Amphetamine increases motivation of humans and mice as measured by breakpoint, but does not affect an Electroencephalographic biomarker.

Translation of drug targets from preclinical studies to clinical trials has been aided by cross-species behavioral tasks, but evidence for brain-based engagement during task performance is still required. Cross-species progressive ratio breakpoint tasks (PRBTs) measure motivation-related behavior and are pharmacologically and clinically sensitive. We recently advanced elevated parietal alpha power as a cross-species electroencephalographic (EEG) biomarker of PRBT engagement. Given that amphetamine increases breakpoint in mice, we tested its effects on breakpoint and parietal alpha power in both humans and mice. Twenty-three healthy participants performed the PRBT with EEG after amphetamine or placebo in a double-blind design. C57BL/6J mice were trained on PRBT with EEG (n = 24) and were treated with amphetamine or vehicle. A second cohort of mice was trained on PRBT without EEG (n = 40) and was treated with amphetamine or vehicle. In humans, amphetamine increased breakpoint. In mice, during concomitant EEG, 1 mg/kg of amphetamine significantly decreased breakpoint. In cohort 2, however, 0.3 mg/kg of amphetamine increased breakpoint consistent with human findings. Increased alpha power was observed in both species as they reached breakpoint, replicating previous findings. Amphetamine did not affect alpha power in either species. Amphetamine increased effort in humans and mice. Consistent with previous reports, elevated parietal alpha power was observed in humans and mice as they performed the PRBT. Amphetamine did not affect this EEG biomarker of effort. Hence, these findings support the pharmacological predictive validity of the PRBT to measure effort in humans and mice and suggest that this EEG biomarker is not directly reflective of amphetamine-induced changes in effort.

The Strength of Alpha Oscillations in the Electroencephalogram Differently Affects Algorithms Used for Anesthesia Monitoring.

BACKGROUND: Intraoperative patient monitoring using the electroencephalogram (EEG) can help to adequately adjust the anesthetic level. Therefore, the processed EEG (pEEG) provides the anesthesiologist with the estimated anesthesia level. The commonly used approaches track the changes from a fast- and a low-amplitude EEG during wakefulness to a slow- and a high-amplitude EEG under general anesthesia. However, besides these changes, another EEG feature, a strong oscillatory activity in the alpha band (8-12 Hz), develops in the frontal EEG. Strong alpha-band activity during general anesthesia seems to reflect an appropriate anesthetic level for certain anesthetics, but the way the common pEEG approaches react to changes in the alpha-band activity is not well explained. Hence, we investigated the impact of an artificial alpha-band modulation on pEEG approaches used in anesthesia research. METHODS: We performed our analyses based on 30 seconds of simulated sedation (n = 25) EEG, simulated anesthesia (n = 25) EEG, and EEG episodes from 20 patients extracted from a steady state that showed a clearly identifiable alpha peak in the density spectral array (DSA) and a state entropy (GE Healthcare) around 50, indicative of adequate anesthesia. From these traces, we isolated the alpha activity by band-pass filtering (8-12 Hz) and added this alpha activity to or subtracted it from the signals in a stepwise manner. For each of the original and modified signals, the following pEEG values were calculated: (1) spectral edge frequency (SEF95), (2) beta ratio, (3) spectral entropy (SpEntr), (4) approximate entropy (ApEn), and (5) permutation entropy (PeEn). RESULTS: The pEEG approaches showed different reactions to the alpha-band modification that depended on the data set and the amplification step. The beta ratio and PeEn decreased with increasing alpha activity for all data sets, indicating a deepening of anesthesia. The other pEEG approaches behaved nonuniformly. SEF95, SpEntr, and ApEn decreased with increasing alpha for the simulated anesthesia data (arousal) but decreased for simulated sedation. For the patient EEG, ApEn indicated an arousal, and SEF95 and SpEntr showed a nonuniform change. CONCLUSIONS: Changes in the alpha-band activity lead to different reactions for different pEEG approaches. Hence, the presence of strong oscillatory alpha activity that reflects an adequate level of anesthesia may be interpreted differently, by an either increasing (arousal) or decreasing (deepening) pEEG value. This could complicate anesthesia navigation and prevent the adjustment to an adequate, alpha-dominant anesthesia level, when titrating by the pEEG values.

