Prefrontal activation during simulated driving in people with schizophrenia: A functional near-infrared spectroscopy study
DOI: 10.1016/j.psychres.2023.115285
archive: archived pipeline: cataloged verified
Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)
Summary
This study investigates whether people with schizophrenia (PWS) exhibit driving skill vulnerabilities that are not apparent in behavioral performance but are reflected in brain activity. Despite legal frameworks in many countries restricting driving privileges for individuals with schizophrenia, empirical evidence regarding their actual driving risk remains contradictory and limited. While some studies suggest cognitive impairments in PWS, others find no significant difference in driving performance compared to healthy controls (HCs). The authors hypothesized that PWS might require greater neural resources to maintain driving performance, particularly under high cognitive load, and used functional near-infrared spectroscopy (fNIRS) to assess prefrontal cortex activation during simulated driving. The study included 20 PWS and 20 HCs, all of whom were daily drivers aged 25–50 with at least five years of experience. Participants performed four tasks on a high-fidelity driving simulator: sudden braking at 50 km/h and 100 km/h, and navigating left and right curves at 50 km/h. fNIRS measured hemodynamic activity in the dorsolateral prefrontal cortex (DLPFC) and frontal pole. Driving performance was evaluated via brake reaction time and steering stability, while cognitive functions were assessed using standardized tests. Behavioral analysis revealed no significant differences in driving performance between PWS and HCs across any of the four tasks. However, fNIRS data showed that PWS exhibited significantly higher activation in both the left and right DLPFC during the 100 km/h sudden braking task compared to HCs. No such differences were observed during the lower-speed braking or curve tasks. Furthermore, a significant negative correlation was found between brake reaction time and left DLPFC activity in both groups during the high-speed braking task, indicating that greater prefrontal activation was associated with faster braking responses. The findings suggest that while PWS can perform driving tasks comparably to HCs, they may rely on compensatory neural mechanisms, specifically increased DLPFC recruitment, to manage high cognitive loads such as emergency braking at high speeds. This aligns with compensatory scaffolding theory, where additional brain resources are mobilized to maintain performance despite underlying neural inefficiencies. The study concludes that PWS who drive daily may be capable of safe community driving, as their behavioral control and mental load processing mechanisms appear similar to those of HCs, albeit with higher neural effort under demanding conditions. These results challenge blanket restrictions on driving for PWS and highlight the need for further research into specific risk factors and compensatory strategies.
Provenance
The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed.
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-08-09 |
| archive | success | unpaywall | — | — | 2 | 2026-08-09 |
| extract | success | cached | — | — | 3 | 2026-08-10 |
| clean | success | clean | — | — | 1 | 2026-08-09 |
| chunk | success | chunk | — | — | 1 | 2026-08-09 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-08-09 |
| enrich | success | semantic_scholar | — | — | 1 | 2026-08-09 |
| promote | success | — | — | — | 1 | 2026-08-09 |
| summarize | success | llm | qwen3.6-27b-nvidia | summ-v5 | 2 | 2026-08-10 |
| tag | success | vector_similarity | — | — | 10 | 2026-08-11 |
| verify | partial | — | — | — | 2 | 2026-08-10 |
Summary generated by qwen3.6-27b-nvidia on 2026-08-10; verification: verified_with_issues.
Topics
Ranked by relevance to this paper. Hover a topic for its definition.
Information type
What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).
- Empirical Findings: physiological data, behavioral performance data
- Theoretical Contribution: computational model