Conscious but not thinking-Mind-blanks during visuomotor tracking: An fMRI study of endogenous attention lapses.

Attention lapses (ALs) are complete lapses of responsiveness in which performance is briefly but completely disrupted and during which, as opposed to microsleeps, the eyes remain open. Although the phenomenon of ALs has been investigated by behavioural and physiological means, the underlying cause of an AL has largely remained elusive. This study aimed to investigate the underlying physiological substrates of behaviourally identified endogenous ALs during a continuous visuomotor task, primarily to answer the question: Were the ALs during this task due to extreme mind-wandering or mind-blanks? The data from two studies were combined, resulting in data from 40 healthy non-sleep-deprived subjects (20M/20F; mean age 27.1 years, 20-45). Only 17 of the 40 subjects were used in the analysis due to a need for a minimum of two ALs per subject. Subjects performed a random 2-D continuous visuomotor tracking task for 50 and 20 min in Studies 1 and 2, respectively. Tracking performance, eye-video, and functional magnetic resonance imaging (fMRI) were recorded simultaneously. A human expert visually inspected the tracking performance and eye-video recordings to identify and categorise lapses of responsiveness as microsleeps or ALs. Changes in neural activity during 85 ALs (17 subjects) relative to responsive tracking were estimated by whole-brain voxel-wise fMRI and by haemodynamic response (HR) analysis in regions of interest (ROIs) from seven key networks to reveal the neural signature of ALs. Changes in functional connectivity (FC) within and between the key ROIs were also estimated. Networks explored were the default mode network, dorsal attention network, frontoparietal network, sensorimotor network, salience network, visual network, and working memory network. Voxel-wise analysis revealed a significant increase in blood-oxygen-level-dependent activity in the overlapping dorsal anterior cingulate cortex and supplementary motor area region but no significant decreases in activity; the increased activity is considered to represent a recovery-of-responsiveness process following an AL. This increased activity was also seen in the HR of the corresponding ROI. Importantly, HR analysis revealed no trend of increased activity in the posterior cingulate of the default mode network, which has been repeatedly demonstrated to be a strong biomarker of mind-wandering. FC analysis showed decoupling of external attention, which supports the involuntary nature of ALs, in addition to the neural recovery processes. Other findings were a decrease in HR in the frontoparietal network before the onset of ALs, and a decrease in FC between default mode network and working memory network. These findings converge to our conclusion that the ALs observed during our task were involuntary mind-blanks. This is further supported behaviourally by the short duration of the ALs (mean 1.7 s), which is considered too brief to be instances of extreme mind-wandering. This is the first study to demonstrate that at least the majority of complete losses of responsiveness on a continuous visuomotor task are, if not due to microsleeps, due to involuntary mind-blanks.

Cerebral perfusion is not impaired in persons with moderate obstructive sleep apnoea when awake.

PURPOSE: It is well established that, together with a multitude of other adverse effects on health, severe obstructive sleep apnoea causes reduced cerebral perfusion and, in turn, reduced cerebral function. Less clear is the impact of moderate obstructive sleep apnoea (OSA). Our aim was to determine if cerebral blood flow is impaired in people diagnosed with moderate OSA. METHODS: Twenty-four patients diagnosed with moderate OSA (15 ≤ apnoea-hypopnea index (AHI) < 30) were recruited (aged 32-72, median 59 years, 10 female). Seven controls (aged 42-73 years, median 62 years, 4 female) with an AHI < 5 were also recruited. The OSA status of all participants was confirmed at baseline by unattended polysomnography and they had an MRI arterial-spin-labelling scan of cerebral perfusion. RESULTS: Neither global perfusion nor voxel-wise perfusion differed significantly between the moderate-OSA and control groups. We also compared the average perfusion across three regional clusters, which had been found in a previous study to have significant perfusion differences with moderate-severe OSA versus control, and found no significant difference in perfusion between the two groups. The perfusions were also very close, with means of 50.2 and 51.8 mL/100 g/min for the moderate-OSAs and controls, respectively, with a negligible effect size (Cohen's d = 0.10). CONCLUSION: We conclude that cerebral perfusion is not impaired in people with moderate OSA and that cerebral flow regulatory mechanisms can cope with the adverse effects which occur in moderate OSA. This is an important factor in clinical decisions for prescription of continuous positive airway pressure therapy (CPAP).

