Electroencephalographic biomarkers of psychosis: present and future.

Commentary Biological Psychiatry Electroencephalographic Biomarkers of Psychosis: Present and Future Gregory A. Light and Scott Makeig “Psychiatry is a young, still developing science that must, against sharp opposition, gradually achieve the position it deserves according to its scientiﬁc and practical importance. There is no doubt that it will achieve this position—for it has at its disposal the same weapons which have served the other branches of medicine so well: clinical observation, the microscope and experimentation” (1). The extent to which schizophrenia (SZ) and psychotic bipolar disorder (BD) represent distinct illnesses has been the focus of debate since Kraepelin and Blueler’s early descriptions of dementia praecox and manic depressive insanity. Their hope, expressed more than a century ago, was that the tools of neuroscience at the time (“clinical observation, the microscope and experimentation”) would lead to improved understanding and treatments of these devastat- ing disorders. In the past century, spectacular advances have occurred at the intersections of neuroscience, psychopharma- cology, and genomics. However, few, if any, laboratory tests to inform diagnoses, guide treatments, and monitor response to interventions have graduated from laboratories to clinics. Clinicians still must rely on behavioral observation and careful interview techniques to make inferences about patients’ inner experiences and deductions about the impacted neural sys- tems. Although we have reﬁned indirect clinical assessments for diagnosis and treatment, these methods have evolved relatively little since the late 19th century. In this issue of Biological Psychiatry, Ethridge et al. (2) from the Bipolar-Schizophrenia Network on Intermediate Pheno- types (B-SNIP) provide a sophisticated characterization of response to auditory deviance in a heterogeneous sample of 940 patients with SZ, patients with BD, and ﬁrst-degree family members tested at ﬁve geographically distributed sites. Such large and diverse participant cohorts provide substantial conﬁdence in the robustness and generalizability of neuro- physiologic ﬁndings of familial risk as a prelude to genetic analyses. The authors apply a novel approach to examining evoked electroencephalography (EEG) responses to deviant auditory (“oddball”) stimuli interleaved in a train of standard tones. Although most endophenotype studies assess only a single diagnostic group, the B-SNIP group uncovered strong evidence of both shared and unique deﬁcits in sensory and cognitive processes across psychotic disorders. In particular, some of the biomarkers of familial risk (N100, P3b) were more speciﬁc to SZ, whereas another response abnormality (P2) was speciﬁc to BD, and another (N2) was common to both psychoses. This landmark B-SNIP study by Ethridge et al. begins to address some long-standing limitations of traditional EEG analysis. Their results support the increasingly tangible possibility of integrating neurophysiologic biomarkers into 21st century diagnostics and therapeutics and add to accumulating evidence that understanding and treatment of varying psy- chotic states of individual patients may be improved in the near future using low-cost, EEG measures sensitive to the underlying neurobiology of SZ and BD. EEG Sources and EEG Scalp Channels Well-established biophysics of brain volume conduction dic- tate that currents recorded at scalp channels do not ﬂow directly upward from underlying cortex. Rather, nearly every scalp electrode sums potentials from nearly every cortical source area. The difﬁculty in deriving accurate estimates of the brain sources of recorded scalp channel potentials is the primary reason that EEG has been denigrated as being a low‐ resolution brain imaging modality despite its superior time resolution and other desirable qualities. However, most clinical studies focus on a single frontocentral electrode channel at which both peak amplitudes and patient deﬁcits tend to be largest—even when scalp-channel information is available from multiple sensors. To attempt to use more of this now readily available EEG information, Ethridge et al. employ principal component ana- lysis (PCA) to distill objectively averaged event-related poten- tial responses into distinct elements with forthcoming genomic analyses of PCA–derived EEG endophenotypes. PCA capita- lizes on spatial relationships across sensors, reducing both noise and redundant scalp-channel information to a few variables that capture as much of the trial-averaged response variance as possible. Toward More Robust EEG Biomarkers In our view, the measurement advance of Ethridge et al. represents a ﬁrst step toward extracting more information about cortical function available in EEG. Future studies of this and other rich psychiatric EEG datasets may wish to capitalize on information about cortical source-level response dynamics available via decomposition of the unaveraged multichannel EEG signals into spatiotemporally and functionally distinct source signals. As is well known, raw EEG data include and may even be dominated by nonphysiologic noise (e.g., line noise, electrode movement artifacts) plus potentials contrib- uted by nonbrain physiological processes (e.g., muscle activ- ity, eye blinks and saccades). Dealing with nonbrain artifacts can be particularly difﬁcult in clinical samples. Brain‐generated contributions to EEG signals predominantly sum far-ﬁeld potentials arising from locally coherent cortical ﬁeld activities within small cortical areas that function as effective EEG sources. SEE COMPANION ARTICLE ON PAGE 127 http://dx.doi.org/10.1016/j.biopsych.2014.11.002 ISSN: 0006-3223 Published by Elsevier Inc on behalf of Society of Biological Psychiatry Biological Psychiatry January, 2015; 77:87–89 www.sobp.org/journal