Tracking transient changes in the intrinsic neural frequency architecture: Oxytocin facilitates non-harmonic relationships between alpha and theta rhythms in the resting brain.

Shifts in the peak frequencies of oscillatory neural rhythms have been put forward as a principal mechanism by which cross-frequency coupling and decoupling is implemented in the brain. This notion is based on the mathematical reality that neural oscillations can only fully synchronize when their peak frequencies form harmonic 2:1 relationships (e.g., f2=f1/2). Non-harmonic cross-frequency relationships, on the other hand (based on the irrational golden mean 1.618.:1), provide the highest physiologically possible desynchronized state (reducing the occurrence of spurious, noisy, background coupling), and are therefore anticipated to characterize the resting state of the brain, in which no selective information processing takes place. The present study sought to assess whether the transient occurrence of 1.6:1 non-harmonic and 2:1 harmonic relationships between peak frequencies in the alpha (8-14 Hz) and theta (4-8 Hz) bands - respectively facilitating states of decoupling or coupling between oscillatory rhythms - are impacted by the intranasal administration of a single-dose of oxytocin (OT) or placebo. To do so, continuous resting-state electroencephalography (5 min eyes open, 19 electrodes) was obtained from 96 healthy adult men before and after nasal spray administration. The transient formation of non-harmonic cross-frequency configurations between alpha and theta peak frequencies was significantly increased after OT nasal spray administration, indicating an effect of OT on reducing the intrinsic occurrence of spurious (noisy) background phase synchronizations during resting-state. As a group, the OT group also showed a significant parallel increase in high-frequency and decrease in low-frequency heart rate variability, confirming a homeostatic role of OT in balancing parasympathetic drive. Overall, non-harmonic cross-frequency configurations have been put forward to lay the ground for a healthy neural network allowing the opportunity for an efficient transition from resting state to activity. The observed effects of OT on cross-frequency dynamics are therefore interpreted to reflect a homeostatic role of OT in increasing the signal-to-noise properties of the intrinsic EEG neural frequency architecture, i.e., by precluding the occurrence of 'noisy', unwanted, spurious couplings among neural rhythms in the resting brain.

Valproate but not levetiracetam slows the EEG alpha peak frequency - A pharmaco-EEG study.

OBJECTIVE: Studies of the effect of valproate (VPA) on the background EEG have shown varying results. Therefore, we compared the effect of VPA and levetiracetam (LEV) on the EEG alpha peak frequency (APF). METHODS: We retrospectively examined the APF in resting-state EEG of patients undergoing inpatient video-EEG monitoring (VEM) during withdrawal of VPA or LEV. We assessed APF trends by computing linear fits across individual patients' APF as a function of consecutive days, and correlated the APF and daily antiseizure medication (ASM) doses on a single-patient and group level. RESULTS: The APF in the VPA-group significantly increased over days with falling VPA doses (p = 0.005, n = 13), but did not change significantly in the LEV-group (p = 0.47, n = 18). APF correlated negatively with daily ASM doses in the VPA-group (average of r = -0.74 ± 0.12 across patients, p = 0.0039), but not in the LEV-group (average of r = -0.17 ± 0.18 across patients, p = 0.4072). CONCLUSIONS: Our results suggest that VPA treatment slows the APF. This APF reduction correlates with the daily dose of VPA and is not present in LEV treatment. SIGNIFICANCE: Our study identifies a VPA-related slowing of the APF even in patients without electroencephalographic or overt clinical signs of encephalopathy.

Measuring the effects of first antiepileptic medication in Temporal Lobe Epilepsy: Predictive value of quantitative-EEG analysis.

