Previous studies have shown that patients with schizophrenia and bipolar disorder have deficits in cortical inhibition. Through the combination of interleaved transcranial magnetic stimulation and electroencephalography, we have recently reported on methods in which cortical inhibition can be measured from the dorsolateral prefrontal cortex, a cortical region that is more closely associated with the pathophysiology of schizophrenia. Furthermore, it is possible to index cortical inhibition of specific oscillatory frequencies including the gamma band (30-50 Hz) whose modulation has been related to higher order cortical processing. In this study, we show that patients with schizophrenia have significant deficits of cortical inhibition of gamma oscillations in the dorsolateral prefrontal cortex compared to healthy subjects and patients with bipolar disorder, while no deficits are demonstrated in the motor cortex. These results suggest that the lack of inhibition of gamma oscillations in the dorsolateral prefrontal cortex may represent an important frontal neurophysiological deficit, which may be responsible for the spectrum of deficits commonly found in schizophrenia.

IMPORTANCE Magnetic seizure therapy (MST) is a novel therapeutic option for treatment-resistant depression (TRD). Suicidal ideation is often associated with TRD and contributes to the increased mortality and morbidity of the disorder. OBJECTIVE To identify a biomarker that may serve as an indicator of remission of suicidal ideation following a course of MST by using cortical inhibition measures from interleaved transcranial magnetic stimulation and electroencephalography (TMS-EEG). DESIGN, SETTING, AND PARTICIPANTS Thirty-three patients with TRD were part of an open-label clinical trial of MST treatment. Data from 27 patients (82%) were available for analysis in this study. Baseline TMS-EEG measures were assessed within 1 week before the initiation of MST treatment using the TMS-EEG measures of cortical inhibition (ie, N100 and long-interval cortical inhibition [LICI]) from the left dorsolateral prefrontal cortex and the left motor cortex, with the latter acting as a control site. INTERVENTIONS The MST treatments were administered under general anesthesia, and a stimulator coil consisting of 2 individual cone-shaped coils was used. MAIN OUTCOMES AND MEASURES Suicidal ideation was evaluated before initiation and after completion of MST using the Scale for Suicide Ideation (SSI). Measures of cortical inhibition (ie, N100 and LICI) from the left dorsolateral prefrontal cortex were selected. N100 was quantified as the amplitude of the negative peak around 100 milliseconds in the TMS-evoked potential (TEP) after a single TMS pulse. LICI was quantified as the amount of suppression in the double-pulse TEP relative to the single-pulse TEP. RESULTS Of the 27 patients included in the analyses, 15 (56%) were women; mean (SD) age of the sample was 46.0 (15.3) years. At baseline, patients had a mean SSI score of 9.0 (6.8), with 8 of 27 patients (30%) having a score of 0. After completion of MST, patients had a mean SSI score of 4.2 (6.3) (pre-post treatment mean difference, 4.8 [6.7]; paired t 26 = 3.72; P = .001), and 18 of 27 individuals (67%) had a score of 0 for a remission rate of 53%. The N100 and LICI in the frontal cortex-but not in the motor cortex-were indicators of remission of suicidal ideation with 89% accuracy, 90% sensitivity, and 89% specificity (area under the curve, 0.90; P = .003). CONCLUSIONS AND RELEVANCE These results suggest that cortical inhibition may be used to identify patients with TRD who are most likely to experience remission of suicidal ideation following a course of MST. Stronger inhibitory neurotransmission at baseline may reflect the integrity of transsynaptic networks that are targeted by MST for optimal therapeutic response.

Gamma (g)-oscillations (30-50 Hz) represent important electrophysiological measures, which are generated through the execution of higher order cognitive tasks (eg, working memory) in the dorsolateral prefrontal cortex (DLPFC). By contrast, cortical inhibition (CI) refers to a neurophysiological process in which GABAergic inhibitory interneurons selectively suppress the activation of other neurons in the cortex. Recently, abnormalities in both CI and g-oscillations have been associated with various neuropsychiatric disorders including schizophrenia. Animal research suggests that suppression of g-oscillations is, in part, mediated through GABAergic inhibitory neurotransmission. However, no such evidence has been demonstrated in human, largely because of technological limitations. Recently, we reported on novel methods permitting the recording of CI from the DLPFC through transcranial magnetic stimulation (TMS) combined with electroencephalography (EEG). The aim of this study was to examine the effects of GABAergic inhibitory neurotransmission on g-oscillations by combining TMS with EEG. Long interval cortical inhibition (LICI), a paired TMS paradigm, was used to index GABA B receptor mediated inhibitory neurotransmission in the motor cortex and DLPFC of healthy individuals. g-Oscillations were significantly inhibited by LICI (38.1±26.5%; pp0.013) in the DLPFC but not in the motor cortex. These results provide neurophysiological evidence to demonstrate g-oscillations are inhibited by LICI in the DLPFC but not in the motor cortex. Such specificity suggests that the modulation of g-oscillations may represent an important neurophysiological process that may, in part, be responsible for optimal DLPFC functioning in healthy human subjects.

