Electroencephalogram Studies Research Articles

A microservices architecture for processing large electroencephalogram studies

Electrical signatures characteristic of complex neurological activity and neuropsychiatric disease are embedded in electroencephalography (EEG) signal data. To firmly establish new correlations between these brain electrical pulses and cognition, behavior, and disorders, researchers must achieve adequate statistical power to validate and mitigate uncertainties in their findings. This necessitates the usage of extensive studies involving large volumes of raw EEG data files from multiple subjects, data which must be preprocessed before conducting further analysis. While conventional processing and analysis of these raw data have been performed using isolated physical lab environments and stovepiped applications, there is a growing necessity for processing and analysis solutions that enable distributed processing of large data collections. This study presents a novel microservices approach as an alternative and complementary solution for retrieving and preprocessing EEG signal data. The approach leverages serverless technologies to deliver a highly scalable solution for processing massive amounts of EEG data. Deployed within a public cloud environment, we assess the efficacy of this method when employing various container orchestration configurations. This work demonstrates the capability for substantial enhancements in processing speeds, particularly when dealing with extensive EEG datasets.

Comparing retro-cue benefit mechanisms in visual working memory: completely valid vs. highly valid retro-cues

Visual working memory (VWM) plays a crucial role in temporarily maintaining and manipulating visual information. Retro-cue benefit (RCB) refers to the enhancement of memory performance when attention is directed toward a subset of items in VWM after their initial encoding. Our recent electroencephalogram (EEG) studies indicate that cue validity affects the mechanisms underlying RCB formation. However, previous research has not thoroughly examined whether these mechanisms differ between completely valid and highly valid cue conditions. This study investigates the consistency of RCB mechanisms under conditions of complete (100%) and high (80%) retro-cue validity. We manipulated retro-cue validity and examined cognitive processing mechanisms under different validity conditions using EEG. Specifically, we focused on the N2pc component, which reflects attentional resource allocation, and the contralateral delay activity (CDA) component, which reflects the quantity of information retained in VWM. The results, encompassing both behavioral and event-related potential (ERP) findings, show that participants in both the 100% and 80% cue validity conditions exhibit robust RCB. Notably, the degree of RCB remains consistent across these conditions, indicating that participants utilize retro-cues to enhance VWM performance to the same extent. In the 80% cue validity condition, a significant retro-cue cost (RCC) was observed, indicating that participants selectively discarded uncued items from VWM. In invalid trials, response accuracy drops to chance levels, supporting the removal hypothesis. ERP results reveal that attentional resource allocation (N2pc) and the quantity of retained information (CDA) remain uniform across cue validity conditions. The mechanism responsible for RCB formation appears to involve an all-or-nothing process of discarding uncued information rather than a flexible resource allocation strategy. This study provides insights into attention allocation and information-processing mechanisms in VWM, suggesting that conclusions drawn from tasks with completely valid retro-cues can be integrated with findings from highly valid cue tasks. These findings also illuminate the flexibility of internal attentional resource allocation during RCB formation and contribute to our understanding of attention processes in VWM.

Adaptation patterns and their associations with mismatch negativity: An electroencephalogram (EEG) study with controlled expectations.

Adaptation refers to the decreased neural response that occurs after repeated exposure to a stimulus. While many electroencephalogram (EEG) studies have investigated adaptation by using either single or multiple repetitions, the adaptation patterns under controlled expectations manifested in the two main auditory components, N1 and P2, are still largely unknown. Additionally, although multiple repetitions are commonly used in mismatch negativity (MMN) experiments, it is unclear how adaptation at different time windows contributes to this phenomenon. In this study, we conducted an EEG experiment with 37 healthy adults using a random stimulus arrangement and extended tone sequences to control expectations. We tracked the amplitudes of the N1 and P2 components across the first 10 tones to examine adaptation patterns. Our findings revealed an L-shaped adaptation pattern characterised by a significant decrease in N1 amplitude after the first repetition (N1 initial adaptation), followed by a continuous, linear increase in P2 amplitude after the first repetition (P2 subsequent adaptation), possibly indicating model adjustment. Regression analysis demonstrated that the peak amplitudes of both the N1 initial adaptation and the P2 subsequent adaptation significantly accounted for variance in MMN amplitude. These results suggest distinct adaptation patterns for multiple repetitions across different components and indicate that the MMN reflects a combination of two processes: the initial adaptation in the N1 and a continuous model adjustment effect in the P2. Understanding these processes separately could have implications for models of cognitive processing and clinical disorders.

