Influence of phosphatidylserine on cognitive performance and cortical activity after induced stress

Luteolin alleviates depression-like behavior by modulating glycerophospholipid metabolism in the hippocampus and prefrontal cortex of LOD rats

BACKGROUND

Late-onset depression (LOD) is defined as primary depression that first manifests after the age of 65. Luteolin (LUT) is a natural flavonoid that has shown promising antidepressant effects and improvement in neurological function in previous studies.

AIMS

In this study, we utilized UPLC-MS/MS non-targeted metabolomics techniques, along with molecular docking technology and experimental validation, to explore the mechanism of LUT in treating LOD from a metabolomics perspective.

RESULTS

The behavioral results of our study demonstrate that LUT significantly ameliorated anxiety and depression-like behaviors while enhancing cognitive function in LOD rats. Metabolomic analysis revealed that the effects of LUT on LOD rats were primarily mediated through the glycerophospholipid metabolic pathway in the hippocampus and prefrontal cortex. The levels of key lipid metabolites, phosphatidylserine (PS), phosphatidylcholine (PC), and phosphatidylethanolamine (PE), in the glycerophospholipid metabolic pathway were significantly altered by LUT treatment, with PC and PE showing significant correlations with behavioral indices. Molecular docking analysis indicated that LUT had strong binding activity with phosphatidylserine synthase 1 (PTDSS1), phosphatidylserine synthase 2 (PTDSS2), and phosphatidylserine decarboxylase (PISD), which are involved in the transformation and synthesis of PC, PE, and PS. Lastly, our study explored the reasons for the opposing trends of PC, PE, and PS in the hippocampus and prefrontal cortex from the perspective of autophagy, which may be attributable to the bidirectional regulation of autophagy in distinct brain regions.

CONCLUSIONS

Our results revealed significant alterations in the glycerophospholipid metabolism pathways in both the hippocampus and prefrontal cortex of LOD rats. Moreover, LUT appears to regulate autophagy disorders by specifically modulating glycerophospholipid metabolism in different brain regions of LOD rats, consequently alleviating depression-like behavior in these animals.

EEG-Based Cross-Subject Driver Drowsiness Recognition With an Interpretable Convolutional Neural Network

In the context of electroencephalogram (EEG)-based driver drowsiness recognition, it is still challenging to design a calibration-free system, since EEG signals vary significantly among different subjects and recording sessions. Many efforts have been made to use deep learning methods for mental state recognition from EEG signals. However, existing work mostly treats deep learning models as black-box classifiers, while what have been learned by the models and to which extent they are affected by the noise in EEG data are still underexplored. In this article, we develop a novel convolutional neural network combined with an interpretation technique that allows sample-wise analysis of important features for classification. The network has a compact structure and takes advantage of separable convolutions to process the EEG signals in a spatial-temporal sequence. Results show that the model achieves an average accuracy of 78.35% on 11 subjects for leave-one-out cross-subject drowsiness recognition, which is higher than the conventional baseline methods of 53.40%-72.68% and state-of-the-art deep learning methods of 71.75%-75.19%. Interpretation results indicate the model has learned to recognize biologically meaningful features from EEG signals, e.g., alpha spindles, as strong indicators of drowsiness across different subjects. In addition, we also explore reasons behind some wrongly classified samples with the interpretation technique and discuss potential ways to improve the recognition accuracy. Our work illustrates a promising direction on using interpretable deep learning models to discover meaningful patterns related to different mental states from complex EEG signals.

Fields or firings? Comparing the spike code and the electromagnetic field hypothesis

Where is consciousness? Neurobiological theories of consciousness look primarily to synaptic firing and "spike codes" as the physical substrate of consciousness, although the specific mechanisms of consciousness remain unknown. Synaptic firing results from electrochemical processes in neuron axons and dendrites. All neurons also produce electromagnetic (EM) fields due to various mechanisms, including the electric potential created by transmembrane ion flows, known as "local field potentials," but there are also more meso-scale and macro-scale EM fields present in the brain. The functional role of these EM fields has long been a source of debate. We suggest that these fields, in both their local and global forms, may be the primary seat of consciousness, working as a gestalt with synaptic firing and other aspects of neuroanatomy to produce the marvelous complexity of minds. We call this assertion the "electromagnetic field hypothesis." The neuroanatomy of the brain produces the local and global EM fields but these fields are not identical with the anatomy of the brain. These fields are produced by, but not identical with, the brain, in the same manner that twigs and leaves are produced by a tree's branches and trunk but are not the same as the branches and trunk. As such, the EM fields represent the more granular, both spatially and temporally, aspects of the brain's structure and functioning than the neuroanatomy of the brain. The brain's various EM fields seem to be more sensitive to small changes than the neuroanatomy of the brain. We discuss issues with the spike code approach as well as the various lines of evidence supporting our argument that the brain's EM fields may be the primary seat of consciousness. This evidence (which occupies most of the paper) suggests that oscillating neural EM fields may make firing in neural circuits oscillate, and these oscillating circuits may help unify and guide conscious cognition.