OBJECTIVE: To determine the quantitative EEG responses in a population of drug-naïve patients with Temporal Lobe Epilepsy (TLE) after Levetiracetam (LEV) initiation as first antiepileptic drug (AED). We hypothesized that the outcome of AED treatment can be predicted from EEG data in patients with TLE. METHODS: Twenty-three patients with TLE and twenty-five healthy controls were examined. Clinical outcome was dichotomized into seizure-free (SF) and non-seizure-free (NSF) after two years of LEV. EEG parameters were compared between healthy controls and patients with TLE at baseline (EEGpre) and after three months of AED therapy (EEGpre-post) and between SF and NSF patients. Receiver Operating Characteristic curves models were built to test whether EEG parameters predicted outcome. RESULTS: AED therapy induces an increase in EEG power for Alpha (p = 0.06) and a decrease in Theta (p < 0.05). Connectivity values were lower in SF compared to NSF patients (p < 0.001). Quantitative EEG predicted outcome after LEV treatment with an estimated accuracy varying from 65.2% to 91.3% (area under the curve [AUC] = 0.56-0.93) for EEGpre and from 69.9% to 86.9% (AUC = 0.69-0.94) for EEGpre-post. CONCLUSIONS: AED therapy induces EEG modifications in TLE patients, and such modifications are predictive of clinical outcome. SIGNIFICANCE: Quantitative EEG may help understanding the effect of AEDs in the central nervous system and offer new prognostic biomarkers for patients with epilepsy.

The influence of induction speed on the frontal (processed) EEG.

The intravenous injection of the anaesthetic propofol is clinical routine to induce loss of responsiveness (LOR). However, there are only a few studies investigating the influence of the injection rate on the frontal electroencephalogram (EEG) during LOR. Therefore, we focused on changes of the frontal EEG especially during this period. We included 18 patients which were randomly assigned to a slow or fast induction group and recorded the frontal EEG. Based on this data, we calculated the power spectral density, the band powers and band ratios. To analyse the behaviour of processed EEG parameters we calculated the beta ratio, the spectral entropy, and the spectral edge frequency. Due to the prolonged induction period in the slow injection group we were able to distinguish loss of responsiveness to verbal command (LOvR) from loss of responsiveness to painful stimulus (LOpR) whereas in the fast induction group we could not. At LOpR, we observed a higher relative alpha and beta power in the slow induction group while the relative power in the delta range was lower than in the fast induction group. When concentrating on the slow induction group the increase in relative alpha power pre-LOpR and even before LOvR indicated that frontal EEG patterns, which have been suggested as an indicator of unconsciousness, can develop before LOR. Further, LOvR was best reflected by an increase of the alpha to delta ratio, and LOpR was indicated by a decrease of the beta to alpha ratio. These findings highlight the different spectral properties of the EEG at various levels of responsiveness and underline the influence of the propofol injection rate on the frontal EEG during induction of general anesthesia.

DMT alters cortical travelling waves.

Psychedelic drugs are potent modulators of conscious states and therefore powerful tools for investigating their neurobiology. N,N, Dimethyltryptamine (DMT) can rapidly induce an extremely immersive state of consciousness characterized by vivid and elaborate visual imagery. Here, we investigated the electrophysiological correlates of the DMT-induced altered state from a pool of participants receiving DMT and (separately) placebo (saline) while instructed to keep their eyes closed. Consistent with our hypotheses, results revealed a spatio-temporal pattern of cortical activation (i.e. travelling waves) similar to that elicited by visual stimulation. Moreover, the typical top-down alpha-band rhythms of closed-eyes rest were significantly decreased, while the bottom-up forward wave was significantly increased. These results support a recent model proposing that psychedelics reduce the 'precision-weighting of priors', thus altering the balance of top-down versus bottom-up information passing. The robust hypothesis-confirming nature of these findings imply the discovery of an important mechanistic principle underpinning psychedelic-induced altered states.

Low Frontal Alpha Power Is Associated With the Propensity for Burst Suppression: An Electroencephalogram Phenotype for a "Vulnerable Brain".

