminant functions to identify between individuals with and without mTBIs (Arciniegas, 2011). Two main issues have been highlighted by Arciniegas (2011) with discriminant functions: 1) the extent to which it can distinguish mTBI individuals from non-mTBI individuals and 2) the ability to discern qEEG abnormalities relating to mTBI from other neuropsychiatric disorders, such as anxiety or depression. Research has shown that diagnosis using discriminant functions has good accuracy but is not as high as diagnosis established from clinical evaluation, which is perceived as the ‘gold standard’ (Arciniegas, 2011). Additionally, even with high sensitivity scores (greater than 90%), false negatives still occur, meaning that individuals with concussions are getting missed (Arciniegas, 2011). Therefore, qEEG cannot be used solely as a screening tool (Arciniegas, 2011). In regards to the second point, research has demonstrated that the discriminant functions associated with qEEG are unable to distinguish between differential diagnoses and mTBI, therefore advising caution before applying it in a clinical or forensic setting (Arciniegas, 2011). Despite this, qEEG shows considerable promise in the evaluation of mTBI and persistent concussive symptoms, unlike conventional EEG. Many emerging technologies like Brain Scope, an EEG device that detects brain bleeds and examines likelihood of concussion and severity, has been receiving more interest (Brain Gauge, n.d.). It can be expected that this area of study will continue to develop and improve as more research is carried out in regards to the two issues listed above.


Arciniegas, D. B. (2011). Clinical electrophysiologic assessments and mild traumatic brain injury: state-of-the-science and implications for clinical practice. International Journal  of Psychophysiology, 82(1), 41-52. 

BrainScope. (n.d.). Science and Technology. 

Nuwer, M. R., Hovda, D. A., Schrader, L. M., & Vespa, P.M. (2005). Routine and quantitative EEG in mild traumatic brain injury. Clinical Neurophysiology, 116(9), 2001-2025.