EEG Signal Classification using K-Nearest Neighbor Method to Measure Impulsivity Level

Impulsivity is the tendency to act without considering consequences or without careful planning. It involves a quick response to a stimulus without sufficient consideration of the consequences. Impulsivity needs to be measured and detected because it has a significant impact on various aspects of a person's life. The factors that influence the level of impulsivity include social environment, stress level, mental health, and genetic factors. Impulsivity can be divided into multiple components, such as reduced sensitivity to unfavorable behavioral outcomes, a disregard for long-term implications, and quick and spontaneous responses to stimuli. Electroencephalogram (EEG) studies can identify specific brain wave patterns such as, Alpha, Betha, Theta, and Gamma waves everything based on an individual brain's level of impulsivity. Signals from the brain are processed to extract specific features that reflect the user's intentions. EEG records brain activity without surgery, and this information is used for the diagnosis, monitoring, and treatment of neurological diseases, as well as scientific research on the brain and mind. K-Nearest Neighbor (KNN) is a classification algorithm that functions by utilizing several K nearest data values (its neighbors) as a reference to determine the class of new data. The K-Nearest Neighbors (KNN) algorithm is used for classification, clustering, and pattern recognition in EEG data where clustering is in 4 classifications (Impulsive, Not Impulsive, Potentially Impulsive, and Very Potentially Impulsive). This classification model shows high accuracy (Training Data: 94.7%, Testing: 91.3%, and Validation Data: 91.8%). This research shows that the KNN algorithm is effective for assessing the degree of impulsivity.

Associations of Plasma Glutamatergic Metabolites with Alpha Desynchronization during Cognitive Interference and Working Memory Tasks in Asymptomatic Alzheimer's Disease.

Electroencephalogram (EEG) studies have suggested compensatory brain overactivation in cognitively healthy (CH) older adults with pathological beta-amyloid(Aβ42)/tau ratios during working memory and interference processing. However, the association between glutamatergic metabolites and brain activation proxied by EEG signals has not been thoroughly investigated. We aim to determine the involvement of these metabolites in EEG signaling. We focused on CH older adults classified under (1) normal CSF Aβ42/tau ratios (CH-NATs) and (2) pathological Aβ42/tau ratios (CH-PATs). We measured plasma glutamine, glutamate, pyroglutamate, and γ-aminobutyric acid concentrations using tandem mass spectrometry and conducted a correlational analysis with alpha frequency event-related desynchronization (ERD). Under the N-back working memory paradigm, CH-NATs presented negative correlations (r = ~-0.74--0.96, p = 0.0001-0.0414) between pyroglutamate and alpha ERD but positive correlations (r = ~0.82-0.95, p = 0.0003-0.0119) between glutamine and alpha ERD. Under Stroop interference testing, CH-NATs generated negative correlations between glutamine and left temporal alpha ERD (r = -0.96, p = 0.037 and r = -0.97, p = 0.027). Our study demonstrated that glutamine and pyroglutamate levels were associated with EEG activity only in CH-NATs. These results suggest cognitively healthy adults with amyloid/tau pathology experience subtle metabolic dysfunction that may influence EEG signaling during cognitive challenge. A longitudinal follow-up study with a larger sample size is needed to validate these pilot studies.

Three-dimensional infrared scanning: an enhanced approach for spatial registration of probes for neuroimaging.

