Vigilance States Research Articles

Blink-induced changes in pupil dynamics are consistent and heritable

Pupil size and blink rates are heritable but the extent to which they interact with one another has not been properly investigated. Though changes in pupil size due to eye blinks have been reported, they are considered a pupillary artifact. In this study we used the HCP 7T fMRI dataset with resting state eye-tracking data obtained in monozygotic and dizygotic twins to assess their heritability and their interactions. For this purpose, we characterized the pupil dilation (positive peak) and constriction (negative peak) that followed blink events, which we describe as blink-induced pupillary response (BIPR). We show that the BIPR is highly consistent with a positive dilatory peak (D-peak) around 500ms and a negative constricting peak (C-peak) around 1s. These patterns were reproducible within- and between-subjects across two time points and differed by vigilance state (vigilant versus drowsy). By comparing BIPR between monozygotic and dizygotic twins we show that BIPR have a heritable component with significant additive genetic (A) and environmental (E) factors dominating the structural equation models, particularly in the time-domain for both D- and C-peaks (a2 between 42 and 49%) and shared effects (C) as observed in the amplitude domain for the C-peak. Blink duration, pupil size and blink rate were also found to be highly heritable (a2 up to 62% for pupil size). Our study provides evidence of that shared environmental and additive genetic factors influence BIPR and indicates that BIPR should not be treated as a coincidental artefact. Instead BIPR appears to be a component of a larger oculomotor system that we label here as Oculomotor Adaptive System, that is genetically determined.

Multimodal state-dependent connectivity analysis of arousal and autonomic centers in the brainstem and basal forebrain.

Vigilance is a continuously altering state of cortical activation that influences cognition and behavior and is disrupted in multiple brain pathologies. Neuromodulatory nuclei in the brainstem and basal forebrain are implicated in arousal regulation and are key drivers of widespread neuronal activity and communication. However, it is unclear how their large-scale brain network architecture changes across dynamic variations in vigilance state (i.e., alertness and drowsiness). In this study, we leverage simultaneous EEG and 3T multi-echo functional magnetic resonance imaging (fMRI) to elucidate the vigilance-dependent connectivity of arousal regulation centers in the brainstem and basal forebrain. During states of low vigilance, most of the neuromodulatory nuclei investigated here exhibit a stronger global correlation pattern and greater connectivity to the thalamus, precuneus, and sensory and motor cortices. In a more alert state, the nuclei exhibit the strongest connectivity to the salience, default mode, and auditory networks. These vigilance-dependent correlation patterns persist even after applying multiple preprocessing strategies to reduce systemic vascular effects. To validate our findings, we analyze two large 3T and 7T fMRI datasets from the Human Connectome Project and demonstrate that the static and vigilance-dependent connectivity profiles of the arousal nuclei are reproducible across 3T multi-echo, 3T single-echo, and 7T single-echo fMRI modalities. Overall, this work provides novel insights into the role of neuromodulatory systems in vigilance-related brain activity.

MCLAS adaptively rescues disease-specific sleep and wake phenotypes in neurodegeneration

Sleep alterations are hallmarks of prodromal Alzheimer’s (AD) and Parkinson’s disease (PD), with fundamental neuropathological processes of both diseases showing susceptibility of change upon deep sleep modulation. However, promising pharmacological deep sleep enhancement results are hindered by specificity and scalability issues, thus advocating for noninvasive slow-wave activity (SWA) boosting methods to investigate the links between deep sleep and neurodegeneration. Accordingly, we have recently introduced mouse closed-loop auditory stimulation (mCLAS), which is able to successfully boost SWA during deep sleep in neurodegeneration models. Here, we aim at further exploring mCLAS’ acute effect onto disease-specific sleep and wake alterations in AD (Tg2576) and PD (M83) mice. We found that mCLAS adaptively rescues pathological sleep and wake traits depending on the disease-specific impairments observed at baseline in each model. Notably, in AD mice mCLAS significantly increases NREM long/short bout ratio, decreases vigilance state distances by decreasing transition velocities and increases the percentage of cumulative time spent in NREM sleep in the last three hours of the dark period. Contrastingly, in PD mice mCLAS significantly decreases NREM sleep consolidation, by potentiating faster and more frequent transitions between vigilance states, decreases average EMG muscle tone during REM sleep and increases alpha power in WAKE and NREM sleep. Overall, our results indicate that mCLAS selectively prompts an acute alleviation of neurodegeneration-associated sleep and wake phenotypes, by either potentiating sleep consolidation and vigilance state stability in AD or by rescuing bradysomnia and decreasing cortical hyperexcitability in PD. Further experiments assessing the electrophysiological, neuropathological and behavioural long-term effects of mCLAS in neurodegeneration may majorly impact the clinical establishment of sleep-based therapies.

