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Abnormal EEG Microstates Linked to Major Depression & Related Cognitive Impairment (2024 Study)

In the quest to understand the enigmatic nature of depression, scientists are turning to the intricate patterns of brain activity, seeking clues hidden within the electrical storm of thoughts and emotions.

By examining electroencephalography (EEG) microstates—brief, recurring patterns of brain activity—researchers have begun to piece together how depression alters the fundamental dynamics of the brain.

This cutting-edge exploration not only sheds light on the neural underpinnings of depression but also paves the way for novel diagnostic tools and treatments, offering hope in the shadow of this pervasive condition.


  1. EEG Microstates as Neural Fingerprints: EEG microstates are considered the “atoms” of thought, representing the brain’s rapid shifts in state, and are believed to correspond to fundamental processes of information processing.
  2. Depression’s Distinct Signature: Studies reveal that individuals with depression exhibit unique patterns in their EEG microstates, specifically in microstates C and D, hinting at potential biomarkers for the condition.
  3. Link to Cognitive Functions: Research has found a correlation between certain EEG microstate patterns and cognitive functions in people with depression, suggesting a relationship between these patterns and the severity of depressive symptoms.
  4. Future Directions in Depression Diagnosis & Treatment: The findings from EEG microstate analysis could lead to more precise diagnostic methods and targeted treatments, revolutionizing how depression is approached in clinical settings.

Source: World Journal of Psychiatry (2024)

What are EEG Microstates?

EEG microstates are brief, recurring patterns of brain activity that last for milliseconds and are thought to represent the fundamental building blocks of human thought and perception.

They are captured by electroencephalography (EEG), a non-invasive technique that records electrical activity generated by the brain’s neurons.

These microstates are characterized by specific topographic maps that reflect the distribution of electrical potentials across the scalp at a given moment in time.

The brain’s activity shifts rapidly between these microstates, with each one potentially corresponding to different cognitive and neural processes.

Researchers have identified several canonical microstates (typically labeled A, B, C, D) that are consistent across individuals and have been linked to distinct neural networks and functions.

EEG Microstates Link to Depression

The linkage between EEG microstates and depression can be understood both causally and correlationally.

Changes in the patterns and dynamics of microstates may reflect underlying neural disruptions associated with depressive symptoms, such as altered attention, rumination, and cognitive control.

For example, alterations in the duration, occurrence, and contribution of specific microstates (such as an increase in microstate C and a decrease in microstate D) have been observed in individuals with depression, suggesting a disruption in the neural networks associated with cognitive control and attention.

These changes could contribute to the cognitive and emotional symptoms of depression, including persistent negative thinking, difficulty concentrating, and impaired decision-making.

Therefore, the relationship between microstate alterations and depression may arise from changes in the brain’s functional connectivity and information processing, contributing to the disorder’s symptomatology.

Common EEG Changes in Depression

In addition to specific microstate alterations, depression is associated with other EEG changes.

These commonly include an increase in theta and alpha band activity, particularly in frontal regions, which may be related to reduced cortical arousal and altered emotional regulation.

Decreased beta activity can also be observed, potentially reflecting impaired cognitive processing and attention.

Furthermore, asymmetries in frontal lobe activity, with increased right-frontal activation, have been linked to depression, possibly underpinning the tendency towards negative emotional states.

These EEG changes complement the findings related to microstates, offering a broader view of the neurophysiological alterations associated with depression.

(Related: Depressed vs. Anxious Brains: Brain Waves & Connectivity)

Major Findings: EEG Microstates, Depression, Cognition (2024 Study)

Peng et al. evaluated EEG microstates in individuals with depression versus healthy controls.

1. Alterations in Microstate Parameters

Increased Duration, Occurrence, & Contribution of Microstate C

In patients with depression, microstate C exhibited a notable increase in its duration, occurrence, and contribution compared to healthy controls.

Specifically, the duration was significantly longer, the occurrence (frequency of appearance) was higher, and its contribution (the proportion of total time spent in this state) exceeded that observed in the control group.

