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Despite the growing interest in monitoring techniques based on neurophysiological signals, current biomarkers are primarily validated only for detecting passive mental fatigue under monotonous conditions. The objective of this study is to evaluate the sensitivity of the MDrow index, which is based on EEG Alpha band activity, previously validated for detecting passive mental fatigue, with respect to active mental fatigue, i.e., the mental fatigue occurring in cognitively demanding driving scenarios. Methods: A simulated experimental protocol was developed featuring three driving scenarios with increasing complexity: monotonous, urban, and urban with dual tasks. Nineteen participants took part in the experiment, during which electroencephalogram (EEG), photoplethysmogram (PPG), and electrodermal activity (EDA) data were collected in addition to subjective assessments, namely the Karolinska Sleepiness Scale (KSS) and the Driving Activity Load Index (DALI) questionnaires. Results:The findings indicate that MDrow shows sensitivity to both passive and active mental fatigue (p &lt; 0.001), thereby demonstrating stability even in the presence of additional cognitive demands. Furthermore, Heart Rate (HR) and Heart Rate Variability (HRV) increased significantly during the execution of more complex tasks, thereby suggesting a heightened response to mental workload in comparison to mental fatigue alone. Conversely, electrodermal measures evidenced no sensitivity to mental fatigue-related changes. Conclusions: These findings confirm the MDrow index\u2019s validity as an objective and continuous marker of mental fatigue, even under cognitively demanding conditions.<\/jats:p>","DOI":"10.3390\/brainsci15091001","type":"journal-article","created":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T14:31:41Z","timestamp":1758033101000},"page":"1001","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Analysis of Neurophysiological Correlates of Mental Fatigue in Both Monotonous and Demanding Driving Conditions"],"prefix":"10.3390","volume":"15","author":[{"given":"Francesca","family":"Dello Iacono","sequence":"first","affiliation":[{"name":"Department of Computer, Automatic and Management Engineering, Faculty of Information Engineering, Computer Science and Statistics, Sapienza University of Rome, 00185 Rome, 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Rome, 00185 Rome, Italy"},{"name":"College of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3831-6620","authenticated-orcid":false,"given":"Pietro","family":"Aric\u00f2","sequence":"additional","affiliation":[{"name":"Department of Computer, Automatic and Management Engineering, Faculty of Information Engineering, Computer Science and Statistics, Sapienza University of Rome, 00185 Rome, Italy"},{"name":"BrainSigns srl, Via Tirso, 14, 00198 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8560-5671","authenticated-orcid":false,"given":"Gianluca","family":"Borghini","sequence":"additional","affiliation":[{"name":"Department of Molecular Medicine, Faculty of Pharmacy and Medicine, Sapienza University of Rome, 00185 Rome, Italy"},{"name":"BrainSigns srl, Via Tirso, 14, 00198 Rome, 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