Improved Mild Closed Head Traumatic Brain Injury Outcomes With a Brain-Computer Interface Amplified Cognitive Remediation Training
| Autor: | Dallas C Hack, Jason H. Huang, Peter Mikulecky, Curtis T Cripe, Rebecca Cooper |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
executive cognitive control
medicine.medical_specialty Traumatic brain injury 030204 cardiovascular system & hematology brain computer interface 03 medical and health sciences 0302 clinical medicine Physical medicine and rehabilitation Chart review medicine Psychology Depression (differential diagnoses) Brain–computer interface cognitive remediation training Artificial neural network business.industry traumatic brain injury General Engineering Cognition quantitative electroencephalography Quantitative electroencephalography medicine.disease mtbi Neurology Cognitive remediation therapy qeeg bci Radiology business 030217 neurology & neurosurgery |
| Zdroj: | Cureus |
| ISSN: | 2168-8184 |
| DOI: | 10.7759/cureus.14996 |
| Popis: | This study is a retrospective chart review of 200 clients who participated in a non-verbal restorative cognitive remediation training (rCRT) program between 2012 and 2020. Each client participated in the program for about 16 weeks, and the study as a whole occurred over a five-year period. The program was applied to effect proper neural functional remodeling needed to support resilient, flexible, and adaptable behaviors after encountering a mild closed head traumatic brain injury (mTBI). The rCRT program focused on improving functional performance in executive cognitive control networks as defined by fMRI studies. All rCRT activities were delivered in a semi-game-like manner, incorporating a brain-computer interface (BCI) that provided in-the-moment neural network performance integrity metrics (nPIMs) used to adjust the level of play required to properly engage long-term potentiation (LTP) and long-term depression (LTD) network learning rules. This study reports on t-test and Reliable Change Index (RCI) changes found within individual cognitive abilities’ performance metrics derived from the Woodcock-Johnson Cognitive Abilities III Test. We compared pre- and post-scores from seven cognitive abilities considered dependent on executive cognitive control networks against seven non-executive control abilities. We observed significant improvements (p < 10-4) with large Cohen’s deffect sizes (0.78-1.20) across 13 of 14 cognitive ability domains with a medium effect size (0.49) on the remaining one. The mean percent change for the pooled trained domain was double that observed for the pooled untrained domain, at 17.2% versus 8.3%, respectively. To further adjust for practice effects, practice effect RCI values were computed and further supported the effectiveness of the rCRT (trained RCI 1.4-4.8; untrained RCI 0.08-0.75). |
| Databáze: | OpenAIRE |
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