Accurate spatial registration of probes (e.g., optodes and electrodes) for measurement of brain activity is a crucial aspect in many neuroimaging modalities. It may increase measurement precision and enable the transition from channel-based calculations to volumetric representations. This technical note evaluates the efficacy of a commercially available infrared three-dimensional (3D) scanner under actual experimental (or clinical) conditions and provides guidelines for its use. We registered probe positions using an infrared 3D scanner and validated them against magnetic resonance imaging (MRI) scans on five volunteer participants. Our analysis showed that with standard cap fixation, the average Euclidean distance of probe position among subjects could reach up to 43mm, with an average distance of 15.25mm [standard deviation (SD) = 8.0]. By contrast, the average distance between the infrared 3D scanner and the MRI-acquired positions was 5.69mm (SD = 1.73), while the average difference between consecutive infrared 3D scans was 3.43mm (SD = 1.62). The inter-optode distance, which was fixed at 30mm, was measured as 29.28mm (SD = 1.12) on the MRI and 29.43mm (SD = 1.96) on infrared 3D scans. Our results demonstrate the high accuracy and reproducibility of the proposed spatial registration method, making it suitable for both functional near-infrared spectroscopy and electroencephalogram studies. The 3D infrared scanning technique for spatial registration of probes provides economic efficiency, simplicity, practicality, repeatability, and high accuracy, with potential benefits for a range of neuroimaging applications. We provide practical guidance on anonymization, labeling, and post-processing of acquired scans.

Comparison of power spectra from overnight electroencephalography between patients with Down syndrome and matched control subjects.

Electroencephalograms can capture brain oscillatory activities during sleep as a form of electrophysiological signals. We analysed electroencephalogram recordings from full-night in-laboratory polysomnography from 100 patients with Down syndrome, and 100 age- and sex-matched controls. The ages of patients with Down syndrome spanned 1 month to 31 years (median 4.4 years); 84 were younger than 12 years, and 54 were male. From each electroencephalogram, we extracted relative power in six frequency bands or rhythms (delta, theta, alpha, slow sigma, fast sigma, and beta) from six channels (frontal F3 and F4, central C3 and C4, and occipital O1 and O2) during five sleep stages (N3, N2, N1, R and W)-180 features in all. We examined differences in relative power between Down syndrome and control electroencephalograms for each feature separately. During wake and N1 sleep stages, alpha rhythms (8.0-10.5 Hz) had significantly lower power in patients with Down syndrome than controls. Moreover, the rate of increase in alpha power with age during rapid eye movement sleep was significantly slower in Down syndrome than control subjects. During wake and N1 sleep, delta rhythms (0.25-4.5 Hz) had higher power in patients with Down syndrome than controls. During N2 sleep, slow sigma rhythms (10.5-12.5 Hz) had lower power in patients with DS than controls. These findings extend previous research from routine electroencephalogram studies demonstrating that patients with Down syndrome had reduced circadian amplitude-the difference between wake alpha power and deep sleep delta power was smaller in Down syndrome than control subjects. We envision that these brain oscillatory activities may be used as surrogate markers for clinical trials for patients with Down syndrome.

Prediction of pharmacological treatment efficacy using electroencephalography-based salience network in patients with major depressive disorder.

Recent resting-state electroencephalogram (EEG) studies have consistently reported an association between aberrant functional brain networks (FBNs) and treatment-resistant traits in patients with major depressive disorder (MDD). However, little is known about the changes in FBNs in response to external stimuli in these patients. This study investigates whether changes in the salience network (SN) could predict responsiveness to pharmacological treatment in resting-state and external stimuli conditions. Thirty-one drug-naïve patients with MDD (aged 46.61 ± 10.05, female 28) and twenty-one healthy controls (aged 43.86 ± 14.14, female 19) participated in the study. After 8 weeks of pharmacological treatment, the patients were divided into non-remitted MDD (nrMDD, n = 14) and remitted-MDD (rMDD, n = 17) groups. EEG data under three conditions (resting-state, standard, and deviant) were analyzed. The SN was constructed with three cortical regions as nodes and weighted phase-lag index as edges, across alpha, low-beta, high-beta, and gamma bands. A repeated measures analysis of the variance model was used to examine the group-by-condition interaction. Machine learning-based classification analyses were also conducted between the nrMDD and rMDD groups. A notable group-by-condition interaction was observed in the high-beta band between nrMDD and rMDD. Specifically, patients with nrMDD exhibited hypoconnectivity between the dorsal anterior cingulate cortex and right insula (p = 0.030). The classification analysis yielded a maximum classification accuracy of 80.65%. Our study suggests that abnormal condition-dependent changes in the SN could serve as potential predictors of pharmacological treatment efficacy in patients with MDD.