Influences of examination periods on the state of alertness of students at the Biosciences UFR of the Felix HOUPHOUET-BOIGNY University in Abidjan (Côte d’Ivoire)

Introduction: University exam periods are marked by increased workload and pressure to perform, leading to changes in lifestyle habits. These changes can strongly affect the physiological and psychological state of students. Objective: This study examines the influence of exam periods on the state of vigilance of students at the UFR Biosciences of the Félix HOUPHOUËT-BOIGNY University of Abidjan (Côte d’Ivoire). Methodology: A questionnaire survey was conducted among 100 students, including 50 during exam periods and 50 outside exam periods. Results: The results reveal a significant reduction in sleep duration during exams (5.54 ± 1.33 hours compared to 8.50 ± 1.64 hours during normal periods) and an increase in revision time (4.38 ± 1.85 hours versus 2 ± 0.88 hours). The alertness index decreased significantly during exams (0.95 ± 0.20 versus 1.67 ± 0.26). However, neither the number of examinations per day, nor the timing of revisions, nor their duration have a significant impact on vigilance. Thesis results suggest that exam periods negatively affect students ' alertness, mainly due to changes in sleep and study habits. Conclusion: This study highlights the importance of a balance between revision and rest to maintain optimal alertness during exams.

Sex differences in sleep deficits in mice with an autism-linked Shank3 mutation

BackgroundInsomnia is more prevalent in individuals with Autism Spectrum Disorder (ASD), can worsen core-symptoms and reduces quality of life of both individuals and caregivers. Although ASD is four times more prevalent in males than females, less is known about sex specific sleep differences in autistic individuals. Recent ASD studies suggest that sleep problems may be more severe in females, which aligns with the sex bias seen in insomnia for the general population. We have previously shown that male mice with a mutation in the high confidence ASD gene Shank3, Shank3∆C, recapitulate most aspects of the ASD insomnia phenotype. The objective of the present study was to leverage the Shank3∆C model to investigate sex-specific effects in sleep using polysomnography.MethodsAdult male and female Shank3∆C and wildtype (WT) littermates were first recorded for 24 h of baseline recordings. Subsequently, they were sleep deprived (SD) for five hours via gentle handling and allowed 19 h of recovery sleep to characterize the homeostatic response to SD. Vigilance states (rapid eye movement (REM) sleep, non-rapid eye movement (NREM) sleep and wake) were assigned by manual inspection using SleepSign. Data processing, statistical analysis and visualization were conducted using MATLAB.ResultsSex and genotype effects were found during baseline sleep and after SD. At baseline, male Shank3∆C mice sleep less during the dark period (active phase) while female Shank3∆C mice sleep less during the light period (rest phase) and sleep more during the dark period. Both male and female Shank3∆C mice show reduced spectral power in NREM sleep. We detect a significant effect of sex and genotype in sleep onset latency and homeostatic sleep pressure (sleepiness). In addition, while male Shank3∆C mice fail to increase sleep time following SD as seen in WT, female Shank3∆C mice decrease sleep time.ConclusionsOverall, our study demonstrates sex differences in sleep architecture and homeostatic response to SD in adult Shank3∆C mice. Thus, our study demonstrates an interaction between sex and genotype in Shank3∆C mice and supports the use of the Shank3∆C model to better understand mechanisms contributing to the sex differences in insomnia in ASD in clinical populations.

BW312 Hordeum vulgare semi-dwarf mutant exhibits a shifted metabolic profile towards pathogen resistance.

