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Simulated Driving and Brain Imaging: Combining Behavior, Brain Activity, and Virtual Reality

Published online by Cambridge University Press:  07 November 2014

Kara N. Carvalho ,
Godfrey D. Pearlson ,
Robert S. Astur  and
Vince D. Calhoun
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Abstract

Introduction:

Virtual reality in the form of simulated driving is a useful tool for studying the brain. Various clinical questions can be addressed, including both the role of alcohol as a modulator of brain function and regional brain activation related to elements of driving.

Objective:

We reviewed a study of the neural correlates of alcohol intoxication through the use of a simulated-driving paradigm and wished to demonstrate the utility of recording continuous-driving behavior through a new study using a programmable driving simulator developed at our center.

Methods:

Functional magnetic resonance imaging data was collected from subjects while operating a driving simulator. Independent component analysis (ICA) was used to analyze the data. Specific brain regions modulated by alcohol, and relationships between behavior, brain function, and alcohol blood levels were examined with aggregate behavioral measures. Fifteen driving epochs taken from two subjects while also recording continuously recorded driving variables were analyzed with ICA.

Results:

Preliminary findings reveal that four independent components correlate with various aspects of behavior. An increase in braking while driving was found to increase activation in motor areas, while cerebellar areas showed signal increases during steering maintenance, yet signal decreases during steering changes. Additional components and significant findings are further outlined.

Conclusion:

In summary, continuous behavioral variables conjoined with ICA may offer new insight into the neural correlates of complex human behavior.

Type
Original Research
Information
CNS Spectrums , Volume 11 , Issue 1 , January 2006 , pp. 52 - 62
Copyright
Copyright © Cambridge University Press 2006

