Application of electroencephalography to the study of cognitive and brain functions in schizophrenia

Investigating cortical complexity and connectivity in rats with schizophrenia

Background

The above studies indicate that the SCZ animal model has abnormal gamma oscillations and abnormal functional coupling ability of brain regions at the cortical level. However, few researchers have focused on the correlation between brain complexity and connectivity at the cortical level. In order to provide a more accurate representation of brain activity, we studied the complexity of electrocorticogram (ECoG) signals and the information interaction between brain regions in schizophrenic rats, and explored the correlation between brain complexity and connectivity.

Methods

We collected ECoG signal from SCZ rats. The frequency domain and time domain functional connectivity of SCZ rats were evaluated by magnitude square coherence and mutual information (MI). Permutation entropy (PE) and permutation Lempel-Ziv complexity (PLZC) were used to analyze the complexity of ECoG, and the relationship between them was evaluated. In addition, in order to further understand the causal structure of directional information flow among brain regions, we used phase transfer entropy (PTE) to analyze the effective connectivity of the brain.

Results

Firstly, in the high gamma band, the complexity of brain regions in SCZ rats is higher than that in normal rats, and the neuronal activity is irregularity. Secondly, the information integration ability of SCZ rats decreased and the communication of brain network information was hindered at the cortical level. Finally, compared with normal rats, the causal relationship between brain regions of SCZ rats was closer, but the information interaction center was not clear.

Conclusion

The above findings suggest that at the cortical level, complexity and connectivity are valid biomarkers for identifying SCZ. This bridges the gap between peak potentials and EEG. This may help to understand the pathophysiological mechanisms at the cortical level in schizophrenics.

A low-cost, wireless, 4-channel EEG measurement system used in virtual reality environments

The combination of Virtual Reality (VR) technology and Electroencephalography (EEG) measurements has shown tremendous potential in the fields of psychology and neuroscience research. However, the majority of EEG measurement devices currently available are expensive, bulky, uncomfortable to wear, and difficult to integrate with VR headsets. These limitations have hindered the development of related research fields. This study describes a low-cost (60.07 USD), small-sized, wireless, high-precision, low-power consumption 4-channel EEG measurement system (NeuroVista) for frontal area EEG measurements, which can be used with a VR headset, enabling EEG measurements in VR environments. The system has an input-referred noise of less than 0.9480 μ V r m s , a common mode rejection ratio of over 96 dB, a measurement resolution of less than 0.1 μ V , a bandwidth of 0.5 ∼ 45 Hz, and works at a sampling rate of 250 Hz. It also supports metal dry electrodes and includes a built-in analog bandpass filter, right-leg drive circuit, and built-in digital lowpass filter and notch filter, which can reduce noise during measurement. Researchers can reconstruct the electrode system to measure regions of interest according to their needs.

Using Nonhuman Primate Models to Reverse-Engineer Prefrontal Circuit Failure Underlying Cognitive Deficits in Schizophrenia

In this chapter, I review studies in nonhuman primates that emulate the circuit failure in prefrontal cortex responsible for working memory and cognitive control deficits in schizophrenia. These studies have characterized how synaptic malfunction, typically induced by blockade of NMDAR, disrupts neural function and computation in prefrontal networks to explain errors in cognitive tasks that are seen in schizophrenia. This work is finding causal relationships between pathogenic events of relevance to schizophrenia at vastly different levels of scale, from synapses, to neurons, local, circuits, distributed networks, computation, and behavior. Pharmacological manipulation, the dominant approach in primate models, has limited construct validity for schizophrenia pathogenesis, as the disease results from a complex interplay between environmental, developmental, and genetic factors. Genetic manipulation replicating schizophrenia risk is more advanced in rodent models. Nonetheless, gene manipulation in nonhuman primates is rapidly advancing, and primate developmental models have been established. Integration of large scale neural recording, genetic manipulation, and computational modeling in nonhuman primates holds considerable potential to provide a crucial schizophrenia model moving forward. Data generated by this approach is likely to fill several crucial gaps in our understanding of the causal sequence leading to schizophrenia in humans. This causal chain presents a vexing problem largely because it requires understanding how events at very different levels of scale relate to one another, from genes to circuits to cognition to social interactions. Nonhuman primate models excel here. They optimally enable discovery of causal relationships across levels of scale in the brain that are relevant to cognitive deficits in schizophrenia. The mechanistic understanding of prefrontal circuit failure they promise to provide may point the way to more effective therapeutic interventions to restore function to prefrontal networks in the disease.

SparNet: A Convolutional Neural Network for EEG Space-Frequency Feature Learning and Depression Discrimination

Depression affects many people around the world today and is considered a global problem. Electroencephalogram (EEG) measurement is an appropriate way to understand the underlying mechanisms of major depressive disorder (MDD) to distinguish depression from normal control. With the development of deep learning methods, many researchers have adopted deep learning models to improve the classification accuracy of depression recognition. However, there are few studies on designing convolution filters for spatial and frequency domain feature learning in different brain regions. In this study, SparNet, a convolutional neural network composed of five parallel convolutional filters and the SENet, is proposed to learn EEG space-frequency domain characteristics and distinguish between depressive and normal control. The model is trained and tested by the cross-validation method of subject division. The results show that SparNet achieves a sensitivity of 95.07%, a specificity of 93.66%, and an accuracy of 94.37% in classification. Therefore, our results can conclude that the proposed SparNet model is effective in detecting depression using EEG signals. It also indicates that the combination of spatial information and frequency domain information is an effective way to identify patients with depression.

Topological Data Analysis as a New Tool for EEG Processing

Electroencephalography (EEG) is a widely used cerebral activity measuring device for both clinical and everyday life applications. In addition to denoising and potential classification, a crucial step in EEG processing is to extract relevant features. Topological data analysis (TDA) as an emerging tool enables to analyse and understand data from a different angle than traditionally used methods. As a higher dimensional analogy of graph analysis, TDA can model rich interactions beyond pairwise relations. It also distinguishes different dynamics of EEG time series. TDA remains largely unknown to the EEG processing community while it fits well the heterogeneous nature of EEG signals. This short review aims to give a quick introduction to TDA and how it can be applied to EEG analysis in various applications including brain-computer interfaces (BCIs). After introducing the objective of the article, the main concepts and ideas of TDA are explained. Next, how to implement it for EEG processing is detailed, and lastly the article discusses the benefits and limitations of the method.

The Influence of Filters on EEG-ERP Testing: Analysis of Motor Cortex in Healthy Subjects

The raw EEG signal is always contaminated with many different artifacts, such as muscle movements (electromyographic artifacts), eye blinking (electrooculographic artifacts) or power line disturbances. All artifacts must be removed for correct data interpretation. However, various noise reduction methods significantly influence the final shape of the EEG signal and thus its characteristic values, latency and amplitude. There are several types of filters to eliminate noise early in the processing of EEG data. However, there is no gold standard for their use. This article aims to verify and compare the influence of four various filters (FIR, IIR, FFT, NOTCH) on the latency and amplitude of the EEG signal. By presenting a comparison of selected filters, the authors intend to raise awareness among researchers as regards the effects of known filters on latency and amplitude in a selected area-the sensorimotor area.

Use of cognitive event-related potentials in the management of psychiatric disorders: Towards an individual follow-up and multi-component clinical approach

Relapse prevention remains a major challenge in psychiatry, thus indicating that the established treatment methods combining psychotherapy with neuropharmacological interventions are not entirely effective. In recent years, several intervention strategies have been devised that are aimed at improving psychiatric treatment by providing a complementary set of add-on tools that can be used by clinicians to improve current patient assessment. Among these, cognitive event-related potentials (ERPs) have been indexed as valuable biomarkers of the pathophysiological mechanisms of various mental illnesses. However, despite decades of research, their clinical utility is still controversial and a matter of debate. In this opinion review, I present the main arguments supporting the use of cognitive ERPs in the management of psychiatric disorders, stressing why it is currently still not the case despite the vast number of ERP studies to date. I also propose a clinically-oriented suitable way in which this technique could - in my opinion - be effectively incorporated into individual patient care by promotion of the use of individual ERP test-retest sessions and the use of a multi-component approach.