Plant hormonal mutants, which do not produce or are insensitive to hormones, are often affected in their growth and development, but other metabolic rearrangements might be involved. A trade-off between growth and stress response is necessary for the plant survival. Here, we explore the metabolic profile and the pathogen resistance of a brassinosteroid-insensitive Hordeum vulgare L. semi-dwarf mutant, BW312. We investigate BW312 metabolism through a chemical enrichment analysis, confirming a shifted metabolic profile towards pathogen resistance. The effective pathogen resistance of the mutant was tested in presence of Pyrenophora teres and Fusarium graminearum. Four compound families were increased in the mutant (pyrrolidines, basic amino acids, alkaloids, monounsaturated fatty acids), while two compound families were decreased (pyrrolidinones, anthocyanins). Dipeptides were also altered (increased and decreased). BW312 displayed a better resistance to Pyrenophora teres in the earliest stage of infection with a 21.5% decrease of the lesion length 10days after infection. BW312 also exhibited a reduced lesion length (43.3%) and a reduced browning of the lesions (55.5%) when exposed to Fusarium graminearum at the seedling stage. The observed metabolomic shift strongly suggests that the BW312 semi-dwarf mutant is in a primed state, resulting in a standby state of alertness to pathogens.

Sleep in the dromedary camel: features of the 'first night effect'.

The 'first night effect' (FNE) is a well-known phenomenon in polysomnographic (PSG) sleep studies, resulting in significant variations in the macrostructure of wakefulness and sleep states, particularly between the initial and subsequent sleep recording sessions. The FNE phenomenon during sleep has been studied in various species, revealing complex variations between several sessions of sleep recording. The present study used a non-invasive PSG method to examine differences between various vigilance states in four adult female dromedary camels during 4 consecutive nights and days of sleep recording. The results indicate the presence of a FNE in the architecture of the dromedary camel's vigilance states. On the first night, the proportions of wakefulness and light non-rapid eye movment (NREM) sleep (drowsiness) were higher, at a mean (standard error of the mean [SEM]) of 40.92% (0.88%) and 14.93% (0.37%), respectively; while the proportion of rumination (mean [SEM] 29.55% [0.92%]) was lower compared to consecutive nights. No FNE was found on deep NREM sleep, while night-time REM sleep had a shorter proportion during the first night compared to subsequent consecutive nights. A significantly lower REM/total sleep time (TST) ratio was observed on the first night. Daytime comparisons did not show any significant differences for the different vigilance states. The increase in wakefulness and light NREM sleep and the reduction in REM sleep and REM/TST sleep on the first night indicate a decline in sleep quality in the dromedary camel due to the FNE. Thus, we recommend excluding from a PSG sleep study at least the first session/night of the recordings to ensure accurate results.

Assessing the risk of pedestrian crossing behavior on suburban roads using structural equation model

While pedestrian crashes on suburban roads have received more attention over recent years, the role of pedestrian crossing risk in areas adjacent to pedestrian crossing facilities, such as pedestrian overpasses, has been neglected. Most pedestrians in suburban areas tend to avoid pedestrian overpasses, exhibiting crossing behaviors that increase the likelihood of pedestrian-involving crashes. As a result of the presence of overpasses, drivers may think that there are no pedestrians in the surroundings, so they choose a speed based only on the prevailing traffic and road environment without accounting for potential interactions with pedestrians. Consequently, crashes will occur, with pedestrians typically being the most seriously affected casualties. In this study, using video recordings from a suburban road in Amol-Babol, Iran, the risk of pedestrian crossing behavior in areas near pedestrian overpasses is investigated. The speed selection behavior of drivers in these areas has also been examined using speedometer cameras. To quantify the level of risk for pedestrians when interacting with approaching vehicles during the crossing movements, the post encroachment time (PET) was used as a surrogate safety measure. Based on critical thresholds of PET, three different risk levels were identified using a K-means algorithm: high, medium, and low risk. To identify the elements affecting the risk of pedestrian crossing behavior, structural equation models were estimated for all three risk levels. The results showed that human factors, relating to both drivers and pedestrians, have a dominant impact on pedestrian safety, especially in high and medium risk contexts. Road and vehicle factors were also found to have statistically observable effects on pedestrian safety, but to a milder extent compared to human factors. The findings of this study highlight the need for intervening in several aspects of vehicle-pedestrian interactions with critical importance for pedestrian safety, including road users’ performance and compliance, state of alertness, and interaction with road infrastructure.