Microstate C is generally associated with cognitive control networks, indicating that depression may involve persistent activation or over-engagement of these networks.

Decreased Duration, Occurrence, & Contribution of Microstate D

Conversely, microstate D showed a significant decrease across these parameters in the depression group.

This microstate is linked to the brain’s dorsal attention networks, suggesting that individuals with depression may experience reduced engagement or dysfunction within these attention-related neural processes.

2. Cognitive Function Correlations

Visuospatial & Constructional Abilities

A particularly intriguing aspect of the study was the positive correlation between the visuospatial/constructional scores from the RBANS and the transition probability from microstate C to B in patients with depression.

This finding suggests that the more frequent transition between these specific microstates may relate to the cognitive domain of visuospatial and constructional skills.

Since microstate B is associated with visual processing, this correlation could imply that depression affects how individuals with the disorder process or allocate attention to visual and spatial information, potentially leading to a more intense or prolonged focus on negative visual stimuli or ruminations.

3. Potential as Depression Biomarkers

The distinct patterns observed in microstates C and D among individuals with depression point to the potential of these EEG microstate alterations as biomarkers for the condition.

These patterns reflect underlying differences in neural processing and network engagement that are characteristic of depression, suggesting avenues for more targeted and personalized approaches to diagnosis and treatment.


  • Microstate C as a Marker of Cognitive Control Engagement: The heightened parameters of microstate C could serve as indicators of altered cognitive control mechanisms in depression, potentially contributing to the pervasive rumination and difficulty in shifting attention away from negative stimuli seen in this condition.
  • Microstate D & Attentional Processes: The reduced engagement of microstate D may reflect deficits in the dorsal attention network, possibly underlying the attentional biases towards negative information and the difficulties in concentration reported by individuals with depression.

EEG Microstates vs. Depression & Cognition (2024 Study)

By focusing on EEG microstates, the study sought to identify potential biomarkers for depression and to understand how these neural patterns correlate with the severity of depressive symptoms and cognitive impairments.


  • Participants: The study included 24 patients diagnosed with depression and 32 healthy controls, selected using the Structured Clinical Interview for DSM Disorders (SCID) based on the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-V) criteria.
  • Data Collection: Data were collected on demographic and clinical characteristics, along with scores from the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS; Chinese version) for cognitive assessment and EEG for neural activity analysis.
  • EEG Recording & Preprocessing: EEG data were recorded using a 128-electrode system and preprocessed to filter noise and artifacts. The data were then analyzed to identify EEG microstate sequences using the atomize and agglomerate hierarchical clustering (AAHC) algorithm.
  • Statistical Analysis: Independent sample t-tests, chi-square tests, and analysis of covariance (ANCOVA) were used to assess differences between groups. Pearson correlation analysis was employed to explore relationships between EEG microstates, cognitive functions, and depression severity scales.


  • EEG Microstates: Compared to healthy controls, patients with depression showed significant alterations in the duration, occurrence, and contribution of microstate C (increased) and microstate D (decreased).
  • Cognitive Correlations: A positive correlation was found between the visuospatial/constructional scores of the RBANS and the transition probability of microstate class C to B in the depression group, suggesting a link between specific EEG microstate transitions and cognitive functions.
  • Depression Biomarkers: The study’s results support the notion that certain EEG microstate characteristics, particularly those related to microstates C and D, can serve as potential biomarkers for depression, reflecting underlying neural differences in patients with this condition.


  • Sample Size: The relatively small sample size of the study may limit the generalizability of the findings.
  • Cross-sectional Design: The cross-sectional nature of the study does not allow for the examination of causal relationships between EEG microstates and depression or the assessment of changes over time.
  • Generalizability: The study’s findings may not be directly generalizable to all individuals with depression, especially considering the heterogeneity of the condition and the diversity of the population.
  • Methodological Variability: Differences in EEG recording and analysis techniques across studies may contribute to variability in findings, necessitating standardized protocols for future research.

