Cargando…
EEG-Based Neurocognitive Metrics May Predict Simulated and On-Road Driving Performance in Older Drivers
The number of older drivers is steadily increasing, and advancing age is associated with a high rate of automobile crashes and fatalities. This can be attributed to a combination of factors including decline in sensory, motor, and cognitive functions due to natural aging or neurodegenerative disease...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6341028/ https://www.ncbi.nlm.nih.gov/pubmed/30697156 http://dx.doi.org/10.3389/fnhum.2018.00532 |
_version_ | 1783388878002978816 |
---|---|
author | Rupp, Greg Berka, Chris Meghdadi, Amir H. Karić, Marija Stevanović Casillas, Marc Smith, Stephanie Rosenthal, Theodore McShea, Kevin Sones, Emily Marcotte, Thomas D. |
author_facet | Rupp, Greg Berka, Chris Meghdadi, Amir H. Karić, Marija Stevanović Casillas, Marc Smith, Stephanie Rosenthal, Theodore McShea, Kevin Sones, Emily Marcotte, Thomas D. |
author_sort | Rupp, Greg |
collection | PubMed |
description | The number of older drivers is steadily increasing, and advancing age is associated with a high rate of automobile crashes and fatalities. This can be attributed to a combination of factors including decline in sensory, motor, and cognitive functions due to natural aging or neurodegenerative diseases such as HIV-Associated Neurocognitive Disorder (HAND). Current clinical assessment methods only modestly predict impaired driving. Thus, there is a need for inexpensive and scalable tools to predict on-road driving performance. In this study EEG was acquired from 39 HIV+ patients and 63 healthy participants (HP) during: 3-Choice-Vigilance Task (3CVT), a 30-min driving simulator session, and a 12-mile on-road driving evaluation. Based on driving performance, a designation of Good/Poor (simulator) and Safe/Unsafe (on-road drive) was assigned to each participant. Event-related potentials (ERPs) obtained during 3CVT showed increased amplitude of the P200 component was associated with bad driving performance both during the on-road and simulated drive. This P200 effect was consistent across the HP and HIV+ groups, particularly over the left frontal-central region. Decreased amplitude of the late positive potential (LPP) during 3CVT, particularly over the left frontal regions, was associated with bad driving performance in the simulator. These EEG ERP metrics were shown to be associated with driving performance across participants independent of HIV status. During the on-road evaluation, Unsafe drivers exhibited higher EEG alpha power compared to Safe drivers. The results of this study are 2-fold. First, they demonstrate that high-quality EEG can be inexpensively and easily acquired during simulated and on-road driving assessments. Secondly, EEG metrics acquired during a sustained attention task (3CVT) are associated with driving performance, and these metrics could potentially be used to assess whether an individual has the cognitive skills necessary for safe driving. |
format | Online Article Text |
id | pubmed-6341028 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-63410282019-01-29 EEG-Based Neurocognitive Metrics May Predict Simulated and On-Road Driving Performance in Older Drivers Rupp, Greg Berka, Chris Meghdadi, Amir H. Karić, Marija Stevanović Casillas, Marc Smith, Stephanie Rosenthal, Theodore McShea, Kevin Sones, Emily Marcotte, Thomas D. Front Hum Neurosci Neuroscience The number of older drivers is steadily increasing, and advancing age is associated with a high rate of automobile crashes and fatalities. This can be attributed to a combination of factors including decline in sensory, motor, and cognitive functions due to natural aging or neurodegenerative diseases such as HIV-Associated Neurocognitive Disorder (HAND). Current clinical assessment methods only modestly predict impaired driving. Thus, there is a need for inexpensive and scalable tools to predict on-road driving performance. In