Virtual reality, machine learning, and statistical modeling reveal an association between multiple concussion history and impaired perceptual decision-making
Gary B Wilkerson, Mohammad Joghataee, Ashish Gupta, Jose Gerardo Tamez-Peña · 2026
Read Virtual reality, machine learning, and statistical modeling reveal an association between multiple concussion history and impaired perceptual decision-making by Gary B Wilkerson, Mohammad Joghataee, Ashish Gupta, Jose Gerardo Tamez-Peña (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/PMC13592604.txt.
Description
Gary B Wilkerson and three colleagues test whether virtual reality movement measures can expose lasting effects of repeated concussion. Standard clinic checks miss subtle changes in how the brain decides and moves. Their pooled data covered 202 healthy adolescents and young adults who turned their necks, reached, and lunged toward moving visual targets inside a headset. Timing, speed accuracy trade offs, and trial to trial wobble were recorded.
One neck measure, correct responses per second at the decision stage, best separated youths with multiple concussions from those with none or one. It also tracked tightly with response wobble, matching two parts of a classic decision model. Wilkerson and the team suggest the paired measures may flag a lingering deficit after repeated head injury.
Catalog record
| CREATOR | Gary B Wilkerson, Mohammad Joghataee, Ashish Gupta, Jose Gerardo Tamez-Peña |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 34 KB |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |