Aligning strategies for using EEG as a surrogate biomarker: A review of preclinical and clinical research

Machine learning of brain-specific biomarkers from EEG

BACKGROUND

Electroencephalography (EEG) has a long history as a clinical tool to study brain function, and its potential to derive biomarkers for various applications is far from exhausted. Machine learning (ML) can guide future innovation by harnessing the wealth of complex EEG signals to isolate relevant brain activity. Yet, ML studies in EEG tend to ignore physiological artefacts, which may cause problems for deriving biomarkers specific to the central nervous system (CNS).

METHODS

We present a framework for conceptualising machine learning from CNS versus peripheral signals measured with EEG. A signal representation based on Morlet wavelets allowed us to define traditional brain activity features (e.g. log power) and alternative inputs used by state-of-the-art ML approaches based on covariance matrices. Using more than 2600 EEG recordings from large public databases (TUAB, TDBRAIN), we studied the impact of peripheral signals and artefact removal techniques on ML models in age and sex prediction analyses.

FINDINGS

Across benchmarks, basic artefact rejection improved model performance, whereas further removal of peripheral signals using ICA decreased performance. Our analyses revealed that peripheral signals enable age and sex prediction. However, they explained only a fraction of the performance provided by brain signals.

INTERPRETATION

We show that brain signals and body signals, both present in the EEG, allow for prediction of personal characteristics. While these results may depend on specific applications, our work suggests that great care is needed to separate these signals when the goal is to develop CNS-specific biomarkers using ML.

FUNDING

All authors have been working for F. Hoffmann-La Roche Ltd.

Antinociceptive effects of Raphanus sativus sprouts involve the opioid and 5-HT1A serotonin receptors, cAMP/cGMP pathways, and the central activity of sulforaphane

Raphanus sativus L. cv. Sango, commonly known as red radish, is widely consumed around the world as a vegetable, but its benefit in pain relief is not sufficiently investigated. This study aimed to evaluate the antinociceptive effects of R. sativus and a possible mechanism of action. An aqueous extract of R. sativus sprouts (AERSS) was investigated by parenteral (10, 30, and 100 mg kg-1, i.p.) and enteral (500 mg kg-1, p.o.) administration in the neurogenic and inflammatory phases of the formalin test, where gastric damage was also evaluated as a possible adverse effect. Ketorolac (5 mg kg-1, i.p.) was used as the reference drug. Endogenous opioid and 5-HT1A serotonin receptors, as well as the cAMP/NO-cGMP pathways, were explored in the study of a possible mechanism of action by using their corresponding antagonists: naloxone, 1 mg kg-1, i.p., WAY100635, 1 mg kg-1, i.p., and enzymatic activators or inhibitors, respectively. Sulforaphane (SFN), a known bioactive metabolite, was analyzed using electroencephalography (EEG) to evidence its central involvement. A significant and dose-dependent antinociceptive activity was observed with the AERSS resembling the antinociceptive effect of the reference drug, with an equivalent significant response with a dose of 500 mg kg-1, p.o. without causing gastric damage. The participation of the endogenous opioid and 5-HT1A serotonin receptors at central and peripheral levels was also observed, with a differential participation of cAMP/NO-cGMP. SFN as one metabolite produced significant changes in the EEG analysis, reinforcing its effects on the CNS. Our preclinical evidence supports the benefits of consuming Raphanus sativus cv. Sango sprouts for pain relief.

Use of Quantitative Electroencephalography to Inform Age- and Sex-Related Differences in NMDA Receptor Function Following MK-801 Administration

Sex- and age-related differences in symptom prevalence and severity have been widely reported in patients with schizophrenia, yet the underlying mechanisms contributing to these differences are not well understood. N-methyl-D-aspartate (NMDA) receptor hypofunction contributes to schizophrenia pathology, and preclinical models often use NMDA receptor antagonists, including MK-801, to model all symptom clusters. Quantitative electroencephalography (qEEG) represents a translational approach to measure neuronal activity, identify targetable biomarkers in neuropsychiatric disorders and evaluate possible treatments. Abnormalities in gamma power have been reported in patients with schizophrenia and correspond to psychosis and cognitive impairment. Further, as gamma power reflects cortical glutamate and GABA signaling, it is highly sensitive to changes in NMDA receptor function, and NMDA receptor antagonists aberrantly increase gamma power in rodents and humans. To evaluate the role of sex and age on NMDA receptor function, MK-801 (0.03-0.3 mg/kg, SC) was administered to 3- and 9-month-old male and female Sprague-Dawley rats that were implanted with wireless EEG transmitters to measure cortical brain function. MK-801-induced elevations in gamma power were observed in 3-month-old male and female and 9-month-old male rats. In contrast, 9-month-old female rats demonstrated blunted maximal elevations across a wide dose range. Importantly, MK-801-induced hyperlocomotor effects, a common behavioral screen used to examine antipsychotic-like activity, were similar across all groups. Overall, sex-by-age-related differences in gamma power support using qEEG as a translational tool to evaluate pathological progression and predict treatment response across a heterogeneous population.

Translational In Vivo Assays in Behavioral Biology

The failure of preclinical research to advance successful candidate medications in psychiatry has created a paradigmatic crisis in psychiatry. The Research Domain Criteria (RDoC) initiative was designed to remedy this situation with a neuroscience-based approach that employs multimodal and cross-species in vivo methodology to increase the probability of translational findings and, consequently, drug discovery. The present review underscores the feasibility of this methodological approach by briefly reviewing, first, the use of multidimensional and cross-species methodologies in traditional behavioral pharmacology and, subsequently, the utility of this approach in contemporary neuroimaging and electrophysiology research-with a focus on the value of functionally homologous studies in nonhuman and human subjects. The final section provides a brief review of the RDoC, with a focus on the potential strengths and weaknesses of its domain-based underpinnings. Optimistically, this mechanistic and multidimensional approach in neuropsychiatric research will lead to novel therapeutics for the management of neuropsychiatric disorders.

Pharmaco-EEG analysis of ligands varying in selectivity for α1 subunit-containing GABAA receptors during the active phase in rats

RATIONALE

Benzodiazepines are known to evoke changes in cortical electrophysiological activity that can be correlated with action at distinct γ-aminobutyric acid type A (GABAA) receptor subtypes.

OBJECTIVES

We used electroencephalography (EEG) paired with electromyography (EMG) to evaluate the role of α1 subunit-containing GABAA receptors (α1GABAARs) in benzodiazepine-induced sedation and changes in EEG band frequencies during the active phase of the light/dark cycle.

METHODS

Male Sprague-Dawley rats (N = 4/drug) were surgically instrumented with EEG/EMG electrodes. The rats were injected i.p. with zolpidem, an α1GABAAR-preferring compound, or L-838,417, which has selective efficacy for α2/3/5 subunit-containing GABAARs (i.e., α1GABAAR-sparing compound), in comparison with the non-selective benzodiazepine, triazolam.

RESULTS

All ligands evaluated induced changes in sleep-wake states during the active phase consistent with an increase in slow-wave sleep (SWS). The degree of SWS increase appeared to be related to the magnitude of delta power band changes induced by the ligands, with the strongest effects engendered by the α1GABAAR-preferring drug zolpidem and the weakest effects by the α1GABAAR-sparing compound, L-838,417. Consistent with other research, a selective increase in beta band power was observed with L-838,417, which may be associated with α2GABAAR-mediated anxiolysis.

CONCLUSIONS

Overall, these findings support the establishment of pharmaco-EEG "signatures" for identifying subtype-selective GABAA modulators in vivo.

