Purpose of review: To review emerging vision-based assessments in the evaluation of concussion.
Recent findings: Involvement of the visual pathways is common following concussion, the mildest form of traumatic brain injury. The visual system contains widely distributed networks that are prone to neurophysiologic changes after a concussion, resulting in visual symptoms and ocular motor dysfunction. Vision-based testing is increasingly used to improve detection and assess head injury. Several rapid automatized naming (RAN) tasks, such as the King-Devick test and the Mobile Universal Lexicon Evaluation System, show capacity to identify athletes with concussion. Video-oculography (VOG) has gained widespread use in eye-tracking and gaze-tracking studies of head trauma from which objective data have shown increased saccadic latencies, saccadic dysmetria, errors in predictive target tracking, and changes in vergence in concussed individuals.
Summary: RAN tasks demonstrate promise as rapid screening tools for concussion. Further investigation will involve assessment of the role for age, characterization of learning effects over repeated measurements, and identification of optimal thresholds for clinically significant performance decrements. Various RAN tasks are likely to be functionally distinct, engaging different neural networks according to the demands of each task. Measures of saccades, smooth pursuit eye-movements, the vestibulo-ocular reflex and, more recently, disparity vergence are candidate vision-based markers for concussion. Work to adopt these assessments to the sideline or clinical environments is ongoing.