The Effects of Directional and Non-Directional Stimuli during a Visuomotor Task and Their Correlation with Reaction Time: An ERP Study

Different visual stimuli can capture and shift attention into different directions. Few studies have explored differences in brain response due to directional (DS) and non-directional visual stimuli (nDS). To explore the latter, event-related potentials (ERP) and contingent negative variation (CNV) during a visuomotor task were evaluated in 19 adults. To examine the relation between task performance and ERPs, the participants were divided into faster (F) and slower (S) groups based on their reaction times (RTs). Moreover, to reveal ERP modulation within the same subject, each recording from the single participants was subdivided into F and S trials based on the specific RT. ERP latencies were analysed between conditions ((DS, nDS); (F, S subjects); (F, S trials)). Correlation was analysed between CNV and RTs. Our results reveal that the ERPs' late components are modulated differently by DS and nDS conditions in terms of amplitude and location. Differences in ERP amplitude, location and latency, were also found according to subjects' performance, i.e., between F and S subjects and trials. In addition, results show that the CNV slope is modulated by the directionality of the stimulus and contributes to motor performance. A better understanding of brain dynamics through ERPs could be useful to explain brain states in healthy subjects and to support diagnoses and personalized rehabilitation in patients with neurological diseases.

Zebrafish EEG predicts the efficacy of antiepileptic drugs

Background: Pharmacological evaluation of antiepileptic drugs (AEDs) using mammalian animals takes long time and is expensive. The zebrafish is a species commonly used to study brain functions, neurological diseases, and drug toxicity, and attracts more attention as an alternative animal model to substitute or supplement mammalian animals in drug development. Electroencephalogram (EEG) is a key indicator for diagnosing brain diseases such as epilepsy, by directly measuring the brain activity. We propose a novel method for pharmacological evaluation of AEDs based on EEG from adult zebrafish, which allows researchers to select more clinically valuable drugs at the early stage of AED screening. Methods: To evaluate the efficacy of AEDs, zebrafish EEG signals were measured after administering six AEDs (valproate acid, gabapentin, ethosuximide, oxcarbazepine, tiagabine, and topiramate) at various doses to pentylenetetrazol (PTZ)-induced seizure models. The change in seizure activity was investigated according to doses. The antiepileptic effect was determined by observing a significant decrease in at least one out of three indicators of the number, total duration, and mean duration of ictal events. Results: Using EEG signals from adult zebrafish, antiepileptic effects were observed with all six AEDs. Among them, antiepileptic effects depending on dose were confirmed with valproate acid, gabapentin, ethosuximide, and tiagabine. Moreover, the 50% effective doses (ED50) of valproate acid and tiagabine were determined based on zebrafish EEG for the first time, indicating that the quantitative inter-species comparison of the AED efficacy is possible between zebrafish and mammals such as rodents. Significance: The results show that zebrafish can be used to effectively and quantitatively evaluate the efficacy of AEDs based on EEG, the same method to evaluate antiepileptic effects in mammals, suggesting that the proposed method can contribute in reducing the cost and duration of search for AEDs and thus accelerate the drug development cycles.

Dietary supplements in neurological diseases and brain aging

A healthy diet shapes a healthy mind. Diet quality has a strong association with brain health. Diet influences the onset and consequences of neurological diseases, and dietary factors may influence mental health at individual and population level. The link between unhealthy diet, impaired cognitive function and neurodegenerative diseases indicates that adopting a healthy diet would ultimately afford prevention and management of neurological diseases and brain aging. Neurodegenerative diseases are of multifactorial origin and result in progressive loss of neuronal function in the brain, leading to cognitive impairment and motoneuron disorders. The so-called Mediterranean diet (MedDiet) with its healthy ingredients rich in antioxidant, anti-inflammatory, immune, neuroprotective, antidepressant, antistress and senolytic activity plays an essential role in the prevention and management of neurological diseases and inhibits cognitive decline in neurodegenerative diseases such as Alzheimer's, Parkinson's and Huntington's diseases. The MedDiet also modulates the gut-brain axis by promoting a diversity of gut microbiota. In view of the importance of diet in neurological diseases management, this review focuses on the dietary components, natural compounds and medicinal plants that have proven beneficial in neurological diseases and for brain health. Among them, polyphenols, omega-3 fatty acids, B vitamins and several ayurvedic herbs have promising beneficial effects.

