Skip to content

Adriana Michalak

4 papers in the library · 1 citation · publishing 2023-2026

Papers

Sort Most recent Most cited

Immersive NREM2 dreaming preserves subjective sleep depth against declining sleep pressure.

PLoS Biology March 1, 2026 Adriana Michalak, Davide Marzoli, Francesco Pietrogiacomi et al.

Perceived sleep depth is a key determinant of subjective sleep quality, traditionally thought to reflect unconsciousness and reduced cortical activation. Here, we combined high-density EEG with a serial awakening paradigm during NREM2 (N2) sleep in healthy human participants to examine its neural and experiential correlates. As expected, deeper sleep was associated with reduced cortical...

Immersive NREM dreaming preserves subjective sleep depth against declining sleep pressure

bioRxiv (Cold Spring Harbor Laboratory) September 8, 2025 Adriana Michalak, Davide Marzoli, Francesco Pietrogiacomi et al. preprint

Perceived sleep depth is a key determinant of subjective sleep quality, traditionally thought to reflect unconsciousness and reduced cortical activation. Here, we combined high-density EEG with a serial awakening paradigm during NREM sleep to examine its neural and experiential correlates. As expected, deeper sleep was associated with reduced cortical activation, reflected in a lower...

Automatic Annotation of Dream Report’s Emotional Content with Large Language Models

Workshop on Computational Linguistics and Clinical Psychology 2024 Lorenzo Bertolini, Valentina Elce, Adriana Michalak et al.

In the field of dream research, the study of dream content typically relies on the analysis of verbal reports provided by dreamers upon awakening from their sleep. This task is classically performed through manual scoring provided by trained annotators, at a great time expense. While a consistent body of work suggests that natural language processing (NLP) tools can support the automatic...

Automatic Scoring of Dream Reports' Emotional Content with Large Language Models

arXiv (Cornell University) February 28, 2023 Lorenzo Bertolini, Valentina Elce, Adriana Michalak et al. 1 citation

In the field of dream research, the study of dream content typically relies on the analysis of verbal reports provided by dreamers upon awakening from their sleep. This task is classically performed through manual scoring provided by trained annotators, at a great time expense. While a consistent body of work suggests that natural language processing (NLP) tools can support the automatic...