Electroencephalography-based classification of Alzheimer's disease spectrum during computer-based cognitive testing.

Alzheimer's disease (AD) is a progressive disease leading to cognitive decline, and to prevent it, researchers seek to diagnose mild cognitive impairment (MCI) early. Particularly, non-amnestic MCI (naMCI) is often mistaken for normal aging as the representative symptom of AD, memory decline, is absent. Subjective cognitive decline (SCD), an intermediate step between normal aging and MCI, is crucial for prediction or early detection of MCI, which determines the presence of AD spectrum pathology. We developed a computer-based cognitive task to classify the presence or absence of AD pathology and stage within the AD spectrum, and attempted to perform multi-stage classification through electroencephalography (EEG) during resting and memory encoding state. The resting and memory-encoding states of 58 patients (20 with SCD, 10 with naMCI, 18 with aMCI, and 10 with AD) were measured and classified into four groups. We extracted features that could reflect the phase, spectral, and temporal characteristics of the resting and memory-encoding states. For the classification, we compared nine machine learning models and three deep learning models using Leave-one-subject-out strategy. Significant correlations were found between the existing neurophysiological test scores and performance of our computer-based cognitive task for all cognitive domains. In all models used, the memory-encoding states realized a higher classification performance than resting states. The best model for the 4-class classification was cKNN. The highest accuracy using resting state data was 67.24%, while it was 93.10% using memory encoding state data. This study involving participants with SCD, naMCI, aMCI, and AD focused on early Alzheimer's diagnosis. The research used EEG data during resting and memory encoding states to classify these groups, demonstrating the significance of cognitive process-related brain waves for diagnosis. The computer-based cognitive task introduced in the study offers a time-efficient alternative to traditional neuropsychological tests, showing a strong correlation with their results and serving as a valuable tool to assess cognitive impairment with reduced bias.

Reliability Analysis of PAUT Based on the Round-Robin Test for Pipe Welds with Thermal Fatigue Cracks.

Thermal fatigue cracks occurring in pipes in nuclear power plants pose a high degree of risk. Thermal fatigue cracks are generated when the thermal fatigue load caused by local temperature gradients is repeatedly applied. The flaws are mainly found in welds, owing to the effects of stress concentration caused by the material properties and geometric shapes of welds. Thermal fatigue pipes are classified as targets of risk-informed in-service inspection, for which ultrasonic testing, a volumetric non-destructive testing method, is applied. With the advancement of ultrasonic testing techniques, various studies have been conducted recently to apply the phased array ultrasonic testing (PAUT) method to the inspection of thermal fatigue cracks occurring on pipes. A quantitative reliability analysis of the PAUT method must be performed to apply the PAUT method to on-site thermal fatigue crack inspection. In this study, to evaluate the quantitative reliability of the PAUT method for thermal fatigue cracks, we fabricated crack specimens with the thermal fatigue mechanism applied to the pipe welds. We performed a round-robin test to collect PAUT data and determine the validity of the detection performance (probability of detection; POD) and the error in the sizing accuracy (root-mean-square error; RMSE) evaluation. The analysis results of the POD and sizing performance of the length and depth of thermal fatigue cracks were comparatively evaluated with the acceptance criteria of the American Society of Mechanical Engineers Code to confirm the effectiveness of applying the PAUT method.

Effects of altered functional connectivity on motor imagery brain-computer interfaces based on the laterality of paralysis in hemiplegia patients.

Motor imagery (MI)-based brain-computer interfaces are widely employed for improving the rehabilitation of paralyzed people and their quality of life. It has been well documented that brain activity patterns in the primary motor cortex and sensorimotor cortex during MI are similar to those of motor execution/imagery. However, individuals paralyzed owing to various neurological disorders have debilitated activation of the motor control region. Therefore, the differences in brain activation based on the paralysis location should be considered. We analyzed brain activation patterns using the electroencephalogram (EEG) acquired while performing MI on the right upper limb to investigate hemiplegia-related brain activation patterns. Participants with hemiplegia of the right upper limb (n=7) and left upper limb (n=4) performed the MI task within the right upper limb. EEG signals were acquired using 14 channels based on a 10-20 global system, and analyzed for event-related desynchronization (ERD) based on event-related spectral perturbation and functional connectivity, using the weighted phase-lag index of both hemispheres at the location of hemiplegia. Enhanced ERD was found in the ipsilateral region, compared to the contralateral region, after MI of the affected limb. The reduced difference in the centrality of the channels was observed in all subjects, likely reflecting an altered brain network from increased interhemispheric connections. Furthermore, the tendency of distinct network-based features depending on the MI task on the affected limb was diluted between the inter-hemispheres. Analysis of interaction between inter-region using functional connectivity could provide avenues for further investigation of BCI strategy through the brain state of individuals with hemiplegia.