Anti-seizure effects of norepinephrine-induced free fatty acid release

The brain's ability to rapidly transition between sleep, quiet wakefulness, and states of high vigilance is remarkable. Cerebral norepinephrine (NE) plays a key role in promoting wakefulness, but how does the brain avoid neuronal hyperexcitability upon arousal? Here, we show that NE exposure results in the generation of free fatty acids (FFAs) within the plasma membrane from both astrocytes and neurons. In turn, FFAs dampen excitability by differentially modulating the activity of astrocytic and neuronal Na+, K+, ATPase. Direct application of FFA to the occipital cortex in awake, behaving mice dampened visual-evoked potential (VEP). Conversely, blocking FFA production via local application of a lipase inhibitor heightened VEP and triggered seizure-like activity. These results suggest that FFA release is a crucial step in NE signaling that safeguards against hyperexcitability. Targeting lipid-signaling pathways may offer a novel therapeutic approach for seizure prevention.

Meningococcal Carriage in Children with Atypical Hemolytic Uremic Syndrome Receiving Eculizumab Therapy.

Eculizumab is a first-line treatment for atypical hemolytic uremic syndrome (aHUS), and patients undergoing eculizumab therapy may become more susceptible to infection caused by Neisseria meningitidis (Nm). While meningococcal vaccination is required for patients undergoing eculizumab therapy, there is limited knowledge about meningococcal carriage in children with aHUS. We aimed to evaluate (1) the prevalence of Nm carriage, (2) serogroup distribution, and (3) the immunization status of children undergoing eculizumab treatment for aHUS. The Meningo-aHUS study is a prospective, multi-center study evaluating meningococcal carriage in children and adolescents in Türkiye receiving eculizumab for aHUS. We noted the age, gender, daycare, school, or university attendance, passive smoking status, previous infection and antibiotic use, and previous immunization history, including meningococcal vaccines, from the medical records of those children with aHUS. We collected nasopharyngeal samples, tested them for Nm using real-time polymerase chain reaction, and performed a serogroup analysis on the positive samples. We collected nasopharyngeal samples from 62 children with aHUS. Out of 62 children, 61 (98.4%) had received at least one dose of the meningococcal vaccine. The median time since the last meningococcal vaccine dose was 15 months (1-59 months). We detected meningococcal carriage in three (4.8%, 95% CI 1.0-13.5) children, and all three strains were non-groupable (NG). No other serogroups were detected. Almost all the children received their risk-group meningococcal immunization, including booster doses. A 4.8% of children with aHUS carried NG meningococci and, no vaccine serogroups were detected. Patients treated with eculizumab remain profoundly susceptible to IMD due to these NG meningococcal strains. The occurrence of breakthrough cases and carriage of Nm, especially NG strains, highlights the significance of maintaining a state of constant alertness, promptly seeking medical attention, and swiftly treating any symptoms that align with IMD, regardless of their vaccination status or antibiotic prophylaxis.

Audiovisual messages may improve the processing of traffic information and driver attention during partially automated driving: An EEG study

Partially autonomous vehicles can help minimize human errors. However, being free from some driving subtasks can result in a low vigilance state, which can affect the driver’s attention towards the road. The present study first tested whether drivers of partially autonomous vehicles would benefit from the addition of auditory versions of the messages presented in variable message signs (VMS), particularly, when they find themselves in a monotonous driving situation. A second aim was to test whether the addition of auditory messages would also produce an indirect effect on the driver’s vigilance, improving performance on other driving subtasks not related to the message processing. Forty-three volunteers participated in a driving simulator study. They completed two tasks: (a) a VMS task, where they had to regain manual control of the car if the VMS message was critical, and (b) a car-following task, where they had to pay attention to the preceding car to respond to occasional brake events. Behavioral and EEG data were registered. Overall, results indicated that the addition of audio messages helped drivers process VMS information more effectively and maintain a higher level of vigilance throughout the driving time. These findings would provide useful information for the development of partially automated vehicles, as their design must guarantee that the driver remains attentive enough to assume control when necessary.