BACKGROUND: A number of recent studies have reported an association between intraoperative burst suppression and postoperative delirium. These studies suggest that anesthesia-induced burst suppression may be an indicator of underlying brain vulnerability. A prominent feature of electroencephalogram (EEG) under propofol and sevoflurane anesthesia is the frontal alpha oscillation. This frontal alpha oscillation is known to decline significantly during aging and is generated by prefrontal brain regions that are particularly prone to age-related neurodegeneration. Given that burst suppression and frontal alpha oscillations are both associated with brain vulnerability, we hypothesized that anesthesia-induced frontal alpha power could also be associated with burst suppression. METHODS: We analyzed EEG data from a previously reported cohort in which 155 patients received propofol (n = 60) or sevoflurane (n = 95) as the primary anesthetic. We computed the EEG spectrum during stable anesthetic maintenance and identified whether or not burst suppression occurred during the anesthetic. We characterized the relationship between burst suppression and alpha power using logistic regression. We proposed 5 different models consisting of different combinations of potential contributing factors associated with burst suppression: (1) a Base Model consisting of alpha power; (2) an Extended Mechanistic Model consisting of alpha power, age, and drug dosing information; (3) a Clinical Confounding Factors Model consisting of alpha power, hypotension, and other confounds; (4) a Simplified Model consisting only of alpha power and propofol bolus administration; and (5) a Full Model consisting of all of these variables to control for as much confounding as possible. RESULTS: All models show a consistent significant association between alpha power and burst suppression while adjusting for different sets of covariates, all with consistent effect size estimates. Using the Simplified Model, we found that for each decibel decrease in alpha power, the odds of experiencing burst suppression increased by 1.33-fold. CONCLUSIONS: In this study, we show how a decrease in anesthesia-induced frontal alpha power is associated with an increased propensity for burst suppression, in a manner that captures individualized information above and beyond a patient's chronological age. Lower frontal alpha band power is strongly associated with higher propensity for burst suppression and, therefore, potentially higher risk of postoperative neurocognitive disorders. We hypothesize that low frontal alpha power and increased propensity for burst suppression together characterize a "vulnerable brain" phenotype under anesthesia that could be mechanistically linked to brain metabolism, cognition, and brain aging.

Differential effects of traxoprodil and S-ketamine on quantitative EEG and auditory event-related potentials as translational biomarkers in preclinical trials in rats and mice.

Quantitative Electroencephalography (qEEG) and event-related potential (ERP) assessment have emerged as powerful tools to unravel translational biomarkers in preclinical and clinical psychiatric drug discovery trials. The aim of the present study was to compare the GluN2B negative allosteric modulator (NAM) traxoprodil (CP-101,606) with the unselective NMDA receptor channel blocker S-ketamine to give insight into central target engagement and differentiation on multiple EEG readouts. For qEEG recordings telemetric transmitters were implanted in male Wistar rats. Recorded EEG data were analyzed using fast Fourier transformation to determine power spectra and vigilance states. Additionally, body temperature and locomotor activity were assessed via telemetry. For recordings of auditory event-related potentials (AERP) male C57Bl/6J mice were chronically implanted with deep electrodes using a tethered system. Power spectral analysis revealed a significant increase in gamma power following ketamine treatment, whereas traxoprodil (6&18 mg/kg) induced an overall decrease primarily within alpha and beta bands. Additionally, ketamine disrupted sleep and enhanced time spent in wake vigilance states, whereas traxoprodil did not alter sleep-wake architecture. AERP and mismatch negativity (MMN) revealed that ketamine (10 mg/kg) selectively disrupts auditory deviance detection, whereas traxoprodil (6 mg/kg) did not alter MMN at clinically relevant doses. In contrast to ketamine treatment, traxoprodil did not produce hyperactivity and hypothermia. In conclusion, ketamine and traxoprodil showed very different effects on diverse EEG readouts differentiating selective GluN2B antagonism from non-selective pan-NMDA-R antagonists like ketamine. These readouts are thus perfectly suited to support drug discovery efforts on NMDA-R and understanding the different functions of NMDA-R subtypes.

Cortical Connectivity Moderators of Antidepressant vs Placebo Treatment Response in Major Depressive Disorder: Secondary Analysis of a Randomized Clinical Trial.