Generation of synthetic EEG data for training algorithms supporting the diagnosis of major depressive disorder

Introduction

Major depressive disorder (MDD) is the most common mental disorder worldwide, leading to impairment in quality and independence of life. Electroencephalography (EEG) biomarkers processed with machine learning (ML) algorithms have been explored for objective diagnoses with promising results. However, the generalizability of those models, a prerequisite for clinical application, is restricted by small datasets. One approach to train ML models with good generalizability is complementing the original with synthetic data produced by generative algorithms. Another advantage of synthetic data is the possibility of publishing the data for other researchers without risking patient data privacy. Synthetic EEG time-series have not yet been generated for two clinical populations like MDD patients and healthy controls.

Methods

We first reviewed 27 studies presenting EEG data augmentation with generative algorithms for classification tasks, like diagnosis, for the possibilities and shortcomings of recent methods. The subsequent empirical study generated EEG time-series based on two public datasets with 30/28 and 24/29 subjects (MDD/controls). To obtain baseline diagnostic accuracies, convolutional neural networks (CNN) were trained with time-series from each dataset. The data were synthesized with generative adversarial networks (GAN) consisting of CNNs. We evaluated the synthetic data qualitatively and quantitatively and finally used it for re-training the diagnostic model.

Results

The reviewed studies improved their classification accuracies by between 1 and 40% with the synthetic data. Our own diagnostic accuracy improved up to 10% for one dataset but not significantly for the other. We found a rich repertoire of generative models in the reviewed literature, solving various technical issues. A major shortcoming in the field is the lack of meaningful evaluation metrics for synthetic data. The few studies analyzing the data in the frequency domain, including our own, show that only some features can be produced truthfully.

Discussion

The systematic review combined with our own investigation provides an overview of the available methods for generating EEG data for a classification task, their possibilities, and shortcomings. The approach is promising and the technical basis is set. For a broad application of these techniques in neuroscience research or clinical application, the methods need fine-tuning facilitated by domain expertise in (clinical) EEG research.

Functional connectivity analysis on electroencephalography signals reveals potential biomarkers for treatment response in major depression

BACKGROUND

The treatment efficacy varies across individual patients with major depressive disorder (MDD). It lacks robust electroencephalography (EEG) markers for an antidepressant-responsive phenotype.

METHOD

This is an observational study enrolling 28 patients with MDD and 33 healthy controls (mean age of 40.7 years, and 71.4% were women). Patients underwent EEG exams at baseline (week0) and week1, while controls' EEG recordings were acquired only at week0. A resting eye-closing EEG segment was analyzed for functional connectivity (FC). Four parameters were used in FC analysis: (1) node strength (NS), (2) global efficiency (GE), (3) clustering coefficient (CC), and (4) betweenness centrality (BC).

RESULTS

We found that controls had higher values in delta wave in the indices of NS, GE, BC, and CC than MDD patients at baseline. After treatment with antidepressants, patients' FC indices improved significantly, including GE, mean CC, and mean NS in the delta wave. The FC in the alpha and beta bands of the responders were higher than those of the non-responders.

CONCLUSIONS

The FC of the MDD patients at baseline without treatment was worse than that of controls. After treatment, the FC improved and was close to the values of controls. Responders showed better FC in the high-frequency bands than non-responders, and this feature exists in both pre-treatment and post-treatment EEG.

Anxiolytic-like Effects and Quantitative EEG Profile of Palmitone Induces Responses Like Buspirone Rather Than Diazepam as Clinical Drugs

Anxiety is a mental disorder with a growing worldwide incidence due to the SARS-CoV-2 virus pandemic. Pharmacological therapy includes drugs such as benzodiazepines (BDZs) or azapirones like buspirone (BUSP) or analogs, which unfortunately produce severe adverse effects or no immediate response, respectively. Medicinal plants or their bioactive metabolites are a shared global alternative to treat anxiety. Palmitone is one active compound isolated from Annona species due to its tranquilizing activity. However, its influence on neural activity and possible mechanism of action are unknown. In this study, an electroencephalographic (EEG) spectral power analysis was used to corroborate its depressant activity in comparison with the anxiolytic-like effects of reference drugs such as diazepam (DZP, 1 mg/kg) and BUSP (4 mg/kg) or 8-OH-DPAT (1 mg/kg), alone or in the presence of the GABA_A (picrotoxin, PTX, 1 mg/kg) or serotonin 5-HT_1A receptor antagonists (WAY100634, WAY, 1 mg/kg). The anxiolytic-like activity was assayed using the behavioral response of mice employing open-field, hole-board, and plus-maze tests. EEG activity was registered in both the frontal and parietal cortex, performing a 10 min baseline and 30 min recording after the treatments. As a result, anxiety-like behavior was significantly decreased in mice administered with palmitone, DZP, BUSP, or 8-OH-DPAT. The effect of palmitone was equivalent to that produced by 5-HT_1A receptor agonists but 50% less effective than DZP. The presence of PTX and WAY prevented the anxiolytic-like response of DZP and 8-OH-DPAT, respectively. Whereas only the antagonist of the 5-HT_1A receptor (WAY) inhibited the palmitone effects. Palmitone and BUSP exhibited similar changes in the relative power bands after the spectral power analysis. This response was different to the changes induced by DZP. In conclusion, brain electrical activity was associated with the anxiolytic-like effects of palmitone implying a serotoninergic rather than a GABAergic mechanism of action.

Three simple steps to improve the interpretability of EEG-SVM studies

Machine-learning systems that classify electroencephalography (EEG) data offer important perspectives for the diagnosis and prognosis of a wide variety of neurological and psychiatric conditions, but their clinical adoption remains low. We propose here that much of the difficulties translating EEG-machine-learning research to the clinic result from consistent inaccuracies in their technical reporting, which severely impair the interpretability of their often-high claims of performance. Taking example from a major class of machine-learning algorithms used in EEG research, the support-vector machine (SVM), we highlight three important aspects of model development (normalization, hyperparameter optimization, and cross-validation) and show that, while these three aspects can make or break the performance of the system, they are left entirely undocumented in a shockingly vast majority of the research literature. Providing a more systematic description of these aspects of model development constitute three simple steps to improve the interpretability of EEG-SVM research and, in fine, its clinical adoption.

Predictive Power of Cognitive Biomarkers in Neurodegenerative Disease Drug Development: Utility of the P300 Event-Related Potential

Neurodegenerative diseases, such as Alzheimer's disease (AD), and their associated deterioration of cognitive function are common causes of disability. The slowly developing pathology of neurodegenerative diseases necessitates early diagnosis and monitored long-term treatment. Lack of effective therapies coupled with an improved rate of early diagnosis in our aging population have created an urgent need for the development of novel drugs, as well as the need for reliable biomarkers for treatment response. These issues are especially relevant for AD, in which the rate of clinical trial drug failures has been very high. Frequently used biomarker evaluation procedures, such as positron emission tomography or cerebrospinal fluid measurements of phospho-tau and amyloid beta, are invasive and costly, and not universally available or accessible. This review considers the functionality of the event-related potential (ERP) P300 methodology as a surrogate biomarker for predicting the procognitive potential of drugs in clinical development for neurocognitive disorders. Through the application of standardized electroencephalography (EEG) described here, ERP P300 can be reliably measured. The P300 waveform objectively measures large-scale neuronal network functioning and working memory processes. Increased ERP P300 latency has been reported throughout the literature in disorders of cognition, supporting the potential utility of ERP P300 as a biomarker in many neurological and neuropsychiatric disorders, including AD. Specifically, evidence presented here supports ERP P300 latency as a quantitative, unbiased measure for detecting changes in cognition in patients with AD dementia through the progression from mild to moderate cognitive impairment and after drug treatment.