Wired for sound: The effect of sound on the epileptic brain

Sound waves are all around us resonating at audible and inaudible frequencies. Our ability to hear is crucial in providing information and enabling interaction with our environment. The human brain generates neural oscillations or brainwaves through synchronised electrical impulses. In epilepsy these brainwaves can change and form rhythmic bursts of abnormal activity outwardly appearing as seizures. When two waveforms meet, they can superimpose onto one another forming constructive, destructive or mixed interference. The effects of audible soundwaves on epileptic brainwaves has been largely explored with music. The Mozart Sonata for Two Pianos in D major, K. 448 has been examined in a number of studies where significant clinical and methodological heterogeneity exists. These studies report variable reductions in seizures and interictal epileptiform discharges. Treatment effects of Mozart Piano Sonata in C Major, K.545 and other composer interventions have been examined with some musical exposures, for example Hayden's Symphony No. 94 appearing pro-epileptic. The underlying anti-epileptic mechanism of Mozart music is currently unknown, but interesting research is moving away from dopamine reward system theories to computational analysis of specific auditory parameters. In the last decade several studies have examined inaudible low intensity focused ultrasound as a neuro-modulatory intervention in focal epilepsy. Whilst acute and chronic epilepsy rodent model studies have consistently demonstrated an anti-epileptic treatment effect this is yet to be reported within large scale human trials. Inaudible infrasound is of concern since at present there are no reported studies on the effects of exposure to infrasound on epilepsy. Understanding the impact of infrasound on epilepsy is critical in an era where sustainable energies are likely to increase exposure.

A Review of Equine Sleep: Implications for Equine Welfare

Sleep is a significant biological requirement for all living mammals due to its restorative properties and its cognitive role in memory consolidation. Sleep is ubiquitous amongst all mammals but sleep profiles differ between species dependent upon a range of biological and environmental factors. Given the functional importance of sleep, it is important to understand these differences in order to ensure good physical and psychological wellbeing for domesticated animals. This review focuses specifically on the domestic horse and aims to consolidate current information on equine sleep, in relation to other species, in order to (a) identify both quantitatively and qualitatively what constitutes normal sleep in the horse, (b) identify optimal methods to measure equine sleep (logistically and in terms of accuracy), (c) determine whether changes in equine sleep quantity and quality reflect changes in the animal's welfare, and (d) recognize the primary factors that affect the quantity and quality of equine sleep. The review then discusses gaps in current knowledge and uses this information to identify and set the direction of future equine sleep research with the ultimate aim of improving equine performance and welfare. The conclusions from this review are also contextualized within the current discussions around the “social license” of horse use from a welfare perspective.

Performance prediction in a visuo-motor task: the contribution of EEG analysis

Brain state in the time preceding the task affects motor performance at single trial level. Aim of the study was to investigate, through a single trial analysis of the Power Spectral Density (PSD) of the cortical sources of EEG rhythms, whether there are EEG markers, which can predict trial-by-trial the subject's performance as measured by the reaction time (RT). 20 healthy adult volunteers performed a specific visuomotor task while continuously recorded with a 64 electrodes EEG. For each single trial, the PSD of the cortical sources of EEG rhythms was obtained from EEG data to cortical current density time series in 12 regions of interest at Brodmann areas level. Results showed a statistically significant increase of posterior and limbic alpha 1 and of frontal beta 2 power, and a reduction of frontal and limbic delta and of temporal alpha 1 power, during triggering stimulus presentation for better performance, namely faster responses. At single trial level, correlation analyses between RTs and significant PSD, revealed positive correlations in frontal delta, temporal alpha 1, and limbic delta bands, and negative ones in frontal beta 2, parietal alpha 1, and occipital alpha 1 bands. Furthermore, the subject's faster responses have been found as correlated with the similarity between the PSD values in parietal and occipital alpha 1. Predicting individual's performance at single trial level, might be extremely useful in the clinical context, since it could allow to launch rehabilitative therapies in the most efficient brain state, avoiding useless interventions.

Radiation exposure and mitochondrial insufficiency in chronic fatigue and immune dysfunction syndrome

Chronic fatigue and Immune Dysfunction Syndrome (CFIDS) is a heterogeneous disease that may be promoted by various environmental stressors, including viral infection, toxin uptake, and ionizing radiation exposure. Previous studies have identified mitochondrial dysfunction in CFIDS patients, including modulation of mitochondrial respiratory chain activity, deletions in the mitochondrial genome, and upregulation of reactive oxygen species (ROS). This paper focuses on radiation effects and hypothesizes that CFIDS is primarily caused by stressor-induced mitochondrial metabolic insufficiency, which results in decreased energy production and anabolic metabolites required for normal cellular metabolism. Furthermore, tissues neighbouring or distant from directly perturbed tissues compensate for this dysfunction, which causes symptoms associated with CFIDS. This hypothesis is justified by reviewing the links between radiation exposure and CFIDS, cancer, immune dysfunction, and induction of oxidative stress. Moreover, the relevance of mitochondria in cellular responses to radiation and metabolism are discussed and putative mitochondrial biomarkers for CFIDS are introduced. Implications for diagnosis are then described, including a potential urine assay and PCR test for mitochondrial genome mutations. Finally, future research needs are offered with an emphasis on where rapid progress may be made to assist the afflicted.

