{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T06:04:47Z","timestamp":1789452287739,"version":"build-2803163510"},"reference-count":50,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T00:00:00Z","timestamp":1789430400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Aging Neurosci."],"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>Aging increases crash risk through failures to prioritize safety-critical actions amid competing information. The neural basis of adaptive cognitive control under these demands remains insufficiently understood.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This study examined age effects on braking prioritization in 44 drivers (23 younger, 21 older) using a car-following simulation with lane keeping, in which participants withheld sign responses whenever brake signals took priority. Participants completed Sign (button press to classify road signs), Brake (pedal press to the brake lights of the car ahead), and dual-demand signBrake trials (simultaneous Sign and Brake, braking prioritized). Measures included reaction time, errors, mean absolute steering-wheel angle, blink metrics, ERPs (N1, P3, and LFN), time-frequency power, and multivariate pattern analysis (MVPA) of age decoding.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Older adults exhibited selective signBrake costs, with slower and less accurate braking than younger adults, and a larger mean absolute steering-wheel angle. In both groups, steering-wheel angle decreased from the pre- to the post-stimulus period, with the largest drop in signBrake. Blink rate did not differ by age, but younger adults exhibited longer blink durations and larger amplitude-velocity ratios, suggesting differences in how blinks punctuate attentional sampling during driving. The LFN (late frontal negativity), a preparatory index of response control, showed weaker condition-related differentiation in older adults, who also exhibited larger N1 but smaller P3 amplitudes. This pattern fits greater early visual attentional selection and weaker later evaluation and context updating. Time-frequency analyses revealed reduced frontal theta, parietal alpha, and central beta power in older adults across conditions. Central beta demonstrated the strongest Age \u00d7 Condition modulation, driven mainly by older adults, while younger adults showed no reliable condition differences, which fits weaker post-stimulus attentional gating and altered sensorimotor tuning during action selection. MVPA decoded age group above chance after stimulus onset in all three conditions. Cross-condition decoding succeeded across train-test pairings, consistent with a distributed age-related neural signature that generalizes across contexts.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>These findings tie signBrake performance costs to weaker preparatory control differentiation and altered post-stimulus dynamics that support braking under interference. This reduced flexibility may contribute to age-related declines in driving safety in moments that call for rapid, goal-directed control.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fnagi.2026.1864407","type":"journal-article","created":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T05:36:18Z","timestamp":1789450578000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Aging on the road: neural and behavioral correlates of cognitive control during distracted driving"],"prefix":"10.3389","volume":"18","author":[{"given":"Emad","family":"Alyan","sequence":"first","affiliation":[{"name":"Department of Ergonomics, Leibniz Research Centre for Working Environment and Human Factors","place":["Dortmund, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephan","family":"Getzmann","sequence":"additional","affiliation":[{"name":"Department of Ergonomics, Leibniz Research Centre for Working Environment and Human Factors","place":["Dortmund, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Edmund","family":"Wascher","sequence":"additional","affiliation":[{"name":"Department of Ergonomics, Leibniz Research Centre for Working Environment and Human Factors","place":["Dortmund, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Melanie","family":"Karthaus","sequence":"additional","affiliation":[{"name":"Department of Ergonomics, Leibniz Research Centre for Working Environment and Human Factors","place":["Dortmund, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,9,15]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"e41164","DOI":"10.1016\/j.heliyon.2024.e41164","article-title":"Age-related differences in eye blink-related neural activity and functional connectivity during driving","volume":"11","author":"Alyan","year":"2025","journal-title":"Heliyon"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"5745","DOI":"10.1109\/JBHI.2023.3317508","article-title":"Decoding eye blink and related EEG activity in realistic working environments","volume":"27","author":"Alyan","year":"2023","journal-title":"IEEE J. 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