Memory-Enhancing Effect of 8-Week Consumption of the Quercetin-Enriched Culinary Herbs-Derived Functional Ingredients: A Randomized, Double-Blind, Placebo-Controlled Clinical Trial

Due to great demand for memory enhancers, the memory-enhancing effects and the possible underlying mechanisms of the functional ingredients derived from the combined extract of Polygonum odoratum and Morus alba were investigated. A total of 45 participants randomly received either a placebo or the developed herbal supplement at a dose of 50 or 1500 mg/day. The consumption was done once daily for 8 weeks. Working memory was assessed via both an event-related potential and computerized battery tests at baseline and at the end of the 8-week study period. Acetylcholinesterase (AChE) and monoamine oxidase type A and type B (MAO-A, MAO-B) levels were also measured at the end of the study. The subjects who consumed the supplement containing a developed functional ingredient at a dose of 1500 mg/day showed reduced latencies but increased amplitudes of N100 and P300. An improvement in working memory and the suppression of AChE, MAO-A, and MAO-B activities were also observed. Therefore, this study clearly demonstrates the cognitive enhancing effect of the developed herbal congee, which may be associated with the suppressions of AChE and both types of MAO.

Event-Related Potentials as Markers of Efficacy for Combined Working Memory Training and Transcranial Direct Current Stimulation Regimens: A Proof-of-Concept Study

Our brains are often under pressure to process a continuous flow of information in a short time, therefore facing a constantly increasing demand for cognitive resources. Recent studies have highlighted that a lasting improvement of cognitive functions may be achieved by exploiting plasticity, i.e., the brain’s ability to adapt to the ever-changing cognitive demands imposed by the environment. Transcranial direct current stimulation (tDCS), when combined with cognitive training, can promote plasticity, amplify training gains and their maintenance over time. The availability of low-cost wearable devices has made these approaches more feasible, albeit the effectiveness of combined training regimens is still unclear. To quantify the effectiveness of such protocols, many researchers have focused on behavioral measures such as accuracy or reaction time. These variables only return a global, non-specific picture of the underlying cognitive process. Electrophysiology instead has the finer grained resolution required to shed new light on the time course of the events underpinning processes critical to cognitive control, and if and how these processes are modulated by concurrent tDCS. To the best of our knowledge, research in this direction is still very limited. We investigate the electrophysiological correlates of combined 3-day working memory training and non-invasive brain stimulation in young adults. We focus on event-related potentials (ERPs), instead of other features such as oscillations or connectivity, because components can be measured on as little as one electrode. ERP components are, therefore, well suited for use with home devices, usually equipped with a limited number of recording channels. We consider short-, mid-, and long-latency components typically elicited by working memory tasks and assess if and how the amplitude of these components are modulated by the combined training regimen. We found no significant effects of tDCS either behaviorally or in brain activity, as measured by ERPs. We concluded that either tDCS was ineffective (because of the specific protocol or the sample under consideration, i.e., young adults) or brain-related changes, if present, were too subtle. Therefore, we suggest that other measures of brain activity may be more appropriate/sensitive to training- and/or tDCS-induced modulations, such as network connectivity, especially in young adults.

Safety, Tolerability, Pharmacokinetics, and Pharmacodynamics of the Positive Modulator of HGF/MET, Fosgonimeton, in Healthy Volunteers and Subjects with Alzheimer's Disease: Randomized, Placebo-Controlled, Double-Blind, Phase I Clinical Trial

Background:

Fosgonimeton (ATH-1017) is being developed as a first-in-class regenerative therapy for people with Alzheimer’s disease (AD) and dementia; potentially improving dementia symptoms and altering disease progression by reversing synaptic disconnection and neuronal loss.

Objective:

This randomized, double-blind, placebo-controlled phase I trial (NCT03298672) evaluated the safety, tolerability, pharmacokinetics, and pharmacodynamics of fosgonimeton.

Methods:

Fosgonimeton was administered once daily via subcutaneous injection to 88 subjects. The single ascending dose study enrolled healthy young male subjects (n = 48; age, 33.4±6.3 years; dose, 2, 6, 20, 40, 60, or 90 mg); the multiple ascending dose study enrolled healthy elderly subjects (n = 29; age, 63.8±4.0 years; dose, 20, 40, 60, or 80 mg; 9-day duration); and the fixed-dose study enrolled AD subjects (n = 11; age, 69.2±7.1 years; dose, 40 mg; 9-day duration). Quantitative electroencephalogram (qEEG) and event-related potential (ERP) P300 measured neurophysiological signals following fosgonimeton treatment, supporting brain penetration and target engagement.

Results:

Fosgonimeton and placebo were shown to be safe and well-tolerated across all doses. Pharmacokinetic results for fosgonimeton were dose-proportional, with no sex effect or accumulation over 9 days. The main effect of fosgonimeton on qEEG was acute and sustained gamma power induction. In AD subjects, there was a significant effect toward ERP P300 latency normalization compared with placebo (p = 0.027; n = 7 at 40 mg fosgonimeton versus n = 4 placebo).

Conclusion:

These results support the continued development of fosgonimeton as a novel therapeutic for people with AD and dementia. The fast-onset normalization of ERP P300 latency in AD subjects suggests enhancement of synaptic function and potential procognitive effects.

Feasibility of Repeated Assessment of Cognitive Function in Older Adults Using a Wireless, Mobile, Dry-EEG Headset and Tablet-Based Games

Access to affordable, objective and scalable biomarkers of brain function is needed to transform the healthcare burden of neuropsychiatric and neurodegenerative disease. Electroencephalography (EEG) recordings, both resting and in combination with targeted cognitive tasks, have demonstrated utility in tracking disease state and therapy response in a range of conditions from schizophrenia to Alzheimer's disease. But conventional methods of recording this data involve burdensome clinic visits, and behavioural tasks that are not effective in frequent repeated use. This paper aims to evaluate the technical and human-factors feasibility of gathering large-scale EEG using novel technology in the home environment with healthy adult users. In a large field study, 89 healthy adults aged 40-79 years volunteered to use the system at home for 12 weeks, 5 times/week, for 30 min/session. A 16-channel, dry-sensor, portable wireless headset recorded EEG while users played gamified cognitive and passive tasks through a tablet application, including tests of decision making, executive function and memory. Data was uploaded to cloud servers and remotely monitored via web-based dashboards. Seventy-eight participants completed the study, and high levels of adherence were maintained throughout across all age groups, with mean compliance over the 12-week period of 82% (4.1 sessions per week). Reported ease of use was also high with mean System Usability Scale scores of 78.7. Behavioural response measures (reaction time and accuracy) and EEG components elicited by gamified stimuli (P300, ERN, Pe and changes in power spectral density) were extracted from the data collected in home, across a wide range of ages, including older adult participants. Findings replicated well-known patterns of age-related change and demonstrated the feasibility of using low-burden, large-scale, longitudinal EEG measurement in community-based cohorts. This technology enables clinically relevant data to be recorded outside the lab/clinic, from which metrics underlying cognitive ageing could be extracted, opening the door to potential new ways of developing digital cognitive biomarkers for disorders affecting the brain.

