Researchers continue to search for reliable ways to predict which patients will respond to ketamine for treatment-resistant depression. As advances in interventional psychiatry continue to reshape the field, a new study suggests that complex brain activity measured with electroencephalography (EEG) could provide valuable clues about treatment response before clinical improvement becomes fully apparent.
Although ketamine has transformed the treatment landscape for many individuals with depression that has not responded to conventional therapies, a substantial number of patients experience limited benefit. Identifying biological markers that distinguish responders from nonresponders remains one of the most important goals in modern psychiatric research.
The Challenge Of Predicting Ketamine Response
Intravenous ketamine can produce antidepressant effects within hours, a dramatic contrast to the weeks often required for traditional antidepressants. Despite these rapid benefits, clinicians currently have few objective tools to determine which patients are most likely to improve.
Most previous neuroimaging studies have focused on connections between pairs of brain regions. While these approaches have expanded understanding of depression, they may overlook the far more complex communication that occurs across multiple brain networks simultaneously.
The new investigation explored whether higher-order interactions between several brain regions could provide a more informative picture of how ketamine changes brain function.
Ketamine EEG Biomarkers Capture Complex Brain Activity
The study analyzed data from a randomized, double-blind clinical trial involving 30 older military veterans with treatment-resistant depression. Participants received either a single 40 minute intravenous ketamine infusion at varying doses or the active comparator midazolam.
Researchers collected resting-state EEG recordings and mismatch negativity measurements before treatment and again one hour, 24 hours, and seven days after infusion.
Instead of examining only traditional connectivity measures, investigators used a mathematical framework known as O-information. This approach evaluates higher-order interactions, measuring whether groups of brain regions work together through redundancy or synergy rather than simply analyzing pairs of regions.
This method allows researchers to quantify large-scale information processing that may better reflect how the human brain coordinates complex cognitive and emotional functions.
Why Higher-Order Brain Networks Matter
Depression affects multiple interconnected neural systems rather than isolated brain regions. Higher-order interaction analysis attempts to capture this complexity by evaluating coordinated activity across three or more regions simultaneously.
The investigators observed dynamic changes following ketamine treatment that evolved over the course of a week. The strongest effects appeared one hour after infusion within the alpha frequency band before shifting toward theta activity at 24 hours. By the seventh day, changes partially reappeared within beta and gamma frequency bands.
These evolving patterns suggest that ketamine produces a staged reorganization of large-scale brain communication rather than a single short-lived neurological event.
Brain Changes Were Linked To Clinical Improvement
One of the study’s most intriguing findings involved alpha-band redundancy measured 24 hours after ketamine administration.
Patients who demonstrated larger increases in this higher-order brain activity experienced greater improvement in depressive symptoms by Day 7. Although the analysis was exploratory, the relationship suggests that these EEG measurements may eventually serve as functional biomarkers for antidepressant response.
The investigators also found that several EEG features correlated with acute dissociative symptoms, an expected effect of ketamine treatment. Importantly, some of these associations remained statistically significant even after correction for multiple comparisons, indicating that the observed neural changes were unlikely to be random findings.
A Different Way To Study Ketamine’s Effects
Much of the existing ketamine literature emphasizes neurotransmitters, receptor biology, or conventional functional connectivity. This research instead focuses on how large networks of brain regions exchange information during recovery from depression.
By applying multivariate information theory to EEG recordings, the investigators captured nonlinear interactions that standard connectivity analyses often miss. These measurements provide a broader perspective on brain organization and may offer greater sensitivity to treatment-induced changes.
Because EEG is widely available, relatively inexpensive, and noninvasive, this approach could become more practical for future clinical applications than advanced neuroimaging techniques that require specialized equipment.
Implications For Precision Psychiatry
Although additional studies involving larger and more diverse populations will be necessary, these findings support the growing movement toward biomarker-guided psychiatric treatment.
If validated, higher-order EEG analysis could help clinicians identify patients most likely to benefit from ketamine while improving understanding of how rapid antidepressant therapies reorganize brain function over time.
The study also highlights the importance of looking beyond simple brain connectivity toward more sophisticated measures of network communication. As computational neuroscience continues to advance, these methods may become valuable tools for personalizing psychiatric care and accelerating the development of more targeted interventions for treatment-resistant depression.
Citations
Shah K, Herzog R, Swann AC, et al. High-order brain interactions during ketamine-induced state changes: A functional marker of response in late-life treatment-resistant depression? Molecular Psychiatry. 2026. PubMed: https://pubmed.ncbi.nlm.nih.gov/42401545/
Shah K, Herzog R, Swann AC, et al. High-order brain interactions during ketamine-induced state changes: A functional marker of response in late-life treatment-resistant depression? Molecular Psychiatry. DOI: https://doi.org/10.1038/s41398-026-04212-1
Explore more at https://www.interventionalpsychiatry.org/