Behind the Wheel: Exploring Gray Matter Variations in Experienced Drivers

Overview

Journal PeerJ

Specialties Biology
Environmental Health
General Medicine

Date 2024 Apr 15

PMID 38618564

Authors

Jiangtao Chen

Xiaoyu Chen

Li Gong

Di Zhang

Qiang Liu

Affiliations

Soon will be listed here.

Abstract

Background: Driving is a complex skill involving various cognitive activities. Previous research has explored differences in the brain structures related to the navigational abilities of drivers compared to non-drivers. However, it remains unclear whether changes occur in the structures associated with low-level sensory and higher-order cognitive abilities in drivers.

Methods: Gray matter volume, assessed voxel-based morphometry analysis of T1-weighted images, is considered a reliable indicator of structural changes in the brain. This study employs voxel-based morphological analysis to investigate structural differences between drivers ( = 22) and non-drivers ( = 20).

Results: The results indicate that, in comparison to non-drivers, drivers exhibit significantly reduced gray matter volume in the middle occipital gyrus, middle temporal gyrus, supramarginal gyrus, and cerebellum, suggesting a relationship with driving-related experience. Furthermore, the volume of the middle occipital gyrus, and middle temporal gyrus, is found to be marginally negative related to the years of driving experience, suggesting a potential impact of driving experience on gray matter volume. However, no significant correlations were observed between driving experiences and frontal gray matter volume.

Conclusion: These findings suggest that driving skills and experience have a pronounced impact on the cortical areas responsible for low-level sensory and motor processing. Meanwhile, the influence on cortical areas associated with higher-order cognitive function appears to be minimal.

References

Ventsislavova P, Gugliotta A, Pena-Suarez E, Garcia-Fernandez P, Eisman E, Crundall D . What happens when drivers face hazards on the road?. Accid Anal Prev. 2016; 91:43-54. DOI: 10.1016/j.aap.2016.02.013. View

Park H, Friston K . Structural and functional brain networks: from connections to cognition. Science. 2013; 342(6158):1238411. DOI: 10.1126/science.1238411. View

Weng J, Kao T, Huang G, Tyan Y, Tseng H, Ho M . Evaluation of structural connectivity changes in betel-quid chewers using generalized q-sampling MRI. Psychopharmacology (Berl). 2017; 234(13):1945-1955. DOI: 10.1007/s00213-017-4602-0. View

Vaquero L, Hartmann K, Ripolles P, Rojo N, Sierpowska J, Francois C . Structural neuroplasticity in expert pianists depends on the age of musical training onset. Neuroimage. 2015; 126:106-19. DOI: 10.1016/j.neuroimage.2015.11.008. View

Schlaug G . The brain of musicians. A model for functional and structural adaptation. Ann N Y Acad Sci. 2001; 930:281-99. View

Calhoun V, Pekar J, McGinty V, Adali T, Watson T, Pearlson G . Different activation dynamics in multiple neural systems during simulated driving. Hum Brain Mapp. 2002; 16(3):158-67. PMC: 6872105. DOI: 10.1002/hbm.10032. View

Maguire E, Gadian D, Johnsrude I, Good C, Ashburner J, Frackowiak R . Navigation-related structural change in the hippocampi of taxi drivers. Proc Natl Acad Sci U S A. 2000; 97(8):4398-403. PMC: 18253. DOI: 10.1073/pnas.070039597. View

Gaser C, Dahnke R, Thompson P, Kurth F, Luders E, The Alzheimers Disease Neuroimaging Initiative . CAT: a computational anatomy toolbox for the analysis of structural MRI data. Gigascience. 2024; 13. PMC: 11299546. DOI: 10.1093/gigascience/giae049. View

Spiers H, Maguire E . Neural substrates of driving behaviour. Neuroimage. 2007; 36(1):245-55. PMC: 2570440. DOI: 10.1016/j.neuroimage.2007.02.032. View

10.

Lappi O . The Racer's Brain - How Domain Expertise is Reflected in the Neural Substrates of Driving. Front Hum Neurosci. 2015; 9:635. PMC: 4656842. DOI: 10.3389/fnhum.2015.00635. View

11.

Kuhn S, Banaschewski T, Bokde A, Buchel C, Quinlan E, Desrivieres S . Brain structure and habitat: Do the brains of our children tell us where they have been brought up?. Neuroimage. 2020; 222:117225. DOI: 10.1016/j.neuroimage.2020.117225. View

12.

Lesourd M, Osiurak F, Navarro J, Reynaud E . Involvement of the Left Supramarginal Gyrus in Manipulation Judgment Tasks: Contributions to Theories of Tool Use. J Int Neuropsychol Soc. 2017; 23(8):685-691. DOI: 10.1017/S1355617717000455. View

13.

Dayan E, Cohen L . Neuroplasticity subserving motor skill learning. Neuron. 2011; 72(3):443-54. PMC: 3217208. DOI: 10.1016/j.neuron.2011.10.008. View

14.

Hanggi J, Koeneke S, Bezzola L, Jancke L . Structural neuroplasticity in the sensorimotor network of professional female ballet dancers. Hum Brain Mapp. 2009; 31(8):1196-206. PMC: 6870845. DOI: 10.1002/hbm.20928. View

15.

Jancke L, Shah N, Peters M . Cortical activations in primary and secondary motor areas for complex bimanual movements in professional pianists. Brain Res Cogn Brain Res. 2000; 10(1-2):177-83. DOI: 10.1016/s0926-6410(00)00028-8. View

16.

Draganski B, Gaser C, Busch V, Schuierer G, Bogdahn U, May A . Neuroplasticity: changes in grey matter induced by training. Nature. 2004; 427(6972):311-2. DOI: 10.1038/427311a. View

17.

Peng L, Zeng L, Liu Q, Wang L, Qin J, Xu H . Functional connectivity changes in the entorhinal cortex of taxi drivers. Brain Behav. 2018; 8(9):e01022. PMC: 6160637. DOI: 10.1002/brb3.1022. View

18.

Imamizu H, Miyauchi S, Tamada T, Sasaki Y, Takino R, Putz B . Human cerebellar activity reflecting an acquired internal model of a new tool. Nature. 2000; 403(6766):192-5. DOI: 10.1038/35003194. View

19.

Smith S, Nichols T . Threshold-free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference. Neuroimage. 2008; 44(1):83-98. DOI: 10.1016/j.neuroimage.2008.03.061. View

20.

McDowell T, Holmes N, Sunderland A, Schurmann M . TMS over the supramarginal gyrus delays selection of appropriate grasp orientation during reaching and grasping tools for use. Cortex. 2018; 103:117-129. DOI: 10.1016/j.cortex.2018.03.002. View