Advanced EEG-based learning approaches to predict schizophrenia: Promises and pitfalls

The complexity and heterogeneity of schizophrenia symptoms challenge an objective diagnosis, which is typically based on behavioral and clinical manifestations. Moreover, the boundaries of schizophrenia are not precisely demarcated from other nosologic categories, such as bipolar disorder. The early detection of schizophrenia can lead to a more effective treatment, improving patients' quality of life. Over the last decades, hundreds of studies aimed at specifying the neurobiological mechanisms that underpin clinical manifestations of schizophrenia, using techniques such as electroencephalography (EEG). Changes in event-related potentials of the EEG have been associated with sensory and cognitive deficits and proposed as biomarkers of schizophrenia. Besides contributing to a more effective diagnosis, biomarkers can be crucial to schizophrenia onset prediction and prognosis. However, any proposed biomarker requires substantial clinical research to prove its validity and cost-effectiveness. Fueled by developments in computational neuroscience, automatic classification of schizophrenia at different stages (prodromal, first episode, chronic) has been attempted, using brain imaging pattern recognition methods to capture differences in functional brain activity. Advanced learning techniques have been studied for this purpose, with promising results. This review provides an overview of recent machine learning-based methods for schizophrenia classification using EEG data, discussing their potentialities and limitations. This review is intended to serve as a starting point for future developments of effective EEG-based models that might predict the onset of schizophrenia, identify subjects at high-risk of psychosis conversion or differentiate schizophrenia from other disorders, promoting more effective early interventions.

EEG-Based Measures in At-Risk Mental State and Early Stages of Schizophrenia: A Systematic Review

Introduction: Electrophysiological (EEG) abnormalities in subjects with schizophrenia have been largely reported. In the last decades, research has shifted to the identification of electrophysiological alterations in the prodromal and early phases of the disorder, focusing on the prediction of clinical and functional outcome. The identification of neuronal aberrations in subjects with a first episode of psychosis (FEP) and in those at ultra high-risk (UHR) or clinical high-risk (CHR) to develop a psychosis is crucial to implement adequate interventions, reduce the rate of transition to psychosis, as well as the risk of irreversible functioning impairment. The aim of the review is to provide an up-to-date synthesis of the electrophysiological findings in the at-risk mental state and early stages of schizophrenia. Methods: A systematic review of English articles using Pubmed, Scopus, and PsychINFO was undertaken in July 2020. Additional studies were identified by hand-search. Electrophysiological studies that included at least one group of FEP or subjects at risk to develop psychosis, compared to healthy controls (HCs), were considered. The heterogeneity of the studies prevented a quantitative synthesis. Results: Out of 319 records screened, 133 studies were included in a final qualitative synthesis. Included studies were mainly carried out using frequency analysis, microstates and event-related potentials. The most common findings included an increase in delta and gamma power, an impairment in sensory gating assessed through P50 and N100 and a reduction of Mismatch Negativity and P300 amplitude in at-risk mental state and early stages of schizophrenia. Progressive changes in some of these electrophysiological measures were associated with transition to psychosis and disease course. Heterogeneous data have been reported for indices evaluating synchrony, connectivity, and evoked-responses in different frequency bands. Conclusions: Multiple EEG-indices were altered during at-risk mental state and early stages of schizophrenia, supporting the hypothesis that cerebral network dysfunctions appear already before the onset of the disorder. Some of these alterations demonstrated association with transition to psychosis or poor functional outcome. However, heterogeneity in subjects' inclusion criteria, clinical measures and electrophysiological methods prevents drawing solid conclusions. Large prospective studies are needed to consolidate findings concerning electrophysiological markers of clinical and functional outcome.

Wireless Sensors for Brain Activity—A Survey

Over the last decade, the area of electroencephalography (EEG) witnessed a progressive move from high-end large measurement devices, relying on accurate construction and providing high sensitivity, to miniature hardware, more specifically wireless wearable EEG devices. While accurate, traditional EEG systems need a complex structure and long periods of application time, unwittingly causing discomfort and distress on the users. Given their size and price, aside from their lower sensitivity and narrower spectrum band(s), wearable EEG devices may be used regularly by individuals for continuous collection of user data from non-medical environments. This allows their usage for diverse, nontraditional, non-medical applications, including cognition, BCI, education, and gaming. Given the reduced need for standardization or accuracy, the area remains a rather incipient one, mostly driven by the emergence of new devices that represent the critical link of the innovation chain. In this context, the aim of this study is to provide a holistic assessment of the consumer-grade EEG devices for cognition, BCI, education, and gaming, based on the existing products, the success of their underlying technologies, as benchmarked by the undertaken studies, and their integration with current applications across the four areas. Beyond establishing a reference point, this review also provides the critical and necessary systematic guidance for non-medical EEG research and development efforts at the start of their investigation.

The electrophysiology correlation of the cognitive bias in anxiety under uncertainty

The intolerance of uncertainty (IU) model holds that excessive emotional response under uncertain conditions is conducive to the maintenance of anxiety, and individuals with a high anxiety level may exhibit a negative bias and experience anxiety when processing uncertain information. However, the dynamic electrophysiological correlation of this negative bias is not clear. Therefore, we used an adapted study–test paradigm to explore the changes in the electroencephalography (EEG) of subjects when processing uncertain cues and certain cues (certain neutral and certain threatening) and correlated the differences with anxiety level. The behavioral results showed that there was a significant positive correlation between the trait anxiety score and β value under the threatening condition, which indicated that individuals with high trait anxiety take a more conservative approach in the face of negative stimuli. The results of EEG showed that during the test stage, the components N1 and P2, which are related to early perception, had significant conditional main effects. Meanwhile, under uncertain conditions, the N1 peak was positively correlated with the state anxiety score. In the study stage, we found that the N400 component was significantly larger in the early study stage than in the late study stage under uncertain conditions. In sum, individuals with high anxiety levels had a negative bias in the early cue processing of the test stage, and anxiety did not affect the study stage.

Progressive Impairment of Mismatch Negativity Is Reflective of Underlying Pathophysiological Changes in Patients With First-Episode Psychosis

BACKGROUND

Although mismatch negativity (MMN) is associated with the pathophysiology of schizophrenia, whether MMN progressively worsens during the initial years of psychotic disorder has not yet been sufficiently studied. We aimed to investigate whether longitudinal reduction of MMN occurs in patients with first-episode psychosis (FEP) and whether it is reflective of change in cognitive functioning or clinical status.

METHODS

MMN and the clinical status of 25 patients with FEP were measured and the Trail Making Test (TMT) was administered at baseline and reassessed after 1 year of usual treatment. The MMN of 25 matched healthy controls (HCs) was measured at baseline. Repeated-measures analysis of variance was used to compare MMNs at baseline among the groups, and paired t-test was utilized to compare the baseline and 1-year MMN amplitudes of FEP patients. To identify the association between changes in MMN and changes in cognitive, symptomatic, or functional status over 1 year, multiple regression analysis was used to control for other possible confounders.

RESULTS

MMN amplitudes at baseline were significantly attenuated in FEP patients compared to those in HC. The 1-year follow-up MMN amplitude decreased significantly at the Fz electrode site in the FEP group. Additionally, the decreased MMN amplitude significantly correlated with worsened TMT part B (TMT-B) performance over 1 year but did not correlate with symptomatic or functional improvement.

CONCLUSIONS

FEP patients with an MMN amplitude reduction showed worsening of cognitive functioning, which might reflect pathophysiological progression during the early years of a psychotic episode.