Mindfulness meditation alters neural oscillations independently of arousal

Neuroscience has identified that mindfulness meditation induces a state of relaxed alertness, characterised by changes in theta and alpha oscillations and reduced sympathetic arousal, although the underlying mechanisms remain unclear. This study aims to address this gap by examining changes in neural oscillations and arousal during mindfulness meditation using both traditional and data-driven methods. Fifty-two healthy young adults underwent electroencephalography (EEG) and skin conductance level (SCL) recordings during resting baseline and mindfulness meditation conditions, both conducted with eyes closed. The EEG data revealed a significant decrease in traditional alpha (8–13 Hz) amplitude during mindfulness meditation compared to rest. However, no significant differences were observed between conditions in traditional delta, theta, beta, or gamma amplitudes. Frequency Principal Components Analysis (fPCA) was employed as a data-driven approach, identifying six components consistent across conditions. A complex delta-theta-alpha component significantly increased during mindfulness meditation. In contrast, low alpha (~9.5 Hz) and low alpha-beta (~11 Hz) components decreased significantly during mindfulness meditation. No significant differences were observed between conditions in the delta, high alpha, and high alpha-beta components. Additionally, there were no significant differences in SCL between conditions, nor were there correlations between traditional alpha or fPCA components and SCL. These findings support the conceptualisation of mindfulness meditation as a state of relaxed alertness, characterised by changes in neural oscillations likely associated with attention and awareness. However, the observed changes do not appear to be driven by arousal.

Fluoxetine, but not paroxetine, alters the jaw-closing muscle activity during non-rapid eye movement sleep in mice

Sleep bruxism is an involuntary, exaggerated jaw-closing activity during sleep. Selective serotonin reuptake inhibitor (SSRI) use is a risk factor for bruxism. However, the effect of various SSRIs on masseter (jaw-closing) muscle activity remains unclear. Here, we examined the effects of long-term administration of two SSRIs, fluoxetine (FLX) and paroxetine (PRX), for 14 days on masseter muscle activity during wakefulness, non-rapid eye movement (NREM) sleep, and rapid eye movement (REM) sleep for 24 h in mice. Vigilance states were scored based on electroencephalographic, electrooculography and neck electromyographic (EMG) activities. The EMG activity of the masseter muscle was quantified in 6 h periods. FLX and PRX did not affect the duration of the three vigilance states. Both drugs significantly prolonged the REM sleep episode duration while decreasing the number of episodes. FLX significantly increased REM sleep onset latency. Neither FLX nor PRX affected the mean masseter EMG activity during wakefulness. FLX significantly increased the relative time of masseter muscle activity in NREM sleep during 02:00–08:00 and 08:00–14:00, while PRX did not affect three vigilance states. Overall, FLX had a limited but significant effect on masseter muscle activity in NREM sleep during specific periods.

Generalizability of electroencephalographic interpretation using artificial intelligence: An external validation study.

The automated interpretation of clinical electroencephalograms (EEGs) using artificial intelligence (AI) holds the potential to bridge the treatment gap in resource-limited settings and reduce the workload at specialized centers. However, to facilitate broad clinical implementation, it is essential to establish generalizability across diverse patient populations and equipment. We assessed whether SCORE-AI demonstrates diagnostic accuracy comparable to that of experts when applied to a geographically different patient population, recorded with distinct EEG equipment and technical settings. We assessed the diagnostic accuracy of a "fixed-and-frozen" AI model, using an independent dataset and external gold standard, and benchmarked it against three experts blinded to all other data. The dataset comprised 50% normal and 50% abnormal routine EEGs, equally distributed among the four major classes of EEG abnormalities (focal epileptiform, generalized epileptiform, focal nonepileptiform, and diffuse nonepileptiform). To assess diagnostic accuracy, we computed sensitivity, specificity, and accuracy of the AI model and the experts against the external gold standard. We analyzed EEGs from 104 patients (64 females, median age = 38.6 [range = 16-91] years). SCORE-AI performed equally well compared to the experts, with an overall accuracy of 92% (95% confidence interval [CI] = 90%-94%) versus 94% (95% CI = 92%-96%). There was no significant difference between SCORE-AI and the experts for any metric or category. SCORE-AI performed well independently of the vigilance state (false classification during awake: 5/41 [12.2%], false classification during sleep: 2/11 [18.2%]; p = .63) and normal variants (false classification in presence of normal variants: 4/14 [28.6%], false classification in absence of normal variants: 3/38 [7.9%]; p = .07). SCORE-AI achieved diagnostic performance equal to human experts in an EEG dataset independent of the development dataset, in a geographically distinct patient population, recorded with different equipment and technical settings than the development dataset.