Long-term effects of volanesorsen on triglycerides and pancreatitis in patients with familial chylomicronaemia syndrome (FCS) in the UK Early Access to Medicines Scheme (EAMS).

BACKGROUND AND AIMS: The VOL4002 study assessed the efficacy and safety of volanesorsen in 22 adults with genetically confirmed familial chylomicronaemia syndrome (FCS) treated in the UK Early Access to Medicines Scheme (EAMS), with ("prior exposure") or without ("treatment naive") previous treatment in the APPROACH and/or APPROACH-OLE volanesorsen phase 3 studies. METHODS: Data collection focused on triglyceride (TG) levels, platelet counts and pancreatitis events. Pancreatitis incidence during volanesorsen treatment was compared against the 5-year period preceding volanesorsen exposure. Volanesorsen 285 mg was self-administered subcutaneously once every 2 weeks. RESULTS: Individual patient volanesorsen exposure ranged from 6 to 51 months (total cumulative exposure, 589 months). Among treatment-naive patients (n = 12), volanesorsen treatment resulted in an averaged median 52% reduction (-10.6 mmol/L) from baseline (26.4 mmol/L) in TG levels at 3 months, which were maintained through time points over 15 months of treatment (47%-55% reductions). Similarly, prior-exposure patients (n = 10) experienced a 51% reduction (-17.8 mmol/L) from pre-treatment baseline (28.0 mmol/L), with reductions of 10%-38% over 21 months of treatment. A comparison of pancreatitis event rates found a 74% reduction from the 5-year period before (one event/2.8 years) and during (one event/11.0 years) volanesorsen treatment. Platelet declines were consistent with observations in phase 3 clinical trials. No patient recorded a platelet count <50 × 109/L. CONCLUSIONS: This longitudinal study supports the efficacy of volanesorsen in patients with FCS for lowering TG levels over treatment periods up to 51 months with no apparent safety signals related to increased duration of exposure.

Increased cerebral activity during microsleeps reflects an unconscious drive to re-establish consciousness.

BACKGROUND: Microsleeps are brief instances of sleep, causing complete lapses in responsiveness and partial or total extended closure of both eyes. Microsleeps can have devastating consequences, particularly in the transportation sector. STUDY OBJECTIVES: Questions remain regarding the neural signature and underlying mechanisms of microsleeps. This study aimed to gain a better understanding of the physiological substrates of microsleeps, which might lead to a better understanding of the phenomenon. METHODS: Data from an earlier study, involving 20 healthy non-sleep-deprived subjects, were analysed. Each session lasted 50 min and required subjects to perform a 2-D continuous visuomotor tracking task. Simultaneous data collection included tracking performance, eye-video, EEG, and fMRI. A human expert visually inspected each participant's tracking performance and eye-video recordings to identify microsleeps. Our interest was in microsleeps of ≥4-s duration, leaving us with a total of 226 events from 10 subjects. The microsleep events were divided into four 2-s segments (pre, start, end, and post) (with a gap in the middle, between start and end segments, for microsleeps >4 s), then each segment was analysed relative to its prior segment by examining changes in source-reconstructed EEG power in the delta, theta, alpha, beta, and gamma bands. RESULTS: EEG power increased in the theta and alpha bands between the pre and start of microsleeps. There was also increased power in the delta, beta, and gamma bands between the start and end of microsleeps. Conversely, there was a reduction in power between the end and post of microsleeps in the delta and alpha bands. These findings support previous findings in the delta, theta, and alpha bands. However, increased power in the beta and gamma bands has not been previously reported. CONCLUSIONS: We contend that increased high-frequency activity during microsleeps reflects unconscious 'cognitive' activity aimed at re-establishing consciousness following falling asleep during an active task.

Preliminary evidence supporting a new enzymatic debridement product for use in chronic wounds.