Age-related differences in transient gamma band activity during working memory maintenance through adolescence

Adolescence is a stage of development characterized by neurodevelopmental specialization of cognitive processes. In particular, working memory continues to improve through adolescence, with increases in response accuracy and decreases in response latency continuing well into the twenties. Human electroencephalogram (EEG) studies indicate that gamma oscillations (35-65Hz) during the working memory delay period support the maintenance of mnemonic information guiding subsequent goal-driven behavior, which decrease in power with development. Importantly, recent electrophysiological studies have shown that gamma events, more so than sustained activity, may underlie working memory maintenance during the delay period. However, developmental differences in gamma events during working memory have not been studied. Here, we used EEG in conjunction with a novel spectral event processing approach to investigate age-related differences in transient gamma band activity during a memory guided saccade (MGS) task in 164 10- to 30-year-olds. Total gamma power was found to significantly decrease through adolescence, replicating prior findings. Results from the spectral event pipeline showed age-related decreases in the mean power of gamma events and trial-by-trial power variability across both the delay period and fixation epochs of the MGS task. In addition, we found that while event number decreased with age during the fixation period, the developmental decrease during the delay period was more dramatic, resulting in an increase in event spiking from fixation to delay in adolescence but not adulthood. While average power of the transient gamma events was found to mediate age-related differences in total gamma power in the fixation and delay periods, the number of gamma events was related to total power in only the delay period, suggesting that the power of gamma events may underlie the sustained gamma activity seen in EEG literature while the number of events may directly support age-related improvements in working memory maintenance. Our findings provide compelling new evidence for mechanistic changes in neural processing characterized by refinements in neural function as behavior becomes optimized in adulthood.

Age-Related Modifications of Electroencephalogram Coherence in Mice Models of Alzheimer’s Disease and Amyotrophic Lateral Sclerosis

In 5xFAD mice of 6-, 9-, 12-, and 18-month ages and their wild-type (WT5xFAD) littermates, we analyzed baseline EEG coherence between the cortex, hippocampus/putamen, ventral tegmental area, and substantia nigra. Additionally, EEG coherence between the cortex and putamen was analyzed in 2- and 5-month-old FUS mice. In the 5xFAD mice, suppressed levels of inter-structural coherence vs. those in WT5xFAD littermates were observed at ages of 6, 9, and 12 months. In 18-month-old 5xFAD mice, only the hippocampus ventral tegmental area coherence was significantly reduced. In 2-month-old FUS vs. WTFUS mice, the cortex-putamen coherence suppression, dominated in the right hemisphere, was observed. In 5-month-old mice, EEG coherence was maximal in both groups. Neurodegenerative pathologies are accompanied by the significant attenuation of intracerebral EEG coherence. Our data are supportive for the involvement of age-related adaptive mechanisms in intracerebral disturbances produced by neurodegeneration.

To treat or not to treat? High-potency benzodiazepine use in a case of comorbid hallucinogen persisting perception disorder and alcohol use disorder.

