The lifestyle of new middle-aged and older adults in Taiwan described by wearable device: age and gender differences.

Studies of lifestyle through comprehensive objective and subjective measurements of health outcomes are lacking. An examination of lifestyle factors in middle-aged and older adults in terms of age, gender, and the interaction effect of age and gender from physiological and psychological perspectives are imperative. Recent advances in technology such as actigraphy have facilitated objective measurements. This exploratory study contributes to research on age and gender interactions on circadian rhythm, physical activity, sleep, and psychological variables by employing wrist accelerometers to measure behavioral circadian rhythm objectively and by using questionnaires to assess psychological status subjectively. The data were drawn from 218 participants aged 50 and older from the "Middle-aged and older adults Chinese Health and Actigraphy in Taiwan (MOCHA-T)". The results: (1) older adult group is associated with declined physical activity (MVPA time 79.9 min VS. 107.9 min, p = .002), worse sleep efficiency (78.1% VS. 81.9%, p = .008), and earlier lifestyle (Acrophase 14.19 h VS. 14.69 h, p = .01) comparing to middle-aged group. (2) Women have a more regular lifestyle (Interdaily stability 0.6 VS. 051, p < 0.001), higher physical activity (MVPA time 105.7 min VS. 79.3 min, p = .004), and better sleep efficiency (81.6% VS. 77.8%, p = .011) than men. (3) Significant age-by-gender interactions existed in life satisfaction (p = .025), relative amplitude (p = .016), and total wake time (p = .038). Furthermore, aging was associated with significant increases in life satisfaction among men as well as significant decreases in relative amplitude and reductions in the total wake time among women. In conclusion, aging exerted differential effects on life satisfaction in men as well as relative amplitude and the total wake time in women. This result highlights disparities in lifestyle arising from interconnected social and biological challenges.

Probing the neural dynamics of musicians' and non-musicians' consonant/dissonant perception: Joint analyses of electrical encephalogram (EEG) and functional magnetic resonance imaging (fMRI).

The perception of two (or more) simultaneous musical notes, depending on their pitch interval(s), could be broadly categorized as consonant or dissonant. Previous literature has suggested that musicians and non-musicians adopt different strategies when discerning music intervals: while musicians rely on the frequency ratios between the two fundamental frequencies, such as "perfect fifth" (3:2) as consonant and "tritone" (45:32) as dissonant intervals; non-musicians may rely on the presence of 'roughness' or 'beats', generated by the difference of fundamental frequencies, as the key elements of 'dissonance'. The separate Event-Related Potential (ERP) differences in N1 and P2 along the midline electrodes provided evidence congruent with such 'separate reliances'. To replicate and to extend, in this study we reran the previous experiment, and separately collected fMRI data of the same protocol (with sparse sampling modifications). The behavioral and EEG results largely corresponded to our previous finding. The fMRI results, with the joint analyses by univariate, psycho-physiological interaction, and representational similarity analysis (RSA) approaches, further reinforce the involvement of central midline-related brain regions, such as ventromedial prefrontal and dorsal anterior cingulate cortex, in consonant/dissonance judgments. The final spatiotemporal searchlight RSA provided convincing evidence that the medial prefrontal cortex, along with the bilateral superior temporal cortex, is the joint locus of midline N1 and dorsal anterior cingulate cortex for the P2 effect (for musicians). Together, these analyses reaffirm that musicians rely more on experience-driven knowledge for consonance/dissonance perception; but also demonstrate the advantages of multiple analyses in constraining the findings from both EEG and fMRI.

Collaborative Human-Computer Vision Operative Video Analysis Algorithm for Analyzing Surgical Fluency and Surgical Interruptions in Endonasal Endoscopic Pituitary Surgery: Cohort Study.