Differences in functional network between focal onset nonconvulsive status epilepticus and toxic metabolic encephalopathy: application to machine learning models for differential diagnosis.

We aimed to compare network properties between focal-onset nonconvulsive status epilepticus (NCSE) and toxic/metabolic encephalopathy (TME) during periods of periodic discharge using graph theoretical analysis, and to evaluate the applicability of graph measures as markers for the differential diagnosis between focal-onset NCSE and TME, using machine learning algorithms. Electroencephalography (EEG) data from 50 focal-onset NCSE and 44 TMEs were analyzed. Epochs with nonictal periodic discharges were selected, and the coherence in each frequency band was analyzed. Graph theoretical analysis was performed to compare brain network properties between the groups. Eight different traditional machine learning methods were implemented to evaluate the utility of graph theoretical measures as input features to discriminate between the two conditions. The average degree (in delta, alpha, beta, and gamma bands), strength (in delta band), global efficiency (in delta and alpha bands), local efficiency (in delta band), clustering coefficient (in delta band), and transitivity (in delta band) were higher in TME than in NCSE. TME showed lower modularity (in delta band) and assortativity (in alpha, beta, and gamma bands) than NCSE. Machine learning algorithms based on EEG global graph measures classified NCSE and TME with high accuracy, and gradient boosting was the most accurate classification model with an area under the receiver operating characteristics curve of 0.904. Our findings on differences in network properties may provide novel insights that graph measures reflecting the network properties could be quantitative markers for the differential diagnosis between focal-onset NCSE and TME.

Enhanced functional connectivity in the reward circuitry in healthy adults with weekend catch-up sleep.

We aimed to identify structural and functional changes in healthy adults with catch-up sleep (CUS), we applied seed-based functional connectivity (FC) analysis using resting-state functional magnetic resonance imaging (MRI). We hypothesized that deficits in reward processing could be a fundamental mechanism underlying the motivation of taking CUS. Then, 55 healthy adults voluntarily (34 with CUS and 21 without CUS) participated in this study. Voxel-based morphometry was performed to explore region of gray matter volume (GMV) difference between CUS and non-CUS groups. Between-group comparison of FC was then carried out using resting-state functional MRI analysis seeding at the region of volume difference. Moreover, the region of volume difference and the strength of FC were correlated with scores of questionnaires for reward-seeking behavior and clinical variables. CUS group had a higher reward-seeking tendency, and increased GMV in the bilateral nucleus accumbens and right superior frontal gyrus relative to non-CUS group. FC analysis seeding at the bilateral accumbens revealed increases of FC in the bilateral medial prefrontal cortex in CUS group compared to non-CUS group. The questionnaire scores reflecting the reward-seeking tendency were correlated with the FC strength between bilateral accumbens and medial prefrontal cortex. Our results indicate that CUS is associated with reward-seeking tendency and increased GMV and FC in regions responsible for reward network. Our findings suggest that enhanced reward network could be the crucial mechanism underlying taking CUS and might be implicated in the detrimental effects of circadian misalignment.

Inherent seizure susceptibility in patients with antihistamine-induced acute symptomatic seizure: a resting-state EEG analysis.