Concurrent electrophysiological recording and cognitive testing in a rodent touchscreen environment

Challenges in therapeutics development for neuropsychiatric disorders can be attributed, in part, to a paucity of translational models capable of capturing relevant phenotypes across clinical populations and laboratory animals. Touch-sensitive procedures are increasingly used to develop innovative animal models that better align with testing conditions used in human participants. In addition, advances in electrophysiological techniques have identified neurophysiological signatures associated with characteristics of neuropsychiatric illness. The present studies integrated these methodologies by developing a rat flanker task with electrophysiological recordings based on reverse-translated protocols used in human electroencephalogram (EEG) studies of cognitive control. Various touchscreen-based stimuli were evaluated for their ability to efficiently gain stimulus control and advance to flanker test sessions. Optimized stimuli were then examined for their elicitation of prototypical visual evoked potentials (VEPs) across local field potential (LFP) wires and EEG skull screws. Of the stimuli evaluated, purple and green photographic stimuli were associated with efficient training and expected flanker interference effects. Orderly stimulus-locked outcomes were also observed in VEPs across LFP and EEG recordings. These studies along with others verify the feasibility of concurrent electrophysiological recordings and rodent touchscreen-based cognitive testing and encourage future use of this integrated approach in therapeutics development.

Alprazolam-induced EEG spectral power changes in rhesus monkeys: a translational model for the evaluation of the behavioral effects of benzodiazepines

RATIONALE

Benzodiazepines induce electroencephalography (EEG) changes in rodents and humans that are associated with distinct behavioral effects and have been proposed as quantitative biomarkers for GABA_A receptor modulation. Specifically, central EEG beta and occipital EEG delta activity have been associated with anxiolysis and sedation, respectively. The extent to which nonhuman primates show the same dose- and topography-dependent effects remained unknown.

OBJECTIVES

We aimed at establishing a nonhuman primate model for the evaluation of benzodiazepine EEG pharmacology.

METHODS

Four adult male rhesus monkeys were prepared with fully implantable telemetry devices that monitored activity, peripheral body temperature, and contained two EEG (central and occipital), one electromyography (EMG), and one electrooculography channel. We investigated daytime alprazolam-induced changes in EEG spectral power, sleep-wake states, EMG activity, locomotor activity, and body temperature. Alprazolam (0.01-1.8 mg/kg, i.m.) or vehicle was administered acutely, and telemetry recording was conducted for 1 h.

RESULTS

Daytime alprazolam dose-dependently increased central EEG power (including beta activity), increased occipital EEG delta power, and decreased occipital EEG alpha, theta, and sigma power. There was an ~8-fold difference in the potency of alprazolam to increase central EEG beta vs. occipital EEG delta activity (based on relative EEG power). The highest dose, which increased both central EEG beta and occipital EEG delta relative power, induced sedative effects (increased time spent in N1 and N2 sleep stages) and decreased peripheral body temperature and locomotor activity.

CONCLUSIONS

Alprazolam induces dose- and topography-dependent EEG changes in rhesus monkeys and provides a valuable model for studying benzodiazepine pharmacology.

Evaluation of SAMP8 Mice as a Model for Sleep-Wake and Rhythm Disturbances Associated with Alzheimer's Disease: Impact of Treatment with the Dual Orexin (Hypocretin) Receptor Antagonist Lemborexant

Background:

Many patients with Alzheimer’s disease (AD) display circadian rhythm and sleep-wake disturbances. However, few mouse AD models exhibit these disturbances. Lemborexant, a dual orexin receptor antagonist, is under development for treating circadian rhythm disorders in dementia.

Objective:

Evaluation of senescence-accelerated mouse prone-8 (SAMP8) mice as a model for sleep-wake and rhythm disturbances in AD and the effect of lemborexant by assessing sleep-wake/diurnal rhythm behavior.

Methods:

SAMP8 and control senescence-accelerated mouse resistant-1 (SAMR1) mice received vehicle or lemborexant at light onset; plasma lemborexant and diurnal cerebrospinal fluid (CSF) orexin concentrations were assessed. Sleep-wake behavior and running wheel activity were evaluated.

Results:

Plasma lemborexant concentrations were similar between strains. The peak/nadir timing of CSF orexin concentrations were approximately opposite between strains. During lights-on, SAMP8 mice showed less non-rapid eye movement (non-REM) and REM sleep than SAMR1 mice. Lemborexant treatment normalized wakefulness/non-REM sleep in SAMP8 mice. During lights-off, lemborexant-treated SAMR1 mice showed increased non-REM sleep; lemborexant-treated SAMP8 mice displayed increased wakefulness. SAMP8 mice showed differences in electroencephalogram architecture versus SAMR1 mice. SAMP8 mice exhibited more running wheel activity during lights-on. Lemborexant treatment reduced activity during lights-on and increased activity in the latter half of lights-off, demonstrating a corrective effect on overall diurnal rhythm. Lemborexant delayed the acrophase of activity in both strains by approximately 1 hour.

Conclusion:

SAMP8 mice display several aspects of sleep-wake and rhythm disturbances in AD, notably mistimed activity. These findings provide some preclinical rationale for evaluating lemborexant in patients with AD who experience sleep-wake and rhythm disturbances.

Auditory evoked potentials and suicidal behaviors in patients with major depressive disorders

Loudness dependence of auditory evoked potentials (LDAEP) has been proposed as a biological marker of central serotonergic activity related to suicides. This study’s objective was to analyze the difference in LDAEP between depressed patients with suicide attempts (SA) and suicidal ideation (SI). It included 130 participants (45 depressed patients with SA, 49 depressed patients with SI, and 36 healthy controls) aged > 18 years who exhibited LDAEP during electroencephalography. Psychological characteristics and event-related potentials of the three groups were compared. There was no significant difference in LDAEP between major depressive disorder (MDD) patients with SA and SI (p = 0.59). MDD patients with SI, who attempted suicide had significantly lower LDAEP than healthy controls (p = 0.01 and p = 0.01, respectively). However, the significance disappeared when psychological characteristics were controlled. Our results suggest that LDAEP might not be possible biomarkers for suicidal behaviors in patients with MDD. Further studies to assess the biological basis of suicide and identify the underlying dimensions that mediate the relationship between the biological basis and suicidal behaviors will be needed.

Objective Assessments in Diagnoses and Treatment: A Proposed Change in Paradigm

For patients with psychiatric disorders, current diagnostic and treatment approaches are far from optimal. The clinical interview drives the standard approach-matching symptoms to diagnostic criteria-and results in standardized pharmacological and behavioral treatments, often, with inadequate outcome; but now, recent imaging advances can correlate behavioral assessments with brain function and measure them against normative databases to provide data critical for the reevaluation of patient diagnosis and treatment. This article addresses the data that support a redefinition of our current paradigm. We believe a neurobehavioral approach provides for more personalized treatment approaches unbound from classically defined diagnostic biases.

Preclinical Neuropathic Pain Assessment; the Importance of Translatability and Bidirectional Research

For patients suffering with chronic neuropathic pain the need for suitable novel therapies is imperative. Over recent years a contributing factor for the lack of development of new analgesics for neuropathic pain has been the mismatch of primary neuropathic pain assessment endpoints in preclinical vs. clinical trials. Despite continuous forward translation failures across diverse mechanisms, reflexive quantitative sensory testing remains the primary assessment endpoint for neuropathic pain and analgesia in animals. Restricting preclinical evaluation of pain and analgesia to exclusively reflexive outcomes is over simplified and can be argued not clinically relevant due to the continued lack of forward translation and failures in the clinic. The key to developing new analgesic treatments for neuropathic pain therefore lies in the development of clinically relevant endpoints that can translate preclinical animal results to human clinical trials. In this review we discuss this mismatch of primary neuropathic pain assessment endpoints, together with clinical and preclinical evidence that supports how bidirectional research is helping to validate new clinically relevant neuropathic pain assessment endpoints. Ethological behavioral endpoints such as burrowing and facial grimacing and objective measures such as electroencephalography provide improved translatability potential together with currently used quantitative sensory testing endpoints. By tailoring objective and subjective measures of neuropathic pain the translatability of new medicines for patients suffering with neuropathic pain will hopefully be improved.