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References

REFERENCES

1.US Department of Transportation. National Highway Traffic Safety Administration. Traffic Safety Facts 2002 Alcohol. Report No DOT HS 809 606.Google Scholar
2.Arnedt, JT, Wilde, GJ, Munt, PW, MacLean, AW. How do prolonged wakefulness and alcohol compare in the decrements they produce on a simulated driving task? Accid Anal Prev. 2001;33:337–344.Google Scholar
3.Linnoila, M, Mattila, MJ. Interaction of alcohol and drugs on psychomotor skills as demonstrated by a driving simulator. Br J Pharmacol. 1973;47:671P–672P.Google Scholar
4.Rimm, DC, Sininger, RA, Faherty, JD, Whitley, MD, Perl, MB. A balanced placebo investigation of the effects of alcohol vs. alcohol expectancy on simulated driving behavior. Addict Behav. 1982;7:27–32.Google Scholar
5.Deery, HA, Fildes, BN. Young novice driver subtypes: relationship to high-risk behavior, traffic accident record, and simulator driving performance. Hum Factors. 1999;41:628–643.Google Scholar
6.Verster, JC, Volkerts, ER, Verbaten, MN. Effects of alprazolam on driving ability, memory functioning and psychomotor performance: a randomized, placebo-controlled study. Neuropsychopharmacology. 2002;27:260–269.Google Scholar
7.McGinty, VB, Shih, RA, Garrett, ES, Calhoun, VD, Pearlson, GD. Assessment of intoxicated driving with a simulator: a validation study with on road driving. In: Proceedings Human Centered Transportation Simulation Conference. Paper presented at: Annual Meeting of Human Centered Transportation Simulation Conference. November 4-7, 2001; Iowa City, IA.Google Scholar
8.Worsley, KJ, Friston, KJ. Analysis of fMRI time-series revisited–again. Neuroimage. 1995;2:173–181.Google Scholar
9.McKeown, MJ, Makeig, S, Brown, GGet al.Analysis of fMRI data by blind separation into independent spatial component. Hum Brain Mapp. 1998;6:160–188.Google Scholar
10.Biswal, BB, Ulmer, JL. Blind source separation of multiple signal sources of fMRI data sets using independent component analysis. J Comput Assist Tomogr. 1999;23:265–71.Google Scholar
11.Calhoun, VD, Adali, T, Pearlson, GD, Pekar, JJ. Spatial and temporal independent component analysis of functional MRI data containing a pair of task-related waveforms. Hum Brain Mapp. 2001;13:43–53.Google Scholar
12.Kapur, BM. Computer Blood Alcohol Calculator v1.20 ARF Software. Toronto, Canada: Addiction Research Foundation; 1989.Google Scholar
13.Calhoun, VD, Adali, T, McGinty, V, Pekar, JJ, Watson, T, Pearlson, GD. fMRI activation in a visual-perception task: network of areas detected using the general linear model and independent components analysis. Neuroimage. 2001;14:1080–1088.Google Scholar
14.Calhoun, VD, Altschul, D, McGinty, V, Shih, RA, Scott, D, Pearlson, GD. Alcohol intoxication effects on visual perception: an fMRI study. Hum Brain Mapp. 2004;21:15–26.Google Scholar
15.Calhoun, VD, Pekar, JJ, McGinty, VB, Adali, T, Watson, TD, Pearlson, GD. Different activation dynamics in multiple neural systems during simulated driving. Hum Brain Mapp. 2002;16:158–167.Google Scholar
16.Calhoun, VD, Pekar, JJ, Pearlson, GD. Alcohol intoxication effects on simulated driving: Exploring Alcohol-Dose Effects on Brain Activation Using Functional MRI. Neuropsychopharmacology. 2004;29:2097–2107.Google Scholar
17.Calhoun, VD, Adali, T, Pearlson, GD, Pekar, JJ. A Method for Making Group Inferences from Functional MRI Data Using Independent Component Analysis. Hum Brain Mapp. 2001 March 1;14(3):140–51.Google Scholar
18.Egolf, EA, Kiehl, KA, Calhoun, VD. Group ICA of fMRI Toolbox (GIFT) [computer program]. Available at http://icatb.sourceforge.net/; 2004.Google Scholar
19.Peterson, JB, Rothfleisch, J, Zelazo, PD, Pihl, RO. Acute alcohol intoxication and cognitive functioning. J Stud Alcohol. 1990;51:114–122.Google Scholar
20.Volkow, ND, Mullani, N, Gould, L, et al.Effects of acute alcohol intoxication on cerebral blood flow measured with PET. Psychiatry Res. 1988;24:201–209.Google Scholar
21.Mascord, D, Walls, J, Starmes, G. Fatigue and alcohol: interactive effects on human performance in driving-related tasks. In: Hartley, L, ed. Fatigues and Driving: Driver Impairment, Driver Fatigue, and Driving Simulation. London, UK: Taylor and Francis; 1995;189–205.Google Scholar
22.Levin, JM, Ross, MH, Mendelson, JH, et al.Reduction in BOLD fMRI response to primary visual stimulation following alcohol ingestion. Psychiatry Res. 1998;82:135–146.Google Scholar
23.Groeger, J.Understanding Driving: Applying Cognitive Psychology to a Complex Everyday Task. New York, NY: Psychology Press; 2000.Google Scholar
24. Statistical Parametric Mapping [computer program]. Natick, Mass: The MathWorks, Inc.; 2002.Google Scholar
25.Freire, L, Roche, A, Mangin, JF. What is the best similarity measure for motion correction in fMRI time series? IEEE Trans Med Imaging. 2002;21:470–484.Google Scholar
26.Freire, L, Mangin, JF. Motion correction algorithms may create spurious brain activations in the absence of subject motion. Neuroimage. 2001;14:709–722.Google Scholar
27.Friston, K, Ashburner, J, Frith, CD, Poline, JP, Heather, JD, Frackowiak, RS. Spatial registration and normalization of images. Hum Brain Mapp. 1995;2:165–189.Google Scholar