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Neurodriving

Neurodriving. Behavioral and structural brain imaging data. Materials and Methods. Participants 17 high and 17 low risk-taking male adolescents aged 18-19 years Personality tests Assessed propensity for risky behavior and vulnerability to peer influence

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Neurodriving

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  1. Neurodriving Behavioral and structural brain imaging data

  2. Materials and Methods • Participants • 17 high and 17 low risk-taking male adolescents aged 18-19 years • Personality tests • Assessed propensity for risky behavior and vulnerability to peer influence • Simulated driving task (Stoplight game) • Investigated risky driving behavior and the effects of social pressure • Participants made decisions on whether to stop at an intersection with traffic lights or to run through the intersection and chance a collision with another vehicle (and a longer delay), with the goal of reaching the end of a track as quickly as possible. • Social context • Manipulated by informing the participants that the performance would be compared with those of their peers. • Structural differences in gray and white matter of the brain • Gray matter: voxel-based morphometry (VBM) • White matter: diffusion tensor imaging (DTI) • Comparisons according to the participants’ personality test results and actual risk-taking behavior in a simulated driving task

  3. Results • Behavioral data • The personality tests could not predict actual risk-taking behavior during task performance. • Manipulation of social context through peer competition exerted a clear influence on the participant’s decision making: Participants from both high and low risk-taking groups took more risks to get to the goal faster and spent more time in making either Go or Stop decisions during the competition condition. • Structural brain imaging data • No significant difference in gray matter volume and white matter integrity between high and low risk-taking adolescents according to personality test results • Significantly higher white matter integrity in the high risk-taking group according to actual risk-taking behavior during task performance, suggesting that increased risky behavior during adolescence is not necessarily attributed to the immature brain as conventional wisdom  says

  4. Stoplightgame • A schematic track with intersections (horizontal lines) with varying distances is shown on the right bottom. The screen pictures depict main events of an example trial. Participants made decisions after the traffic lights at the intersection turned yellow. Stop-decision resulted in a short 3-s waiting with another car crossing from the side, while Go-decision could result in either a pass with no delay or a crash and a longer 6-s delay. The game screen displayed time on the upper side counting down from 5 min. A progress bar on the left side showed the position of the car and the intersections on the track.

  5. Distribution of high and low risk-taking groups Personality test results Driving task performance

  6. Behavioral data Go response rates Go and Stop response time

  7. Structuralbrainimaging data Areas of difference between High and Low risk-taking groups (red), areas of positive correlation between the total number of Go responses and FA (green), and areas of overlap of these two results (yellow). A: right occipital white matter; B: right anterior internal capsule; C: splenium; D: left anterior frontal subgyral white matter; E: left frontal subgyral white matter; F: left premotor subgyral white matter

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