Scn2a haploinsufficient mice display a spectrum of phenotypes affecting anxiety, sociability, memory flexibility and ampakine CX516 rescues their hyperactivity

Background

Mutations of the SCN2A gene encoding a voltage-gated sodium channel alpha-II subunit Nav1.2 are associated with neurological disorders such as epilepsy, autism spectrum disorders, intellectual disability, and schizophrenia. However, causal relationships and pathogenic mechanisms underlying these neurological defects, especially social and psychiatric features, remain to be elucidated.

Methods

We investigated the behavior of mice with a conventional or conditional deletion of Scn2a in a comprehensive test battery including open field, elevated plus maze, light-dark box, three chambers, social dominance tube, resident-intruder, ultrasonic vocalization, and fear conditioning tests. We further monitored the effects of the positive allosteric modulator of AMPA receptors CX516 on these model mice.

Results

Conventional heterozygous Scn2a knockout mice (Scn2a^KO/+) displayed novelty-induced exploratory hyperactivity and increased rearing. The increased vertical activity was reproduced by heterozygous inactivation of Scn2a in dorsal-telencephalic excitatory neurons but not in inhibitory neurons. Moreover, these phenotypes were rescued by treating Scn2a^KO/+ mice with CX516. Additionally, Scn2a^KO/+ mice displayed mild social behavior impairment, enhanced fear conditioning, and deficient fear extinction. Neuronal activity was intensified in the medial prefrontal cortex of Scn2a^KO/+ mice, with an increase in the gamma band.

Conclusions

Scn2a^KO/+ mice exhibit a spectrum of phenotypes commonly observed in models of schizophrenia and autism spectrum disorder. Treatment with the CX516 ampakine, which ameliorates hyperactivity in these mice, could be a potential therapeutic strategy to rescue some of the disease phenotypes.

Electronic supplementary material

The online version of this article (10.1186/s13229-019-0265-5) contains supplementary material, which is available to authorized users.

Effect of GAD1 genotype status on auditory attention and acute nicotine administration in healthy volunteers

OBJECTIVE

The effects of GABA modulating drugs and nicotine, the prototypical nicotinic cholinergic agonist, on attention have been investigated using subcomponents of the P300 event-related potentials (ERP), which index involuntary (P3a) and voluntary attention (P3b). However, investigations into how such pharmacologic effects interact with genetic features in the GABA system remain unclear. This study examined the moderating effects of a single nucleotide polymorphism (rs7557793) in the glutamic acid decarboxylase 67 (GAD1) gene, which is implicated in the conversion of glutamate to GABA, on P300-indices of auditory attentional processing; the influence of nicotine administration was also assessed.

METHODS

The effects of GAD1 genotype (TT/CC/CT) were examined on the P3a/b in response to an auditory selective attention task in healthy, nonsmoking male volunteers (N = 126; 18-40 years). Participants responded to rare target stimuli (P3b-eliciting) and ignored frequent nontarget stimuli as well as rare distractor stimuli (P3a-eliciting). In a subsample (N = 59), P3a/b profiles to acute nicotine (vs. placebo) administration were examined as a function of GAD1 genotype. As a secondary aim, earlier sensory processes were assessed with N200 ERP subcomponents elicited by novel (N2a) and target (N2b) auditory stimuli.

RESULTS

GAD1 allelic variation moderated early sensory processes, enhancing N2a amplitudes in CT versus TT carriers. Further, TT homozygotes exhibited larger P3b amplitudes than CC homozygotes in the placebo versus nicotine condition. Regardless of genotype, nicotine versus placebo moderated the N200 ERP.

CONCLUSION

These findings expand our knowledge regarding the attentional effects of GAD1 genetic variants in relation to nicotine.

Interrogating the Relationship Between Schizotypy, the Catechol-O-Methyltransferase (COMT) Val158Met Polymorphism, and Neuronal Oscillatory Activity

The COMT Val158Met polymorphism affects the availability of synaptic dopamine in the prefrontal cortex and has been widely studied as a genetic risk factor for psychosis. Schizotypy is associated with an increased risk of psychosis, with some studies implicating similar neurobiological mechanisms to schizophrenia. The present study sought to interrogate the link between the COMT Val158Met polymorphism and schizotypy using electroencephalogram (EEG) to identify neurophysiological mechanisms underpinning psychosis risk. Neurotypical (N = 91) adults were genotyped for the COMT Val158Met polymorphism, completed the Schizotypal Personality Questionnaire (SPQ), and had eyes open resting-state EEG recorded for 4 min. SPQ suspiciousness subscale scores were higher for individuals homozygous for Val/Val and Met/Met versus Val/Met genotypes. Delta, theta, alpha-2, beta-1, and beta-2 amplitudes were lower for Val/Val than Met/Met individuals. Lower theta amplitudes were correlated with higher total SPQ scores (P = 0.050), and multiple regression revealed that higher delta, and lower theta and beta-2 amplitudes (but not COMT genotype) best predicted total SPQ scores (P = 0.014). This study demonstrates the importance of COMT genotype in determining trait suspiciousness and EEG oscillatory activity. It also highlights relationships between dopaminergic alterations, EEG and schizotypy that are dissimilar to those observed in schizophrenia.

Why cognitive event-related potentials (ERPs) should have a role in the management of alcohol disorders

Alcohol dependence is currently one of the most serious public health problems. Indeed, 3-8% of all deaths worldwide are attributable to effects of alcohol consumption. Although the first step in alcohol dependence treatment is straightforward, the main problem for clinicians lies with the prevention of relapse, as 40-70% of patients who only undergo psychosocial therapy resume alcohol use within a year following treatment. This review of the literature regarding event-related potentials (ERPs) is focused on two major neurocognitive factors that partially account for the inability of many alcoholics to remain abstinent: attentional biases towards alcohol-related stimuli that increase the urge to drink, and impaired response inhibition towards these cues that makes it more difficult for alcoholics to resist the temptation to drink. On this basis, we propose new research avenues to better implement ERPs in the management of alcohol disorders, according to four main directions that relate to (1) the development of ERP serial recordings; (2) the promotion of a multi-component ERP approach; (3) the definition of multi-site guidelines; and (4) the use of more representative laboratory situations through the use of more compelling environments.

Binary classification of multichannel-EEG records based on the ϵ-complexity of continuous vector functions

BACKGROUND AND OBJECTIVE

A crucial step in a classification of electroencephalogram (EEG) records is the feature selection. The feature selection problem is difficult because of the complex structure of EEG signals. To classify the EEG signals with good accuracy, most of the recently published studies have used high-dimensional feature spaces. Our objective is to create a low-dimensional feature space that enables binary classification of EEG records.

METHODS

The proposed approach is based on our theory of the ϵ-complexity of continuous functions, which is extended here (see Appendix) to the case of vector functions. This extension permits us to handle multichannel-EEG records. The method consists of two steps. Firstly, we estimate the ϵ-complexity coefficients of the original signal and its finite differences. Secondly, we utilize the random forest (RF) or support vector machine (SVM) classifier.

RESULTS

We demonstrated the performance of our method on simulated data. We also applied it to the problem of classification of multichannel-EEG records related to a group of healthy adolescents (39 subjects) and a group of adolescents with schizophrenia (45 subjects). We found that the random forest classifier provides a superior result. In particular, out-of-bag accuracy in the case of RF was 85.3%. Using 10-fold cross-validation (CV), RF gave an average accuracy of 84.5% on a test set, whereas SVM gave an accuracy of 81.07%. We note that the highest accuracy on CV was 89.3%. To compare our method with the classical approach, we performed classification using the spectral features. In this case, the best performance was achieved using seven-dimensional feature space, with an average accuracy of 83.6%.

CONCLUSIONS

We developed a model-free method for binary classification of EEG records. The feature space was reduced to four dimensions. The results obtained indicate the effectiveness of the proposed method.

Tolcapone-Enhanced Neurocognition in Healthy Adults: Neural Basis and Predictors

BACKGROUND

Failure of procognitive drug trials in schizophrenia may reflect the clinical heterogeneity of schizophrenia, underscoring the need to identify biomarkers of treatment sensitivity. We used an experimental medicine design to test the procognitive effects of a putative procognitive agent, tolcapone, using an electroencephalogram-based cognitive control task in healthy subjects.

