ArticleHuman brain mapping2015
Large-scale functional brain network changes in taxi drivers: evidence from resting-state fMRI.
Article in Human brain mapping, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.
- Occupational Neuroplasticity in the Human Brain: A Critical Review and Meta-Analysis of Neuroimaging Studies.Frontiers in human neuroscience · 2020Pooled it
- Dynamic Analysis of Gray Matter and White Matter Functional Network Connectivity in Individuals with Temporal Lobe Epilepsy.Research square · 2026Article
- Article
- Naturalistic driving measures of route selection associate with resting state networks in older adults.Scientific reports · 2022Article
- Left parietal involvement in motion sickness susceptibility revealed by multimodal magnetic resonance imaging.Human brain mapping · 2022Article
- Aberrant neurovascular coupling in Leber's hereditary optic neuropathy: Evidence from a multi-model MRI analysis.Frontiers in neuroscience · 2022Article
- Effective Connectivity Analysis of Brain Activated Regions during Distracted Driving.Brain sciences · 2021Article
- Brain parcellation driven by dynamic functional connectivity better capture intrinsic network dynamics.Human brain mapping · 2021Article
- Evaluation of Effective Connectivity Between Brain Areas Activated During Simulated Driving Using Dynamic Causal Modeling.Frontiers in behavioral neuroscience · 2020Article
- Functional connectivity changes in the entorhinal cortex of taxi drivers.Brain and behavior · 2018Article
- Dynamic functional network connectivity in idiopathic generalized epilepsy with generalized tonic-clonic seizure.Human brain mapping · 2017Article
- Brain Functional Plasticity Driven by Career Experience: A Resting-State fMRI Study of the Seafarer.Frontiers in psychology · 2017Article
- Sleepiness and Driving: Multidimensional Legal, Social, Technological, and Biological Challenges.Sleep · 2016Article
Corrections and comments
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Authors and funding
5 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Driving a car in the environment is a complex behavior that involves cognitive processing of visual information to generate the proper motor outputs and action controls. Previous neuroimaging studies have used virtual simulation to identify the brain areas that are associated with various driving-related tasks. Few studies, however, have focused on the specific patterns of functional organization in the driver's brain. The aim of this study was to assess differences in the resting-state networks (RSNs) of the brains of drivers and nondrivers. Forty healthy subjects (20 licensed taxi drivers, 20 nondrivers) underwent an 8-min resting-state functional MRI acquisition. Using independent component analysis, three sensory (primary and extrastriate visual, sensorimotor) RSNs and four cognitive (anterior and posterior default mode, left and right frontoparietal) RSNs were retrieved from the data. We then examined the group differences in the intrinsic brain activity of each RSN and in the functional network connectivity (FNC) between the RSNs. We found that the drivers had reduced intrinsic brain activity in the visual RSNs and reduced FNC between the sensory RSNs compared with the nondrivers. The major finding of this study, however, was that the FNC between the cognitive and sensory RSNs became more positively or less negatively correlated in the drivers relative to that in the nondrivers. Notably, the strength of the FNC between the left frontoparietal and primary visual RSNs was positively correlated with the number of taxi-driving years. Our findings may provide new insight into how the brain supports driving behavior.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.