Effect of early postmenopause and premenopause on resting-state electroencephalographic and their correlation with ovarian hormone levels.

This study aimed to compare the effect of the early postmenopausal period on resting-state electroencephalographic spectral power with that of the premenopausal period and to analyze the correlation between electroencephalographic spectral power values and endogenous ovarian hormone levels. This study involved 13 early postmenopausal women and 10 premenopausal women in the early follicular, 10 in the ovulatory phase, and 10 in the early luteal phase who underwent resting-state quantitative electroencephalographic spectral power with eyes closed and endogenous ovarian hormone measurements. The delta, theta, alpha1, alpha2, beta1, and beta2 absolute power were compared between the early postmenopausal and premenopausal groups. Correlations between electroencephalographic spectral power values and 17β estradiol, progesterone, follicle-stimulating hormone (FSH), and luteinizing hormone levels were analyzed in early postmenopausal women. Compared with the premenopausal group, the early postmenopausal group showed significantly higher resting-state theta power in the frontal region, alpha1 and alpha2 power in the frontal and central regions, beta1 power in the frontal, central, parietal, and occipital regions, and beta2 power in the centroparietal region. Beta2 power values were positively correlated with FSH levels. The current findings highlight that early postmenopausal women show greater resting-state alpha and beta power, which suggests cortical excitability of fast frequency bands involved in states of alertness, focus of attention, cognition, and emotion. Additionally, we emphasized the effect of FSH levels on fast cortical activation in early postmenopausal women.

Case study on retail investors: Technological innovation and stock market dynamics

The emergence of sophisticated trading platforms, mobile applications, and algorithmic trading systems has triggered a transformation in how retail investors engage in stock market investment. This case explores the primary determinants influencing retail investors' adoption of technology-driven trading platforms. It looks at elements including accessibility, convenience, and the availability of real-time market data. Further, this case discusses the impact that online investment communities and social media platforms have on the formation of retail investors' investment decisions. The case study additionally addresses algorithmic trading, high-frequency trading, and market manipulation, as well as ethical concerns associated with the application of technology in stock market trading. In addition, the function of regulatory bodies in accommodating the swift progression of technological innovation to safeguard investors' interests and maintain market integrity is scrutinised. The study offers useful information on prospective trends and obstacles in technology-driven stock market trading for retail investors by examining scholarly literature and industry reports. This underscores the importance for investors to maintain a state of alertness to minimise potential hazards linked to their dependence on technological advances while simultaneously leveraging the prospects offered by developments in trading technology.

Clinical symptoms and neuroanatomical substrates of daytime sleepiness in Parkinson’s disease

Clinical and neuroanatomical correlates of daytime sleepiness in Parkinson’s disease (PD) remain inconsistent in the literature. Two studies were conducted here. The first evaluated the interrelation between non-motor and motor symptoms, using a principal component analysis, associated with daytime sleepiness in PD. The second identified the neuroanatomical substrates associated with daytime sleepiness in PD using magnetic resonance imaging (MRI). In the first study, 77 participants with PD completed an extensive clinical, cognitive testing and a polysomnographic recording. In the second study, 29 PD participants also underwent MRI acquisition of T1-weighted images. Vertex-based cortical and subcortical surface analysis, deformation-based morphometry, and voxel-based morphometry were performed to assess the association between daytime sleepiness severity and structural brain changes in participants. In both studies, the severity of daytime sleepiness and the presence of excessive daytime sleepiness (EDS; total score >10) were measured using the Epworth Sleepiness Scale. We found that individuals with EDS had a higher score on a component including higher dosage of dopamine receptor agonists, motor symptoms severity, shorter sleep latency, and greater sleep efficiency. Moreover, increased daytime sleepiness severity was associated with a larger surface area in the right insula, contracted surfaces in the right putamen and right lateral amygdala, and a larger surface in the right posterior amygdala. Hence, daytime sleepiness in PD was associated with dopaminergic receptor agonists dosage, motor impairment, and objective sleep measures. Moreover, neuroanatomical changes in cortical and subcortical regions related to vigilance, motor, and emotional states were associated with more severe daytime sleepiness.