We compared neural activities and network properties between the antihistamine-induced seizures (AIS) and seizure-free groups, with the hypothesis that patients with AIS might have inherently increased neural activities and network properties that are easily synchronized. Resting-state electroencephalography (EEG) data were collected from 27 AIS patients and 30 healthy adults who had never had a seizure. Power spectral density analysis was used to compare neural activities in each localized region. Functional connectivity (FC) was measured using coherence, and graph theoretical analyses were performed to compare network properties between the groups. Machine learning algorithms were applied using measurements found to be different between the groups in the EEG analyses as input features. Compared with the seizure-free group, the AIS group showed a higher spectral power in the entire regions of the delta, theta, and beta bands, as well as in the frontal areas of the alpha band. The AIS group had a higher overall FC strength, as well as a shorter characteristic path length in the theta band and higher global efficiency, local efficiency, and clustering coefficient in the beta band than the seizure-free group. The Support Vector Machine, k-Nearest Neighbor, and Random Forest models distinguished the AIS group from the seizure-free group with a high accuracy of more than 99%. The AIS group had seizure susceptibility considering both regional neural activities and functional network properties. Our findings provide insights into the underlying pathophysiological mechanisms of AIS and may be useful for the differential diagnosis of new-onset seizures in the clinical setting.

Augmented ocular vestibular-evoked myogenic potentials in postural orthostatic tachycardia syndrome.

PURPOSE: To delineate the association between otolith function and changes in mean orthostatic blood pressure (BP) and heart rate (HR) in patients with postural orthostatic tachycardia syndrome (POTS). METHODS: Forty-nine patients with POTS were prospectively recruited. We analyzed the results of ocular vestibular-evoked myogenic potentials (oVEMPs) and cervical vestibular-evoked myogenic potentials (cVEMPs), as well as head-up tilt table tests using a Finometer. The oVEMP and cVEMP responses were obtained using tapping stimuli and 110 dB tone-burst sounds, respectively. We measured maximal changes in 5-s averaged systolic BP (SBP), diastolic BP (DBP), and heart rate (HR) within 15 s and during 10 min after tilting. We compared the results with those of 20 age- and sex-matched healthy participants. RESULTS: The n1-p1 amplitude of oVEMPs was larger in patients with POTS than in healthy participants (p = 0.001), whereas the n1 latency (p = 0.280) and interaural difference (p = 0.199) did not differ between the two. The n1-p1 amplitude was a positive predictor for POTS (odds ratio 1.07, 95% confidence interval 1.01-1.13, p = 0.025). Body weight (p = 0.007) and n1-p1 amplitude of oVEMP (p = 0.019) were positive predictors for ΔSBP15s in POTS, whereas aging was a negative predictor (p = 0.005). These findings were not observed in healthy participants. CONCLUSIONS: Augmented utricular inputs may be associated with a relative predominance of sympathetic over vagal control of BP and HR, especially for an early response during orthostasis in patients with POTS. Overt sympathoexcitation due to exaggerated utricular input and lack of readaptation may be associated with the pathomechanism of POTS.

Differentiating amnestic from non-amnestic mild cognitive impairment subtypes using graph theoretical measures of electroencephalography.

The purpose of this study was to explore different patterns of functional networks between amnestic mild cognitive impairment (aMCI) and non-aMCI (naMCI) using electroencephalography (EEG) graph theoretical analysis. The data of 197 drug-naïve individuals who complained cognitive impairment were reviewed. Resting-state EEG data was acquired. Graph analyses were performed and compared between aMCI and naMCI, as well as between early and late aMCI. Correlation analyses were conducted between the graph measures and neuropsychological test results. Machine learning algorithms were applied to determine whether the EEG graph measures could be used to distinguish aMCI from naMCI. Compared to naMCI, aMCI showed higher modularity in the beta band and lower radius in the gamma band. Modularity was negatively correlated with scores on the semantic fluency test, and the radius in the gamma band was positively correlated with visual memory, phonemic, and semantic fluency tests. The naïve Bayes algorithm classified aMCI and naMCI with 89% accuracy. Late aMCI showed inefficient and segregated network properties compared to early aMCI. Graph measures could differentiate aMCI from naMCI, suggesting that these measures might be considered as predictive markers for progression to Alzheimer's dementia in patients with MCI.

Autonomic Dysfunction in Sleep Disorders: From Neurobiological Basis to Potential Therapeutic Approaches.

