A one-channel electrocardiogram (ECG) channel is recommended during electroencephalogram (EEG) recordings principally to help establish ECG or pulse wave contamination of the ECG EEG. However, the ECG recording, in itself, provides useful clinical information, principally the detection of arrhythmias, especially atrial fibrillation (AF), which indicates heart disease that can predispose to embolic stroke and systemic embolism. We sought to determine the prevalence of AF routine recordings in our EEG laboratory in a general hospital.

We reviewed the consecutive EEG reports for the past 7 years to determine how often AF was detected in various age groups.

We found AF in 0–0.2% per decade of life until age 60–69 years, 2.7% for 70–79 years, 5% for 80–89 years, and 8% for 90–99 years.

We suggest that the ECG trace should be carefully analyzed for AF, especially in patients over 60 years of age. When detected, it should be brought to the referring doctor’s attention.

In a serial compound conditioning paradigm, a sequence of several conditioned stimuli (CS) is predictive to an unconditioned stimulus (US) (e.g., CSA->CSB->US). Animal research showed that, when the US is aversive, CSA elicits the strongest conditioned response, while CSB appears redundant. These effects of primacy and proximity have never been investigated in humans.

To study the effects of temporal proximity of imminent threat and safety in serial compound conditioning.

Twenty-two participants were presented with sequences [CSA->CSB->CSC->CSD]. In 55 trials all four CS were identical vowels (e.g, [oh]), and no US was presented. In the other 55 trials, the CSA was different (CSA+, e.g., [uh]), and the CSD was followed by an electrical shock (US) 2.5 times higher than the individual pain threshold.

No ERP component distinguished between CS- and CS+ for the first three stimuli in the sequence (i.e., CSA, CSB, CSC). The last CS (CSD) elicited a strong fronto-central CNV only when it was followed by US. Moreover, already after the CSA- (which signalized that no shock would be presented on that trial) the power of alpha oscillations over the somatosensory cortex significantly increased, particularly on the side contralateral to the hand that was electrically stimulated on US trials. The alpha increment lasted up to the onset of the US.

The data indicate two possible mechanisms of adjustment to predictable threat, one of which relies on safety signals (manifested in alpha increment), and the other is related to flight response (manifested in the CNV immediately preceding the shock).

Emotion self-regulation relies both on cognitive and behavioral strategies implemented to modulate the subjective experience and/or the behavioral expression of a given emotion.

While it is known that a network encompassing fronto-cingulate and parietal brain areas is engaged during successful emotion regulation, the functional mechanisms underlying failures in emotion suppression are still unclear.

We analyzed facial-view video and high-density EEG recordings of nineteen healthy adult subjects (26±3yrs, 10F) during an emotion suppression (ES) and a free expression (FE) task performed on two consecutive days. An actigraph was worn for 7-days and used to determine sleep-time before each experiment. Changes in facial expression were identified and manually marked on the video recordings. Continuous hd-EEG recordings were preprocessed using standard approaches to reduce artifactual activity and source-modeled using sLORETA.

Changes in facial expression during ES, but not FE, were preceded by local increases in sleep-like activity (1-4Hz) in in brain areas responsible for emotional suppression, including bilateral anterior insula and anterior cingulate cortex, and in right middle/inferior frontal gyrus (p<0.05, corrected; Figures 1 and 2). Moreover, shorter sleep duration the night prior to the ES experiment correlated with the number of behavioral errors (p=0.01; Figure 3) and tended to be associated with higher frontal sleep-like activity during emotion suppression failures (p=0.05).

These results indicate that local sleep-like activity may represent the cause of emotion suppression failures in humans, and may offer a functional explanation for previous observations linking lack of sleep, changes in frontal activity and emotional dysregulation.

No significant relationships.

The recognition of the conditioned-unconditioned stimulus (CS-US) association in classical conditioning is referred to as contingency awareness. The neural underpinnings of contingency awareness in human fear conditioning are poorly understood.

We aimed to explore the EEG correlates of contingency awareness.

Here, we recorded electroencephalography (EEG) from a sample of 20 participants in a semantic conditioning experiment. In the acquisition phase the participants were presented with sequences of words from two semantic categories paired with tactile stimulation followed by presentation of a neutral sound (US-) ((e.g., animals -> left hand vibration -> US-, clothes -> right hand vibration -> US-). In the test phase the association violated in 50% of trials which followed by a presentation of a loud noise (US+). The participants were only instructed to listen carefully. On the basis of self-reported contingency awareness, twenty participants were divided in aware (N=12) and unaware (N=8) group.