Importance: Despite the widespread awareness of functional magnetic resonance imaging findings suggesting a role for cortical connectivity networks in treatment selection for major depressive disorder, its clinical utility remains limited. Recent methodological advances have revealed functional magnetic resonance imaging-like connectivity networks using electroencephalography (EEG), a tool more easily implemented in clinical practice. Objective: To determine whether EEG connectivity could reveal neural moderators of antidepressant treatment. Design, Setting, and Participants: In this nonprespecified secondary analysis, data were analyzed from the Establishing Moderators and Biosignatures of Antidepressant Response in Clinic Care study, a placebo-controlled, double-blinded randomized clinical trial. Recruitment began July 29, 2011, and was completed December 15, 2015. A random sample of 221 outpatients with depression aged 18 to 65 years who were not taking medication for depression was recruited and assessed at 4 clinical sites. Analysis was performed on an intent-to-treat basis. Statistical analysis was performed from November 16, 2018, to May 23, 2019. Interventions: Patients received either the selective serotonin reuptake inhibitor sertraline hydrochloride or placebo for 8 weeks. Main Outcomes and Measures: Electroencephalographic orthogonalized power envelope connectivity analyses were applied to resting-state EEG data. Intent-to-treat prediction linear mixed models were used to determine which pretreatment connectivity patterns were associated with response to sertraline vs placebo. The primary clinical outcome was the total score on the 17-item Hamilton Rating Scale for Depression, administered at each study visit. Results: Of the participants recruited, 9 withdrew after first dose owing to reported adverse effects, and 221 participants (150 women; mean [SD] age, 37.8 [12.7] years) underwent EEG recordings and had high-quality pretreatment EEG data. After correction for multiple comparisons, connectome-wide analyses revealed moderation by connections within and between widespread cortical regions-most prominently parietal-for both the antidepressant and placebo groups. Greater alpha-band and lower gamma-band connectivity predicted better placebo outcomes and worse antidepressant outcomes. Lower connectivity levels in these moderating connections were associated with higher levels of anhedonia. Connectivity features that moderate treatment response differentially by treatment group were distinct from connectivity features that change from baseline to 1 week into treatment. The group mean (SD) score on the 17-item Hamilton Rating Scale for Depression was 18.35 (4.58) at baseline and 26.14 (30.37) across all time points. Conclusions and Relevance: These findings establish the utility of EEG-based network functional connectivity analyses for differentiating between responses to an antidepressant vs placebo. A role emerged for parietal cortical regions in predicting placebo outcome. From a treatment perspective, capitalizing on the therapeutic components leading to placebo response differentially from antidepressant response should provide an alternative direction toward establishing a placebo signature in clinical trials, thereby enhancing the signal detection in randomized clinical trials. Trial Registration: ClinicalTrials.gov identifier: NCT01407094.

Evidence that alpha blocking is due to increases in system-level oscillatory damping not neuronal population desynchronisation.

The attenuation of the alpha rhythm following eyes-opening (alpha blocking) is among the most robust features of the human electroencephalogram with the prevailing view being that it is caused by changes in neuronal population synchrony. To further study the basis for this phenomenon we use theoretically motivated fixed-order Auto-Regressive Moving-Average (ARMA) time series modelling to study the oscillatory dynamics of spontaneous alpha-band electroencephalographic activity in eyes-open and eyes-closed conditions and its modulation by the NMDA antagonist ketamine. We find that the reduction in alpha-band power between eyes-closed and eyes-open states is explicable in terms of an increase in the damping of stochastically perturbed alpha-band relaxation oscillatory activity. These changes in damping are putatively modified by the antagonism of NMDA-mediated glutamatergic neurotransmission but are not directly driven by changes in input to cortex nor by reductions in the phase synchronisation of populations of near identical oscillators. These results not only provide a direct challenge to the dominant view of the role that thalamus and neuronal population de-/synchronisation have in the genesis and modulation of alpha electro-/magnetoencephalographic activity but also suggest potentially important physiological determinants underlying its dynamical control and regulation.

In pursuit of a sensitive EEG functional connectivity outcome measure for clinical trials in Alzheimer's disease.

OBJECTIVE: In clinical trials in Alzheimer's Disease (AD), an improvement of impaired functional connectivity (FC) could provide biological support for the potential efficacy of the drug. Electroencephalography (EEG) analysis of the SAPHIR-trial showed a treatment induced improvement of global relative theta power but not of FC measured by the phase lag index (PLI). We compared the PLI with the amplitude envelope correlation with leakage correction (AEC-c), a presumably more sensitive FC measure. METHODS: Patients with early AD underwent 12 weeks of placebo or treatment with PQ912, a glutaminylcyclase inhibitor. Eyes-closed task free EEG was measured at baseline and follow-up (PQ912 n = 47, placebo n = 56). AEC-c and PLI were measured in multiple frequency bands. Change in FC was compared between treatment groups by using two models of covariates. RESULTS: A significant increase in global AEC-c in the alpha frequency band was found with PQ912 treatment compared to placebo (p = 0.004, Cohen's d = 0.58). The effect remained significant when corrected for sex, country, ApoE ε4 carriage, age, baseline value (model 1; p = 0.006) and change in relative alpha power (model 2; p = 0.004). CONCLUSIONS: Functional connectivity in early AD, measured with AEC-c in the alpha frequency band, improved after PQ912 treatment. SIGNIFICANCE: AEC-c may be a robust and sensitive FC measure for detecting treatment effects.