this study EEG was acquired from 39 HIV+ patients and 63 healthy participants (HP) during: 3-Choice-Vigilance Task (3CVT), a 30-min driving simulator session, and a 12-mile on-road driving evaluation. Based on driving performance, a designation of Good/Poor (simulator) and Safe/Unsafe (on-road drive) was assigned to each participant. Event-related potentials (ERPs) obtained during 3CVT showed increased amplitude of the P200 component was associated with bad driving performance both during the on-road and simulated drive. This P200 effect was consistent across the HP and HIV+ groups, particularly over the left frontal-central region. Decreased amplitude of the late positive potential (LPP) during 3CVT, particularly over the left frontal regions, was associated with bad driving performance in the simulator. These EEG ERP metrics were shown to be associated with driving performance across participants independent of HIV status. During the on-road evaluation, Unsafe drivers exhibited higher EEG alpha power compared to Safe drivers. The results of this study are 2-fold. First, they demonstrate that high-quality EEG can be inexpensively and easily acquired during simulated and on-road driving assessments. Secondly, EEG metrics acquired during a sustained attention task (3CVT) are associated with driving performance, and these metrics could potentially be used to assess whether an individual has the cognitive skills necessary for safe driving. Frontiers Media S.A. 2019-01-15 /pmc/articles/PMC6341028/ /pubmed/30697156 http://dx.doi.org/10.3389/fnhum.2018.00532 Text en Copyright © 2019 Rupp, Berka, Meghdadi, Karić, Casillas, Smith, Rosenthal, McShea, Sones and Marcotte. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Rupp, Greg Berka, Chris Meghdadi, Amir H. Karić, Marija Stevanović Casillas, Marc Smith, Stephanie Rosenthal, Theodore McShea, Kevin Sones, Emily Marcotte, Thomas D. EEG-Based Neurocognitive Metrics May Predict Simulated and On-Road Driving Performance in Older Drivers |
title | EEG-Based Neurocognitive Metrics May Predict Simulated and On-Road Driving Performance in Older Drivers |
title_full | EEG-Based Neurocognitive Metrics May Predict Simulated and On-Road Driving Performance in Older Drivers |
title_fullStr | EEG-Based Neurocognitive Metrics May Predict Simulated and On-Road Driving Performance in Older Drivers |
title_full_unstemmed | EEG-Based Neurocognitive Metrics May Predict Simulated and On-Road Driving Performance in Older Drivers |
title_short | EEG-Based Neurocognitive Metrics May Predict Simulated and On-Road Driving Performance in Older Drivers |
title_sort | eeg-based neurocognitive metrics may predict simulated and on-road driving performance in older drivers |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6341028/ https://www.ncbi.nlm.nih.gov/pubmed/30697156 http://dx.doi.org/10.3389/fnhum.2018.00532 |
work_keys_str_mv | AT ruppgreg eegbasedneurocognitivemetricsmaypredictsimulatedandonroaddrivingperformanceinolderdrivers AT berkachris eegbasedneurocognitivemetricsmaypredictsimulatedandonroaddrivingperformanceinolderdrivers AT meghdadiamirh eegbasedneurocognitivemetricsmaypredictsimulatedandonroaddrivingperformanceinolderdrivers AT karicmarijastevanovic eegbasedneurocognitivemetricsmaypredictsimulatedandonroaddrivingperformanceinolderdrivers AT casillasmarc eegbasedneurocognitivemetricsmaypredictsimulatedandonroaddrivingperformanceinolderdrivers AT smithstephanie eegbasedneurocognitivemetricsmaypredictsimulatedandonroaddrivingperformanceinolderdrivers AT rosenthaltheodore eegbasedneurocognitivemetricsmaypredictsimulatedandonroaddrivingperformanceinolderdrivers AT mcsheakevin eegbasedneurocognitivemetricsmaypredictsimulatedandonroaddrivingperformanceinolderdrivers AT sonesemily eegbasedneurocognitivemetricsmaypredictsimulatedandonroaddrivingperformanceinolderdrivers AT marcottethomasd eegbasedneurocognitivemetricsmaypredictsimulatedandonroaddrivingperformanceinolderdrivers |