BACKGROUND: The endonasal endoscopic approach (EEA) is effective for pituitary adenoma resection. However, manual review of operative videos is time-consuming. The application of a computer vision (CV) algorithm could potentially reduce the time required for operative video review and facilitate the training of surgeons to overcome the learning curve of EEA. OBJECTIVE: This study aimed to evaluate the performance of a CV-based video analysis system, based on OpenCV algorithm, to detect surgical interruptions and analyze surgical fluency in EEA. The accuracy of the CV-based video analysis was investigated, and the time required for operative video review using CV-based analysis was compared to that of manual review. METHODS: The dominant color of each frame in the EEA video was determined using OpenCV. We developed an algorithm to identify events of surgical interruption if the alterations in the dominant color pixels reached certain thresholds. The thresholds were determined by training the current algorithm using EEA videos. The accuracy of the CV analysis was determined by manual review, and the time spent was reported. RESULTS: A total of 46 EEA operative videos were analyzed, with 93.6%, 95.1%, and 93.3% accuracies in the training, test 1, and test 2 data sets, respectively. Compared with manual review, CV-based analysis reduced the time required for operative video review by 86% (manual review: 166.8 and CV analysis: 22.6 minutes; P<.001). The application of a human-computer collaborative strategy increased the overall accuracy to 98.5%, with a 74% reduction in the review time (manual review: 166.8 and human-CV collaboration: 43.4 minutes; P<.001). Analysis of the different surgical phases showed that the sellar phase had the lowest frequency (nasal phase: 14.9, sphenoidal phase: 15.9, and sellar phase: 4.9 interruptions/10 minutes; P<.001) and duration (nasal phase: 67.4, sphenoidal phase: 77.9, and sellar phase: 31.1 seconds/10 minutes; P<.001) of surgical interruptions. A comparison of the early and late EEA videos showed that increased surgical experience was associated with a decreased number (early: 4.9 and late: 2.9 interruptions/10 minutes; P=.03) and duration (early: 41.1 and late: 19.8 seconds/10 minutes; P=.02) of surgical interruptions during the sellar phase. CONCLUSIONS: CV-based analysis had a 93% to 98% accuracy in detecting the number, frequency, and duration of surgical interruptions occurring during EEA. Moreover, CV-based analysis reduced the time required to analyze the surgical fluency in EEA videos compared to manual review. The application of CV can facilitate the training of surgeons to overcome the learning curve of endoscopic skull base surgery. TRIAL REGISTRATION: ClinicalTrials.gov NCT06156020; https://clinicaltrials.gov/study/NCT06156020.

The Potential Neurological Impact of Intraoperative Hyponatremia Using Histidine-Tryptophan-Ketoglutarate Cardioplegia Infusion in Adult Cardiac Surgery.

Background and Objectives: The relationship between histidine-tryptophan-ketoglutarate (HTK)-induced hyponatremia and brain injury in adult cardiac surgery patients is unclear. This study analyzed postoperative neurological outcomes after intraoperative HTK cardioplegia infusion. Materials and Methods: A prospective cohort study was conducted on 60 adult patients who underwent cardiac surgery with cardiopulmonary bypass. Of these patients, 13 and 47 received HTK infusion and conventional hyperkalemic cardioplegia, respectively. The patients' baseline characteristics, intraoperative data, brain injury markers, Mini-Mental State Examination (MMSE) scores, and quantitative electroencephalography (qEEG) data were collected. Electrolyte changes during cardiopulmonary bypass, the degree of hyponatremia, and any associated brain insults were evaluated. Results: The HTK group presented with acute hyponatremia during cardiopulmonary bypass, which was intraoperatively corrected through ultrafiltration and normal saline administration. Postoperative sodium levels were higher in the HTK group than in the conventional cardioplegia group. The change in neuron-specific enolase levels after cardiopulmonary bypass was significantly higher in the HTK group (p = 0.043). The changes showed no significant differences using case-control matching. qEEG analysis revealed a significant increase in relative delta power in the HTK group on postoperative day (POD) 7 (p = 0.018); however, no significant changes were noted on POD 60. The MMSE scores were not significantly different between the two groups on POD 7 and POD 60. Conclusions: HTK-induced acute hyponatremia and rapid correction with normal saline during adult cardiac surgeries were associated with a potential short-term but not long-term neurological impact. Further studies are required to determine the necessity of correction for HTK-induced hyponatremia.

The middle-aged and older Chinese adults' health using actigraphy in Taiwan (MOCHA-T): protocol for a multidimensional dataset of health and lifestyle.