Stability of frontal alpha asymmetry in depressed patients during antidepressant treatment.

INTRODUCTION: Frontal alpha asymmetry (FAA) is a proposed prognostic biomarker in major depressive disorder (MDD), conventionally acquired with electroencephalography (EEG). Although small studies attributed trait-like properties to FAA, a larger sample is needed to reliably asses this characteristic. Furthermore, to use FAA to predict treatment response, determining its stability, including the potential dependency on depressive state or medication, is essential. METHODS: In the international Study to Predict Optimized Treatment in Depression (iSPOT-D), a multi-center, randomized, prospective open-label trial, 1008 MDD participants were randomized to treatment with escitalopram, sertraline or venlafaxine-extended release. Treatment response was established eight weeks after treatment initiation and resting state EEG was measured both at baseline and after eight weeks (n = 453). RESULTS: FAA did not change significantly after eight weeks of treatment (n = 453, p = .234), nor did we find associations with age, sex, depression severity, or change in depression severity. After randomizing females to escitalopram or sertraline, for whom treatment response could be predicted in an earlier study, FAA after eight weeks resulted in equivalent response prediction as baseline FAA (one tailed p = .028). CONCLUSION: We demonstrate that FAA is a stable trait, robust to time, state and pharmacological status. This confirms FAA stability. Furthermore, as prediction of treatment response is irrespective of moment of measurement and use of medication, FAA can be used as a state-invariant prognostic biomarker with promise to optimize MDD treatments.

Caffeine Increased Muscle Endurance Performance Despite Reduced Cortical Activation and Unchanged Neuromuscular Efficiency and Corticomuscular Coherence.

The central and peripheral effects of caffeine remain debatable. We verified whether increases in endurance performance after caffeine ingestion occurred together with changes in primary motor cortex (MC) and prefrontal cortex (PFC) activation, neuromuscular efficiency (NME), and electroencephalography-electromyography coherence (EEG-EMG coherence). Twelve participants performed a time-to-task failure isometric contraction at 70% of the maximal voluntary contraction after ingesting 5 mg/kg of caffeine (CAF) or placebo (PLA), in a crossover and counterbalanced design. MC (Cz) and PFC (Fp1) EEG alpha wave and vastus lateralis (VL) muscle EMG were recorded throughout the exercise. EEG-EMG coherence was calculated through the magnitude squared coherence analysis in MC EEG gamma-wave (CI > 0.0058). Moreover, NME was obtained as the force-VL EMG ratio. When compared to PLA, CAF improved the time to task failure (p = 0.003, d = 0.75), but reduced activation in MC and PFC throughout the exercise (p = 0.027, d = 1.01 and p = 0.045, d = 0.95, respectively). Neither NME (p = 0.802, d = 0.34) nor EEG-EMG coherence (p = 0.628, d = 0.21) was different between CAF and PLA. The results suggest that CAF improved muscular performance through a modified central nervous system (CNS) response rather than through alterations in peripheral muscle or central-peripheral coupling.

Working Memory Capacity Is Negatively Associated with Memory Load Modulation of Alpha Oscillations in Retention of Verbal Working Memory.

Working memory capacity (WMC) measures the amount of information that can be maintained online in the face of distraction. Past work has shown that the efficiency with which the frontostriatal circuit filters out task-irrelevant distracting information is positively correlated with WMC. Recent work has demonstrated a role of posterior alpha oscillations (8-13 Hz) in providing a sensory gating mechanism. We investigated the relationship between memory load modulation of alpha power and WMC in two verbal working memory experiments. In both experiments, we found that posterior alpha power increased with memory load during memory, in agreement with previous reports. Across individuals, the degree of alpha power modulation by memory load was negatively associated with WMC, namely, the higher the WMC, the less alpha power was modulated by memory load. After the administration of topiramate, a drug known to affect alpha oscillations and have a negative impact on working memory function, the negative correlation between memory load modulation of alpha power and WMC was no longer statistically significant but still somewhat detectable. These results suggest that (1) individuals with low WMC demonstrate stronger alpha power modulation by memory load, reflecting possibly an increased reliance on sensory gating to suppress task-irrelevant information in these individuals, in contrast to their high WMC counterparts who rely more on frontal areas to perform this function and (2) this negative association between memory load modulation of alpha oscillations and WMC is vulnerable to drug-related cognitive disruption.