The aware group expressed a non-lateralized effect of alpha-beta (12-23 Hz) suppression along with a more negative CNV at central channels preceding presentation of the vibration (main effect of Group). Also, CNV was more negative in expectation of US+ comparing with expectation of US- in the aware group but not in the unaware group.

The results indicate that contingency awareness is accompanied by neural patterns reflecting expectation as can be seen in the suppression of somatosensory alpha-beta activity before expected presentation of the vibration as well as in CNV in expectation of an aversive event.

Studies on fear conditioning have made important contributions to the understanding of affective learning mechanisms as well as its applications (e.g., anxiety disorders, post-traumatic stress disorder). However, central mechanisms of sleep related consolidation of fear memory in humans have been almost neglected by previous studies.

In the current study we aimed to test effects of sleep and a period wakefulness on fear conditioned responses.

In our experiment in a group 18 healthy volunteers event-related brain potentials (ERP), heart rate variability (HRV) and behavioral responses were recorded during a fear conditioning procedure presented twice, before daytime sleep (2h) or control intervention (a period of wakefulness) and after. The conditioning procedure involved pairing of a neutral tone (CS+) with a highly unpleasant sound (UCS+).

Differential conditioning manifested itself in the contingent negative variance (CNV)-like slow ERP component. Both period of sleep and wakefulness resulted in an increased amplitude of the CNV to CS+. But we did not find an interaction effect of Time (Pre-Post) by Intervention (Sleep-Wake), suggesting that sleep did not affect the conditioned response differently as compared to a period of wakefulness. An apparent increase in HRV after a period of wakefulness did not affect fear conditioned responses (CNV and valence ratings).

To summarize, the data indicate that fear memories are consolidated with the course of time with no beneficial effect of sleep; relearning of fear causes stronger differential responses as measured by slow wave amplitude but not behavior; increase of HRV does not affect fear learning.

Despite innovative treatments, the impairment in real-life functioning in subjects with schizophrenia (SCZ) remains an unmet need in the care of these patients. Recently, real-life functioning in SCZ was associated with abnormalities in different electrophysiological indices. It is still not clear whether this relationship is mediated by other variables, and how the combination of different EEG abnormalities influences the complex outcome of schizophrenia.

The purpose of the study was to find EEG patterns which can predict the outcome of schizophrenia and identify recovered patients.

Illness-related and functioning-related variables were measured in 61 SCZ at baseline and after four-years follow-up. EEGs were recorded at the baseline in resting-state condition and during two auditory tasks. We performed Sparse Partial Least Square (SPLS) Regression, using EEG features, age and illness duration to predict clinical and functional features at baseline and follow up. Through a Linear Support Vector Machine (Linear SVM) we used electrophysiological and clinical scores derived from SPLS regression, in order to classify recovered patients at follow-up.

We found one significant latent variable (p<0.01) capturing correlations between independent and dependent variables at follow-up (RHO=0.56). Among individual predictors, age and illness-duration showed the highest scores; however, the score for the combination of the EEG features was higher than all other predictors. Within dependent variables, negative symptoms showed the strongest correlation with predictors. Scores resulting from SPLS Regression classified recovered patients with 90.1% of accuracy.

A combination of electrophysiological markers, age and illness-duration might predict clinical and functional outcome of schizophrenia after 4 years of follow-up.

Machine learning has increasingly been applied to classification of psychosis spectrum in neuroimaging research. However, a number of multimodal studies using MRI and electroencephalography (EEG) is quite limited.

To assess the power of multimodal structural MRI (sMRI) and EEG data to provide pairwise discrimination between first-episode schizophrenia (FES) patients, individuals at ultra-high-risk of psychosis (UHR), and healthy controls (HC) using machine learning algorithms.

46 FES male patients, 39 UHR individuals, and 54 matched HC underwent sMRI (3T Philips scanner) and electroencephalography. T1-weighted images were processed via FreeSurfer to obtain cortical and subcortical measures. L2 regularized logistic regression was used to evaluate the efficacy of diagnostic prediction.

The accuracies of pairwise discriminations were: 87% for FES vs HC (specificity 83%, sensitivity 91%); 77% for FES vs UHR (specificity 76%, sensitivity 79%); 75% for UHR vs HC (specificity 77%, sensitivity 73%).