BACKGROUND AND OBJECTIVES: Older adults keep transforming with Baby Boomers and Gen Xers being the leading older population. Their lifestyle, however, is not well understood. The middle-aged and older Chinese adults' health using actigraphy in Taiwan (MOCHA-T) collected both objective and subjective data to depict the health and lifestyle of this population. The objectives, design, and measures of the MOCHA-T study are introduced, and the caveats and future directions related to the use of the data are presented. METHODS: People aged 50 and over were recruited from the community, with a subset of women aged 45-49 invited to supplement data on menopause and aging. Four instruments (i.e., self-reported questionnaires, diary, wrist actigraphy recorder, and GPS) were used to collect measures of sociodemographic, health, psychosocial, behavioral, temporal, and spatial data. RESULTS: A total of 242 participants who returned the informed consent and questionnaires were recruited in the MOCHA-T study. Among them, 94.6%, 95.0%, and 25.2% also completed the diary, actigraphy, and GPS data, respectively. There was almost no difference in sociodemographic characteristics between those with and without a completed diary, actigraphy, and GPS data, except for age group and educational level for those who returned completed actigraphy data. CONCLUSION: The MOCHA-T study is a multidimensional dataset that allows researchers to describe the health, behaviors, and lifestyle patterns, and their interactions with the environment of the newer generation of middle-aged and older adults in Taiwan. It can be compared with other countries with actigraphy and GPS-based lifestyle data of middle-aged and older adults in the future.

Polysomnography scoring-related training and quantitative assessment for improving interscorer agreement.

STUDY OBJECTIVES: To efficiently improve the scoring competency of scorers with varying levels of experience across regions in Taiwan, we developed a training program with a cloud-based polysomnography scoring platform to evaluate and improve interscorer agreement. METHODS: A total of 70 scorers from 34 sleep centers in Taiwan (job tenure: 0.5-39.0 years) completed a scoring test. All scorers scored a 742-epoch (30 s/epoch) overnight polysomnography recording of a patient with a moderate apnea-hypopnea index. Subsequently, 8 scoring experts delivered 8 interactive online lectures (each lasting 30 minutes). The training program included identifying scoring weaknesses, highlighting the latest scoring rules, and providing physicians' perspectives. Afterward, the scorers completed the second scoring test on the same participant. Changes in agreement from the first to second scoring test were identified. Sleep staging, sleep parameters, and respiratory events were considered for evaluating scoring agreement. RESULTS: The scorers' agreement in overall sleep stage scoring significantly increased from 74.6 to 82.3% (median score). The proportion of scorers with an agreement of ≥ 80% increased from 20.0% (14/70) to 58.6% (41/70) after the online training program. In addition, the scorers' agreement in overall respiratory-event scoring increased to 88.8% (median score) after training. The scorers with a job tenure of 2.0-4.9 years exhibited the highest level of improvement in overall sleep staging (their median agreement increased from 72.8 to 84.9%; P < .001). CONCLUSIONS: Our interactive online training program efficiently targeted the scorers' scoring weaknesses identified in the first scoring test, leading to substantial improvements in scoring proficiency. CITATION: Liao Y-S, Wu M-C, Li C-X, Lin W-K, Lin C-Y, Liang S-F. Polysomnography scoring-related training and quantitative assessment for improving interscorer agreement. J Clin Sleep Med. 2024;20(2):271-278.

Seed correlation analysis based on brain region activation for ADHD diagnosis in a large-scale resting state data set.

Background: Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder of multifactorial pathogenesis, which is often accompanied by dysfunction in several brain functional connectivity. Resting-state functional MRI have been used in ADHD, and they have been proposed as a possible biomarker of diagnosis information. This study's primary aim was to offer an effective seed-correlation analysis procedure to investigate the possible biomarker within resting state brain networks as diagnosis information. Method: Resting-state functional magnetic resonance imaging (rs-fMRI) data of 149 childhood ADHD were analyzed. In this study, we proposed a two-step hierarchical analysis method to extract functional connectivity features and evaluation by linear classifiers and random sampling validation. Result: The data-driven method-ReHo provides four brain regions (mPFC, temporal pole, motor area, and putamen) with regional homogeneity differences as second-level seeds for analyzing functional connectivity differences between distant brain regions. The procedure reduces the difficulty of seed selection (location, shape, and size) in estimations of brain interconnections, improving the search for an effective seed; The features proposed in our study achieved a success rate of 83.24% in identifying ADHD patients through random sampling (saving 25% as the test set, while the remaining data was the training set) validation (using a simple linear classifier), surpassing the use of traditional seeds. Conclusion: This preliminary study examines the feasibility of diagnosing ADHD by analyzing the resting-state fMRI data from the ADHD-200 NYU dataset. The data-driven model provides a precise way to find reliable seeds. Data-driven models offer precise methods for finding reliable seeds and are feasible across different datasets. Moreover, this phenomenon may reveal that using a data-driven approach to build a model specific to a single data set may be better than combining several data and creating a general model.