Alpha and high gamma phase amplitude coupling during motor imagery and weighted cross-frequency coupling to extract discriminative cross-frequency patterns

Motor imagery modulates specific neural oscillations like actual movement does. Representatively, suppression of the alpha power (e.g., event-related desynchronization [ERD]) is the typical pattern of motor imagery in the motor cortex. However, in addition to this amplitude-based feature, the coupling across frequencies includes important information about the brain functions and the existence of such complex information has been reported in various invasive studies. Yet, the interaction across multiple frequencies during motor imagery processing is still unclear and has not been widely studied, particularly concerning the non-invasive signals. In this study, we provide empirical evidence of the comodulation between the phase of alpha rhythm and the amplitude of high gamma rhythm during the motor imagery process. We used electroencephalography (EEG) in our investigation during the imagination of left- or right-hand movement recorded from 52 healthy subjects, and quantified the ERD of alpha and phase-amplitude coupling (PAC) which is a relative change of modulation index to the base line period (before the cue). As a result, we found that the coupling between the phase of alpha (8-12 Hz) and the amplitude of high gamma (70-120 Hz) and this PAC decreases during motor imagery and then rebounds to the baseline like alpha ERD (r = 0.29 to 0.42). This correlation between PAC and ERD was particularly stronger in the ipsilateral area. In addition, trials that demonstrated higher alpha power during the ready period (before the cue) showed a larger ERD during motor imagery and similarly, trials with higher modulation index during the ready period yielded a greater decrease in PAC during imagery. In the classification analysis, we found that the effective phase frequency that showed better decoding accuracy in left and right-hand imagery, varied across subjects. Motivated by result, we proposed a weighted cross-frequency coupling (WCFC) method that extracts the maximal discriminative feature by combining band power and CFC. In the evaluation, WCFC with only two electrodes yielded a performance comparable to the conventional algorithm with 64 electrodes in classifying left and right-hand motor imagery. These results indicate that the phase-amplitude frequency plays an important role in motor imagery, and that optimizing this frequency ranges is crucial for extracting information features to decode the motor imagery types.

Effective connectivity in brain networks estimated using EEG signals is altered in children with ADHD

This study presents a methodology developed for estimating effective connectivity in brain networks (BNs) using multichannel scalp EEG recordings. The methodology uses transfer entropy as an information transfer measure to detect pair-wise directed information transfer between EEG signals within δ, θ, α, β and γ-bands. The developed methodology is then used to study the properties of directed BNs in children with attention-deficit hyperactivity disorder (ADHD) and compare them with that of the healthy controls using both statistical and receiver operating characteristic (ROC) analyses. The results indicate that directed information transfer between scalp EEG electrodes in the ADHD subjects differs significantly compared to the healthy ones. The results of the statistical and ROC analyses of frequency-specific graph measures demonstrate their highly discriminative ability between the two groups. Specifically, the graph measures extracted from the estimated directed BNs in the β-band show the highest discrimination between the ADHD and control groups. These findings are in line with the fact that β-band reflects active concentration, motor activity, and anxious mental states. The reported results show that the developed methodology has the capacity to be used for investigating patterns of directed BNs in neuropsychiatric disorders.

An Analysis of the External Validity of EEG Spectral Power in an Uncontrolled Outdoor Environment during Default and Complex Neurocognitive States

Traditionally, quantitative electroencephalography (QEEG) studies collect data within controlled laboratory environments that limit the external validity of scientific conclusions. To probe these validity limits, we used a mobile EEG system to record electrophysiological signals from human participants while they were located within a controlled laboratory environment and an uncontrolled outdoor environment exhibiting several moderate background influences. Participants performed two tasks during these recordings, one engaging brain activity related to several complex cognitive functions (number sense, attention, memory, executive function) and the other engaging two default brain states. We computed EEG spectral power over three frequency bands (theta: 4-7 Hz, alpha: 8-13 Hz, low beta: 14-20 Hz) where EEG oscillatory activity is known to correlate with the neurocognitive states engaged by these tasks. Null hypothesis significance testing yielded significant EEG power effects typical of the neurocognitive states engaged by each task, but only a beta-band power difference between the two background recording environments during the default brain state. Bayesian analysis showed that the remaining environment null effects were unlikely to reflect measurement insensitivities. This overall pattern of results supports the external validity of laboratory EEG power findings for complex and default neurocognitive states engaged within moderately uncontrolled environments.