Prediction of Antidepressant Treatment Outcome Using Event-Related Potential in Patients with Major Depressive Disorder

(1) Background: Prediction of treatment outcome has been one of the core objectives in clinical research of patients with major depressive disorder (MDD). This study explored the possibility of event-related potential (ERP) markers to predict antidepressant treatment outcomes among MDD patients; (2) Methods: Fifty-two patients with MDD were recruited and evaluated through Hamilton depression (HAM-D), Hamilton anxiety rating scale (HAM-A), and CORE. Patients underwent a battery of ERP measures including frontal alpha symmetry (FAA) in the low alpha band (8–10 Hz), mismatch negativity (MMN), and loudness-dependent auditory evoked potentials (LDAEP); (3) Results: During the eight weeks of study, 61% of patients achieved remission, and 77% showed successful treatment responsiveness. Patients with low FAA in F5/F6 demonstrated a significantly higher remission/response ratio and better treatment responsiveness (F (2.560, 117.755) = 3.84, p = 0.016) compared to patients with high FAA. In addition, greater FAA in F7/F8 EEG channels was significantly associated with greater melancholia scores (r = 0.34, p = 0.018). Other ERP markers lacked any significant effect; (4) Conclusions: Our results suggested low FAA (i.e., greater left frontal activity) could reflect a good treatment response in MDD patients. These findings support that FAA could be a promising index in understanding both MDD and melancholic subtype.

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.

Methods in Electrode Implantation and Wiring for Long-Term Continuous EEG Monitoring in Rodent Models of Epilepsy and Behavioral Disturbances

Rodent seizure models that pathologically and behaviorally recapitulate age-tailored epileptic disorders are used by us and others to advance our understanding of the chronobiology and mechanisms of epileptic seizure emergence and their comorbidities and to investigate potential novel treatment strategies. Obtaining prolonged continuous electroencephalogram (EEG) tracings over months is essential in this line of translational research, particularly to assess the relation between electrographic changes and the development of seizures and their various psychiatric and cognitive comorbidities in models where seizures gradually emerge over weeks following brain insults. Here we describe our approach to electrode implantation and wiring in order to successfully obtain high-quality continuous EEG tracings in rats for prolonged periods. A detailed stepwise methodological description is provided with a special focus on the details that help most in avoiding notorious pitfalls such as premature EEG cable disconnections and a poor signal to noise ratio.

Brainwaves Oscillations as a Potential Biomarker for Major Depression Disorder Risk

Major depressive disorder (MDD) is a multidimensional disorder that is characterized by the presence of alterations in mood, cognitive capacity, sensorimotor, and homeostatic functions. Given that about half of the patients diagnosed with MDD do not respond to the various current treatments, new techniques are being sought to predict not only the course of the disease but also the characteristics that differentiate responders from non-responders. Using the electroencephalogram, a noninvasive and inexpensive tool, most studies have proposed that patients with MDD have some lateralization in brain electrical activity, with alterations in alpha and theta rhythms being observed, which would be related to dysfunctions in emotional capacity such as the absence or presence of responses to the different existing treatments. These alterations help in the identification of subjects at high risk of suffering from depression, in the differentiation into responders and nonresponders to various therapies (pharmacological, electroconvulsive therapy, and so on), as well as to establish in which period of the disease the treatment will be more effective. Although the data are still inconclusive and more research is needed, these alpha and theta neurophysiological markers could support future clinical practice when it comes to establishing an early diagnosis and treating state disorders more successfully and accurately of mood disorders.

Study of Frontal Alpha Asymmetry in Mild Depression: A Potential Biomarker or Not?

Background:

Depression, despite being the most common of mental illness lacks any quantifiable and absolute biomarker. Frontal alpha asymmetry (FAA) is proposed as biomarker of depression both in resting and activated state. Yet, the location of extraction of alpha, clinical utility as well as validity of FAA is uncertain. With aim of obtaining clarity on this confusion we conducted this study.

Methodology:

Electroencephalographic frontal alpha power was calculated in patients of depression (n = 24) and compared with healthy controls (n = 17) for the assessment of FAA. Both groups were studied for resting phase and activation phase changes in FAA. For activation phase, auditory stimuli in the form of Indian classical music were used.

Results:

Frontal alpha power was measured across FP1, FP2, F3, F4, F7, and F8. Mean powers were compared in resting (before), activated (during) and postactivated resting stage (after). FAA was statistically significant in F7–F8 pair of electrodes and on F7 electrode when compared between cases and controls.

Conclusion:

Quest for biomarker for depression churned out FAA as frontrunner. Despite of vast amount of research on it, practical utility eludes us. We need to revisit our approach from conventional search of the diagnostic biomarker; as FAA might reflect component of depression but not totally disorder. In our opinion, we are not yet ready for it and have a road ahead to travel.

The relationship between auditory evoked potentials and symptoms of attention-deficit/hyperactivity disorder in adult patients with major depressive disorder

OBJECTIVES

Loudness dependence of auditory evoked potential (LDAEP) has been proposed as a biological marker for central serotonergic activity in depressive illness. A recent study has suggested that serotonin plays an important role in impulsivity and emotional sensitivity that are prominent clinical manifestations in attention deficit and hyperactivity disorder (ADHD). The objective of this study was to examine the association between LDAEP and ADHD symptoms in major depressive disorder (MDD).

METHODS

A total of 60 participants (40 subjects with MDD and 20 healthy controls) aged >18 years who had LDAEPs performed during electroencephalograms were included in this study. ADHD symptoms, depressive, and anxiety symptoms were evaluated. Psychological characteristics and event-related potentials (ERP) were compared among three groups: depression with ADHD symptoms, depression without ADHD symptoms, and healthy controls.

RESULTS

MDD subjects with ADHD symptoms (N = 20) showed significantly lower LDAEP levels than those without ADHD symptoms (N = 20) and healthy controls (N = 20). LDAEP differences between MDD subjects without ADHD symptoms and healthy controls were not statistically significant. In partial correlation analyses adjusted for age and sex, significant correlations of psychological scales of depression, ADHD symptoms, and LDAEPs were found.

CONCLUSION

Results of the present study suggest that LDAEP can reflect adult ADHD symptoms in MDD. Auditory evoked potential appears to be a promising candidate as an evaluation tool for inattention and poor impulse control as well as emotional sensitivity.

Potential Clinical Applications and Future Prospect of Wireless and Mobile Electroencephalography on the Assessment of Cognitive Impairment

Electroencephalography (EEG) systems have been used for assessing cognitive function in dementia for several decades. Studies have demonstrated that EEG in Alzheimer's disease (AD) patients is generally characterized by significant and specific increases in delta and theta power, a decrease in alpha power, and a decrease in the coherence of the fast bands between different brain areas linked by long corticocortical fibers. Posterior EEG characteristics in dementia with Lewy bodies (DLB) allowed discrimination of DLB from AD and controls with high accuracy. Traditional EEG systems require a long application time and discomfort, which limited its use in dementia patients. Alternative tools for assessing cognition may be simple, low-cost, and mobile medical devices such as wireless and mobile EEG (wmEEG) sensor platforms with flexible electronics and stretchable electrode sheets that could be compatible with long-term EEG monitoring even in dementia patients. In this study, we review the utility of EEG in reflecting cognitive function and the prospects for clinical application of wmEEG monitoring for detecting early dementia and discriminating subtypes of dementia effectively and objectively assessing longitudinal cognitive changes. Repeated and longitudinal documentation of EEG using wmEEG will contribute to detection of specific sleep/wake EEG patterns for patients with sleep and wake-related problems related to dementia.