Cognitive Function Deterioration After Cardiopulmonary Bypass: Can Intraoperative Optimal Cerebral Regional Tissue Oxygen Saturation Predict Postoperative Cognitive Function?

OBJECTIVE: Cognitive impairment is a common neurologic complication after cardiac surgery with cardiopulmonary bypass (CPB). This study evaluated postoperative cognitive function to determine predictors of cognitive dysfunction, including intraoperative cerebral regional tissue oxygen saturation (rSO2). DESIGN: A prospective observational cohort study. SETTING: At a single academic tertiary-care center. PARTICIPANTS: A total of 60 adults undergoing cardiac surgery with CPB from January to August 2021. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: All patients underwent Mini-Mental State Examination (MMSE) and quantified electroencephalography (qEEG) 1 day before cardiac surgery, 7 days postoperatively (POD7), and POD60. Intraoperative cerebral rSO2 was monitored continuously. For MMSE, no significant decrease in MMSE score was found on POD7 versus preoperatively (p = 0.09), but POD60 scores showed significant improvement compared with both preoperative (p = 0.02) and POD7 scores (p < 0.001). On qEEG, relative theta power on POD7 was increased versus preoperatively (p < 0.001), but it was decreased on POD60 (POD7 versus POD60, p < 0.001), and was close to preoperative data (p > 0.99). Baseline rSO2 was an independent factor for postoperative MMSE. Both baseline and mean rSO2 showed a significant influence in postoperative relative theta activity, whereas mean rSO2 was the only predictor for the theta-gamma ratio (p = 0.04). CONCLUSIONS: The MMSE in patients undergoing CPB declined at POD7 and recovered by POD60. Lower baseline rSO2 indicated a higher potential for MMSE decline at POD60. Inferior intraoperative mean rSO2 was related to higher postoperative relative theta activity and theta-gamma ratio, implying subclinical or further cognitive impairment.

Home-Use and Real-Time Sleep-Staging System Based on Eye Masks and Mobile Devices with a Deep Learning Model.

PURPOSE: Sleep is an important human activity. Comfortable sensing and accurate analysis in sleep monitoring is beneficial to many healthcare and medical applications. From 2020, owing to the COVID­19 pandemic that spreads between people when they come into close physical contact with one another, the willingness to go to hospital for receiving care has reduced; care-at-home is the trend in modern healthcare. Therefore, a home-use and real-time sleep-staging system is developed in this paper. METHODS: We developed and implemented a real-time sleep staging system that integrates a wearable eye mask for high-quality electroencephalogram/electrooculogram measurement and a mobile device with MobileNETV2 deep learning model for sleep-stage identification. In the experiments, 25 all-night recordings were acquired, 17 of which were used for training, and the remaining eight were used for testing. RESULTS: The averaged scoring agreements for the wake, light sleep, deep sleep, and rapid eye movement stages were 85.20%, 87.17%, 82.87%, and 89.30%, respectively, for our system compared with the manual scoring of PSG recordings. In addition, the mean absolute errors of four objective sleep measurements, including sleep efficiency, total sleep time, sleep onset time, and wake after sleep onset time were 1.68%, 7.56 min, 5.50 min, and 3.94 min, respectively. No significant differences were observed between the proposed system and manual PSG scoring in terms of the percentage of each stage and the objective sleep measurements. CONCLUSION: These experimental results demonstrate that our system provides high scoring agreements in sleep staging and unbiased sleep measurements owing to the use of EEG and EOG signals and powerful mobile computing based on deep learning networks. These results also suggest that our system is applicable for home-use real-time sleep monitoring.

Directions of Deep Brain Stimulation for Epilepsy and Parkinson's Disease.

BACKGROUND: Deep brain stimulation (DBS) is an effective treatment for movement disorders and neurological/psychiatric disorders. DBS has been approved for the control of Parkinson disease (PD) and epilepsy. OBJECTIVES: A systematic review and possible future direction of DBS system studies is performed in the open loop and closed-loop configuration on PD and epilepsy. METHODS: We searched Google Scholar database for DBS system and development. DBS search results were categorized into clinical device and research system from the open-loop and closed-loop perspectives. RESULTS: We performed literature review for DBS on PD and epilepsy in terms of system development by the open loop and closed-loop configuration. This study described development and trends for DBS in terms of electrode, recording, stimulation, and signal processing. The closed-loop DBS system raised a more attention in recent researches. CONCLUSION: We overviewed development and progress of DBS. Our results suggest that the closed-loop DBS is important for PD and epilepsy.

