Conversation effects on neural mechanisms underlying reaction time to visual events while viewing a driving scene: fMRI analysis and asynchrony model

Hsieh, Li; Young, Richard A.; Bowyer, Susan M.; Moran, John; Genik, Richard J.; Green, Christopher C.; Chiang, Yow Ren; Yu, Ya Ju; Liao, Chia Cheng; Seaman, Sean

doi:10.1016/j.brainres.2008.10.002

Cited by 53 publications

(57 citation statements)

References 54 publications

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“…The slight increases in foot RT for conversation vs. baseline are consistent with studies previously conducted in lab or on road alone using similar event detection methods (e.g., Schreiner et al, 2004;Bowyer et al, 2007Bowyer et al, , 2008Bowyer et al, , 2009Hsieh et al, 2009). Our similar pattern of RT effects for covert and overt speech is consistent with lab studies during MEG brain imaging (Bowyer et al, 2008).…”

Section: Discussionsupporting

confidence: 88%

Validation of the Static Load Test for Event Detection During Hands-Free Conversation

Young

Angell

Sullivan

et al. 2009

Proceedings of the 5th International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design : Dr

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Summary:Objective. To see if visual event reaction times (RTs) during handsfree conversation conditions in the Enhanced Static Load Test (ESLT) can predict RTs in similar conditions in on-road driving. Methods. Brake reaction times to random center and side light events were measured while watching a driving video, attempting to keep a marker in the center of the lane with a steering wheel, answering the phone by pressing a button, and carrying on neutral or angry handsfree conversations in covert (silent) or overt mode on a hands-free phone device. Open-road tests were conducted in traffic for subjects with similar side and front light events, with foot reaction times measured while engaged in the same secondary tasks and conditions. Results. Mean RTs for the task segments in the lab were predictive of the mean RTs for the corresponding task segments in the on-road test (r = 0.90, df = 16, p < 0.000001). Conclusion. This study validates the Enhanced Static Load Test as predictive of visual event RTs during open-road driving for the range of experimental conditions and tasks considered.

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Section: Discussionsupporting

confidence: 88%

Validation of the Static Load Test for Event Detection During Hands-Free Conversation

Young

Angell

Sullivan

et al. 2009

Proceedings of the 5th International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design : Dr

Self Cite

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“…The increase in RT to stimulus after driving task should be associated with driving mental fatigue, which is evident by subjective self-report measures. Some researchers proposed an Asynchrony Model in which the extent of neural asynchrony is proportional to the conditioned foot reaction time to visual events while in a driving-like scenario by MEG and fMRI studies [35][36]. Whether the longer RT to oddball task in our study can be explained by the Asynchrony Model still demands a further verifying study.…”

Section: Discussionmentioning

confidence: 61%

“…Some brain regions are of particular importance in maintaining the primary driving performance of event detection during a secondary conversation task. Several researchers have confirmed this conclusion by using both fMRI and MEG methods [35][36]. Maybe it is a good explanation for the EEG rhythm changes on different scalp regions.…”

Section: Discussionmentioning

confidence: 76%

Physiological Assessment of Driving Mental Fatigue Using Wavelet Packet Energy and Random Forests

Zhao¹,

Zheng²,

Zhao³

et al. 2010

Am. J. Biomed. Sci.

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Abstract:This study measured multiple physiological parameters of mental fatigue induced by the simulated driving task. The subjects' mannerisms and driving performance reveal that the driving mental fatigue is induced after long-term simulated driving. The wavelet packet energy (WPE) of EEG were used to extract the features of brain activity in the normal and the mental fatigue states, then random forests (RF) was employed to select key features for differentiating the two states. The experimental results show that the WPE of EEG and the amplitude of P300 are strongly related with driving mental fatigue. The power spectral indices of heart rate variability (HRV) indicate that the sympathetic nervous system may play a leading role and the parasympathetic nervous system is retrained at the end of driving task. Furthermore, RF method can select features effectively, reduce the dimensionality of the feature vectors significantly, and then achieve a recognition accuracy of 97%. The WPE-RF method could be a potential way of assessment of driving mental fatigue.

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“…While many studies focused mainly on the mere identification of neural activity associated with dual-task processing (Dux et al, 2006;Erickson et al, 2005;Herath et al, 2001;Hsieh et al, 2009;Jiang et al, 2004;Schubert and Szameitat, 2003;Szameitat et al, 2002), other research focused more specifically on the identification of cortical areas which are activated exclusively in the dual-task but not in the single-task situation (Adcock et al, 2000;Bunge et al, 2000;D'Esposito et al, 1995;Klingberg, 1998;Smith et al, 2001). In addition, a number of further research questions have been followed, such as testing for functional connectivity in dual-task processing (Dux et al, 2009;Stelzel et al, 2009), the effect of training (Dux et al, 2009;Erickson et al, 2007), or the effect of the amount of cortical overlap of the single tasks on dual-task performance (Just et al, 2001(Just et al, , 2008Klingberg, 1998;Klingberg and Roland, 1997).…”

Section: Introductionmentioning

confidence: 99%

How to test for dual-task-specific effects in brain imaging studies — An evaluation of potential analysis methods

2011

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Conversation effects on neural mechanisms underlying reaction time to visual events while viewing a driving scene: fMRI analysis and asynchrony model

Cited by 53 publications

References 54 publications

Validation of the Static Load Test for Event Detection During Hands-Free Conversation

Validation of the Static Load Test for Event Detection During Hands-Free Conversation

Physiological Assessment of Driving Mental Fatigue Using Wavelet Packet Energy and Random Forests

How to test for dual-task-specific effects in brain imaging studies — An evaluation of potential analysis methods

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