Hallucinogen persisting perception disorder (HPPD) is characterized by visual disturbances that resemble psychedelic intoxication and linger after use has ceased. The most common substances precipitating HPPD, lysergic acid diethylamide (LSD) and psilocybin, are posited to do so via damage to serotonergic neurons involved in vision. Mr. N is a 37-year-old with a history of alcohol, cannabis, LSD, cocaine, and nicotine use disorders who described visual distortions that resolved when he drank heavily or received benzodiazepines for withdrawal. He did not appear psychotic. Over 20 years after his last LSD use, he continued to experience illusions of halos around objects, moving walls, and figures appearing cartoonish. He understood that his perceptual disturbances were not reality based. During hospitalization for suicidal ideation, laboratory tests, head computed tomography (CT), and electroencephalogram (EEG) studies offered no explanation for his visual disturbances other than HPPD. The visual distortions remitted with scheduled clonazepam treatment, although chemical dependency treatment programs were hesitant to accept him while on a benzodiazepine. This case emphasizes the importance of diagnostic clarification when patients present with perceptual disturbances that do not fit typical psychotic presentations. Our discussion will distinguish misperceptions from hallucinations and review the pathophysiology of HPPD. Last, we will discuss management strategies for patients with co-occurring HPPD and substance use disorders. It is necessary to discern the correct cause of visual disturbances in order to provide proper treatment. The risks and benefits of long-term benzodiazepine use must be weighed when deciding whether to prescribe them for patients with comorbid HPPD and alcohol use disorder. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Neuroarchitecture From the Perspective of Circadian Rhythm, Physical, and Mental Health

The field of neuroarchitecture explores how various architectural elements impact human physical and mental health, based on neuroscience principles. With the development of functional neuroimaging and electroencephalogram studies, researchers can now visualize and quantify how different architectural factors affect brain activity, emotions, and cognition. Mobile Brain/Body Imaging is a new research methodology that records a moving person’s brain activity and bodily sensations in real time, promising to be a useful tool for space and urban design. In this article, we discuss neuroarchitecture from the perspective of circadian rhythm, physical health, and mental health. Studies have shown that artificial light at night disrupts the circadian rhythm, leading to acute and chronic negative health effects. Conversely, creating a personcentered light environment or incorporating nature-like elements can have a positive impact on health. Research has also shown that exposure to nature reduces self-rumination and contributes to psychological well-being. Neuroarchitecture studies on other factors, such as ceiling height, wall colors, and the movement of people in the building, should be expanded to gain greater insights and practical applications. The convergence of neuroscience and architecture has the potential to identify architectural elements that benefit human physical and mental health.

Sleep disturbance in schizophrenia spectrum disorders: more than just a symptom?

Sleep disturbance is commonly reported in patients with schizophrenia spectrum disorder (SSD) in the clinical setting. Sleep features can be assessed subjectively, with self-report sleep questionnaires, and objectively with actigraphy and electroencephalogram recordings. Traditionally, electroencephalogram studies have focused on sleep architecture. More recently, numerous studies have investigated alterations in sleep-specific rhythms, including electroencephalogram oscillations, such as sleep spindles and slow waves, in patients with SSD compared with control subjects. Here, I briefly discuss how sleep disturbance is highly prevalent in patients with SSD and I present findings from studies demonstrating abnormalities in sleep architecture and sleep-oscillatory rhythms, with an emphasis on sleep spindles and slow-wave deficits, in these patients. This increasing body of evidence highlights the importance of sleep disturbance in SSD and points to several future research directions with related clinical implications, thus showing that sleep disturbance is more than just a symptom in these patients.

Assessment of impaired consciousness using EEG-based connectivity features and convolutional neural networks.

Growing electroencephalogram (EEG) studies have linked the abnormities of functional brain networks with disorders of consciousness (DOC). However, due to network data's high-dimensional and non-Euclidean properties, it is difficult to exploit the brain connectivity information that can effectively detect the consciousness levels of DOC patients via deep learning. To take maximum advantage of network information in assessing impaired consciousness, we utilized the functional connectivity with convolutional neural network (CNN) and employed three rearrangement schemes to improve the evaluation performance of brain networks. In addition, the gradient-weighted class activation mapping (Grad-CAM) was adopted to visualize the classification contributions of connections among different areas. We demonstrated that the classification performance was significantly enhanced by applying network rearrangement techniques compared to those obtained by the original connectivity matrix (with an accuracy of 75.0%). The highest classification accuracy (87.2%) was achieved by rearranging the alpha network based on the anatomical regions. The inter-region connections (i.e., frontal-parietal and frontal-occipital connectivity) played dominant roles in the classification of patients with different consciousness states. The effectiveness of functional connectivity in revealing individual differences in brain activity was further validated by the correlation between behavioral performance and connections among specific regions. These findings suggest that our proposed assessment model could detect the residual consciousness of patients.