METHODS

Healthy men and women (n=27; ages 18-35 years), homozygous for either the Met/Met or Val/Val rs4680 genotype, received placebo and tolcapone 200 mg orally across 2 test days separated by 1 week in a double-blind, randomized, counterbalanced, within-subject design. On each test day, neurocognitive performance was assessed using the MATRICS Consensus Cognitive Battery and an electroencephalogram-based 5 Choice-Continuous Performance Test.

RESULTS

Tolcapone enhanced visual learning in low-baseline MATRICS Consensus Cognitive Battery performers (d=0.35) and had an opposite effect in high performers (d=0.5), and enhanced verbal fluency across all subjects (P=.03) but had no effect on overall MATRICS Consensus Cognitive Battery performance. Tolcapone reduced false alarm rate (d=0.8) and enhanced frontal P200 amplitude during correctly identified nontarget trials (d=0.6) in low-baseline 5 Choice-Continuous Performance Test performers and had opposite effects in high performers (d=0.5 and d=0.25, respectively). Tolcapone's effect on frontal P200 amplitude and false alarm rate was correlated (rs=-0.4, P=.05). All neurocognitive effects of tolcapone were independent of rs4680 genotype.

CONCLUSION

Tolcapone enhanced neurocognition and engaged electroencephalogram measures relevant to cognitive processes in specific subgroups of healthy individuals. These findings support an experimental medicine model for identifying procognitive treatments and provide a strong basis for future biomarker-informed procognitive studies in schizophrenia patients.

Change in the P300 index - a pilot randomized controlled trial of low-frequency electrical stimulation of acupuncture points in middle-aged men and women

Background

The P300 is a major index used to evaluate improvements in brain function. Although a few studies have reported evaluating the effectiveness of manual acupuncture or electro-acupuncture by monitoring the P300, research in this field is not yet very active. The aim of this study was to investigate the effects of periodic low-frequency electrical stimulation applied to BL62 and KI6 on brain activity by analyzing the P300.

Method

The study was conducted as a randomized double-blind test of 55 subjects in their 50s, including 26 males and 29 females. Each subject received 12 sessions of stimulation over a one-month period. In each session, low-frequency electrical stimulation at an average of 24 μA and 2 Hz was applied to the acupuncture points BL62 and KI6, and event-related potentials (ERPs) were measured before the first session and after the last session of the electrical stimulation.

Results

The results of a chi-square test indicated that the double-blind test was conducted correctly. Compared to the Sham group, all the subjects in the Real stimulation group showed a tendency toward a decreasing P300 latency and increasing P300 amplitude after all 12 sessions of stimulation. In the women, the amplitude significantly increased at Fz, Fcz, Cz, Cpz, and Pz.

Conclusions

With this experiment, the low-frequency electrical stimulation of two acupuncture points (BL62 and K16) was confirmed to have a positive influence on the prevention of natural cerebral aging.

Trial registration

This study was registered at the Clinical Research Information Service (CRIS) of the National Research Institute of Health (https://cris.nih.go.kr/cris/search/search_result_st01_en.jsp?, Registration Number: KCT0001940). The date of registration was June 9, 2016.

Pitch and Duration Mismatch Negativity and Premorbid Intellect in the First Hospitalized Schizophrenia Spectrum

Mismatch negativity (MMN) is a robustly abnormal brainwave in chronically ill schizophrenia that has generated interest as a disease presence biomarker. Reports of MMN reduction in first-episode schizophrenia have been equivocal, raising uncertainty about its reduction at first psychotic break. Here we tested 29 schizophrenia-spectrum participants under 1 year from their first hospitalization for psychosis and 40 age-, gender-, parental socioeconomic status-, and Wechsler Adult Intelligence Scales III Information-matched healthy controls on both pitch and duration MMN. Participants performed a visual checkerboard tracking task while standard (1kHz, 50ms, 80%), pitch-deviant (1.2kHz, 50ms, 10%) and duration-deviant (1kHz, 100ms, 10%) tones were presented over headphones (75 dB) and EEG was recorded. Independent component analysis was used to remove eye movements and visual stimulus processing activity. Groups did not differ in pitch MMN or duration MMN amplitudes. Smaller pitch and duration MMN amplitudes were associated with lower estimates of premorbid intellect in all participants and independently with greater positive symptoms in first hospitalized schizophrenia. Overall MMN reduction was not present in these relatively high functioning individuals at the first episode of schizophrenia, and therefore is not a good disease presence biomarker for this sample. Future research is warranted to determine the degree of MMN reduction at the first episode of psychosis across a greater range of cognitive impairment, the utility of MMN as an indicator of risk or diagnosis, and its role for understanding pathophysiological mechanisms in emerging psychosis.

Spherical Harmonics Reveal Standing EEG Waves and Long-Range Neural Synchronization during Non-REM Sleep

Previous work from our lab has demonstrated how the connectivity of brain circuits constrains the repertoire of activity patterns that those circuits can display. Specifically, we have shown that the principal components of spontaneous neural activity are uniquely determined by the underlying circuit connections, and that although the principal components do not uniquely resolve the circuit structure, they do reveal important features about it. Expanding upon this framework on a larger scale of neural dynamics, we have analyzed EEG data recorded with the standard 10–20 electrode system from 41 neurologically normal children and adolescents during stage 2, non-REM sleep. We show that the principal components of EEG spindles, or sigma waves (10–16 Hz), reveal non-propagating, standing waves in the form of spherical harmonics. We mathematically demonstrate that standing EEG waves exist when the spatial covariance and the Laplacian operator on the head's surface commute. This in turn implies that the covariance between two EEG channels decreases as the inverse of their relative distance; a relationship that we corroborate with empirical data. Using volume conduction theory, we then demonstrate that superficial current sources are more synchronized at larger distances, and determine the characteristic length of large-scale neural synchronization as 1.31 times the head radius, on average. Moreover, consistent with the hypothesis that EEG spindles are driven by thalamo-cortical rather than cortico-cortical loops, we also show that 8 additional patients with hypoplasia or complete agenesis of the corpus callosum, i.e., with deficient or no connectivity between cortical hemispheres, similarly exhibit standing EEG waves in the form of spherical harmonics. We conclude that spherical harmonics are a hallmark of spontaneous, large-scale synchronization of neural activity in the brain, which are associated with unconscious, light sleep. The analogy with spherical harmonics in quantum mechanics suggests that the variances (eigenvalues) of the principal components follow a Boltzmann distribution, or equivalently, that standing waves are in a sort of “thermodynamic” equilibrium during non-REM sleep. By extension, we speculate that consciousness emerges as the brain dynamics deviate from such equilibrium.

Electrophysiological Correlates of Aberrant Motivated Attention and Salience Processing in Unaffected Relatives of Schizophrenia Patients

Patients with schizophrenia (SCZ) exhibit debilitating deficits in attention and affective processing, which are often resistant to treatment and associated with poor functional outcomes. Impaired orientation to task-relevant target information has been indexed by diminished P3b event-related potentials in patients, as well as their unaffected first-degree relatives, suggesting that P3b may be a vulnerability marker for schizophrenia. Despite intact affective valence processing, patients are unable to employ cognitive change strategies to reduce electrophysiological responses to aversive stimuli. Less is known about the attentional processing of emotionally salient task-irrelevant information in patients and unaffected first-degree relatives. The goal of the present study was to examine the neural correlates of salience processing, as indexed by the late positive potential (LPP), during the processing of emotionally salient distractor stimuli in 31 patients with SCZ, 28 first-degree relatives, and 47 control participants using an oddball paradigm. Results indicated that despite intact novelty detection (P3a), both SCZ and first-degree relatives demonstrated deficiencies in attentional processing, reflected in attenuated target-P3b, and aberrant motivated attention, with reduced early-LPP amplitudes for aversive stimuli relative to controls. First-degree relatives revealed a unique enhancement of the late-LPP response, possibly underlying an exaggerated evaluation of salient information and a compensatory engagement of neural circuitry. Furthermore, reduced early-LPP and target-P3b amplitudes were associated with enhanced symptom severity. These findings suggest that, in addition to P3b, LPP may be useful for monitoring clinical state. Future studies will explore the value of P3 and LPP responses as vulnerability markers for early detection and prediction of psychopathology.