Current findings suggest that the patterns of anatomical and functional variability have potential as biomarkers for discrimination between schizophrenia, UHR, and healthy subjects. Furthermore, results show that the selection and multimodality of feature types are important. Specifically, adding EEG data to morphometric measures improved accuracy rates in FES vs HC and FES vs UHR contrasts, whereas standalone EEG data provided higher accuracy compared with morphometric or multimodal data in UHR vs HC discrimination. Expectedly, predictive power for the UHR was smaller than for the FES due to its intermediate anatomical features, located between those observed in healthy controls and those found in patients. The work was supported by RFBR grant 20-013-00748

Different electrophysiological indices have been investigated to identify diagnostic and prognostic markers of schizophrenia (SCZ). However, these indices have limited use in clinical practice, since both specificity and association with illness outcome remain unclear. In recent years, machine learning techniques, through the combination of multidimensional data, have been used to better characterize SCZ and to predict illness course.

The aim of the present study is to identify multimodal electrophysiological biomarkers that could be used in clinical practice in order to improve precision in diagnosis and prognosis of SCZ.

Illness-related and functioning-related variables were measured at baseline in 113 subjects with SCZ and 57 healthy controls (HC), and after four-year follow-up in 61 SCZ. EEGs were recorded at baseline in resting-state condition and during two auditory tasks (MMN-P3a and N100-P3b). Through a Linear Support Vector Machine, using EEG data as predictors, four models were generated in order to classify SCZ and HC. Then, we combined unimodal classifiers’ scores through a stacking procedure. Pearson’s correlations between classifiers score with illness-related and functioning-related variables, at baseline and follow-up, were performed.

Each EEG model produced significant classification (p < 0.05). Global classifier discriminated SCZ from HC with accuracy of 75.4% (p < 0.01). A significant correlation (r=0.40, p=0.002) between the global classifier scores with negative symptoms at follow-up was found. Within negative symptoms, blunted affect showed the strongest correlation.

Abnormalities in electrophysiological indices might be considered trait markers of schizophrenia. Our results suggest that multimodal electrophysiological markers might have prognostic value for negative symptoms.

Transcranial alternating current stimulation (tACS) is a non-invasive brain stimulation technique allowing to induce changes in oscillatory activity. Theta activity has been reported to play a major role in maintenance of information in working memory (WM).

The current study had the initial goal to check the effect of theta tACS on accuracy and resting state EEG in a set of match-to-sample WM tasks.

In the first experiment, we tested 31 participants in the WM task after 20-min tACS applied at Fpz and CPz at 6 Hz, 1 mA.). In the second experiment, we compared the after-effects and online effects of the stimulation in a sample of 25 individuals. Five similar 25-min blocks filled with the same working memory task were distributed over 3 days. We assessed the same group of participants in all three sessions. On the Training day, the participants performed one block without stimulation. On the Sham-Verum day (SV), the first block with Sham stimulation followed by the second block with Verum stimulation. On the Verum-Sham day (VS), the blocks order reversed.

After-effects of the stimulation did not produce any significant changes either in behavior (accuracy in the task) or resting-state EEG (theta frequency band spectral power in the first experiment. In the second experiment, 6 Hz tACS delivered before the WM task was not able to produce any observable changes in working memory performance. The same hold true for online stimulation.

Theta frequency tACS applied to Fpz-CPz electrodes is not an efficient method to improve WM.

It remains unclear to what extent reduced nutritional intake in anorexia nervosa (AN) is a consequence of a reduced motivational response to food. Although self-reports typically suggest AN patients have a reduced appetitive response, behavioral and neurophysiological measures have revealed evidence for both increased and reduced attentional biases towards food stimuli. The mechanisms influencing food perception in AN, might be clarified using time-sensitive magnetoencephalography (MEG) to differentiate the early (more automatic processing) stages from the late (more controlled) stages.

MEG was recorded in 22 partially weight-restored adolescent AN patients and 29 age- and gender-matched healthy control (HC) participants during a rapid serial visual presentation paradigm using 100 high-calorie food, 100 low-calorie food, and 100 non-food pictures. Neural sources of event-related fields were estimated using the L2-Minimum-Norm method and analyzed in early (50–300 ms) and late (350–500 ms) time intervals.

AN patients rated high-calorie food as less palatable and reported overall less food craving than HC participants. Nevertheless, in response to food pictures AN patients showed relative increased neural activity in the left occipito-temporal and inferior frontal regions in the early time interval. No group differences occurred in the late time interval.

MEG results speak against an overall reduced motivational response to food in AN. Instead, relative increased early food processing in the visual cortex suggests greater motivated attention. A greater appetitive response to food might be an adaptive mechanism in a state of undernourishment. Yet, this relative increased food processing in AN was no longer present later, arguably reflecting rapid downregulation.