EFFECT OF CONCENTRATIVE MEDITATION ON REACTION ABILITY

The purpose of the study was to investigate the effect of meditation on reaction ability. Meditation is a practice in which an individual trains the mind or induces a mode of consciousness, either to realize some benefit or as an end in itself. Psychomotor abilities were always considered to be the foundation for technical skill and tactical ability in any given sports. Despite its popularity, little is known about the neural mechanisms by which meditation works, several electroencephalogram (EEG) studies have reported changes in spectral and frequency analysis during meditation inspired by techniques that focus on concentration. FFT (Fast Fourier Transform) was used to analysis investigate the composition of an EEG signal. Since the FFT transforms a signal from the time domain into the frequency domain, frequency distributions of the EEG was observed. With this understanding this research study was conceptualized to investigate effect of concentrative meditation on reaction ability. Fifty students were randomly selected as the subjects for the study. The age of the subjects ranged from 21 to 30 years. The subjects were assigned at random to experimental and control group each group consisting of twenty five students. The study was conducted for a period of eight weeks. The study examined EEG changes during meditation. The investigational paradigm involved 15-20 minutes of meditation, where the subjects were asked to close their eyes and adopt their normal meditation. Two groups comprising of twenty five subjects each were formed i.e. experimental Group and control group. The experimental group was given meditation in the morning session time and no meditational training was given to control group. Each subject of Experimental group was learning concentrative Meditation. Electroencephalogram (EEG) and psychomotor variables used to collect the data before and after meditational training to measure the effect of meditation. These results suggest that meditation provides no improvement in reaction ability. EEG findings from this study suggest that concentrative meditation techniques improves theta and alpha EEG patterns significantly. Key Words: Reaction Ability, Fast Fourier Transform (FFT) and Electroencephalogram.

Frontal and parietal lobes play crucial roles in understanding the disorder of consciousness: A perspective from electroencephalogram studies.

Electroencephalogram (EEG) studies have established many characteristics relevant to consciousness levels of patients with disorder of consciousness (DOC). Although the frontal and parietal brain regions were often highlighted in DOC studies, their electro-neurophysiological roles in constructing human consciousness remain unclear because of the fragmented information from literatures and the complexity of EEG characteristics. Existing EEG studies of DOC patients were reviewed and summarized. Relevant findings and results about the frontal and parietal regions were filtered, compared, and concluded to clarify their roles in consciousness classification and outcomes. The evidence covers multi-dimensional EEG characteristics including functional connectivity, non-linear dynamics, spectrum power, transcranial magnetic stimulation-electroencephalography (TMS-EEG), and event-related potential. Electroencephalogram characteristics related to frontal and parietal regions consistently showed high relevance with consciousness: enhancement of low-frequency rhythms, suppression of high-frequency rhythms, reduction of dynamic complexity, and breakdown of networks accompanied with decreasing consciousness. Owing to the limitations of EEG, existing studies have not yet clarified which one between the frontal and parietal has priority in consciousness injury or recovery. Source reconstruction with high-density EEG, machine learning with large samples, and TMS-EEG mapping will be important approaches for refining EEG awareness locations.