Does Muscle Fatigue Alter EEG Bands of Brain Hemispheres?

Background:

Muscle fatigue has been known to influence brain activity, but very little is known about how cortical centers respond to muscle fatigue.

Objective:

This study was conducted to investigate the effects of muscle contraction and fatigue induced by two different percents of maximal voluntary contraction (MVC) on Electroencephalography (EEG) signals.

Material and Methods:

In this quasi-experimental study, EEG signals were recorded from twenty-one healthy human subjects during three phases (rest, pre fatigue and post fatigue) contraction of Adductor pollicis muscle (APM) at 30% and 70% MVC. The mean powers of EEG bands (alpha, beta and gamma) were computed offline in the frequency domain.

Results:

None of the three phases with each percent of MVC revealed significant differences for all bands (p>0.05). Comparison of two hemispheres showed that right hemisphere gamma band activity was enhanced during pre-fatigue state at 30% MVC (p= 0.042) and post-fatigue state at 70% MVC (p= 0.028). Right hemisphere beta band activity also increased prominently at 70% MVC in post-fatigue condition (p = 0.030).

Conclusion:

These results suggest muscle contraction and fatigue at 30% and 70% MVC have no significant effect on EEG activity, but the trends of beta and gamma band activities are almost similar in each percent of 30% and 70% MVC. Right brain hemisphere shows more activity than left hemisphere in beta and gamma rhythm after fatigue state at 70% MVC.

Brain Activity Correlates With Cognitive Performance Deterioration During Sleep Deprivation

We studied the correlation between oscillatory brain activity and performance in healthy subjects performing the error awareness task (EAT) every 2 h, for 24 h. In the EAT, subjects were shown on a screen the names of colors and were asked to press a key if the name of the color and the color it was shown in matched, and the screen was not a duplicate of the one before (“Go” trials). In the event of a duplicate screen (“Repeat No-Go” trial) or a color mismatch (“Stroop No-Go” trial), the subjects were asked to withhold from pressing the key. We assessed subjects’ (N = 10) response inhibition by measuring accuracy of the “Stroop No-Go” (SNGacc) and “Repeat No-Go” trials (RNGacc). We assessed their reactivity by measuring reaction time in the “Go” trials (GRT). Simultaneously, nine electroencephalographic (EEG) channels were recorded (Fp₂, F₇, F₈, O₁, Oz, Pz, O₂, T₇, and T₈). The correlation between reactivity and response inhibition measures to brain activity was tested using quantitative measures of brain activity based on the relative power of gamma, beta, alpha, theta, and delta waves. In general, response inhibition and reactivity reached a steady level between 6 and 16 h of sleep deprivation, which was followed by sustained impairment after 18 h. Channels F₇ and Fp₂ had the highest correlation to the indices of performance. Measures of response inhibition (RNGacc and SNGacc) were correlated to the alpha and theta waves’ power for most of the channels, especially in the F₇ channel (r = 0.82 and 0.84, respectively). The reactivity (GRT) exhibited the highest correlation to the power of gamma waves in channel Fp₂ (0.76). We conclude that quantitative measures of EEG provide information that can help us to better understand changes in subjects’ performance and could be used as an indicator to prevent the adverse consequences of sleep deprivation.

Individualized pattern recognition for detecting mind wandering from EEG during live lectures

Neural correlates of mind wandering

The ability to detect mind wandering as it occurs is an important step towards improving our understanding of this phenomenon and studying its effects on learning and performance. Current detection methods typically rely on observable behaviour in laboratory settings, which do not capture the underlying neural processes and may not translate well into real-world settings. We address both of these issues by recording electroencephalography (EEG) simultaneously from 15 participants during live lectures on research in orthopedic surgery. We performed traditional group-level analysis and found neural correlates of mind wandering during live lectures that are similar to those found in some laboratory studies, including a decrease in occipitoparietal alpha power and frontal, temporal, and occipital beta power. However, individual-level analysis of these same data revealed that patterns of brain activity associated with mind wandering were more broadly distributed and highly individualized than revealed in the group-level analysis.

Mind wandering detection

To apply these findings to mind wandering detection, we used a data-driven method known as common spatial patterns to discover scalp topologies for each individual that reflects their differences in brain activity when mind wandering versus attending to lectures. This approach avoids reliance on known neural correlates primarily established through group-level statistics. Using this method for individual-level machine learning of mind wandering from EEG, we were able to achieve an average detection accuracy of 80–83%.

Conclusions

Modelling mind wandering at the individual level may reveal important details about its neural correlates that are not reflected when using traditional observational and statistical methods. Using machine learning techniques for this purpose can provide new insight into the varieties of neural activity involved in mind wandering, while also enabling real-time detection of mind wandering in naturalistic settings.