Effects of Exercise on EEG Activity and Standard Tools Used to Assess Concussion

A variety of cognitive assessment tools are used to determine the functional status of the brain before and after injury in athletes. Questionnaires, neuropsychological tests, and electroencephalographic (EEG) measures have been recently used to directly assess brain function on and near the playing field. However, exercise can affect cognitive performance and EEG measures of cortical activity. To date, little empirical evidence exists on the effects of acute exercise on these measures of neurological function. We therefore quantified athlete performance on a standardized battery of concussion assessment tools and EEG measurements immediately before and after acute exercise to simulate conditions of athletic competition. Heart rate and arterial oxygen levels were collected before and after the exercise challenge consisting of a 1-mile run. Together these data, from a gender-balanced cohort of collegiate athletes, demonstrated that moderate to hard levels of acute exercise improved performance on the King-Devick test (K-D test) and Standardized Assessment of Concussion (SAC) component of the Sport Concussion Assessment Tool (SCAT3). Gender played an important role in these effects, and performance was most affected by exercise in female athletes. EEG activity in the theta band (4-8 Hz) was decreased during periods of quiet resting with eyes open or eyes closed. Additionally, exercise produced a slowing of the EEG during the K-D test and a shift to higher frequencies during the balance assessment of the SCAT3. Together, these data indicate that exercise alone can influence outcome measures of cognitive assessment tools used to assess brain function in athletes. Finally, care must be taken to acquire postinjury measurements during a comparable physiologic state to that in which baseline assessment data were measured, and further research is needed into the factors influencing outcome measures of these tests.

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.

Enhanced setup for wired continuous long-term EEG monitoring in juvenile and adult rats: application for epilepsy and other disorders

BACKGROUND

The electroencephalogram (EEG) is a widely used laboratory technique in rodent models of epilepsy, traumatic brain injury (TBI), and other neurological diseases accompanied by seizures. Obtaining prolonged continuous EEG tracings over weeks to months is essential to adequately answer research questions related to the chronobiology of seizure emergence, and to the effect of potential novel treatment strategies. Current EEG recording methods include wired and the more recent but very costly wireless technologies. Wired continuous long-term EEG in rodents remains the mainstay approach but is often technically challenging due to the notorious frequent EEG cable disconnections from the rodent's head, and to poor signal-to-noise ratio especially when simultaneously monitoring multiple animals. Premature EEG cable disconnections and cable movement-related artifacts result from the animal's natural mobility, and subsequent tension on the EEG wires, as well as from potential vigorous and frequent seizures. These challenges are often accompanied by injuries to the scalp, and result in early terminations of costly experiments.

RESULTS

Here we describe an enhanced customized swivel-balance EEG-cage system that allows tension-free rat mobility. The cage setup markedly improves the safety and longevity of current existing wired continuous long-term EEG. Prevention of EEG cable detachments is further enhanced by a special attention to surgical electrode anchoring to the skull. In addition to mechanically preventing premature disconnections, the detailed stepwise approach to the electrical shielding, wiring and grounding required for artifact-free high signal-to-noise ratio recordings is also included. The successful application of our EEG cage system in various rat models of brain insults and epilepsy is described with illustrative high quality tracings of seizures and electrographic patterns obtained during continuous and simultaneous monitoring of multiple rats early and up to 3 months post-brain insult.

CONCLUSION

Our simple-to-implement key modifications to the EEG cage setup allow the safe acquisition of substantial high quality wired EEG data without resorting to the still costly wireless technologies.

Pharmacological classification of centrally acting drugs using EEG in freely moving rats: an old tool to identify new atypical dopamine uptake inhibitors

Atypical dopamine uptake inhibitors (DUIs) bind to the dopamine transporter and inhibit the reuptake of dopamine but have lower abuse potential than psychostimulants. Several atypical DUIs can block abuse-related effects of cocaine and methamphetamine, thus making them potential medication candidates for psychostimulant use disorders. The aim of the current study is to establish an in-vivo assay using EEG for the rapid identification of atypical DUIs with potential for medication development. The typical DUIs cocaine and methylphenidate dose-dependently decreased the power of the alpha, beta, and gamma bands. The atypical DUI modafinil and its F-analog, JBG1-049, decreased the power of beta, but in contrast to cocaine, none of the other frequency bands, while JHW007 did not significantly alter the EEG spectrum. The mu-opioid receptor agonists heroin and morphine dose-dependently decreased the power of gamma and increased power of the other bands. The effect of morphine on EEG power bands was antagonized by naltrexone. The NMDA receptor antagonist ketamine increased the power of all frequency bands. Therefore, typical and atypical DUIs and drugs of other classes differentially affected EEG spectra, showing distinctive features in the magnitude and direction of their effects on EEG. Comparative analysis of the effects of test drugs on EEG indicates a potential atypical profile of JBG1-049 with similar potency and effectiveness to its parent compound modafinil. These data suggest that EEG can be used to rapidly screen compounds for potential activity at specific pharmacological targets and provide valuable information for guiding the early stages of drug development. This article is part of the issue entitled 'Special Issue on Neurotransmitter Transporters'.

Neurophysiological signals as predictive translational biomarkers for Alzheimer's disease treatment: effects of donepezil on neuronal network oscillations in TgF344-AD rats

BACKGROUND

Translational research in Alzheimer's disease (AD) pathology provides evidence that accumulation of amyloid-β and hyperphosphorylated tau, neuropathological hallmarks of AD, is associated with complex disturbances in synaptic and neuronal function leading to oscillatory abnormalities in the neuronal networks that support memory and cognition. Accordingly, our recent study on transgenic TgF344-AD rats modeling AD showed an age-dependent reduction of stimulation-induced oscillations in the hippocampus, and disrupted long-range connectivity together with enhanced neuronal excitability in the cortex, reflected in greatly increased expression of high-voltage spindles, an epileptic absence seizure-like activity. To better understand the translational value of observed oscillatory abnormalities in these rats, we examine here the effects of donepezil, an acetylcholine esterase inhibitor clinically approved for AD treatment.

METHODS

Brainstem nucleus pontis oralis stimulation-induced hippocampal oscillations were recorded under urethane anesthesia in adult (6-month-old) and aged (12-month-old) TgF344-AD and wild-type rats. Spontaneous cortical activity was monitored in a cohort of freely behaving aged rats implanted with frontal and occipital cortical electroencephalography (EEG) electrodes.

RESULTS

Subcutaneous administration of donepezil significantly augmented stimulation-induced hippocampal theta oscillation in aged wild-type rats and both adult and aged TgF344-AD rats, which have been previously shown to have diminished response to nucleus pontis oralis stimulation. Moreover, in adult TgF344-AD rats, donepezil also significantly increased theta phase-gamma amplitude coupling in the hippocampus during stimulation. However, neither of these effects were significantly changed in adult wild-type rats. Under freely behaving conditions, donepezil treatment had the opposite effect on cortical oscillatory connectivity in TgF344-AD and wild-type rats, and it reduced the occurrence of high-voltage spindle activity in TgF344-AD rats.

CONCLUSIONS

Together, these results imply that pharmacologically enhancing cholinergic tone with donepezil could partially reverse oscillatory abnormalities in TgF344-AD rats, which is in line with its clinical effectiveness in AD patients. Therefore, our study suggests good translational opportunities for these neurophysiological signals recorded in TgF344-AD rats, and their application could be considered in drug discovery efforts for developing therapies with disease-modifying potential.

Electroencephalogram alpha asymmetry in patients with depressive disorders: current perspectives

PURPOSE

Electroencephalogram (EEG) alpha asymmetry (AA) in depressive disorders has been of interest over the last few decades, but it continues to remain unclear whether EEG AA can discriminate between healthy and depressive individuals.