Effect of Herbal Perfumes and Synthetic Perfumes on Attention and Cognitive Functions in Young Adults: A Sequential Cross-sectional Study

Introduction: Focused and sustained attention, executive function, working memory and task switching are important cognitive abilities. Efforts to enhance cognitive abilities, have engaged the scientific community since ages. Human beings are exposed to several fragrances and the perception of the sense of smell, plays an important role in the physiological effects of mood, stress, and working capacity. Perception of olfactory stimuli involves complex brain processing, which can be directly associated with cognition and emotion. Several Electroencephalogram (EEG) studies have revealed that, fragrances significantly modulate the activities of different brain waves and are responsible for various states of the brain. Aim: To objectively demonstrate the effect of olfactory stimulation with herbal (rose) perfume on attention and executive functions. Materials and Methods: This sequential cross-sectional study was conducted in the Department of Physiology at Osmania Medical College, Hyderabad, Telangana, India. The duration of the study was one month, from 16th August 2021 to 16th September 2021. Study included 40 healthy participants (15 males and 25 females), aged between 18-30 years to olfactory stimulation by herbal (rose) extract perfume and synthetic (rose) perfume, and the effects are assessed, using the psychophysiological tests viz., Rapid Serial Visual Presentation task (RSVP), Trail Making Tests (TMT) A&B, Ruff Figural Fluency Test (RFT), and compared with the baseline scores, which are then analysed using Paired t-test. The data was analysed by using Statistical Package for Social Sciences (SPSS) version 16.0. Results: Olfactory stimulation with herbal rose perfume enhances the attention and speed of processing, as shown by the nearly significant improvement in the performance of the TMT-A (p-value=0.05433), with decreased time taken to perform the test, whereas, the synthetic rose perfume enhanced the attention, speed, switching between tasks, cognitive fluency, and flexibility. This is evident by the significant improvement in the performance of the TMT-A (p-value=0.00326) and TMT-B (p-value=0.0001693), with decreased time taken to perform the tests. The derived index TMT (B-A), which removes the speed component and is a purer index of executive functions, also showed significant results (p-value=0.002092). Conclusion: The effects of herbal and synthetic rose olfactory stimulation have shown positive influence on the attention and cognitive functions and this finding can be applied to create student friendly learning environments, by providing pleasant stimuli through means of aromatic sprays delivering the odorant in a pulsatile manner at a frequency to overcome the ensuing olfactory adaptation.

FPT, a 2-Aminotetralin, Is a Potent Serotonin 5-HT1A, 5-HT1B, and 5-HT1D Receptor Agonist That Modulates Cortical Electroencephalogram Activity in Adult Fmr1 Knockout Mice.

There are no approved medicines for fragile X syndrome (FXS), a monogenic, neurodevelopmental disorder. Electroencephalogram (EEG) studies show alterations in resting-state cortical EEG spectra, such as increased gamma-band power, in patients with FXS that are also observed in Fmr1 knockout models of FXS, offering putative biomarkers for drug discovery. Genes encoding serotonin receptors (5-HTRs), including 5-HT1A, 5-HT1B, and 5-HT1DRs, are differentially expressed in FXS, providing a rationale for investigating them as pharmacotherapeutic targets. Previously we reported pharmacological activity and preclinical neurotherapeutic effects in Fmr1 knockout mice of an orally active 2-aminotetralin, (S)-5-(2'-fluorophenyl)-N,N-dimethyl-1,2,3,4-tetrahydronaphthalen-2-amine (FPT). FPT is a potent (low nM), high-efficacy partial agonist at 5-HT1ARs and a potent, low-efficacy partial agonist at 5-HT7Rs. Here we report new observations that FPT also has potent and efficacious agonist activity at human 5-HT1B and 5-HT1DRs. FPT's Ki values at 5-HT1B and 5-HT1DRs were <5 nM, but it had nil activity (>10 μM Ki) at 5-HT1FRs. We tested the effects of FPT (5.6 mg/kg, subcutaneous) on EEG recorded above the somatosensory and auditory cortices in freely moving, adult Fmr1 knockout and control mice. Consistent with previous reports, we observed significantly increased relative gamma power in untreated or vehicle-treated male and female Fmr1 knockout mice from recordings above the left somatosensory cortex (LSSC). In addition, we observed sex effects on EEG power. FPT did not eliminate the genotype difference in relative gamma power from the LSSC. FPT, however, robustly decreased relative alpha power in the LSSC and auditory cortex, with more pronounced effects in Fmr1 KO mice. Similarly, FPT decreased relative alpha power in the right SSC but only in Fmr1 knockout mice. FPT also increased relative delta power, with more pronounced effects in Fmr1 KO mice and caused small but significant increases in relative beta power. Distinct impacts of FPT on cortical EEG were like effects caused by certain FDA-approved psychotropic medications (including baclofen, allopregnanolone, and clozapine). These results advance the understanding of FPT's pharmacological and neurophysiological effects.