Sleep disorder has been portrayed as merely a common dissatisfaction with sleep quality and quantity. However, sleep disorder is actually a medical condition characterized by inconsistent sleep patterns that interfere with emotional dynamics, cognitive functioning, and even physical performance. This is consistent with sleep abnormalities being more common in patients with autonomic dysfunction than in the general population. The autonomic nervous system coordinates various visceral functions ranging from respiration to neuroendocrine secretion in order to maintain homeostasis of the body. Because the cell population and efferent signals involved in autonomic regulation are spatially adjacent to those that regulate the sleep-wake system, sleep architecture and autonomic coordination exert effects on each other, suggesting the presence of a bidirectional relationship in addition to shared pathology. The primary goal of this review is to highlight the bidirectional and shared relationship between sleep and autonomic regulation. It also introduces the effects of autonomic dysfunction on insomnia, breathing disorders, central disorders of hypersomnolence, parasomnias, and movement disorders. This information will assist clinicians in determining how neuromodulation can have the greatest therapeutic effects in patients with sleep disorders.

Clinical Reasoning: A 48-Year-Old Woman Presenting With Vertigo, Ptosis, and Red Eyes.

We describe acute vestibular syndrome in a 48-year-old woman with breast cancer who was finally found to have anti-Ma2-associated encephalitis. Although the initial diagnosis was vestibular neuritis elsewhere, progression of symptoms and additional findings of bilateral ptosis and circumlimbal injections, vertical saccadic slowing, and impaired convergence led to a suspicion of a rostral midbrain lesion and final diagnosis. The patient's symptoms and ocular motor signs improved markedly after administration of IV methylprednisolone and oral tacrolimus. Our patient again stresses the importance of scrutinized ocular motor evaluation for detection of central lesions even in patients with the clinical features of unilateral peripheral vestibulopathy.

Altered Brain Networks in Chronic Obstructive Pulmonary Disease: An Electroencephalography Analysis.

Background. Limited data are available regarding brain networks in patients with chronic obstructive pulmonary disease (COPD). Here, we investigated brain networks in COPD using graph theoretical analysis of electroencephalography data. Methods. Thirty-eight patients with COPD and 38 healthy controls underwent scalp electroencephalography. We calculated graph measures including average degree, characteristic path length, global efficiency, local efficiency, clustering coefficient, and modularity and compared them between patients and controls. Results. Average degree, global efficiency, local efficiency, and clustering coefficients were lower, while characteristic path length and modularity were higher in patients with COPD than in controls in the alpha band (P < .05). Significant differences in node degree and global node efficiency between controls and patients were mainly prominent in the medial parieto-central regions in the alpha band. Local efficiency and node clustering coefficients mainly differed in the occipito-parietal regions in the alpha band. We observed no differences in nodal measures in the delta, theta, beta, and gamma bands and no relationships between pulmonary function test parameters and global measures in any frequency bands. Conclusions. The thalamus generates alpha activity and is responsible for controlling respiratory activities to maintain oxygen delivery to tissues in response to chronic hypoxia. We thus speculate that our findings might be related to exposure to chronic hypoxia, implicated in the pathophysiological mechanisms underlying cognitive deficits in patients with COPD. Graph theoretical analysis of resting-state electroencephalography could be considered as a quantitative framework to understand functional networks in COPD.

Intracranial Densitometry-Augmented Machine Learning Enhances the Prognostic Value of Brain CT in Pediatric Patients With Traumatic Brain Injury: A Retrospective Pilot Study.