A new recombinant proteolytic enzyme, isolated from maggot saliva, with fibrinolytic action has been investigated through a series of non-clinical toxicology and in-vitro/in-vivo pharmacology studies to explore its potential safety and efficacy as an enzymatic debridement agent for use in chronic wounds. Studies indicate that the enzyme has a good safety profile. When locally administered, it is not detrimental to wound healing, is non-sensitising and is rapidly inactivated in the systemic circulation. Adverse effects are limited, at very high concentrations, to transient erythema at the site of application. In-vitro testing indicates that the enzyme, whilst selective for fibrin, has additional proteolytic action against collagen and elastin, with enzymatic action for all three substrates being dose dependent. In-vivo, we used an established MRSA biofilm model, in which microbiological counts were used as a surrogate for debridement efficacy. Here, we showed that higher concentrations of the enzyme in a formulated proprietary gel, significantly reduced MRSA counts over a period of 2 to 14 days, and significantly improved the vascularity of the wound at 14 days. Together, these data support the potential for this maggot-derived proteolytic enzyme as a clinically effective debriding agent.

Detection of concealed knowledge via the ERP-based technique Brain Fingerprinting: Real-life and real-crime incidents.

Brain Fingerprinting (BFP) is an electroencephalogram-based system used to detect knowledge, or absence of knowledge of a real-life incident (e.g., a crime) in a person's memory. With the help of BFP, a potential crime suspect can be classified as possessing crime-related information (Information-Present), not possessing crime-related information (Information-Absent), or Indeterminate (BFP unable to classify a subject). In the lab setting, we compare the ground-truth of a subject (i.e., real-life involvement in an incident) against their classification based on BFP testing. We report two studies: replication of BFP with university students (Study 1) and replication of BFP with parolees (Study 2). In Study 1, we tested 31 subjects (24 females, seven males, mean age = 21.3) on either their own or another subject's real-life incident. BFP correctly classified nine Information-Present and 18 Information-Absent subjects, but with one false positive and three exclusions. In Study 2, we tested 17 male parolees (mean age = 47.5) on their own or another parolee's crime incident. BFP correctly classified two Information-Present and six Information-Absent subjects. However, there was also one false positive classification and three Indeterminates. Additionally, we identified three subjects who could not complete the BFP testing and two exclusions. We posit that BFP is not yet at a stage to be considered a robust and accurate crime-detection tool as claimed in former articles. Nevertheless, after addressing the limitations, BFP has considerable potential as an information detection tool in forensic investigations, especially for detecting idiosyncratic crime-relevant knowledge in a perpetrator, in addition to helping to confirm the accuracy of a suspect's claim of innocence.

Effects of cerebellar transcranial direct current stimulation (tDCS) on motor skill learning in swallowing.

OBJECTIVE: This study evaluated the effects of cerebellar tDCS on motor learning for swallowing. METHODS: In a double-blind RCT, 39 healthy adults received either sham, anodal tDCS, or cathodal tDCS in two sessions on two consecutive days. Following 20 min cerebellar tDCS (2 mA) or sham, they underwent swallowing skill training that targeted control of timing and magnitude of submental muscle activation during swallowing. Linear mixed models were used to identify the effects of stimulation on timing and magnitude accuracy as measured by the change in task performance for each training session, and for skill retention on days 3 and 10 post-intervention. RESULTS: Only the sham group had a reduced temporal error from baseline to all following timepoints. When compared to error changes in the sham group, changes from baseline in temporal errors were higher at all timepoints post-intervention for the anodal group, and higher at both retention assessments for the cathodal group. Amplitude errors were smaller for all conditions at all timepoints post-intervention compared to baseline. CONCLUSIONS: Cerebellar tDCS was found to inhibit temporal aspects of motor skill learning in swallowing. For the tDCS parameters used in this study, there is no support for use of tDCS to facilitate swallowing rehabilitation. Trial Registry Number (https://www.anzctr.org.au/): ACTRN12615000451505.IMPLICATIONS FOR REHABILITATIONCerebellar tDCS, in combination with motor skill training, has been demonstrated to increase motor skill learning in healthy individuals and neurologically impaired patients.In this study, cerebellar tDCS applied prior to swallowing skill training adversely affected timing measures of submental muscle activation during swallowing.In contrast to published outcomes in the corticospinal literature, both anodal and cathodal tDCS resulted in a relative inhibitory effect on motor skill learning in swallowing when compared to the sham condition.Swallowing skill training without tDCS produced increased accuracy in outcomes.