Potential Applications of the Findings: EEG Microstates in Depression

The detailed analysis of EEG microstates in individuals with depression versus healthy controls reveals significant neural dynamics that could transform our approach to diagnosing, understanding, and treating depression.

These findings not only underscore the potential of EEG microstates as biomarkers for depression but also open up several avenues for their application in clinical practice and research.

Enhanced Diagnostic Precision

  • Biomarker Development: The distinct EEG microstate patterns identified in depression—specifically, the alterations in microstates C and D—could serve as objective biomarkers for the condition. Integrating these biomarkers into diagnostic protocols could enhance the precision of depression diagnoses, enabling clinicians to distinguish depression from other psychiatric conditions with overlapping symptoms.
  • Subtype Identification: Depression is a heterogenous disorder, with patients exhibiting a wide range of symptoms and severities. The specific patterns of EEG microstate alterations might correlate with particular symptom profiles or subtypes of depression, facilitating a more nuanced classification of the disorder and aiding in the selection of tailored treatment strategies.

Targeted Therapeutic Interventions

  • Neurofeedback Training: The ability to monitor and modulate specific EEG microstate patterns in real-time through neurofeedback provides a promising therapeutic avenue. By training individuals with depression to alter their microstate dynamics—such as increasing the engagement of microstate D or normalizing the transition probabilities between microstates—neurofeedback could help in rectifying the neural imbalances associated with the condition.
  • Personalized Medicine: Understanding the neural underpinnings of depression at the level of EEG microstates opens the door to personalized medicine approaches. Treatments—whether pharmacological, psychological, or neuromodulatory—could be tailored based on an individual’s specific EEG microstate patterns, potentially improving treatment efficacy and reducing the trial-and-error approach currently prevalent in depression management.

Insights into Cognitive Impairments

  • Cognitive Rehabilitation: The correlation between specific EEG microstate alterations and cognitive functions in depression—particularly the association with visuospatial/constructional abilities—highlights potential targets for cognitive rehabilitation. Therapeutic interventions designed to address the neural circuits underlying these cognitive impairments could lead to improved cognitive outcomes for individuals with depression.
  • Understanding Mechanisms of Cognitive Dysfunction: The findings provide a deeper understanding of the mechanisms underlying cognitive dysfunctions in depression, suggesting that altered neural dynamics and network connectivity play a significant role. This knowledge could guide the development of cognitive interventions aimed at restoring normal neural function and improving cognitive health in depressed patients.

Future Research Directions

  • Longitudinal Studies: Further research, particularly longitudinal studies, could explore how EEG microstate patterns change over the course of depression and in response to treatment. Such studies would provide valuable insights into the neural mechanisms of treatment response and the potential for EEG microstates to predict treatment outcomes.
  • Combining EEG with Other Neuroimaging Techniques: Integrating EEG microstate analysis with other neuroimaging modalities, such as fMRI or PET, could offer a more comprehensive view of the neural alterations in depression. This multimodal approach would allow researchers to correlate EEG microstate dynamics with changes in brain structure and function, enriching our understanding of depression’s neural basis.

(Related: 5 Types of Brain Waves: Gamma, Beta, Alpha, Theta, Delta)

Conclusion: EEG Microstates & Depression

This study highlights the intricate relationship between EEG microstates and depression, underscoring the potential of microstate analysis as a tool for understanding the neural basis of this complex disorder.

By revealing specific alterations in the duration, occurrence, and contribution of microstates C and D, the findings provide insight into the disrupted neural dynamics underlying depression’s cognitive and emotional symptoms.

These microstate changes, alongside other EEG alterations observed in depression, suggest a broader pattern of neurophysiological disruption that could inform future diagnostic and therapeutic approaches.

Ultimately, this research not only advances our understanding of depression’s neural underpinnings but also highlights the promise of EEG microstate analysis in enhancing our ability to diagnose, treat, and comprehend the neural intricacies of depression.


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