Neural Correlates of Schizophrenia Negative Symptoms: Distinct Subtypes Impact Dissociable Brain Circuits

BACKGROUND

The negative symptoms of schizophrenia include deficits in emotional expression and motivation. These deficits are stable over the course of illness and respond poorly to current medications. Previous studies have focused on negative symptoms as a single category; however, individual symptoms might be related to separate neurological disturbances. We analyzed data from the Functional Biomedical Informatics Research Network dataset to explore the relationship between individual negative symptoms and functional brain activity during an auditory oddball task.

METHODS

Functional magnetic resonance imaging was conducted on 89 schizophrenia patients and 106 healthy controls during a two-tone auditory oddball task. Blood oxygenation level-dependent (BOLD) signal during the target tone was correlated with severity of five negative symptom domains from the Scale for the Assessment of Negative Symptoms.

RESULTS

The severity of alogia, avolition/apathy and anhedonia/asociality was negatively correlated with BOLD activity in distinct sets of brain regions associated with processing of the target tone, including basal ganglia, thalamus, insular cortex, prefrontal cortex, posterior cingulate and parietal cortex.

CONCLUSIONS

Individual symptoms were related to different patterns of functional activation during the oddball task, suggesting that individual symptoms might arise from distinct neural mechanisms. This work has potential to inform interventions that target these symptom-related neural disruptions.

Relationships between the resting-state network and the P3: Evidence from a scalp EEG study

The P3 is an important event-related potential that can be used to identify neural activity related to the cognitive processes of the human brain. However, the relationships, especially the functional correlations, between resting-state brain activity and the P3 have not been well established. In this study, we investigated the relationships between P3 properties (i.e., amplitude and latency) and resting-state brain networks. The results indicated that P3 amplitude was significantly correlated with resting-state network topology, and in general, larger P3 amplitudes could be evoked when the resting-state brain network was more efficient. However, no significant relationships were found for the corresponding P3 latency. Additionally, the long-range connections between the prefrontal/frontal and parietal/occipital brain regions, which represent the synchronous activity of these areas, were functionally related to the P3 parameters, especially P3 amplitude. The findings of the current study may help us better understand inter-subject variation in the P3, which may be instructive for clinical diagnosis, cognitive neuroscience studies, and potential subject selection for brain-computer interface applications.

Brown Norway rats, a putative schizophrenia model, show increased electroencephalographic activity at rest and decreased event-related potential amplitude, power, and coherence in the auditory sensory gating paradigm

In recent schizophrenia clinical research, electroencephalographic (EEG) oscillatory activities induced by a sensory stimulus or behavioral tasks have gained considerable interest as functional and pathophysiological biomarkers. The Brown Norway (BN) rat is a putative schizophrenia model that shows naturally low sensorimotor gating and deficits in cognitive performance, although other phenotypes have not been studied. The present study aimed to investigate the neurophysiological features of BN rats, particularly EEG/event-related potential (ERP). EEG activity was recorded at rest and during the auditory sensory gating paradigm under an awake, freely moving condition. Frequency and ERP analysis were performed along with time-frequency analysis of evoked power and intertrial coherence. Compared with Wistar-Kyoto rats, a well-documented control line, BN rats showed increased EEG power at rest, particularly in the theta and gamma ranges. In ERP analysis, BN rats showed reduced N40-P20 amplitude but normal sensory gating. The rats also showed reduced evoked power and intertrial coherence against auditory stimuli. These results suggest that BN rats show features of EEG/ERP measures clinically relevant to schizophrenia and may provide additional opportunities for translational research.

Finding the missing-stimulus mismatch negativity (MMN) in early psychosis: altered MMN to violations of an auditory gestalt

The mismatch negativity (MMN) is an EEG-derived event-related potential (ERP) elicited by any violation of a predicted auditory 'rule', regardless of whether one is attending to the stimuli, and is thought to reflect updating of the stimulus context. Chronic schizophrenia patients exhibit robust MMN deficits, while MMN reduction in first-episode and early phase psychosis is significantly less consistent. Traditional two-tone "oddball" MMN measures of sensory information processing may be considered too simple for use in early phase psychosis in which pathology has not progressed fully, and a paradigm that probes higher order processes may be more appropriate for elucidating auditory change detection deficits. This study investigated whether MMN deficits could be detected in early phase psychosis (EP) patients using an abstract 'missing stimulus' pattern paradigm (Salisbury, 2012). The stimuli were 400 groups of six tones (1000Hz, 50ms duration, 330ms stimulus onset asynchrony), which was presented with an inter-trial interval of 750ms. Occasionally a group contained a deviant, meaning that it was missing either the 4th or 6th tone (50 trials each). EEG recordings of 13 EP patients (≤5year duration of illness) and 15 healthy controls (HC) were collected. Patients and controls did not significantly differ on age or years of education. Analyses of MMN amplitudes elicited by missing stimuli revealed amplitude reductions in EP patients, suggesting that these deficits are present very early in the progression of the illness. While there were no correlations between MMN measures and measures such as duration of illness, medication dosage or age, MMN amplitude reductions were correlated with positive symptomatology (i.e. auditory hallucinations). These findings suggest that MMNs elicited by the 'missing stimulus' paradigm are impaired in psychosis patients early in the progression of illness and that previously reported MMN-indexed deficits related to auditory hallucinations in chronic patients may also be present in EP patients. As such, this paradigm may have promise in identifying early processing deficits in this population.

Abnormal dynamics of EEG oscillations in schizophrenia patients on multiple time scales

Neuronal oscillations reflect the activity of neuronal ensembles engaged in integrative cognition, and may serve as a functional measure for the cognitive impairment in schizophrenia. This study aims to reveal the abnormal amplitude dynamics of electroencephalogram (EEG) oscillations in schizophrenia patients on multiple time scales. EEGs were recorded from schizophrenia patients ( n = 19) and healthy controls ( n = 16) while they were at resting state with eyes closed, at resting state with eyes open, and at watching video. Detrended fluctuation analysis and measures of life-time and waiting-time were used to characterize the abnormal dynamics of EEG oscillations on both long (1-20 s) and short (≤1 s) time scales. Abnormal dynamics of EEG oscillations in alpha and beta bands were observed. In particular, compared with healthy controls, schizophrenia patients have smaller DFA exponent (implying weaker long-range temporal correlation) in the left fronto-temporal area and smaller DFA exponent, smaller life-time (indicating shorter oscillation burst), and smaller waiting-time in the occipital area in beta band at resting state with eyes open. In addition, schizophrenia patients have larger DFA exponent, larger life-time, and larger waiting-time at some clustered channels in the temporo-parietal area in alpha band at watching video. The present results provide new insights for cognitive deficits and the underlying neuronal dysfunction in schizophrenia.