Cortical inhibition (CI) is measured by transcranial magnetic stimulation (TMS) combined with electromyography (EMG) through long-interval CI (LICI) and cortical silent period (CSP) paradigms. Recently, we illustrated that LICI can be measured from the dorsolateral prefrontal cortex (DLPFC) through combined TMS with electroencephalography (EEG). We further demonstrated that LICI had different effects on cortical oscillations in the DLPFC compared with motor cortex. The purpose of this study was to establish the validity and reliability of TMS-EEG indices of CI and to replicate our previous findings in an extended sample. The validity of TMS-EEG was examined by evaluating its relationship to standard EMG measures of LICI and the CSP in the left motor cortex in 36 and 16 subjects, respectively. Test-retest reliability was examined in 14 subjects who returned for a repeat session within 7 days of the first session. LICI was applied to the left DLPFC in 30 subjects to compare LICI in the DLPFC with that in the motor cortex. In the motor cortex, EEG measures of LICI correlated with EMG measures of LICI and CSP. All indices of LICI showed high test-retest reliability in motor cortex and DLPFC. Gamma and beta oscillations were significantly inhibited in the DLPFC but not in the motor cortex, confirming previous findings in an extended sample. These findings demonstrate that indexing LICI through TMS combined with EEG is a valid and reliable method to evaluate inhibition from motor and prefrontal regions.

IMPORTANCE Social and economic costs of depression are exacerbated by prolonged periods spent identifying treatments that would be effective for a particular patient. Thus, a tool that reliably predicts an individual patient's response to treatment could significantly reduce the burden of depression. OBJECTIVE To estimate how accurately an outcome of escitalopram treatment can be predicted from electroencephalographic (EEG) data on patients with depression. DESIGN, SETTING, AND PARTICIPANTS This prognostic study used a support vector machine classifier to predict treatment outcome using data from the first Canadian Biomarker Integration Network in Depression (CAN-BIND-1) study. The CAN-BIND-1 study comprised 180 patients (aged 18-60 years) diagnosed with major depressive disorder who had completed 8 weeks of treatment. Of this group, 122 patients had EEG data recorded before the treatment; 115 also had EEG data recorded after the first 2 weeks of treatment. INTERVENTIONS All participants completed 8 weeks of open-label escitalopram (10-20 mg) treatment. MAIN OUTCOMES AND MEASURES The ability of EEG data to predict treatment outcome, measured as accuracy, specificity, and sensitivity of the classifier at baseline and after the first 2 weeks of treatment. The treatment outcome was defined in terms of change in symptom severity, measured by the Montgomery-Åsberg Depression Rating Scale, before and after 8 weeks of treatment. A patient was designated as a responder if the Montgomery-Åsberg Depression Rating Scale score decreased by at least 50% during the 8 weeks and as a nonresponder if the score decrease was less than 50%. RESULTS Of the 122 participants who completed a baseline EEG recording (mean [SD] age, 36.3 [12.7] years; 76 [62.3%] female), the classifier was able to identify responders with an estimated accuracy of 79.2% (sensitivity, 67.3%; specificity, 91.0%) when using only the baseline EEG data. For a subset of 115 participants who had additional EEG data recorded after the first 2 weeks of treatment, use of these data increased the accuracy to 82.4% (sensitivity, 79.2%; specificity, 85.5%). CONCLUSIONS AND RELEVANCE These findings demonstrate the potential utility of EEG as a treatment planning tool for escitalopram therapy. Further development of the classification tools presented in this study holds the promise of expediting the search for optimal treatment for each patient.