Contrastive fine-grained domain adaptation network for EEG-based vigilance estimation

Vigilance state is crucial for the effective performance of users in brain-computer interface (BCI) systems. Most vigilance estimation methods rely on a large amount of labeled data to train a satisfactory model for the specific subject, which limits the practical application of the methods. This study aimed to build a reliable vigilance estimation method using a small amount of unlabeled calibration data. We conducted a vigilance experiment in the designed BCI-based cursor-control task. Electroencephalogram (EEG) signals of eighteen participants were recorded in two sessions on two different days. And, we proposed a contrastive fine-grained domain adaptation network (CFGDAN) for vigilance estimation. Here, an adaptive graph convolution network (GCN) was built to project the EEG data of different domains into a common space. The fine-grained feature alignment mechanism was designed to weight and align the feature distributions across domains at the EEG channel level, and the contrastive information preservation module was developed to preserve the useful target-specific information during the feature alignment. The experimental results show that the proposed CFGDAN outperforms the compared methods in our BCI vigilance dataset and SEED-VIG dataset. Moreover, the visualization results demonstrate the efficacy of the designed feature alignment mechanisms. These results indicate the effectiveness of our method for vigilance estimation. Our study is helpful for reducing calibration efforts and promoting the practical application potential of vigilance estimation methods.

Blink-induced changes in pupil dynamics are consistent and heritable.

Pupil size and blink rates are heritable but the extent to which they interact with one another has not been properly investigated. Though changes in pupil size due to eye blinks have been reported, they are considered a pupillary artifact. In this study we used the HCP 7T fMRI dataset with resting state eye-tracking data obtained in monozygous and dizygous twins to assess their heritability and their interactions. For this purpose, we characterized the pupil dilation (positive peak) and constriction (negative peak) that followed blink events, which we describe as blink-induced pupillary response (BIPR). We show that the BIPR is highly consistent with a positive dilatory peak (D-peak) around 500ms and a negative constricting peak (C-peak) around 1s. These patterns were reproducible within- and between- subjects across two time points and differed by vigilance state (vigilant versus drowsy). By comparing BIPR between monozygous and dizygous twins we show that BIPR have a heritable component with significant additive genetic (A) and environmental (E) factors dominating the structural equation models, particularly in the time-domain for both D- and C-peaks and amplitude domain for the C-peak. (a2 between 42-49%). Blink duration, pupil size and blink rate were also found to be highly heritable (a2 up to 62% for pupil size). Our study documents an association between BIPR and wakefulness and indicates that BIPR should not be treated as a coincidental artefact, but part of a larger oculomotor system that we label here as Oculomotor Adaptive System, OAS, that is genetically determined.

Classifier Combination Supported by the Sleep-Wake Cycle Improves EEG Seizure Prediction Performance.

Seizure prediction is a promising solution to improve the quality of life for drug-resistant patients, which concerns nearly 30% of patients with epilepsy. The present study aimed to ascertain the impact of incorporating sleep-wake information in seizure prediction. We developed five patient-specific prediction approaches that use vigilance state information differently: i) using it as an input feature, ii) building a pool of two classifiers, each with different weights to sleep/wake training samples, iii) building a pool of two classifiers, each with only sleep/wake samples, iv) changing the alarm-threshold concerning each sleep/wake state, and v) adjusting the alarm-threshold after a sleep-wake transition. We compared these approaches with a control method that did not integrate sleep-wake information. Our models were tested with data (43 seizures and 482 hours) acquired during presurgical monitoring of 17 patients from the EPILEPSIAE database. As EPILEPSIAE does not contain vigilance state annotations, we developed a sleep-wake classifier using 33 patients diagnosed with nocturnal frontal lobe epilepsy from the CAP Sleep database. Although different patients may require different strategies, our best approach, the pool of weighted predictors, obtained 65% of patients performing above chance level with a surrogate analysis (against 41% in the control method). The inclusion of vigilance state information improves seizure prediction. Higher results and testing with long-term recordings from daily-life conditions are necessary to ensure clinical acceptance. As automated sleep-wake detection is possible, it would be feasible to incorporate these algorithms into future devices for seizure prediction.