Development of a rule-based automatic five-sleep-stage scoring method for rats.

BACKGROUND: Sleep problem or disturbance often exists in pain or neurological/psychiatric diseases. However, sleep scoring is a time-consuming tedious labor. Very few studies discuss the 5-stage (wake/NREM1/NREM2/transition sleep/REM) automatic fine analysis of wake-sleep stages in rodent models. The present study aimed to develop and validate an automatic rule-based classification of 5-stage wake-sleep pattern in acid-induced widespread hyperalgesia model of the rat. RESULTS: The overall agreement between two experts' consensus and automatic scoring in the 5-stage and 3-stage analyses were 92.32% (κ = 0.88) and 94.97% (κ = 0.91), respectively. Standard deviation of the accuracy among all rats was only 2.93%. Both frontal-occipital EEG and parietal EEG data showed comparable accuracies. The results demonstrated the performance of the proposed method with high accuracy and reliability. Subtle changes exhibited in the 5-stage wake-sleep analysis but not in the 3-stage analysis during hyperalgesia development of the acid-induced pain model. Compared with existing methods, our method can automatically classify vigilance states into 5-stage or 3-stage wake-sleep pattern with a promising high agreement with sleep experts. CONCLUSIONS: In this study, we have performed and validated a reliable automated sleep scoring system in rats. The classification algorithm is less computation power, a high robustness, and consistency of results. The algorithm can be implanted into a versatile wireless portable monitoring system for real-time analysis in the future.

Development of a human-computer collaborative sleep scoring system for polysomnography recordings.

The overnight polysomnographic (PSG) recordings of patients were scored by an expert to diagnose sleep disorders. Visual sleep scoring is a time-consuming and subjective process. Automatic sleep staging methods can help; however, the mechanism and reliability of these methods are not fully understood. Therefore, experts often need to rescore the recordings to obtain reliable results. Here, we propose a human-computer collaborative sleep scoring system. It is a rule-based automatic sleep scoring method that follows the American Academy of Sleep Medicine (AASM) guidelines to perform an initial scoring. Then, the reliability level of each epoch is analyzed based on physiological patterns during sleep and the characteristics of various stage changes. Finally, experts would only need to rescore epochs with a low-reliability level. The experimental results show that the average agreement rate between our system and fully manual scorings can reach 90.42% with a kappa coefficient of 0.85. Over 50% of the manual scoring time can be reduced. Due to the demonstrated robustness and applicability, the proposed approach can be integrated with various PSG systems or automatic sleep scoring methods for sleep monitoring in clinical or homecare applications in the future.

Spike densities of the amygdala and neocortex reflect progression of kindled motor seizures.

Amygdala kindling is a common temporal lobe-like seizure model. In the present study, temporal and spectral analyses of the ictal period were investigated throughout amygdala kindling in response to different behavioral seizures. Right-side amygdala was kindled to induce epileptiform afterdischarges (ADs). ADs of both the frontal cortex and amygdala were analyzed. Powers of the low (0-9 Hz)- and high (12-30 Hz)-frequency bands in response to different behavioral seizures were calculated. Densities of upward and downward peaks of spikes, which reflected information of spike count and spike pattern, throughout kindle-induced ADs were calculated. Progression was seen in the temporal and spectral characteristics of amygdala-kindled ADs in response to behaviors. Numbers of significant differences of all 1-s AD segments between two Racine's seizure stages were significantly higher in upward and downward indexes of the temporal spike than those using the spectral method in both the amygdala and neocortex. Ability for distinguishing seizure stages was significantly higher in temporal spike density of amygdala ADs compared to those of frontal ADs. Our results showed that amygdala kindling caused spectrotemporal changes of activities in the amygdala and frontal cortex. The density of spike-related peaks had better distinguishability in response to behavioral seizures, particularly in a seizure zone of amygdala. The present study provides a new temporal index of spike's peak density to understand progression of motor seizures in the kindling process.

Portable wireless neurofeedback system of EEG alpha rhythm enhances memory.

