Brain entropy, fractal dimensions and predictability: A review of complexity measures for EEG in healthy and neuropsychiatric populations
Zen Juen Lau, Tam Pham, Shen‐hsing Annabel Chen, Dominique Makowski
European Journal of Neuroscience August 19, 2022 DOI: 10.1111/ejn.15800 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Review Peer reviewed |
|---|---|
| Topics | Anxiety |
| Keywords | Electroencephalography Predictability Cognitive psychology Psychopathology Consciousness Artificial intelligence |
| Citations | 225 |
| Key findings | EEG complexity measures show potential as biomarkers for psychopathology, but theoretical and methodological issues must be addressed for consistent interpretation. |
Abstract
Abstract There has been an increasing trend towards the use of complexity analysis in quantifying neural activity measured by electroencephalography (EEG) signals. On top of revealing complex neuronal processes of the brain that may not be possible with linear approaches, EEG complexity measures have also demonstrated their potential as biomarkers of psychopathology such as depression and schizophrenia. Unfortunately, the opacity of algorithms and descriptions originating from mathematical concepts have made it difficult to understand what complexity is and how to draw consistent conclusions when applied within psychology and neuropsychiatry research. In this review, we provide an overview and entry‐level explanation of existing EEG complexity measures, which can be broadly categorized as measures of predictability and regularity. We then synthesize complexity findings across different areas of psychological science, namely, in consciousness research, mood and anxiety disorders, schizophrenia, neurodevelopmental and neurodegenerative disorders, as well as changes across the lifespan, while addressing some theoretical and methodological issues underlying the discrepancies in the data. Finally, we present important considerations when choosing and interpreting these metrics.
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Citations in the library
Cited by 20
- Critical dynamics in spontaneous EEG predict anesthetic-induced loss of consciousness and perturbational complexity. Communications Biology August 5, 2024
- The evolution of N, N-Dimethyltryptamine: from metabolic pathways to brain connectivity. Psychopharmacology April 11, 2025
- Psychedelics, entropic brain theory, and the taxonomy of conscious states: a summary of debates and perspectives. Neuroscience of Consciousness 2023
- Neural complexity EEG biomarkers of rapid and post-rapid ketamine effects in late-life treatment-resistant depression: a randomized control trial Neuropsychopharmacology April 19, 2023
- Neural Geometrodynamics, Complexity, and Plasticity: A Psychedelics Perspective Entropy January 22, 2024
and 15 more in the library
Cites 12
- A Theoretically Based Index of Consciousness Independent of Sensory Processing and Behavior Science Translational Medicine August 14, 2013
- The entropic brain: a theory of conscious states informed by neuroimaging research with psychedelic drugs Frontiers in Human Neuroscience 2014
- Increased spontaneous MEG signal diversity for psychoactive doses of ketamine, LSD and psilocybin Scientific Reports April 19, 2017
- Connectome-harmonic decomposition of human brain activity reveals dynamical repertoire re-organization under LSD. Scientific Reports December 15, 2017
- Global and local complexity of intracranial EEG decreases during NREM sleep Neuroscience of Consciousness January 27, 2017
and 7 more in the library