Traumatic brain injury detection using electrophysiological methods

Measuring neuronal activity with electrophysiological methods may be useful in detecting neurological dysfunctions, such as mild traumatic brain injury (mTBI). This approach may be particularly valuable for rapid detection in at-risk populations including military service members and athletes. Electrophysiological methods, such as quantitative electroencephalography (qEEG) and recording event-related potentials (ERPs) may be promising; however, the field is nascent and significant controversy exists on the efficacy and accuracy of the approaches as diagnostic tools. For example, the specific measures derived from an electroencephalogram (EEG) that are most suitable as markers of dysfunction have not been clearly established. A study was conducted to summarize and evaluate the statistical rigor of evidence on the overall utility of qEEG as an mTBI detection tool. The analysis evaluated qEEG measures/parameters that may be most suitable as fieldable diagnostic tools, identified other types of EEG measures and analysis methods of promise, recommended specific measures and analysis methods for further development as mTBI detection tools, identified research gaps in the field, and recommended future research and development thrust areas. The qEEG study group formed the following conclusions: (1) Individual qEEG measures provide limited diagnostic utility for mTBI. However, many measures can be important features of qEEG discriminant functions, which do show significant promise as mTBI detection tools. (2) ERPs offer utility in mTBI detection. In fact, evidence indicates that ERPs can identify abnormalities in cases where EEGs alone are non-disclosing. (3) The standard mathematical procedures used in the characterization of mTBI EEGs should be expanded to incorporate newer methods of analysis including non-linear dynamical analysis, complexity measures, analysis of causal interactions, graph theory, and information dynamics. (4) Reports of high specificity in qEEG evaluations of TBI must be interpreted with care. High specificities have been reported in carefully constructed clinical studies in which healthy controls were compared against a carefully selected TBI population. The published literature indicates, however, that similar abnormalities in qEEG measures are observed in other neuropsychiatric disorders. While it may be possible to distinguish a clinical patient from a healthy control participant with this technology, these measures are unlikely to discriminate between, for example, major depressive disorder, bipolar disorder, or TBI. The specificities observed in these clinical studies may well be lost in real world clinical practice. (5) The absence of specificity does not preclude clinical utility. The possibility of use as a longitudinal measure of treatment response remains. However, efficacy as a longitudinal clinical measure does require acceptable test-retest reliability. To date, very few test-retest reliability studies have been published with qEEG data obtained from TBI patients or from healthy controls. This is a particular concern because high variability is a known characteristic of the injured central nervous system.

Basic visual dysfunction allows classification of patients with schizophrenia with exceptional accuracy

Basic visual dysfunctions are commonly reported in schizophrenia; however their value as diagnostic tools remains uncertain. This study reports a novel electrophysiological approach using checkerboard visual evoked potentials (VEP). Sources of spectral resolution VEP-components C1, P1 and N1 were estimated by LORETA, and the band-effects (BSE) on these estimated sources were explored in each subject. BSEs were Z-transformed for each component and relationships with clinical variables were assessed. Clinical effects were evaluated by ROC-curves and predictive values. Forty-eight patients with schizophrenia (SZ) and 55 healthy controls participated in the study. For each of the 48 patients, the three VEP components were localized to both dorsal and ventral brain areas and also deviated from a normal distribution. P1 and N1 deviations were independent of treatment, illness chronicity or gender. Results from LORETA also suggest that deficits in thalamus, posterior cingulum, precuneus, superior parietal and medial occipitotemporal areas were associated with symptom severity. While positive symptoms were more strongly related to sensory processing deficits (P1), negative symptoms were more strongly related to perceptual processing dysfunction (N1). Clinical validation revealed positive and negative predictive values for correctly classifying SZ of 100% and 77%, respectively. Classification in an additional independent sample of 30 SZ corroborated these results. In summary, this novel approach revealed basic visual dysfunctions in all patients with schizophrenia, suggesting these visual dysfunctions represent a promising candidate as a biomarker for schizophrenia.

Early somatosensory processing in individuals at risk for developing psychoses

Human cortical somatosensory evoked potentials (SEPs) allow an accurate investigation of thalamocortical and early cortical processing. SEPs reveal a burst of superimposed early (N20) high-frequency oscillations around 600 Hz. Previous studies reported alterations of SEPs in patients with schizophrenia. This study addresses the question whether those alterations are also observable in populations at risk for developing schizophrenia or bipolar disorders. To our knowledge to date, this is the first study investigating SEPs in a population at risk for developing psychoses. Median nerve SEPs were investigated using multichannel EEG in individuals at risk for developing bipolar disorders (n = 25), individuals with high-risk status (n = 59) and ultra-high-risk status for schizophrenia (n = 73) and a gender and age-matched control group (n = 45). Strengths and latencies of low- and high-frequency components as estimated by dipole source analysis were compared between groups. Low- and high-frequency source activity was reduced in both groups at risk for schizophrenia, in comparison to the group at risk for bipolar disorders. HFO amplitudes were also significant reduced in subjects with high-risk status for schizophrenia compared to healthy controls. These differences were accentuated among cannabis non-users. Reduced N20 source strengths were related to higher positive symptom load. These results suggest that the risk for schizophrenia, in contrast to bipolar disorders, may involve an impairment of early cerebral somatosensory processing. Neurophysiologic alterations in schizophrenia precede the onset of initial psychotic episode and may serve as indicator of vulnerability for developing schizophrenia.

Developmental mechanisms in the prodrome to psychosis

Psychotic disorders continue to be among the most disabling and scientifically challenging of all mental illnesses. Accumulating research findings suggest that the etiologic processes underlying the development of these disorders are more complex than had previously been assumed. At the same time, this complexity has revealed a wider range of potential options for preventive intervention, both psychosocial and biological. In part, these opportunities result from our increased understanding of the dynamic and multifaceted nature of the neurodevelopmental mechanisms involved in the disease process, as well as the evidence that many of these entail processes that are malleable. In this article, we review the burgeoning research literature on the prodrome to psychosis, based on studies of individuals who meet clinical high risk criteria. This literature has examined a range of factors, including cognitive, genetic, psychosocial, and neurobiological. We then turn to a discussion of some contemporary models of the etiology of psychosis that emphasize the prodromal period. These models encompass the origins of vulnerability in fetal development, as well as postnatal stress, the immune response, and neuromaturational processes in adolescent brain development that appear to go awry during the prodrome to psychosis. Then, informed by these neurodevelopmental models of etiology, we turn to the application of new research paradigms that will address critical issues in future investigations. It is expected that these studies will play a major role in setting the stage for clinical trials aimed at preventive intervention.

Use of translational pharmacodynamic biomarkers in early-phase clinical studies for schizophrenia

Schizophrenia is a severe mental disorder characterized by cognitive deficits, and positive and negative symptoms. The development of effective pharmacological compounds for the treatment of schizophrenia has proven challenging and costly, with many compounds failing during clinical trials. Many failures occur due to disease heterogeneity and lack of predictive preclinical models and biomarkers that readily translate to humans during early characterization of novel antipsychotic compounds. Traditional early-phase trials consist of single- or multiple-dose designs aimed at determining the safety and tolerability of an investigational compound in healthy volunteers. However, by incorporating a translational approach employing methodologies derived from preclinical studies, such as EEG measures and imaging, into the traditional Phase I program, critical information regarding a compound's dose-response effects on pharmacodynamic biomarkers can be acquired. Furthermore, combined with the use of patients with stable schizophrenia in early-phase clinical trials, significant 'de-risking' and more confident 'go/no-go' decisions are possible.

Biomarkers in psychosis: an approach to early identification and individualized treatment

Numerous biomarkers for somatic disorders are used in routine medical practice. Yet, despite remarkable advances in mental health research, we are not able to identify biomarkers with established clinical utility for mental disorders such as schizophrenia. While identification and characterization of biomarkers are crucial first steps in this process, their predictive diagnostic and treatment utility need to be better developed for clinical practice. The heterogeneity of psychotic disorders etiologically, pathologically and symptomatically presents both a challenge and an opportunity for the use of biomarkers in clinical practice. Simply said, a single biomarker might not exist that necessitates the search for a biomarker profile. In this review we discuss research findings in light of such an approach. We summarize some examples of emerging biomarkers in early psychosis research and delineate how these can be applied to a clinical setting to inform treatment on an individual basis fostering a personalized treatment approach.

