The eternal promise of EEG-based biomarkers: Getting closer?

Neurobehavioral Biomarkers: An EEG Family Reunion

SUMMARY

The field of clinical EEG has had an uneasy relationship with the use of this technology for clinical cognitive applications and often for good reason. However, apart from its clinical use, EEG has had a tradition as a major tool in cognitive psychology and cognitive neuroscience dating back at least to the 1960s. Based on accumulated knowledge from its research application, EEG-based biomarkers are beginning to see applications in clinical trials and may eventually enter clinical care. We address concerns surrounding quality control, the treatment of artifact, and normal variants and how developments in engineering, biomarker validation, and implementation science rigorously applied to these tools can lead to well-justified approaches.

Quantitative EEG improves prediction of Sturge-Weber syndrome in infants with port-wine birthmark

OBJECTIVE

Port-wine birthmark (PWB) is a common occurrence in the newborn, and general pediatricians, dermatologists, and ophthalmologists are often called on to make an assessment of risk for Sturge-Weber syndrome (SWS) due to workforce shortages in pediatric neurologists and MRI's low sensitivity for SWS brain involvement in infants. We therefore aimed to develop a quantitative EEG (qEEG) approach to safely screen young infants with PWB for SWS risk and optimal timing of diagnostic MRI.

METHODS

Forty-eight infants (prior to first birthday) underwent EEG recording. Signal processing methods compared voltage between left and right sides using a previously defined pipeline and diagnostic threshold. In this test sample, we compared sensitivity/specificity of the qEEG metric against MRI performed after the first birthday. We also used likelihood ratio testing to determine whether qEEG adds incremental information beyond topographical extent of PWB, another risk marker of brain involvement.

RESULTS

qEEG helped predict SWS risk in the first year of life (p = 0.031), with a sensitivity of 50% and a specificity of 81%. It added about 40% incremental information beyond PWB extent alone (p = 0.042).

CONCLUSION

qEEG adds information to risk prediction in infants with facial PWB.

SIGNIFICANCE

qEEG can be used to help determine whether to obtain an MRI in the first year of life. The data collected can assist in developing a predictive model risk calculator that incorporates both PWB extent and qEEG results, which can be validated and then employed in the community.

Associations between Task-Related Modulation of Motor-Evoked Potentials and EEG Event-Related Desynchronization in Children with ADHD

Children with attention-deficit/hyperactivity disorder (ADHD) have previously shown a decreased magnitude of event-related desynchronization (ERD) during a finger-tapping task, with a large between-group effect. Because the neurobiology underlying several transcranial magnetic stimulation (TMS) measures have been studied in multiple contexts, we compared ERD and 3 TMS measures (resting motor threshold [RMT], short-interval cortical inhibition [SICI], and task-related up-modulation [TRUM]) within 14 participants with ADHD (ages 8-12 years) and 17 control children. The typically developing (TD) group showed a correlation between greater RMT and greater magnitude of alpha (10-13 Hz, here) ERD, and there was no diagnostic interaction effect, consistent with a rudimentary model of greater needed energy input to stimulate movement. Similarly, inhibition measured by SICI was also greater in the TD group when the magnitude of movement-related ERD was higher; there was a miniscule diagnostic interaction effect. Finally, TRUM during a response-inhibition task showed an unanticipated pattern: in TD children, the greater TMS task modulation (TRUM) was associated with a smaller magnitude of ERD during finger-tapping. The ADHD group showed the opposite direction of association: Greater TRUM was associated with larger magnitude of ERD. Prior EEG results have demonstrated specific alterations of task-related modulation of cortical physiology, and the current results provide a fulcrum for multimodal study.

BIOMARKERS AND NEUROBEHAVIORAL DIAGNOSIS

Our current diagnostic methods for treatment planning in Psychiatry and Neurodevelopmental Disabilities leave room for improvement, and null results in clinical trials in these fields may be a result of insufficient tools for patient stratification. Great hope has been placed in novel technologies to improve clinical and trial outcomes, but we have yet to see a substantial change in clinical practice. As we examine attempts at biomarker validation within these fields, we find that it may be the diagnoses themselves that fall short. We now need to improve neuropsychiatric nosologies with a focus on validity based not solely on behavioral features, but on a synthesis that includes genetic and biological data as well. The eventual goal is diagnostic biomarkers and diagnoses themselves based on distinct mechanisms, but such an understanding of the causal relationship across levels of analysis is likely to be elusive for some time. Rather, we propose an approach in the near-term that deconstructs diagnosis into a series of independent, empiric and clinically relevant associations among a single, defined patient group, a single biomarker, a single intervention and a single clinical outcome. Incremental study across patient groups, interventions, outcomes and modalities will lead to a more interdigitated network of knowledge, and correlations in metrics across levels of analysis will eventually give way to the causal understanding that will allow for mechanistically based diagnoses.

Conceptual, Regulatory and Strategic Imperatives in the Early Days of EEG-Based Biomarker Validation for Neurodevelopmental Disabilities

Biological treatment development for syndromal neuropsychiatric conditions such as autism has seen slow progress for decades. Speeding drug discovery may result from the judicious development and application of biomarker measures of brain function to select patients for clinical trials, to confirm target engagement and to optimize drug dose. For neurodevelopmental disorders, electrophysiology (EEG) offers considerable promise because of its ability to monitor brain activity with high temporal resolution and its more ready application for pediatric populations relative to MRI. Here, we discuss conceptual/definitional issues related to biomarker development, discuss practical implementation issues, and suggest preliminary guidelines for validating EEG approaches as biomarkers with a context of use in neurodevelopmental disorder drug development.