Background: The inter- and intrarater variability of conventional computed tomography (CT) classification systems for evaluating the extent of ischemic-edematous insult following traumatic brain injury (TBI) may hinder the robustness of TBI prognostic models. Objective: This study aimed to employ fully automated quantitative densitometric CT parameters and a cutting-edge machine learning algorithm to construct a robust prognostic model for pediatric TBI. Methods: Fifty-eight pediatric patients with TBI who underwent brain CT were retrospectively analyzed. Intracranial densitometric information was derived from the supratentorial region as a distribution representing the proportion of Hounsfield units. Furthermore, a machine learning-based prognostic model based on gradient boosting (i.e., CatBoost) was constructed with leave-one-out cross-validation. At discharge, the outcome was assessed dichotomously with the Glasgow Outcome Scale (favorability: 1-3 vs. 4-5). In-hospital mortality, length of stay (>1 week), and need for surgery were further evaluated as alternative TBI outcome measures. Results: Densitometric parameters indicating reduced brain density due to subtle global ischemic changes were significantly different among the TBI outcome groups, except for need for surgery. The skewed intracranial densitometry of the unfavorable outcome became more distinguishable in the follow-up CT within 48 h. The prognostic model augmented by intracranial densitometric information achieved adequate AUCs for various outcome measures [favorability = 0.83 (95% CI: 0.72-0.94), in-hospital mortality = 0.91 (95% CI: 0.82-1.00), length of stay = 0.83 (95% CI: 0.72-0.94), and need for surgery = 0.71 (95% CI: 0.56-0.86)], and this model showed enhanced performance compared to the conventional CRASH-CT model. Conclusion: Densitometric parameters indicative of global ischemic changes during the acute phase of TBI are predictive of a worse outcome in pediatric patients. The robustness and predictive capacity of conventional TBI prognostic models might be significantly enhanced by incorporating densitometric parameters and machine learning techniques.

Sex differences in seizure effects on social anxiety in persons with epilepsy.

PURPOSE: We investigated sex differences in the effect of seizures on social anxiety in persons with epilepsy. METHOD: In this cross-sectional multicenter study, social anxiety was measured using the short forms of the Social Phobia Scale (SPS-6) and Social Interaction Anxiety Scale (SIAS-6). SPS-6 scores ≥ 9 and SIAS-6 scores ≥ 12 were considered to indicate social phobia and social interaction anxiety, respectively. The Patient Health Questionnaire-9, Stigma Scale-Revised, and Family Adaptation-Partnership-Growth-Affection-Resolve scale were also completed. A logistic regression analysis with an interaction term was used to analyze the data. RESULTS: Out of 285 participants, a SPS-6 score ≥ 9 and a SIAS-6 score ≥ 12 were noted in 62 (21.8%) and 36 (12.6%) of participants, respectively. There was no difference in the prevalence of social anxiety between men and women. Intractable seizures and lack of seizure freedom were associated with a SPS-6 score ≥ 9 and a SIAS-6 score ≥ 12, but statistical significance was lost in the adjusted models. However, intractable seizures and lack of seizure freedom significantly interacted with sex for a SPS-6 score ≥ 9 (p = 0.018) and a SIAS-6 score ≥ 12 (p = 0.048) in both the separate and adjusted models. Specifically, intractable seizures tended to be positively associated with SPS-6 scores ≥ 9 than non-intractable seizures in men only (odds ratio = 2.602, p = 0.068), whereas lack of seizure freedom tended to be negatively associated with SIAS-6 scores ≥ 12 than seizure freedom in women only (odds ratio = 4.804, p = 0.053). CONCLUSION: We found significant sex differences in seizure effects on social anxiety. Intractable seizures were associated with social phobia in men, whereas lack of seizure freedom in the last year was associated with social interaction anxiety in women.

Drinking coffee enhances neurocognitive function by reorganizing brain functional connectivity.

The purpose of this study was to identify the mechanisms underlying effects of coffee on cognition in the context of brain networks. Here we investigated functional connectivity before and after drinking coffee using graph-theoretic analysis of electroencephalography (EEG). Twenty-one healthy adults voluntarily participated in this study. The resting-state EEG data and results of neuropsychological tests were consecutively acquired before and 30 min after coffee consumption. Graph analyses were performed and compared before and after coffee consumption. Correlation analyses were conducted to assess the relationship between changes in graph measures and those in cognitive function tests. Functional connectivity (FC) was reorganized toward more efficient network properties after coffee consumption. Performance in Digit Span tests and Trail Making Test Part B improved after coffee consumption, and the improved performance in executive function was correlated with changes in graph measures, reflecting a shift toward efficient network properties. The beneficial effects of coffee on cognitive function might be attributed to the reorganization of FC toward more efficient network properties. Based on our findings, the patterns of network reorganization could be used as quantitative markers to elucidate the mechanisms underlying the beneficial effects of coffee on cognition, especially executive function.

Regional Gray Matter Volume Changes in Parkinson's Disease with Orthostatic Hypotension.