MATERIALS AND METHODS

A systematic literature search for papers addressing EEG AA using the keywords alpha asymmetry, depression, and EEG was performed in PubMed. All studies were checked for sample size, gender, handedness, reference, recording protocol, EEG band range, impedance, type of analysis, drugs, and comorbidity.

RESULTS

A total of 61 articles were found, of which 44 met our inclusion criteria. They have been consecutively analyzed in respect of methodology and results. Approximately 25% (11/44) of the studies did not mention or ignored handedness, 41% (18/44) of the studies used data with only self-reported handedness, and only 34.1% (15/44) of all studies tested handedness. Only 35% (15/44) of the studies reported pharmacological treatment, and only 35% (15/44) of the studies controlled for medication. A total of 52% (23/44) of the studies reported comorbidity, and only 30% (13/44) of the studies controlled for comorbidity. Only 29.6% (13/44) of the studies reported education. In all, 30.5% (13/44) of the studies analyzed group differences and correlations, while 15.9 (7/44) of the studies used only correlational analyses. A total of 52.3% (23/44) of the studies analyzed only group differences. Alpha range was fixed (8-13 Hz) in 59.1% (26/44) of all studies. Reference to common average was used in seven of 44 studies (15.9%). In all, nine of 44 (20.5%) studies used the midline central position as reference, 22 of 44 (50%) studies used the ear or the mastoid as reference, and four of 44 (9.1%) studies used the nose as reference.

CONCLUSION

Discriminative power of EEG AA for depressed and healthy controls remains unclear. A systematic analysis of 44 studies revealed that differences in methodology and disregarding proper sampling are problematic. Ignoring handedness, gender, age, medication, and comorbidity could explain inconsistent findings. Hence, we formulated a guideline for requirements for future studies on EEG AA in order to allow for better comparisons.

Developing tomorrow's antipsychotics: the need for a more personalised approach

There has been little pharmacological advance in the treatment of schizophrenia since the introduction of chlorpromazine in the 1950s. This may be set to change as recent advances in molecular biology offer the prospect of a better understanding of the pathophysiology of the disorder and allow investigation of the complex interplay of genetic and environmental risk factors. In this review I discuss future approaches to antipsychotic drug development, highlighting the need to better define symptom areas and develop drugs based on an understanding of neurobiological mechanisms. The development of biomarkers has the potential in future to improve differential diagnosis and help predict response to treatment. These developments herald the possibility of a more integrated drug discovery approach and the subsequent provision of more stratified healthcare, and hopefully significant improvements in patient care and improved long-term outcomes.

Predictors for drug effects with brain disease: Shed new light from EEG parameters to brain connectomics

Though researchers spent a lot of effort to develop treatments for neuropsychiatric disorders, the poor translation of drug efficacy data from animals to human hampered the success of these therapeutic approaches in human. Pharmaceutical industry is challenged by low clinical success rates for new drug registration. To maximize the success in drug development, biomarkers are required to act as surrogate end points and predictors of drug effects. The pathology of brain disease could be in part due to synaptic dysfunction. Electroencephalogram (EEG), generating from the result of the postsynaptic potential discharge between cells, could be a potential measure to bridge the gaps between animal and human data. Here we discuss recent progress on using relevant EEG characteristics and brain connectomics as biomarkers to monitor drug effects and measure cognitive changes on animal models and human in real-time. It is expected that the novel approach, i.e. EEG connectomics, will offer a deeper understanding on the drug efficacy at a microcirculatory level, which will be useful to support the development of new treatments for neuropsychiatric disorders.

Electroencephalographic signatures of pain and analgesia in rats

Pain modulates rhythmic neuronal activity recorded by Electroencephalography (EEG) in humans. Our laboratory previously showed that rat models of acute and neuropathic pain manifest increased power in primary somatosensory cortex (S1) recorded by electrocorticography (ECoG). In this study, we hypothesized that pain increases EEG power and corticocortical coherence in different rat models of pain, whereas treatments with clinically effective analgesics reverse these changes. Our results show increased cortical power over S1 and prefrontal cortex (PFC) in awake, freely behaving rat models of acute, inflammatory and neuropathic pain. Coherence between PFC and S1 is increased at a late, but not early, time point during the development of neuropathic pain. Electroencephalography power is not affected by ibuprofen in the acute pain model. However, pregabalin and mexiletine reverse the changes in power and S1-PFC coherence in the inflammatory and neuropathic pain models. These data suggest that quantitative EEG might be a valuable predictor of pain and analgesia in rodents.

EEG machine learning for accurate detection of cholinergic intervention and Alzheimer's disease

Monitoring effects of disease or therapeutic intervention on brain function is increasingly important for clinical trials, albeit hampered by inter-individual variability and subtle effects. Here, we apply complementary biomarker algorithms to electroencephalography (EEG) recordings to capture the brain’s multi-faceted signature of disease or pharmacological intervention and use machine learning to improve classification performance. Using data from healthy subjects receiving scopolamine we developed an index of the muscarinic acetylcholine receptor antagonist (mAChR) consisting of 14 EEG biomarkers. This mAChR index yielded higher classification performance than any single EEG biomarker with cross-validated accuracy, sensitivity, specificity and precision ranging from 88–92%. The mAChR index also discriminated healthy elderly from patients with Alzheimer’s disease (AD); however, an index optimized for AD pathophysiology provided a better classification. We conclude that integrating multiple EEG biomarkers can enhance the accuracy of identifying disease or drug interventions, which is essential for clinical trials.

Discovering the Neural Nature of Moral Cognition? Empirical, Theoretical, and Practical Challenges in Bioethical Research with Electroencephalography (EEG)

In this article we critically review the neural mechanisms of moral cognition that have recently been studied via electroencephalography (EEG). Such studies promise to shed new light on traditional moral questions by helping us to understand how effective moral cognition is embodied in the brain. It has been argued that conflicting normative ethical theories require different cognitive features and can, accordingly, in a broadly conceived naturalistic attempt, be associated with different brain processes that are rooted in different brain networks and regions. This potentially morally relevant brain activity has been empirically investigated through EEG-based studies on moral cognition. From neuroscientific evidence gathered in these studies, a variety of normative conclusions have been drawn and bioethical applications have been suggested. We discuss methodological and theoretical merits and demerits of the attempt to use EEG techniques in a morally significant way, point to legal challenges and policy implications, indicate the potential to reveal biomarkers of psychopathological conditions, and consider issues that might inform future bioethical work.

Early Decision-Making in Drug Development: The Potential Role of Pharmaco-EEG and Pharmaco-Sleep

The pharmaceutical industry has been suffering from low clinical success rates of new drugs for some time with particularly high attrition in early clinical development, especially for drugs aimed at central targets. Both pharmaco-electroencephalography (EEG) and pharmaco-sleep, along with other biomarker techniques, have significant potential to assist with this problem by enabling early decisions to be made about the likelihood of a compound proving successful in the clinic. This paper discusses the role and points of application of biomarker techniques in early drug development. It proposes a framework for the use of pharmaco-EEG and pharmaco-sleep in drug development that (i) relies on the combination of preclinical data and an understanding of translatability to generate robust hypotheses for testing in early clinical studies and (ii) is backed up by a clear decision-making process. The areas that need further development before this framework can be put fully into practice are discussed, along with some possible routes by which this could be achieved through precompetitive co-operation within the industry.