Effect of Volitional Effort on Submental Surface Electromyographic Activity During Healthy Swallowing.

The effortful swallowing technique aims to compensate for or rehabilitate impaired swallowing by using maximal volitional effort to behaviorally modify aspects of swallowing physiology. Given that swallowing is a submaximal task, swallowing at submaximal levels has recently been suggested as a more task-specific therapeutic technique. The aim of this study was to investigate differences in muscle activity during minimum, regular, and maximum effort swallowing of different boluses and across different ages, with the goal of characterizing the task specificity of minimum effort and maximum effort swallowing. Forty-three healthy adults (22 female) representing four age groups (20-39, 40-59, 60-79, and 80 + years) participated in the study. They were verbally cued to swallow saliva and 5 mL water boluses using participant-determined minimum, regular, and maximum levels of effort, in randomized order. sEMG peak amplitude and duration of each swallow were measured. Linear mixed effects analyses demonstrated that compared to regular effort swallowing, maximum effort swallowing resulted in increased sEMG amplitude (p < .001) and prolonged duration (p < .001), while minimum effort swallowing resulted in decreased amplitude (p < .001) but no significant difference in duration (p = .06). These effects occurred regardless of age or bolus type. Differences in sEMG activity were smaller between regular and minimum effort swallowing than regular and maximum effort swallowing. Both increasing and decreasing volitional efforts during swallowing translate to significant modulation of muscle activity. However, regular swallowing is more similar to minimal effort swallowing. Results reinforce the concept of swallowing as a submaximal task, and provide insight into the development of sEMG biofeedback techniques for rehabilitation.

Investigating the neural signature of microsleeps using EEG.

A microsleep (MS) is a complete lapse of responsiveness due to an episode of brief sleep (≲ 15 s) with eyes partially or completely closed. MSs are highly correlated with the risk of car accidents, severe injuries, and death. To investigate EEG changes during MSs, we used a 2D continuous visuomotor tracking (CVT) task and eye-video to identify MSs in 20 subjects performing the 50-min task. Following pre-processing, FFT spectral analysis was used to calculate the activity in the EEG delta, theta, alpha, beta, and gamma bands, followed by eLORETA for source reconstruction. A group statistical analysis was performed to compare the change in activity over EEG bands of an MS to its baseline. After correction for multiple comparisons, we found maximum increases in delta, theta, and alpha activities over the frontal lobe, and beta over the parietal and occipital lobes. There were no significant changes in the gamma band, and no significant decreases in any band. Our results are in agreement with previous studies which reported increased alpha activity in MSs. However, this is the first study to have reported increased beta activity during MSs, which, due to the usual association of beta activity with wakefulness, was unexpected.

Classification of alcoholic EEG signals using wavelet scattering transform-based features.

Following the research question and the relevant dataset, feature extraction is the most important component of machine learning and data science pipelines. The wavelet scattering transform (WST) is a recently developed knowledge-based feature extraction technique and is structurally like a convolutional neural network (CNN). It preserves information in high-frequency, is insensitive to signal deformations, and generates low variance features of real-valued signals generally required in classification tasks. With data from a publicly-available UCI database, we investigated the ability of WST-based features extracted from multichannel electroencephalogram (EEG) signals to discriminate 1.0-s EEG records of 20 male subjects with alcoholism and 20 male healthy subjects. Using record-wise 10-fold cross-validation, we found that WST-based features, inputted to a support vector machine (SVM) classifier, were able to correctly classify all alcoholic and normal EEG records. Similar performances were achieved with 1D CNN. In contrast, the highest independent-subject-wise mean 10-fold cross-validation performance was achieved with WST-based features fed to a linear discriminant (LDA) classifier. The results achieved with two 10-fold cross-validation approaches suggest that the WST together with a conventional classifier is an alternative to CNN for classification of alcoholic and normal EEGs. WST-based features from occipital and parietal regions were the most informative at discriminating between alcoholic and normal EEG records.

RoWDI: rolling window detection of sleep intrusions in the awake brain using fMRI.