Neurodegenerative change in the central nervous system has been suggested as one of the pathophysiological mechanisms of autonomic nervous system dysfunction in Parkinson's disease (PD). We analyzed gray matter (GM) volume changes and clinical parameters in patients with PD to investigate any involvement in the brain structures responsible for autonomic control in patients with PD having orthostatic hypotension (OH). Voxel-based morphometry was applied to compare regional GM volumes between PD patients with and without OH. Multivariate logistic regression analysis using a hierarchical model was carried out to identify clinical factors independently contributing to the regional GM volume changes in PD patients with OH. The Sobel test was used to analyze mediation effects between the independent contributing factors to the GM volume changes. PD patients with OH had more severe autonomic dysfunction and reduction in volume in the right inferior temporal cortex than those without OH. The right inferior temporal volume was positively correlated with the Qualitative Scoring MMSE Pentagon Test (QSPT) score, reflecting visuospatial/visuoperceptual function, and negatively correlated with the Composite Autonomic Severity Score (CASS). The CASS and QSPT scores were found to be factors independently contributing to regional volume changes in the right inferior temporal cortex. The QSPT score was identified as a mediator in which regional GM volume predicts the CASS. Our findings suggest that a decrease in the visuospatial/visuoperceptual process may be involved in the presentation of autonomic nervous system dysfunction in PD patients.

Antihistamines as a common cause of new-onset seizures: a single-center observational study.

OBJECTIVE: Scarce data are available regarding the proportion of drugs that have provoked new-onset seizures. The aim of this study was to investigate the types of causative drugs of drug-induced new-onset seizures in a relatively large population of patients who were admitted to our epilepsy monitoring unit. METHODS: Using a hospital-based database, patients with new-onset seizures were selected and the underlying etiology of new-onset seizures was reviewed. Based on the etiologic conditions, acute symptomatic seizure was classified into 7 groups of provocation factors: drug, alcohol, encephalitis, stroke, hypoxic injury, metabolic, and unclassified. Causative drugs for new-onset seizures were further investigated. RESULTS: Altogether, 363 patients with new-onset seizures were reviewed in this study. The most common cause of new-onset seizures was epilepsy, followed by syncope, acute symptomatic seizure, and others. Drugs were found to be the most common provocation factor for acute symptomatic seizures. The most common causative drug was antihistamine, followed by stimulants, antibiotics, and other drugs. Most patients with antihistamine-induced seizures had normal renal function and were under treatment at the therapeutic dose. CONCLUSION: In our population, antihistamine accounted for the highest proportion of drug-induced seizures. Considering that antihistamines are widely used as over-the-counter drugs around the world, they should be considered a possible cause of new-onset seizures.

Regional analysis of cerebral hemodynamic changes during the head-up tilt test in Parkinson's disease patients with orthostatic intolerance.

Significance: Cerebral oxygenation changes in the superior, middle, and medial gyri were used to elucidate spatial impairments of autonomic hemodynamic recovery during the head-up tilt table test (HUTT) in Parkinson's disease (PD) patients with orthostatic intolerance (OI) symptoms. Aim: To analyze dynamic oxygenation changes during the HUTT and classify PD patients with OI symptoms using clinical and oxygenation features. Approach: Thirty-nine PD patients with OI symptoms [10: orthostatic hypotension (PD-OH); 29: normal HUTT results (PD-NOR)] and seven healthy controls (HCs) were recruited. Prefrontal oxyhemoglobin (HbO) changes during the HUTT were reconstructed with diffuse optical tomography and segmented using the automated anatomical labeling system. Decision trees were used for classification. Results: HCs and PD-NOR patients with positive rates of HbO change (PD-POS) showed the greatest HbO recovery in the superior frontal gyrus (SFG) during tilt. PD-OH and PD-NOR patients with negative rates of HbO change (PD-NEG) showed asymmetric reoxygenation. The classification accuracy was 89.4% for PD-POS versus PD-NEG, 71% for PD-NOR versus PD-OH, and 55.8% for PD-POS versus PD-NEG versus PD-OH. The oxygenation features were more discriminative than the clinical features. Conclusions: PD-OH showed decreased right SFG function, which may be associated with impaired compensatory autonomic responses to orthostatic stress.