Advanced Analysis of Pharmaco-Sleep Data in Humans

Pharmaco-sleep studies in humans aim at the description of the effects of drugs, most frequently substances that act on the central nervous system, by means of quantitative analysis of biosignals recorded in subjects during sleep. Up to 2007, the only standard for the classification of sleep macrostructure that found worldwide acceptance were the rules published in 1968 by Rechtschaffen and Kales. In May 2007, the AASM Manual for the Scoring of Sleep and Associated Events was published by the American Academy of Sleep Medicine, and concerning the classification of sleep stages, these new rules are supposed to replace those developed by Rechtschaffen and Kales. As compared to the rather low interrater reliability of manual sleep scoring, semiautomated approaches may achieve a reliability close to 1 (Cohen's kappa 0.99 for 2 semiautomated scorings as compared to 0.76 for 2 manual scorings) without any decline in validity. Depending on the aim of the pharmaco-sleep study, additional analyses concerning sleep fragmentation, sleep microstructure, sleep depth, sleep processes and local aspects of sleep should be considered. For some of these additional features, rules for visual scoring have been established, while for others automatic analysis is obligatory. Generally, for reasons of cost-effectiveness but also reliability, automatic analysis is preferable to visual analysis. However, the validity of the automatic method applied has to be proven.

Pharmaco-EEG Studies in Animals: An Overview of Contemporary Translational Applications

The contemporary value of animal pharmaco-electroencephalography (p-EEG)-based applications are strongly interlinked with progress in recording and neuroscience analysis methodology. While p-EEG in humans and animals has been shown to be closely related in terms of underlying neuronal substrates, both translational and back-translational approaches are being used to address extrapolation issues and optimize the translational validity of preclinical animal p-EEG paradigms and data. Present applications build further on animal p-EEG and pharmaco-sleep EEG findings, but also on stimulation protocols, more specifically pharmaco-event-related potentials. Pharmaceutical research into novel treatments for neurological and psychiatric diseases has employed an increasing number of pharmacological as well as transgenic models to assess the potential therapeutic involvement of different neurochemical systems and novel drug targets as well as underlying neuronal connectivity and synaptic function. Consequently, p-EEG studies, now also readily applied in modeled animals, continue to have an important role in drug discovery and development, with progressively more emphasis on its potential as a central readout for target engagement and as a (translational) functional marker of neuronal circuit processes underlying normal and pathological brain functioning. In a similar vein as was done for human p-EEG studies, the contribution of animal p-EEG studies can further benefit by adherence to guidelines for methodological standardization, which are presently under construction by the International Pharmaco-EEG Society (IPEG).

Ketamine Protects Gamma Oscillations by Inhibiting Hippocampal LTD

NMDA receptors have been widely reported to be involved in the regulation of synaptic plasticity through effects on long-term potentiation (LTP) and long-term depression (LTD). LTP and LTD have been implicated in learning and memory processes. Besides synaptic plasticity, it is known that the phenomenon of gamma oscillations is critical in cognitive functions. Synaptic plasticity has been widely studied, however it is still not clear, to what degree synaptic plasticity regulates the oscillations of neuronal networks. Two NMDA receptor antagonists, ketamine and memantine, have been shown to regulate LTP and LTD, to promote cognitive functions, and have even been reported to bring therapeutic effects in major depression and Alzheimer’s disease respectively. These compounds allow us to investigate the putative interrelationship between network oscillations and synaptic plasticity and to learn more about the mechanisms of their therapeutic effects. In the present study, we have identified that ketamine and memantine could inhibit LTD, without impairing LTP in the CA1 region of mouse hippocampus, which may underlie the mechanism of these drugs’ therapeutic effects. Our results suggest that NMDA-induced LTD caused a marked loss in the gamma power, and pretreatment with 10 μM ketamine prevented the oscillatory loss via its inhibitory effect on LTD. Our study provides a new understanding of the role of NMDA receptors on hippocampal plasticity and oscillations.

Electroencephalogram alpha asymmetry in geriatric depression : Valid or vanished?

BACKGROUND

A correlation between asymmetry in electroencephalographs (EEG) and depression has been demonstrated in many studies. To the best of our knowledge there are no studies including oldest old geriatric patients.

OBJECTIVE

The objective of this study was to evaluate whether frontal and parietal alpha asymmetry can be used to differentiate between depressed and control patients in a cohort sample with a mean age of 80 years.

MATERIAL AND METHODS

Differences in the EEG were investigated in 39 right-handed female geriatric patients (mean age 80 years) with respect to frontal alpha asymmetry (FAA) and parietal alpha asymmetry (PAA) in depression (n = 14), depression combined with anxiety (n = 11) and normal controls (n = 14) as assessed with the hospital anxiety and depression scale (HADS). Band power was calculated for alpha 1 (6.9-8.9 Hz), alpha 2 (8.9-10.9 Hz) and alpha 3 bands (10.9-12.9 Hz). Furthermore, correlations between frontal and parietal alpha asymmetry and the geriatric depression scale (GDS), the HADS and the mini mental state examination (MMSE) were calculated.

RESULTS

A differentiation between the three groups was not possible with FAA and PAA. Significant correlations were found between PAA alpha 3 band and anxiety and depression.

CONCLUSION

The alpha asymmetry in EEG seemed to disappear with age. Correlations between PAA and anxiety and depression were found. The results are in line with the right (hemisphere) hemi-aging hypothesis.

Behavioral and qEEG effects of the PDE10A inhibitor THPP-1 in a novel rhesus model of antipsychotic activity

RATIONALE

Much preclinical data, almost exclusively using rodent, supports the notion that phosphodiesterase 10A (PDE10A) inhibition may offer an alternative to the current standard of care in schizophrenia. However, concerns persist regarding the clinical translatability of these models for newer drug classes like PDE10A inhibitors.

OBJECTIVES

We therefore sought to characterize the clinical standard risperidone and the PDE10A inhibitor THPP-1 in nonhuman primate, both alone and when used as a combination therapy.

METHODS

THPP-1 and risperidone were tested in a novel rhesus model of stimulant-induced motor activity (SIMA) and in rhesus electroencephalography (EEG).

RESULTS

Consistent with rodent data, both THPP-1 and risperidone significantly attenuated the stimulant effects in SIMA when administered alone, though some differences were noted. Combination therapy with a low dose of risperidone produced significantly more robust effects. THPP-1 and risperidone also produced a marked reduction of wake cycle time and gamma frequency power in EEG. However, THPP-1 differed from risperidone by reducing spectral power of lower frequencies (delta).

CONCLUSIONS

SIMA results suggest that PDE10A inhibition produces antipsychotic-like effects in higher species, and that combination therapy with PDE10A inhibitors may produce more robust efficacy compared to monotherapies. EEG and qEEG results confirm that PDE10A inhibition does share some central signaling effects with clinically effective antipsychotics. The present combination therapy results may carry implications for the manner in which clinical testing of PDE10A inhibitors is conducted.

EEG in non-clinical drug safety assessments: Current and emerging considerations

Electroencephalogram (EEG) data in nonclinical species can play a critical role in the successful evaluation of a compound during drug development, particularly in the evaluation of seizure potential and for monitoring changes in sleep. Yet, while non-invasive electrocardiogram (ECG) monitoring is commonly included in preclinical safety studies, pre-dose or post-dose EEG assessments are not. Industry practices as they relate to preclinical seizure liability and sleep assessments are not well characterized and the extent of preclinical EEG testing varies between organizations. In the current paper, we discuss the various aspects of preclinical EEG to characterize drug-induced seizure risk and sleep disturbances, as well as describe the use of these data in a regulatory context. An overview of EEG technology-its correct application and its limitations, as well as best practices for setting up the animal models is presented. Sleep and seizure detection are discussed in detail. A regulatory perspective on the use of EEG data is provided and, tying together the previous topics is a discussion of the translational aspects of EEG.