Quick summary: A systematic review of 30 studies suggests that background brain activity measured with EEG may help clinicians track how people with depression or schizophrenia respond to treatment. The signals shifted with medication and clinical state, making them more useful for monitoring individual change than for diagnosis. If confirmed, this could cut the trial and error many patients face when finding the right therapy.
People living with schizophrenia or depression often face trial and error when finding the right treatment, as clinicians currently rely mainly on symptom reports that can shift from day to day. New evidence suggests that certain background patterns in everyday brain activity, measured simply with EEG, may offer a clearer view of how the brain is responding to therapy over time. These signals appear more useful for tracking individual change than for assigning a fixed diagnosis.
“The motivation for this project was to identify biomarkers for response to treatments in psychiatry”, said Dr Roger S. McIntyre, professor of psychiatry and pharmacology at the University of Toronto and chairman and executive director of the Brain and Cognition Discovery Foundation.
A systematic review published in Psychiatry and Clinical Neurosciences examined 30 studies covering nearly 2300 adults with schizophrenia spectrum disorders, bipolar disorder, major depressive disorder or treatment resistant depression. The work focused on aperiodic EEG activity, the scale free one over f component of the power spectrum that sits beneath the more familiar brain waves. Researchers typically describe this activity with a slope or exponent and an offset, which are thought to reflect broad features of cortical population dynamics and the balance between excitation and inhibition.
In schizophrenia spectrum disorders the picture was mixed. Several studies found steeper slopes or higher offsets than in healthy people, and some linked reduced flexibility in these signals over time to more severe positive symptoms. Task related recordings and measures of temporal change often showed stronger ties to clinical features than quiet resting state scans alone.
Studies of major depressive disorder and treatment resistant depression told a more consistent story. Flatter slopes and lower offsets appeared more often, especially over central and posterior scalp regions, and similar patterns turned up during sleep. These measures also shifted with treatment. Short term exposure to ketamine or esketamine tended to flatten the slope further, whilst seizure based approaches such as electroconvulsive therapy were linked to steeper slopes. Intracranial recordings in smaller groups connected aperiodic changes in regions such as the subcallosal cingulate and ventromedial prefrontal cortex to the severity of depressive symptoms.
For McIntyre, the biggest takeaway is that “we believe we have differences in the effect of drugs on the electrophysiology of the brain”.
Evidence for bipolar disorder remained limited, drawn mainly from mixed samples or single treatment cohorts, so no clear disorder specific pattern could be defined. Across all three groups the review found that aperiodic parameters responded to clinical state, medication and recording context. This sensitivity supports their potential as within person markers of cortical change rather than as reliable separators between diagnostic categories.
The authors note that methods varied widely across the included studies, from frequency ranges and analysis algorithms to whether recordings were made at rest, during tasks or in sleep. Such differences made direct comparison difficult and ruled out a quantitative meta analysis. They argue that future work needs more consistent approaches, longer term sampling and direct checks against underlying brain chemistry before the signals can move into routine clinical use.
McIntyre said: “The next steps now are to replicate the findings and compare the findings with other research studies.”
If aperiodic EEG activity can be measured reliably, it may help clinicians monitor how an individual’s brain is responding to a given treatment and adjust care more precisely. For people living with these conditions that could mean fewer months spent waiting to see whether a new approach is truly helping.