Objective.Brief episodes of sleep can intrude into the awake human brain due to lack of sleep or fatigue-compromising the safety of critical daily tasks (i.e. driving). These intrusions can also introduce artefactual activity within functional magnetic resonance imaging (fMRI) experiments, prompting the need for an objective and effective method of removing them.Approach.We have developed a method to track sleep-like events in awake humans via rolling window detection of intrusions (RoWDI) of fMRI signal template. These events can then be used in voxel-wise event-related analysis of fMRI data. To test this approach, we generated a template of fMRI activity associated with transition to sleep via simultaneous fMRI and electroencephalogram (EEG) (N= 10). RoWDI was then used to identify sleep-like events in 20 individuals performing a cognitive task during fMRI after a night of partial sleep deprivation. This approach was further validated in an independent fMRI dataset (N= 56).Main results.Our method (RoWDI) was able to infer frequent sleep-like events during the cognitive task performed after sleep deprivation. The sleep-like events were associated with on average of 20% reduction in pupil size and prolonged response time. The blood-oxygen-level-dependent activity during the sleep-like events covered thalami-cortical regions, which although spatially distinct, co-existed with, task-related activity. These key findings were validated in the independent dataset.Significance.RoWDI can reliably detect spontaneous sleep-like events in the human brain. Thus, it may also be used as a tool to delineate and account for neural activity associated with wake-sleep transitions in both resting-state and task-related fMRI studies.

Detection of microsleep states from the EEG: a comparison of feature reduction methods.

Microsleeps are brief lapses in consciousness with complete suspension of performance. They are the cause of fatal accidents in many transport sectors requiring sustained attention, especially driving. A microsleep-warning device, using wireless EEG electrodes, could be used to rouse a user from an imminent microsleep. High-dimensional datasets, especially in EEG-based classification, present challenges as there are often a large number of potentially useful features for detecting the phenomenon of interest. Thus, it is often important to reduce the dimension of the original data prior to training the classifier. In this study, linear dimensionality reduction methods-principal component analysis (PCA) and probabilistic PCA (PPCA)-were compared with eight non-linear dimensionality reduction methods (kernel PCA, classical multi-dimensional scaling, isometric mapping, nearest neighbour estimation, stochastic neighbourhood embedding, autoencoder, stochastic proximity embedding, and Laplacian eigenmaps) on previously collected behavioural and EEG data from eight healthy non-sleep-deprived volunteers performing a 1D-visuomotor tracking task for 1 h. The effectiveness of the feature reduction algorithms was evaluated by visual inspection of class separation on 3D scatterplots, by trustworthiness scores, and by microsleep detection performance on a stacked-generalisation-based linear discriminant analysis (LDA) system estimating the microsleep/responsive state at 1 Hz based on the reduced features. On trustworthiness, PPCA outperformed PCA, but PCA outperformed all of the non-linear techniques. The trustworthiness score for each feature reduction method also correlated strongly with microsleep-state detection performance, providing strong validation of the ability of trustworthiness to estimate the relative effectiveness of feature reduction approaches, in terms of predicting performance, and ability to do so independently of the gold standard. Graphical abstract Proposed microsleep detection system.

Classification of Stroke Patients With Dysphagia Into Subgroups Based on Patterns of Submental Muscle Strength and Skill Impairment.

OBJECTIVES: To identify and characterize subgroups of stroke patients with clinical signs of dysphagia, based on swallowing-related strength and skill impairments of the submental muscle group. DESIGN: Prospective observational study. SETTING: Inpatient rehabilitation centers and community dwellings. PARTICIPANTS: Individuals (N=114), including stroke patients with dysphagia (n=55) and 2 control groups including myopathic patients with dysphagia (n=19) and healthy volunteers (n=40) were included in this study. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Novel clinical assessment of strength (force generation) and skill (spatial and temporal precision of muscle activation) of the submental muscle group during swallowing and nonswallowing behaviors, using surface electromyography and dynamometry. RESULTS: Hierarchical cluster analysis revealed 4 clusters, which could be broadly characterized as cluster 1: intact strength and skill, cluster 2: poor strength and poor nonswallowing skill, cluster 3: poor strength, and cluster 4: poor strength and poor swallowing skill. Membership in cluster was significantly associated with medical diagnosis (P<.001). The majority of healthy and myopathic participants were assigned to clusters 1 and 3, respectively, whereas stroke patients were found in all 4 clusters. Skill outcome measures were more predictive of cluster assignment than strength measures. CONCLUSIONS: Although healthy and myopathic participants demonstrated predominantly homogeneous swallowing patterns of submental muscle function within their etiology, several subgroups were identified within stroke, possibly reflecting different subtypes of swallowing function. Future research should focus on the nature and rehabilitation needs of these subtypes. Assessment of skill in swallowing may be an important but overlooked aspect of rehabilitation.

