For over a century, mental health diagnoses and treatments have relied on subjective observations and patient-reported symptoms. However, the field is shifting towards a data-driven approach known as "precision psychiatry," which aims to personalize mental healthcare for more effective and tolerable treatments. A key component of this approach involves the use of biological measures, or biomarkers, to identify and differentiate subtypes of psychiatric conditions.
The Rise of ERPs as Reliable Biomarkers
Among the various biomarkers under investigation, event-related potentials (ERPs) are showing significant promise. ERPs are functional brain measurements collected through task-related brain activity evident in the electroencephalogram (EEG). These neural biomarkers have demonstrated high test-retest reliability and interpretability across various mental health conditions. For example, ERPs are associated with specific subtypes of depression and can accurately predict the course of depression and the outcomes of particular treatments.
Historical Context and Recent Findings
ERPs have been studied since the 1960s, primarily in psychological and academic research. In recent years, ERP biomarkers have provided insights into mental health conditions such as schizophrenia. Promising ERP biomarkers of depression have focused on patients’ brain responses to rewards, emotional content, decision-making, and attention. These ERPs have been linked to depression and have accurately predicted individuals’ risk for depression and its development over time.
A 2023 study of adolescents with depression found that an ERP associated with the response to emotional stimuli predicted a response to cognitive behavioral therapy, suggesting its potential as a neural biomarker for predicting outcomes in adolescent depression. A 2019 meta-analysis in the Annual Review of Clinical Psychology concluded that ERPs can be used clinically to help identify psychopathology and chart the potential development of conditions beginning as early as childhood.
ERPs in Clinical Trials: Advantages Over fMRI
While psychiatry has largely focused on functional magnetic resonance imaging (fMRI) to measure brain activity, ERPs offer several advantages for clinical trials. EEG studies are simpler and less expensive to administer than MRI-based imaging studies. The cost and complexity of MRI make it difficult to scale for broad clinical trial participation. Additionally, MRI requires specialized training and is unsuitable for patients with claustrophobia or metal implants.
Conversely, ERP data is easier and less expensive to capture. EEG devices do not require as much training to operate as MRI machines, and electrodes often do not need conductive gel, making the studies more tolerable for patients. ERP measures of brain function have also proven more reliable than fMRI-based measures. The reliability, speed, cost, and scalability of EEG and ERPs can help pharmaceutical companies develop novel therapies in less time and with fewer resources.
Applications in Clinical Trial Phases
ERPs can be used to measure brain function at every phase of clinical trials. For example, a quick ERP assessment during participant recruitment could promptly identify appropriate participants who would benefit most from a drug under development, ensuring homogeneity among different cohorts and streamlining clinical trials.
The Future of ERPs in Mental Health
Technological progress has simplified EEG studies and ERP data analysis, making these biomarkers more affordable, scalable, and easy to use for clinicians and patients. Experts anticipate that ERPs will become more incorporated in mental health clinical trials in 2025, moving from academic labs to real-world applications in the emerging field of precision psychiatry. According to Greg Hajcak, Ph.D., chief scientific officer of Universal Brain, "The time is right for ERPs to move from academic labs to real-world import. It is hopeful, if not likely, that ERPs will emerge in the coming years as a standard method of assessing brain function within the emerging and exciting field of precision psychiatry."