Effects of milk-based phospholipids on cognitive performance and subjective responses to psychosocial stress: A randomized, double-blind, placebo-controlled trial in high-perfectionist men

OBJECTIVES

The aim of this study was to examine the stress-buffering potential of phospholipid (PL) intake on cognitive performance and neuroendocrine and psychological responses under conditions of psychosocial stress in a high-stress vulnerable (perfectionist) sample.

METHODS

Fifty-four high-perfectionist men consumed a 6-wk daily intake of a bovine milk-derived PL (2.7 g/d) or placebo drink in a randomized, double-blind, placebo-controlled, parallel groups design. Working memory, executive control function, and acute physiological/subjective responses to an acute psychosocial stressor were examined before and after the 6-wk PL or placebo intake.

RESULTS

PL intake improved post-stress reaction time performance on an attention-switching task (P = 0.01). No significant attenuation of the salivary cortisol stress response was shown. PL intake significantly increased mid-stress induction energetic arousal (P = 0.03). A non-significant reduction in anticipatory subjective stress was reported after PL intake (P = 0.06). Systolic and diastolic blood pressures (P<0.04 and P = 0.01, respectively) were significantly augmented in the PL condition.

CONCLUSIONS

Dietary intake of bovine milk PLs conferred cognitive performance benefit under conditions of psychosocial stress but failed to moderate cortisol response. Moderation of subjective response to stress exposure may have underpinned this performance protection.

Effects of Rifaximin on Central Responses to Social Stress-a Pilot Experiment

Probiotics that promote the gut microbiota have been reported to reduce stress responses, and improve memory and mood. Whether and how antibiotics that eliminate or inhibit pathogenic and commensal gut bacteria also affect central nervous system functions in humans is so far unknown. In a double-blinded randomized study, 16 healthy volunteers (27.00 ± 1.60 years; 9 males) received either rifaximin (600 mg/day) (a poorly absorbable antibiotic) or placebo for 7 days. Before and after the drug intervention, brain activities during rest and during a social stressor inducing feelings of exclusion (Cyberball game) were measured using magnetoencephalography. Social exclusion significantly affected (p < 0.001) mood and increased exclusion perception. Magnetoencephalography showed brain regions with higher activations during exclusion as compared to inclusion, in different frequency bands. Seven days of rifaximin increased prefrontal and right cingulate alpha power during resting state. Low beta power showed an interaction of intervention (rifaximin, placebo) × condition (inclusion, exclusion) during the Cyberball game in the bilateral prefrontal and left anterior cingulate cortex. Only in the rifaximin group, a decrease (p = 0.004) in power was seen comparing exclusion to inclusion; the reduced beta-1 power was negatively correlated with a change in the subjective exclusion perception score. Social stress affecting brain functioning in a specific manner is modulated by rifaximin. Contrary to our hypothesis that antibiotics have advert effects on mood, the antibiotic exhibited stress-reducing effects similar to reported effects of probiotics (supported by NeuroGUT, a EU 7th Framework Programme ITN no. 607652; ClinicalTrials.gov identifier number NCT02793193).

The effect of foot reflexotherapy on the dynamics of cortical oscillatory waves in healthy humans: An EEG study

BACKGROUND

Foot reflexotherapy is a noninvasive complementary therapy that has gained considerable application in several fields of human endeavor. The therapy is used to relieve the symptoms of several ailments. For instance, foot reflexotherapy when applied to the cortical areas of the left or right foot relieves pain and stress. However, the electrophysiological mechanisms of the effect of foot reflexotherapy on cortical activity are not completely understood. While it has been shown that foot reflexotherapy exert positive effects on brain functions, little is known about the effects of this therapy on cortical activities as recorded with electroencephalogram (EEG) in healthy humans. Cortical activity is widely investigated with EEG, a noninvasive recording that is used to study brain activity in different functional states and conditions.

AIM

The aim of this study was to investigate the effect of foot reflexotherapy on EEG rhythms in healthy humans.

MATERIAL AND METHODS

EEG recording before and after reflexological therapy was carried out in seven healthy right-handed males who volunteered for the study.

RESULTS

Analysis of EEG data revealed activation offrontal cortex that resulted to significant increase in beta and gamma spectral powers after foot reflexotherapy (p ˂ 0.05).

CONCLUSION

Foot reflexotherapy is associated with increase in spectral powers in beta and gamma frequency bands. Therefore cortical beta and gamma waves of the EEG could be used as measures of functional activation of the brain, related to foot reflexotherapy.

