Logo image
fNIRS differentiates cognitive workload between concussed adolescents and healthy controls
Abstract   Open access

fNIRS differentiates cognitive workload between concussed adolescents and healthy controls

Hasan Ayaz, Kristy Arbogast, Fairuz Mohammed, Ronni Kessler, Lei Wang, Eileen Storey, Olivia Podolak, Matthew Grady, Andrew Mayer, Catherine McDonald, …
Frontiers in human neuroscience, v 12
2018
url
https://doi.org/10.3389/conf.fnhum.2018.227.00068View
Published, Version of Record (VoR) Open CC BY V4.0

Abstract

Concussion remains a clinical diagnosis based on subjective and non-specific symptoms with additional supporting assessments, such as neurocognitive testing and, more recently, physical examination findings. However, there are no sensitive or specific biomarkers for establishing the diagnosis of concussion. Recent FDA-approval of a blood biomarker that correlates with blood on head computed tomography (CT) in the setting of head injury is a step forward, but since most concussions are not associated with positive head CT scans with blood, there remains a critical gap in the objective diagnosis of concussion. Neuroimaging, particularly fMRI, has been considered as a potential diagnostic modality for concussion, but results have been conflicting, as specific findings associated with injury appear to depend on the severity of injury, timing post-injury and potentially the age of the individual. Functional near infrared spectroscopy (fNIRS) is a potential diagnostic modality due to its portability and ease of use in natural environments, which enable the assessment of cognitive workload as a function of cerebral oxygenation change while performing tasks in the clinical setting (Ayaz et al 2013). We hypothesize that fNIRS is able to distinguish concussed subjects from healthy controls utilizing a standardized assessment, the King-Devick test (Galetta et al 2011), a rapid number-naming reading task.

Metrics

2 Record Views

Details

Logo image