Normalization of EEG in depression after antidepressant treatment with sertraline? A preliminary report.

BACKGROUND: MDD patients with abnormal EEG patterns seem more likely to be non-responsive to the antidepressants escitalopram and venlafaxine, but not sertraline, than patients without EEG abnormalities. This finding suggests that patients with both MDD and abnormal EEGs may differentially respond to antidepressant treatment. In the current study, we investigated whether depressed patients with an abnormal EEG show a normalization of the EEG related to antidepressant treatment and response and whether such effect is drug specific, and whether having had early life stress (ELS) increases the chance of abnormal activity. METHODS: Baseline and week 8 EEGs and depression symptoms were extracted from a large multicenter study (iSPOT-D, n = 1008) where depressed patients were randomized to escitalopram, sertraline, or venlafaxine-XR treatment. We calculated Odds Ratios of EEG normalization and depression response in patients with an abnormal EEG at baseline, comparing sertraline versus other antidepressants. RESULTS: Fifty seven patients with abnormal EEGs were included. EEGs did not normalize significantly more with sertraline compared to other antidepressants (OR = 1.9, p = .280). However, patients with a normalized EEG taking sertraline were 5.2 times more likely to respond than subjects taking other antidepressants (p = .019). ELS was not significantly related to abnormal activity. LIMITATIONS: Neurophysiological recordings were limited in time (two times 2-minute EEGs) and statistical power (n = 57 abnormal EEGs). CONCLUSIONS: Response rates in patients with normalized EEG taking sertraline were significantly larger than in subjects treated with escitalopram/venlafaxine. This adds to personalized medicine and suggests a possible drug repurposing for sertraline.

Sleep deprivation and Modafinil affect cortical sources of resting state electroencephalographic rhythms in healthy young adults.

OBJECTIVE: It has been reported that sleep deprivation affects the neurophysiological mechanisms underpinning the vigilance. Here, we tested the following hypotheses in the PharmaCog project (www.pharmacog.org): (i) sleep deprivation may alter posterior cortical delta and alpha sources of resting state eyes-closed electroencephalographic (rsEEG) rhythms in healthy young adults; (ii) after the sleep deprivation, a vigilance enhancer may recover those rsEEG source markers. METHODS: rsEEG data were recorded in 36 healthy young adults before (Pre-sleep deprivation) and after (Post-sleep deprivation) one night of sleep deprivation. In the Post-sleep deprivation, these data were collected after a single dose of PLACEBO or MODAFINIL. rsEEG cortical sources were estimated by eLORETA freeware. RESULTS: In the PLACEBO condition, the sleep deprivation induced an increase and a decrease in posterior delta (2-4 Hz) and alpha (8-13 Hz) source activities, respectively. In the MODAFINIL condition, the vigilance enhancer partially recovered those source activities. CONCLUSIONS: The present results suggest that posterior delta and alpha source activities may be both related to the regulation of human brain arousal and vigilance in quiet wakefulness. SIGNIFICANCE: Future research in healthy young adults may use this methodology to preselect new symptomatic drug candidates designed to normalize brain arousal and vigilance in seniors with dementia.

Influence of midazolam premedication on intraoperative EEG signatures in elderly patients.

OBJECTIVE: To investigate the influence of midazolam premedication on the EEG-spectrum before and during general anesthesia in elderly patients. METHODS: Patients aged ≥65 years, undergoing elective surgery were included in this prospective observational study. A continuous pre- and intraoperative frontal EEG was recorded in patients who received premedication with midazolam (Mid, n = 15) and patients who did not (noMid, n = 30). Absolute power within the delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), and beta (12-25 Hz) frequency-bands was analyzed in EEG-sections before (pre-induction), and after induction of anesthesia with propofol (post-induction), as well as during general anesthesia with either propofol or volatile-anesthetics (intra-operative). RESULTS: Pre-induction, α-power of Mid patients was lower compared with noMid-patients (α-power: Mid: -10.75 dB vs. noMid: -9.20 dB; p = 0.036). After induction of anesthesia Mid-patients displayed a stronger increase of frontal α-power resulting in higher absolute α-power at post-induction state, (α-power: Mid -3.56 dB vs. noMid: -6.69 dB; p = 0.004), which remained higher intraoperatively (α-power: Mid: -2.12 dB vs. noMid: -6.10 dB; p = 0.024). CONCLUSION: Midazolam premedication alters the intraoperative EEG-spectrum in elderly patients. SIGNIFICANCE: This finding provides further evidence for the role of GABAergic activation in the induction of elevated, frontal α-power during general anesthesia. TRIAL REGISTRY NUMBER: NCT02265263. 23 September 2014. Principal investigator: Prof. Dr. med. Claudia Spies. (https://clinicaltrials.gov/ct2/show/NCT02265263).