Drug Treated Schizophrenia, Schizoaffective and Bipolar Disorder Patients Evaluated by qEEG Absolute Spectral Power and Mean Frequency Analysis

Objective

Research of electroencephalograph (EEG) power spectrum and mean frequency has shown inconsistent results in patients with schizophrenic, schizoaffective and bipolar disorders during medication when compared to normal subjects thus; the characterization of these parameters is an important task.

Methods

We applied quantitative EEG (qEEG) to investigate 38 control, 15 schizophrenic, 7 schizoaffective and 11 bipolar disorder subjects which remaine under the administration of psychotropic drugs (except control group). Absolute spectral power (ASP), mean frequency and hemispheric electrical asymmetry were measured by 19 derivation qEEG. Group mean values were compared with non parametrical Mann-Whitney test and spectral EEG maps with z-score method at p < 0.05.

Results

Most frequent drug treatments for schizophrenic patients were neuroleptic+antiepileptic (40% of cases) or 2 neuroleptics (33.3%). Schizoaffective patients received neuroleptic+benzodiazepine (71.4%) and for bipolar disorder patients neuroleptic+antiepileptic (81.8%). Schizophrenic (at all derivations except for Fp1, Fp2, F8 and T6) and schizoaffective (only at C3) show higher values of ASP (+57.7% and +86.1% respectively) compared to control group. ASP of bipolar disorder patients did not show differences against control group. The mean frequency was higher at Fp1 (+14.2%) and Fp2 (+17.4%) in bipolar disorder patients than control group, but no differences were found in frequencies between schizophrenic or schizoaffective patients against the control group. Majority of spectral differences were found at the left hemisphere in schizophrenic and schizoaffective but not in bipolar disorder subjects.

Conclusion

The present report contributes to characterize quantitatively the qEEG in drug treated schizophrenic, schizoaffective or bipolar disorder patients.

Event-related potentials in substance use disorders: a narrative review based on articles from 1984 to 2012

Mechanisms that mediate the transition from occasional, controlled, drug use to the impaired control that characterizes severe dependence are still a matter of investigation. The etiology of substance use disorders (SUDs) is complex, and in this context of complexity, the concept of "endophenotype," has gained extensive popularity in recent years. The main aim of endophenotypes is to provide a simpler, more proximal target to discover the biological underpinnings of a psychiatric syndrome. In this view, neurocognitive and neurophysiological impairments that suggest functional impairments associated with SUDs have been proposed as possible endophenotypes. Because of its large amplitude and relatively easy elicitation, the most studied of the cognitive brain event-related potentials (ERPs), the P300 component, has been proposed as one possible candidate. However, if a P300 amplitude alteration is a common finding in SUDs, it is also observable in other psychiatric afflictions, suggesting that the associations found may just reflect a common measure of brain dysfunction. On this basis, it has been proposed that a multivariate endophenotype, based on a weighted combination of electrophysiological features, may provide greater diagnostic classification power than any single endophenotype. The rationale for investigating multiple features is to show that combining them provides extra useful information that is not available in the individual features, leading ultimately to a multivariate phenotype.The aim of the present article is to outline the potential usefulness of this kind of "combined electrophysiological procedure" applied to SUDs. We present a review of ERP studies, combining data from people with SUD, family members, and normal control subjects, to verify whether the combination of 4ERPs (P50, MMN, P300, and N400) may produce profiles of cortical anomalies induced by different types of SUD (alcohol vs cocaine vs cannabis vs heroin).

Emotional facial expression processing in depression: data from behavioral and event-related potential studies

Behavioral literature investigating emotional processes in depressive populations (i.e., unipolar and bipolar depression) states that, compared to healthy controls, depressive subjects exhibit disrupted emotional processing, indexed by lower performance and/or delayed response latencies. The development of brain imaging techniques, such as functional magnetic resonance imaging (fMRI), provided the possibility to visualize the brain regions engaged in emotional processes and how they fail to interact in psychiatric diseases. However, fMRI suffers from poor temporal resolution and cognitive function involves various steps and cognitive stages (serially or in parallel) to give rise to a normal performance. Thus, the origin of a behavioral deficit may result from the alteration of a cognitive stage differently situated along the information-processing stream, outlining the importance of access to this dynamic "temporal" information. In this paper, we will illustrate, through depression, the role that should be attributed to cognitive event-related potentials (ERPs). Indeed, owing to their optimal temporal resolution, ERPs can monitor the neural processes engaged in disrupted cognitive function and provide crucial information for its treatment, training of the impaired cognitive functions and guidelines for clinicians in the choice and monitoring of appropriate medication for the patient.

Neuropharmacological modulation of the P3-like event-related potential in a rat two-tone auditory discrimination task with modafinil and NS9283, a positive allosteric modulator of α4β2 nAChRs

The P300 (P3) event-related potential (ERP) is a neurophysiological signal believed to reflect cognitive processing of salient cues, and is thus used as a measure of attention and working memory. Additionally, P3 amplitude and latency is altered in neurological diseases and can be pharmacologically modulated. As P3-like ERPs can be recorded in rodents, it may serve as a potential translational biomarker of value for drug discovery. Here we investigated whether a positive allosteric modulator of α4β2 nicotinic acetylcholine receptors, NS9283, and the psychostimulant modafinil could modulate P3-like ERPs in healthy adult rats performing an auditory oddball discrimination task. ERPs were recorded with electroencephalography electrodes implanted into mediodorsal (MD) thalamus, medial prefrontal cortex, hippocampus and auditory cortex (AC). P3-like ERPs were detected in all brain regions, displaying larger amplitudes in target trials compared to non-target trials. Administration of modafinil (64 mg/kg) decreased P3-like ERP latency in MD thalamus and AC, whereas NS9283 augmented P3-like ERP amplitude in MD thalamus at 0.3 mg/kg and in AC at 3.0 mg/kg. Additionally, N1 pre-attention peak amplitude in MD thalamus was increased with 0.3 mg/kg NS9283. Neither of the compounds enhanced task performance. Rather, modafinil lowered correct rejections in non-target trials. In summary, our findings reveal pharmacological modulation of the rat P3-like ERP in cortical and subcortical regions by modafinil and NS9283. These findings encourage further exploration of the rat P3-like ERP in order to promote the understanding of its meaning within cognition, as well as its applicability as a translatable biomarker in drug development.

The prodrome and clinical risk for psychotic disorders

The psychosis prodrome offers great promise for identifying neural mechanisms involved in psychotic disorders and offers an opportunity to implement empirical interventions to delay, and ultimately ameliorate, illness onset. This article summarizes the literature on individuals in the putatively prodromal phase of psychosis/deemed at clinical high risk (CHR) for psychosis onset. Standardized measurement and manifestation of the CHR syndromes are discussed, followed by empirical findings that highlight the psychological deficits and biological abnormalities seen in CHR syndromes and psychotic disorders. Current controversies surrounding the diagnosis of CHR syndromes and issues related to the treatment of CHR individuals are also presented.

A proposal for reframing schizophrenia research

The current schizophrenia concept is built on experts' agreement on the matter, and it is basically rooted in the epidemiological and clinical evidence. However, the numerous and intensive attempts to find the biological underpinnings of this syndrome face almost constantly a low degree of replication of the results. We have reviewed previously published work to contribute to identify some reasons underlying that failure. The difficulty in replicating biological findings in schizophrenia may relate to the intrinsic heterogeneity among patient samples, acquired through the current diagnostic criteria. As a result, the necessary replication for any finding to be accepted as characteristic data for schizophrenia would be impeded. Therefore, a new frame based on identification of correlates of the most replicated biological anomalies in schizophrenia to date may contribute to overcome those difficulties.

