Non-oscillatory measures of brain activity such as the spectral slope and Lempel-Ziv complexity are affected by many neurological disorders and modulated by sleep. A multitude of frequency ranges, particularly a broadband (encompassing the full spectrum) and narrowband approach, have been used especially for estimating the spectral slope. However, the effects of choosing different frequency ranges have not yet been explored in detail. Here, we evaluated the impact of sleep stage and task-engagement (resting, attention and memory) on slope and complexity in a narrow- (30 – 45Hz) and broadband (1 – 45Hz) frequency range in 28 healthy male human subjects (21.54 ± 1.90 years) using a within-subject design over two weeks with three recording nights and days per subject. We strived to determine how different brain states and frequency ranges affect slope and complexity and how the two measures perform in comparison. In the broadband range, the slope steepened, and complexity decreased continuously from wakefulness to N3 sleep. REM sleep, however, was best discriminated by the narrowband slope. Importantly, slope and complexity also differed between tasks during wakefulness. While the narrowband complexity decreased with task engagement, the slope flattened in both frequency ranges. Interestingly, only the narrowband slope was positively correlated with task performance. Our results show that slope and complexity are sensitive indices of brain state variations during wakefulness and sleep. However, the spectral slope yields more information and could be used for a greater variety of research questions than Lempel-Ziv complexity, especially when a narrowband frequency range is used.Significance StatementWe demonstrate that the spectral slope and Lempel-Ziv complexity differentiate between sleep stages, quiet wakefulness and active tasks, thus making them reliable non-invasive biomarkers of brain states. Critically, these markers were previously assessed in isolation only. Here, we provide evidence that they track highly similar information about the underlying brain state in a broad frequency range (1 – 45Hz). Within this range, slope and complexity distinguish brain states better than in a more narrowband range (30 – 45Hz). However, the slope calculated from the narrowband range is superior in differentiating REM from wakefulness and tracking behavioral performance. Our results demonstrate that the choice of frequency range critically affects the information reflected the spectral slope and Lempel-Ziv complexity.