Early change of prefrontal theta cordance and occipital alpha asymmetry in the prediction of responses to antidepressants.

BACKGROUND: The study evaluated the effectiveness of EEG alpha 1, alpha 2 and theta power, along with prefrontal theta cordance (PFC), frontal and occipital alpha 1, alpha 2 asymmetry (FAA1/2, OAA1/2) at baseline and their changes at week 1 in predicting response to antidepressants. METHOD: Resting-state EEG data were recorded from 103 depressive patients that were treated in average for 5.1 ±â€¯0.9 weeks with SSRIs (n = 57) and SNRIs (n = 46). RESULTS: Fifty-five percent of patients (n = 56) responded to treatment (i.e.reduction of Montgomery-Åsberg Depression Rating Scale score ≥ 50%) and 45% (n = 47) of treated subjects did not reach positive treatment outcome. No differences in EEG baseline alpha and theta power or changes at week 1 for prefrontal, frontal, central, temporal and occipital regions were found between responders and non-responders. Both groups showed no differences at baseline PFC, FAA1/2 and OAA1/2 as well as change of FAA1/2 at week 1. The only parameters associated with treatment outcome were decrease of PFC in responders and increase of OAA1/2 at week 1 in non-responders. There was no influence of the used antidepressant classes on the results. The PFC change at week 1 (PFCC) (area under curve-AUC = 0.75) showed only a numerically higher predictive ability than OAA change in alpha 1 (OAA1C, AUC = 0.64)/alpha 2 (OAA2C, AUC = 0.63). A combined model, where OAA1C was added to PFCC (AUC = 0.79), did not significantly improve response prediction. CONCLUSION: Besides PFCC, we found that OAA1C/OAA2C might be another candidate for EEG predictors of antidepressant response.

TAK-071, a muscarinic M1 receptor positive allosteric modulator, attenuates scopolamine-induced quantitative electroencephalogram power spectral changes in cynomolgus monkeys.

Activation of the muscarinic M1 receptor is a promising approach to improve cognitive deficits associated with cholinergic dysfunction in Alzheimer's disease, dementia with Lewy bodies, and schizophrenia. TAK-071 is an M1-selective positive allosteric modulator that improves cognitive deficits induced by scopolamine, a non-selective muscarinic receptor antagonist, with reduced side effects on gastrointestinal function in rats. In this study, we explored changes in quantitative electroencephalography (qEEG) power bands, with or without scopolamine challenge, as a non-invasive translational biomarker for the effect of TAK-071 in cynomolgus monkeys. Scopolamine has been reported to increase theta and delta power bands and decrease alpha power band in healthy volunteers. In line with the clinical observations, scopolamine (25-100 µg/kg, subcutaneous administration [s.c.]) increased theta and delta power bands in cynomolgus monkeys in a dose-dependent manner, whereas it had the opposite effect on alpha power band. The effects of TAK-071 on scopolamine (25 µg/kg, s.c.)-induced qEEG spectral changes were examined using an acetylcholinesterase inhibitor donepezil and a muscarinic M1/M4 receptor agonist xanomeline as comparative cholinomimetics. TAK-071 (0.3-3 mg/kg, oral administration [p.o.]), donepezil (3 mg/kg, p.o.), and xanomeline (1 mg/kg, s.c.) suppressed the scopolamine-induced increases in alpha, theta, and delta power bands. These results suggest that changes in specific qEEG power bands, in particular theta and delta power bands in the context of scopolamine challenge, could be used as translational biomarkers for the evaluation of TAK-071 in clinical studies.