Age of Acquisition Modulates Alpha Power During Bilingual Speech Comprehension in Noise.

Research on bilingualism has grown exponentially in recent years. However, the comprehension of speech in noise, given the ubiquity of both bilingualism and noisy environments, has seen only limited focus. Electroencephalogram (EEG) studies in monolinguals show an increase in alpha power when listening to speech in noise, which, in the theoretical context where alpha power indexes attentional control, is thought to reflect an increase in attentional demands. In the current study, English/French bilinguals with similar second language (L2) proficiency and who varied in terms of age of L2 acquisition (AoA) from 0 (simultaneous bilinguals) to 15 years completed a speech perception in noise task. Participants were required to identify the final word of high and low semantically constrained auditory sentences such as “Stir your coffee with a spoon” vs. “Bob could have known about the spoon” in both of their languages and in both noise (multi-talker babble) and quiet during electrophysiological recording. We examined the effects of language, AoA, semantic constraint, and listening condition on participants’ induced alpha power during speech comprehension. Our results show an increase in alpha power when participants were listening in their L2, suggesting that listening in an L2 requires additional attentional control compared to the first language, particularly early in processing during word identification. Additionally, despite similar proficiency across participants, our results suggest that under difficult processing demands, AoA modulates the amount of attention required to process the second language.

Local Interactions between Steady-State Visually Evoked Potentials at Nearby Flickering Frequencies.

Steady-state visually evoked potentials (SSVEPs) are widely used to index top-down cognitive processing in human electroencephalogram (EEG) studies. Typically, two stimuli flickering at different temporal frequencies (TFs) are presented, each producing a distinct response in the EEG at its flicker frequency. However, how SSVEP responses in EEGs are modulated in the presence of a competing flickering stimulus just because of sensory interactions is not well understood. We have previously shown in local field potentials (LFPs) recorded from awake monkeys that when two overlapping full-screen gratings are counterphased at different TFs, there is an asymmetric SSVEP response suppression, with greater suppression from lower TFs, which further depends on the relative orientations of the gratings (stronger suppression and asymmetry for parallel compared with orthogonal gratings). Here, we first confirmed these effects in both male and female human EEG recordings. Then, we mapped the response suppression of one stimulus (target) by a competing stimulus (mask) over a much wider range than the previous study. Surprisingly, we found that the suppression was not stronger at low frequencies in general, but systematically varied depending on the target TF, indicating local interactions between the two competing stimuli. These results were confirmed in both human EEG and monkey LFP and electrocorticogram (ECoG) data. Our results show that sensory interactions between multiple SSVEPs are more complex than shown previously and are influenced by both local and global factors, underscoring the need to cautiously interpret the results of studies involving SSVEP paradigms.SIGNIFICANCE STATEMENT Steady-state visually evoked potentials (SSVEPs) are extensively used in human cognitive studies and brain-computer interfacing applications where multiple stimuli flickering at distinct frequencies are concurrently presented in the visual field. We recently characterized interactions between competing flickering stimuli in animal recordings and found that stimuli flickering slowly produce larger suppression. Here, we confirmed these in human EEGs, and further characterized the interactions by using a much wider range of target and competing (mask) frequencies in both human EEGs and invasive animal recordings. These revealed a new "local" component, whereby the suppression increased when competing stimuli flickered at nearby frequencies. Our results highlight the complexity of sensory interactions among multiple SSVEPs and underscore the need to cautiously interpret studies involving SSVEP paradigms.