Reservoir computing approaches to microsleep detection.

Objective.The detection of microsleeps in a wide range of professionals working in high-risk occupations is very important to workplace safety. A microsleep classifier is presented that employs a reservoir computing (RC) methodology. Specifically, echo state networks (ESN) are used to enhance previous benchmark performances on microsleep detection.Approach.A clustered design using a novel ESN-based leaky integrator is presented. The effectiveness of this design lies with the simplicity of using a fine-grained architecture, containing up to 8 neurons per cluster, to capture individualized state dynamics and achieve optimal performance. This is the first study to have implemented and evaluated EEG-based microsleep detection using RC models for the detection of microsleeps from the EEG.Main results.Microsleep state detection was achieved using a cascaded ESN classifier with leaky-integrator neurons employing 60 principal components from 544 power spectral features. This resulted in a leave-one-subject-out average detection in performance ofφ = 0.51 ± 0.07 (mean ± SE), AUC- ROC = 0.88 ± 0.03, and AUC- PR = 0.44 ± 0.09.Significance.Although performance of EEG-based microsleep detection systems is still considered modest, this refined method achieved a new benchmark in microsleep detection.

Neural Correlates of Attention Lapses During Continuous Tasks.

Attention lapses (ALs) are common phenomenon, which can affect our performance and productivity by slowing or suspending responsiveness. Occurrence of ALs during continuous monitoring tasks, such as driving or operating machinery, can lead to injuries and fatalities. However, we have limited understanding of what happens in the brain when ALs intrude during such continuous tasks. Here, we analyzed fMRI data from a study, in which participants performed a continuous visuomotor tracking task during fMRI scanning. A total of 68 ALs were identified from 20 individuals, using visual rating of tracking performance and video-based eye-closure. ALs were found to be associated with increased BOLD fMRI activity partially in the executive control network, and sensorimotor network. Surprisingly, we found no evidence of deactivations.

Estimates of functional cerebral hemispheric differences in monolingual and bilingual people who stutter: dichotic listening paradigm.

Recent studies indicate functional cerebral hemispheric processing differences between monolinguals and bilinguals who stutter, as well as monolinguals and bilinguals who do not stutter. Eighty native German speakers, half of whom were also proficient speakers of English as a second language (L2), were assessed on a dichotic listening paradigm using CV syllables as stimuli. The participants were organised into four different groups according to speech status and language ability: 20 monolinguals who stutter, 20 bilinguals who stutter, 20 monolinguals who do not stutter, and 20 bilinguals who do not stutter. A right ear advantage (REA) was observed across all groups with no significant group differences in regard to hemispheric asymmetry. Although MWS (18 dB) and BWS (16 dB) crossed over to an LEA at an earlier point compared to the MWNS (5 dB) and BWNS (2 dB), the difference between groups was minor and not significant. Thus, a significant difference in REA resistance, as proposed by other researchers, was not reflected in the current study neither for people who stutter nor for bilinguals. In addition, no meaningful relationship was found between dichotic listening and stuttering severity, as well as the four language modalities (listening, speaking, reading, writing). Thus, we contend that neither stuttering nor bilingualism has any non-trivial effect on functional cerebral hemispheric differences in language processing in dichotic listening.

Pharyngeal Swallowing During Wake and Sleep.