Heritability of Sleep EEG Topography in Adolescence: Results from a Longitudinal Twin Study

The topographic distribution of sleep EEG power is a reflection of brain structure and function. The goal of this study was to examine the degree to which genes contribute to sleep EEG topography during adolescence, a period of brain restructuring and maturation. We recorded high-density sleep EEG in monozygotic (MZ; n = 28) and dizygotic (DZ; n = 22) adolescent twins (mean age = 13.2 ± 1.1 years) at two time points 6 months apart. The topographic distribution of normalized sleep EEG power was examined for the frequency bands delta (1-4.6 Hz) to gamma 2 (34.2-44 Hz) during NREM and REM sleep. We found highest heritability values in the beta band for NREM and REM sleep (0.44 ≤ h2 ≤ 0.57), while environmental factors shared amongst twin siblings accounted for the variance in the delta to sigma bands (0.59 ≤ c2 ≤ 0.83). Given that both genetic and environmental factors are reflected in sleep EEG topography, our results suggest that topography may provide a rich metric by which to understand brain function. Furthermore, the frequency specific parsing of the influence of genetic from environmental factors on topography suggests functionally distinct networks and reveals the mechanisms that shape these networks.

A 3D-Printed Sensor for Monitoring Biosignals in Small Animals

Although additive manufacturing technologies, also known as 3D printing, were first introduced in the 1980s, they have recently gained remarkable popularity owing to decreased costs. 3D printing has already emerged as a viable technology in many industries; in particular, it is a good replacement for microfabrication technology. Microfabrication technology usually requires expensive clean room equipment and skilled engineers; however, 3D printing can reduce both cost and time dramatically. Although 3D printing technology has started to emerge into microfabrication manufacturing and medical applications, it is typically limited to creating mechanical structures such as hip prosthesis or dental implants. There have been increased interests in wearable devices and the critical part of such wearable devices is the sensing part to detect biosignals noninvasively. In this paper, we have built a 3D-printed sensor that can measure electroencephalogram and electrocardiogram from zebrafish. Despite measuring biosignals noninvasively from zebrafish has been known to be difficult due to that it is an underwater creature, we were able to successfully obtain electrophysiological information using the 3D-printed sensor. This 3D printing technique can accelerate the development of simple noninvasive sensors using affordable equipment and provide an economical solution to physiologists who are unfamiliar with complicated microfabrication techniques.

Individual Differences in UGV Operation

Unmanned systems operations are complex, cognitively demanding tasks that elicit highly variable workload. The ability to predict performance and workload within these complex tasks can provide a powerful tool for practitioners regarding fit-for-duty verification. Further, monitoring workload aids in diagnostic assessment of factors that impact performance. The goal for this analysis was to examine the quality of cross-task averages of both baseline and concurrent psychophysiological and subjective measures to predict task performance and perceived workload. At a theoretical level, these findings suggest the need for a multivariate conceptualization of processing ‘resources’, encompassing both implicit and explicit responses. At a practical level, both subjective and psychophysiological measures may be necessary for optimizing performance prediction, at least for certain tasks.

Characterizing functional connectivity patterns during saliva swallows in different head positions

BACKGROUND

The anatomical rationale and efficacy of the chin tuck in improving airway protection for some people with swallowing disorders have been well researched and established. However, there are still open questions regarding whether brain activity for swallowing control is altered while performing this chin-tuck maneuver.

METHODS

In this study, we collected EEG signals from 55 healthy adults while swallowing in the neutral and chin-tuck head positions. The time-frequency based synchrony measure was used to form brain networks. We investigated both the small-world properties of these brain networks and differences among the constructed brain networks for the two head positions during swallowing tasks.

RESULTS

We showed that brain networks for swallowing in both head positions exhibit small-world properties. Furthermore, we showed that swallowing in the chin-tuck head position affects brain networks in the Alpha and Gamma frequency bands.

CONCLUSIONS

According to these results, we can tell that the parameter of head position should be considered in future investigations which utilize EEG signals during swallowing activity.

Phosphatidylserine in the brain: metabolism and function

Phosphatidylserine (PS) is the major anionic phospholipid class particularly enriched in the inner leaflet of the plasma membrane in neural tissues. PS is synthesized from phosphatidylcholine or phosphatidylethanolamine by exchanging the base head group with serine, and this reaction is catalyzed by phosphatidylserine synthase 1 and phosphatidylserine synthase 2 located in the endoplasmic reticulum. Activation of Akt, Raf-1 and protein kinase C signaling, which supports neuronal survival and differentiation, requires interaction of these proteins with PS localized in the cytoplasmic leaflet of the plasma membrane. Furthermore, neurotransmitter release by exocytosis and a number of synaptic receptors and proteins are modulated by PS present in the neuronal membranes. Brain is highly enriched with docosahexaenoic acid (DHA), and brain PS has a high DHA content. By promoting PS synthesis, DHA can uniquely expand the PS pool in neuronal membranes and thereby influence PS-dependent signaling and protein function. Ethanol decreases DHA-promoted PS synthesis and accumulation in neurons, which may contribute to the deleterious effects of ethanol intake. Improvement of some memory functions has been observed in cognitively impaired subjects as a result of PS supplementation, but the mechanism is unclear.

