EEG Frequency Bands in Psychiatric Disorders: A Review of Resting State Studies

By J. Newson, T. Thiagarajan. Frontiers in Human Neuroscience, 2019

737 citations recorded by the source corpus.

A significant proportion of the electroencephalography (EEG) literature focuses on differences in historically pre-defined frequency bands in the power spectrum that are typically referred to as alpha, beta, gamma, theta and delta waves. Here, we review 184 EEG studies that report differences in frequency bands in the resting state condition (eyes open and closed) across a spectrum of psychiatric disorders including depression, attention deficit-hyperactivity disorder (ADHD), autism, addiction, bipolar disorder, anxiety, panic disorder, post-traumatic stress disorder (PTSD), obsessive compulsive disorder (OCD) and schizophrenia to determine patterns across disorders. Aggregating across all reported results we demonstrate that characteristic patterns of power change within specific frequency bands are not necessarily unique to any one disorder but show substantial overlap across disorders as well as variability within disorders. In particular, we show that the most dominant pattern of change, across several disorder types including ADHD, schizophrenia and OCD, is power increases across lower frequencies (delta and theta) and decreases across higher frequencies (alpha, beta and gamma). However, a considerable number of disorders, such as PTSD, addiction and autism show no dominant trend for spectral change in any direction. We report consistency and validation scores across the disorders and conditions showing that the dominant result across all disorders is typically only 2.2 times as likely to occur in the literature as alternate results, and typically with less than 250 study participants when summed across all studies reporting this result. Furthermore, the magnitudes of the results were infrequently reported and were typically small at between 20% and 30% and correlated weakly with symptom severity scores. Finally, we discuss the many methodological challenges and limitations relating to such frequency band analysis across the literature. These results caution any interpretation of results from studies that consider only one disorder in isolation, and for the overall potential of this approach for delivering valuable insights in the field of mental health.

Subfields: Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/219143f9b0e94b6f6ff3469e5a848944720d4e0b

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In Cognitive Neuroscience

Citations in the corpus

Non-Neural Sources Systematically Impact Aperiodic EEG Activity (2026, unknown): “For all analyses, except the incremental contamination analysis on ocular artifacts (see below), data from the eyes-closed condition were used, which is most commonly employed in resting state EEG studies 48 .”
Theta activity and cognitive functioning: Integrating evidence from resting-state and task-related developmental electroencephalography (EEG) research (2024, background): “…studies (for reviews, see Arns et al., 2013; Lenartowicz and Loo, 2014; Loo and Makeig, 2012), and increased resting theta/beta ratio has been linked to other mental health conditions such as schizophrenia, obsessive-compulsive disorder (OCD), and internet addiction (Newson and Thiagarajan, 2019).”
Sexual dimorphism in cortical theta rhythms relates to elevated internalizing symptoms during adolescence (2024, unknown): “However, the literature also contains contradictory results, has generally been conducted within specific disorders (e.g., depression, ADHD) rather than examining transdiagnostic criteria within RDoC framework, and does not examine sex differences (Newson & Thiagarajan, 2019).”
Developmental changes in individual alpha frequency: Recording EEG data during public engagement events (2023, background): “For example, there are reports of reduced resting alpha power, resulting in cortical hyperarousal, in people with attention-deficit hyperactivity disorder, schizophrenia, and obsessive-compulsive disorder (Newson & Thiagarajan, 2019).”
Globally elevated excitation–inhibition ratio in children with autism spectrum disorder and below-average intelligence (2021, background): “regulation of local E-I imbalances (7).”
Periodic and aperiodic neural activity displays age-dependent changes across early-to-middle childhood (2021, background): “…et al., 2011; Kahana, 2006), while changes in the frequency or amplitude of oscillations can be a sign of pathological neural activity in a number of psychiatric, neurological, and neurodevelopmental disorders (Başar, 2013; Newson & Thiagarajan, 2018; Voytek & Knight, 2015; Wang et al., 2013).”
Would frontal midline theta indicate cognitive changes induced by non-invasive brain stimulation? A mini review (2023, background): “They may overlap substantially across disorders and may show a great variability within disorders (Newson and Thiagarajan, 2018).”