Sleep is associated with stages of relative cortical quiescence, enabling evaluation of swallowing under periods of reduced consciousness and, hence, absent volition. The aim of this study was to measure and characterize changes in the characteristics of pharyngeal swallows during sleep and wake using high-resolution manometry (HRM). Pharyngeal swallows were recorded with a ManoScan™ HRM in wake-upright, wake-supine, and sleep conditions in 20 healthy participants (mean 27 years; range 21-52). Velopharyngeal and hypopharyngeal segments were analysed separately. Contractile integral, mean peak pressure, inverse velocity of superior-to-inferior pharyngeal pressure, and time to first maximum pressure were analysed with custom-designed software. The supine-wake condition was compared to both upright-wake and sleep conditions using linear mixed effects models. No significant differences were found between supine-wake and upright-wake conditions on any measures. The mean peak pharyngeal pressure was lower during sleep than during the supine-wake condition for both the velopharynx (- 60 mmHg, standard error [SE] = 11, p < 0.001) and hypopharynx (- 59 mmHg, SE = 9, p = 0.001), as was the pharyngeal inverse velocity (- 12 ms/cm, SE = 4, p = 0.012) for the hypopharyngeal segment and the pharyngeal contractile integral (- 32 mmHg s cm, SE = 6, p < 0.001). No significant differences were found in time to the first pharyngeal maximum pressure. This study used HRM to characterize and compare pharyngeal pressures during swallowing in both wake and sleep conditions. No differences were found between upright and supine awake conditions, a finding important to pharyngeal manometric measures made during supine positioning, such as in fMRI. Higher pressures and longer time-related measures of volitional pharyngeal swallowing when awake indicate that cortical input plays an important role in modulation of pharyngeal swallowing.

Detection and Prediction of Microsleeps from EEG using Spatio-Temporal Patterns.

A microsleep is a brief lapse in performance due to an involuntary sleep-related loss of consciousness. These episodes are of particular importance in occupations requiring extended unimpaired visuomotor performance, such as driving. Detection and even prediction of microsleeps has the potential to prevent catastrophic events and fatal accidents. In this study, we examined detection and prediction of microsleeps using EEG data of 8 subjects who performed two 1-h sessions of continuous 1-D tracking. A regularized spatio-temporal filtering and classification (RSTFC) method was used to extract features from 5-s EEG segments. These features were then used to train three different linear classifiers: linear discriminant analysis (LDA), sparse Bayesian learning (SBL), and variational Bayesian logistic regression (VBLR). The performance of microsleep state detection and prediction was evaluated using leave-one-subject-out cross-validation. The detection performance measures were AUCROC 0.96, AUCPR 0.52, and phi 0.47. As expected, prediction of microsleep states with a 0.25-s ahead prediction time resulted in slightly lower performances compared to the detection. Prediction performance measures were substantially higher than those achieved with log-power spectral features, i.e., AUCROC 0.95 (cf. 0.90), AUCPR 0.50 (cf. 0.36), and phi 0.46 (cf. 0.34).

Characteristic changes in the EEG signals between microsleeps and preceding responsive states.

This work aims at identifying characteristic features of EEG to demarcate a microsleep from preceding responsive states. The EEG signals, after reference electrode standardization technique (REST) re-referencing, were processed through a time-varying general linear Kalman filter (TVGLKF) to derive time-varying auto-regressive (TVAR) parameters. The time-varying effective connectivity measure of orthogonal partial directed coherence (OPDC) was obtained for every instant at 256 Hz. Effective connectivity matrices formed using these OPDC measures, with the scalp electrodes as nodes were processed further using graph theory. Community-based measures were investigated and statistical significances compared. Non-parametric Wilcoxon signed rank test was used for significance analysis, with Cohen-type and Common Language effect size (CLES) as measures of effect sizes. The results showed a decrease in directional modularity from anterior to posterior, in theta, alpha, and beta bands in microsleeps. The alpha band showed the highest significance with a Cohen-type effect size of 1.25 and a median percentage difference of 23% across subjects, with a range of 13-28%. Flexibility and integration also decreased with average percentage of 25% (17-35%) and 20% (16-32%), respectively, while recruitment increased on an average of 11% (3-16%), wherever significant across all bands. These community-based measures can help characterize and explain changes in brain mechanisms, and can also serve as potential biomarkers for microsleep detection.