COMBINATION OF HETEROGENEOUS EEG FEATURE EXTRACTION METHODS AND STACKED SEQUENTIAL LEARNING FOR SLEEP STAGE CLASSIFICATION

This work proposes a methodology for sleep stage classification based on two main approaches: the combination of features extracted from electroencephalogram (EEG) signal by different extraction methods, and the use of stacked sequential learning to incorporate predicted information from nearby sleep stages in the final classifier. The feature extraction methods used in this work include three representative ways of extracting information from EEG signals: Hjorth features, wavelet transformation and symbolic representation. Feature selection was then used to evaluate the relevance of individual features from this set of methods. Stacked sequential learning uses a second-layer classifier to improve the classification by using previous and posterior first-layer predicted stages as additional features providing information to the model. Results show that both approaches enhance the sleep stage classification accuracy rate, thus leading to a closer approximation to the experts' opinion.

The effect of phosphatidylserine administration on memory and symptoms of attention-deficit hyperactivity disorder: a randomised, double-blind, placebo-controlled clinical trial

BACKGROUND

Attention-deficit hyperactivity disorder (ADHD) is the most commonly diagnosed behavioural disorder of childhood, affecting 3-5% of school-age children. The present study investigated whether the supplementation of soy-derived phosphatidylserine (PS), a naturally occurring phospholipid, improves ADHD symptoms in children.

METHODS

Thirty six children, aged 4-14 years, who had not previously received any drug treatment related to ADHD, received placebo (n = 17) or 200 mg day(-1) PS (n = 19) for 2 months in a randomised, double-blind manner. Main outcome measures included: (i) ADHD symptoms based on DSM-IV-TR; (ii) short-term auditory memory and working memory using the Digit Span Test of the Wechsler Intelligence Scale for Children; and (iii) mental performance to visual stimuli (GO/NO GO task).

RESULTS

PS supplementation resulted in significant improvements in: (i) ADHD (P < 0.01), AD (P < 0.01) and HD (P < 0.01); (ii) short-term auditory memory (P < 0.05); and (iii) inattention (differentiation and reverse differentiation, P < 0.05) and inattention and impulsivity (P < 0.05). No significant differences were observed in other measurements and in the placebo group. PS was well-tolerated and showed no adverse effects.

CONCLUSIONS

PS significantly improved ADHD symptoms and short-term auditory memory in children. PS supplementation might be a safe and natural nutritional strategy for improving mental performance in young children suffering from ADHD.

The effects of IQPLUS Focus on cognitive function, mood and endocrine response before and following acute exercise

Background

Phosphatidylserine (PS) is a phospholipid found in cell membranes of most animals and plants. PS has been shown to reduce stress and increase performance in runners, cyclists and golfers. The purpose of this study was to investigate the effects of a PS containing formulation on cognitive function, mood and endocrine response before and after intense resistance exercise.

Methods

18 lower body, resistance trained, college aged males ingested 14 days of supplement (IQPLUS Focus, providing 400 mg of soy-derived PS) and a Placebo (PL), in a randomized, double-blind, placebo controlled, cross-over manner. Following 14 days of supplementation, participants performed an acute bout of lower body resistance training. Mood (Profile of Mood States, POMS) and cognitive function (Serial Subtraction Test, SST) were measured prior to, 5 minutes after, and 60 minutes after exercise. Venous blood samples were collected prior to, and 5, 15, 25, 40 and 60 minutes after exercise. Blood samples were analyzed for plasma cortisol and testosterone. Data were analyzed using repeated measures ANOVA.

Results

PS supplementation significantly reduced the time needed for a correct calculation on the SST by 20% (reduced by 1.27 s per calculation; PL: 6.4 s, PS: 5.13 s; p = 0.001), and reduced the total amount of errors by 39% (PL: 1.28 + .69, PS: .78 + .27, p = 0.53), and increased the amount of correct calculations by 13% (PL: 22.1 + 2.24, PS: 24.9 + 1.52, p = 0.07) prior to or in response to exercise compared to PL. Following exercise, there was no difference in SST scores between PS and PL. There were no significant changes in regards to mood or endocrine response to exercise as a result of PS supplementation.

Conclusion

PS supplementation significantly increased cognitive function prior to exercise. Improved cognitive function could benefit athletes and non-athletes alike. PS did not appear to affect mood or endocrine response prior to or following resistance exercise.