Nonhuman primate model of schizophrenia using a noninvasive EEG method

There is growing evidence that impaired sensory-processing significantly contributes to the cognitive deficits found in schizophrenia. For example, the mismatch negativity (MMN) and P3a event-related potentials (ERPs), neurophysiological indices of sensory and cognitive function, are reduced in schizophrenia patients and may be used as biomarkers of the disease. In agreement with glutamatergic theories of schizophrenia, NMDA antagonists, such as ketamine, elicit many symptoms of schizophrenia when administered to normal subjects, including reductions in the MMN and the P3a. We sought to develop a nonhuman primate (NHP) model of schizophrenia based on NMDA-receptor blockade using subanesthetic administration of ketamine. This provided neurophysiological measures of sensory and cognitive function that were directly comparable to those recorded from humans. We first developed methods that allowed recording of ERPs from humans and rhesus macaques and found homologous MMN and P3a ERPs during an auditory oddball paradigm. We then investigated the effect of ketamine on these ERPs in macaques. As found in humans with schizophrenia, as well as in normal subjects given ketamine, we observed a significant decrease in amplitude of both ERPs. Our findings suggest the potential of a pharmacologically induced model of schizophrenia in NHPs that can pave the way for EEG-guided investigations into cellular mechanisms and therapies. Furthermore, given the established link between these ERPs, the glutamatergic system, and deficits in other neuropsychiatric disorders, our model can be used to investigate a wide range of pathologies.

Experimental and clinical usefulness of crossmodal paradigms in psychiatry: an illustration from emotional processing in alcohol-dependence

Crossmodal processing (i.e., the construction of a unified representation stemming from distinct sensorial modalities inputs) constitutes a crucial ability in humans' everyday life. It has been extensively explored at cognitive and cerebral levels during the last decade among healthy controls. Paradoxically however, and while difficulties to perform this integrative process have been suggested in a large range of psychopathological states (e.g., schizophrenia and autism), these crossmodal paradigms have been very rarely used in the exploration of psychiatric populations. The main aim of the present paper is thus to underline the experimental and clinical usefulness of exploring crossmodal processes in psychiatry. We will illustrate this proposal by means of the recent data obtained in the crossmodal exploration of emotional alterations in alcohol-dependence. Indeed, emotional decoding impairments might have a role in the development and maintenance of alcohol-dependence, and have been extensively investigated by means of experiments using separated visual or auditory stimulations. Besides these unimodal explorations, we have recently conducted several studies using audio-visual crossmodal paradigms, which has allowed us to improve the ecological validity of the unimodal experimental designs and to offer new insights on the emotional alterations among alcohol-dependent individuals. We will show how these preliminary results can be extended to develop a coherent and ambitious research program using crossmodal designs in various psychiatric populations and sensory modalities. We will finally end the paper by underlining the various potential clinical applications and the fundamental implications that can be raised by this emerging project.

Mouse models of gene-environment interactions in schizophrenia

Gene-environment interactions (GEIs) likely play significant roles in the pathogenesis of schizophrenia and underlie differences in pathological, behavioral, and clinical presentations of the disease. Findings from epidemiology and psychiatric genetics have assisted in the generation of animal models of GEI relevant to schizophrenia. These models may provide a foundation for elucidating the molecular, cellular, and circuitry mechanisms that mediate GEI in schizophrenia. Here we critically review current mouse models of GEI related to schizophrenia, describe directions for their improvement, and propose endophenotypes to provide a more tangible basis for molecular studies of pathways of GEI and facilitate the identification of novel therapeutic targets.

Genetic association study of the P300 endophenotype in schizophrenia

OBJECTIVE

Although reduced amplitude of the P300 event-related potential is a well-documented intermediate phenotype of schizophrenia, little is known about its genetic underpinnings in patients with schizophrenia. This study aims to examine associations between P300 and a range of candidate genetic variants, selected from either candidate gene studies or genome-wide association studies, in a large sample of patients with schizophrenia.

METHODS

P300 amplitude at the midline parietal electrode and 193 single nucleotide polymorphisms (SNPs) in 67 genes were assessed in 336 patients with schizophrenia. The association between each SNP and P300 amplitude, controlled for illness duration and gender, was evaluated. Associations at p<.01 were considered of potential relevance, while Bonferroni correction was applied to determine formal statistical significance (Bonferroni-corrected threshold of significance p=.0003).

RESULTS

Of the 193 selected SNPs, 4 SNPs showed potentially relevant association with P300 amplitude at a significance level of p<.01. One of these SNPs, rs1045642 in ABCB1, was most convincingly associated with P300 amplitude, reaching formal (Bonferroni-corrected) significance, while there was evidence for possible association with rs1572899 in DISC-1, rs6265 in BDNF and rs1625579 in MIR137.

CONCLUSION

Genetic variation in ABCB1 may be associated with P300 amplitude in patients with schizophrenia. This result may encourage further efforts to elucidate the genetic underpinnings of P300 generation.

The mismatch negativity (MMN)--a unique window to disturbed central auditory processing in ageing and different clinical conditions

In this article, we review clinical research using the mismatch negativity (MMN), a change-detection response of the brain elicited even in the absence of attention or behavioural task. In these studies, the MMN was usually elicited by employing occasional frequency, duration or speech-sound changes in repetitive background stimulation while the patient was reading or watching videos. It was found that in a large number of different neuropsychiatric, neurological and neurodevelopmental disorders, as well as in normal ageing, the MMN amplitude was attenuated and peak latency prolonged. Besides indexing decreased discrimination accuracy, these effects may also reflect, depending on the specific stimulus paradigm used, decreased sensory-memory duration, abnormal perception or attention control or, most importantly, cognitive decline. In fact, MMN deficiency appears to index cognitive decline irrespective of the specific symptomatologies and aetiologies of the different disorders involved.

The use of the EEG in measuring therapeutic drug action: focus on depression and antidepressants

A major issue in proof of concept studies and early clinical trials of novel therapeutic agents is that the active drugs can often have a relatively small additional effect compared with placebo. This is especially the case in psychiatry when we usually have no direct method of measuring the pathology underlying the disorder being studied but, rather, have to rely on the subjective assessment of psychiatric symptoms. The use of the electroencephalogram (EEG) offers two potential major means of addressing this problem. First it is able to provide direct data relating to neural activity that may be abnormal in certain disorders. As such there are opportunities for utilizing the EEG in a variety of ways as an objective outcome measure. Second there is growing evidence that in certain circumstances the EEG can be used to predict which patients are likely to respond to treatment, thus potentially increasing the power of studies by decreasing non-response rates and increasing mean changes in outcome measure. Both of these uses of the EEG are illustrated in reference to the study of mood disorders and in particular depression and its treatment with antidepressants.

White matter alterations related to P300 abnormalities in individuals at high risk for psychosis: an MRI-EEG study

BACKGROUND

Psychosis onset is characterized by white matter and electrophysiologic abnormalities. The relation between these factors in the development of illness is almost unknown. We studied the relation between white matter volumes and P300 in prodromal psychosis.

METHODS

We assessed white matter volume (detected using magnetic resonance imaging) and electrophysiologic response during an oddball task (P300) in healthy controls and individuals at high clinical risk for psychosis (with an "at-risk mental state" [ARMS]).

RESULTS

We included 41 controls and 39 patients with an ARMS in our study. A psychotic disorder developed in 26% of the ARMS group within the follow-up period of 2 years. The P300 amplitude was significantly lower in the ARMS group than in the control group. The ARMS group showed reduced volume of white matter underlying the left superior temporal gyrus and the left superior frontal gyrus and increased volume of white matter underlying the right insula and the right angular gyrus compared with controls. Relative to individuals who did not later become psychotic, the subgroup in whom psychosis subsequently developed had a smaller volume of white matter underlying the left precuneus and the right middle temporal gyrus and increased volume in the white matter underlying the right middle frontal gyrus. We observed a significant interaction in the right middle frontal gyrus: white matter volume was negatively associated with P300 amplitude in the ARMS group and positively associated with P300 amplitude in the control group.

LIMITATIONS

The voxel-based morphometry method alone cannot determine whether abnormal white matter volumes are due to an altered number of axonal connections or decreased myelination.

CONCLUSION

P300 abnormalities precede the onset of psychosis and are directly related to white matter alterations, representing a correlate of an increased vulnerability to disease.