BACKGROUND: Effect of neurofeedback training (NFT) on enhancement of cognitive function or amelioration of clinical symptoms is inconclusive. The trainability of brain rhythm using a neurofeedback system is uncertainty because various experimental designs are used in previous studies. The current study aimed to develop a portable wireless NFT system for alpha rhythm and to validate effect of the NFT system on memory with a sham-controlled group. METHODS: The proposed system contained an EEG signal analysis device and a smartphone with wireless Bluetooth low-energy technology. Instantaneous 1-s EEG power and contiguous 5-min EEG power throughout the training were developed as feedback information. The training performance and its progression were kept to boost usability of our device. Participants were blinded and randomly assigned into either the control group receiving random 4-Hz power or Alpha group receiving 8-12-Hz power. Working memory and episodic memory were assessed by the backward digital span task and word-pair task, respectively. RESULTS: The portable neurofeedback system had advantages of a tiny size and long-term recording and demonstrated trainability of alpha rhythm in terms of significant increase of power and duration of 8-12 Hz. Moreover, accuracies of the backward digital span task and word-pair task showed significant enhancement in the Alpha group after training compared to the control group. CONCLUSIONS: Our tiny portable device demonstrated success trainability of alpha rhythm and enhanced two kinds of memories. The present study suggest that the portable neurofeedback system provides an alternative intervention for memory enhancement.

Development and Evaluation of a Wearable Device for Sleep Quality Assessment.

OBJECTIVE: In this study, a wearable actigraphy recording device with low sampling rate (1 Hz) for power saving and data reduction and a high accuracy wake-sleep scoring method for the assessment of sleep were developed. METHODS: The developed actigraphy recorder was successfully applied to overnight recordings of 81 subjects with simultaneous polysomnography (PSG) measurements. The total length of recording reached 639.8 h. A wake-sleep scoring method based on the concept of movement density evaluation and adaptive windowing was proposed. Data from subjects with good (N = 43) and poor (N = 16) sleep efficiency (SE) in the range of 52.7-97.42% were used for testing. The Bland-Altman technique was used to evaluate the concordance of various sleep measurements between the manual PSG scoring and the proposed actigraphy method. RESULTS: For wake-sleep staging, the average accuracy, sensitivity, specificity, and kappa coefficient of the proposed system were 92.16%, 95.02%, 71.30%, and 0.64, respectively. For the assessment of SE, the accuracy of classifying the subject with good or poor SE reached 91.53%. The mean biases of SE, sleep onset time, wake after sleep onset, and total sleep time were -0.95%, 0.74 min, 2.84 min, and -4.3 min, respectively. CONCLUSION: These experimental results demonstrate the robustness and reliability of our method using limited activity information to estimate wake-sleep stages during overnight recordings. SIGNIFICANCE: The results suggest that the proposed wearable actigraphy system is practical for the in-home screening of objective sleep measurements and objective evaluation of sleep improvement after treatment.

Rapid Amygdala Kindling Causes Motor Seizure and Comorbidity of Anxiety- and Depression-Like Behaviors in Rats.

Amygdala kindling is a model of temporal lobe epilepsy (TLE) with convulsion. The rapid amygdala kindling has an advantage on quick development of motor seizures and for antiepileptic drugs screening. The rapid amygdala kindling causes epileptogenesis accompanied by an anxiolytic response in early isolation of rat pups or depressive behavior in immature rats. However, the effect of rapid amygdala kindling on comorbidity of anxiety- and depression-like behaviors is unexplored in adult rats with normal breeding. In the present study, 40 amygdala stimulations given within 2 days were applied in adult Wistar rats. Afterdischarge (AD) and seizure stage were recorded throughout the amygdala kindling. Anxiety-like behaviors were evaluated by the elevated plus maze (EPM) test and open field (OF) test, whereas depression-like behaviors were assessed by the forced swim (FS) and sucrose consumption (SC) tests. A tonic-clonic convulsion was provoked in the kindle group. Rapid amygdala kindling resulted in a significantly lower frequency entering an open area of either open arms of the EPM or the central zone of an OF, lower sucrose intake, and longer immobility of the FS test in the kindle group. Our results suggest that rapid amygdala kindling elicited severe motor seizures comorbid with anxiety- and depression-like behaviors.

Epileptic Pattern Recognition and Discovery of the Local Field Potential in Amygdala Kindling Process.

Epileptogenesis, which occurs in an epileptic brain, is an important focus for epilepsy. The spectral analysis has been popularly applied to study the electrophysiological activities. However, the resolution is dominated by the window function of the algorithm used and the sample size. In this report, a temporal waveform analysis method is proposed to investigate the relationship of electrophysiological discharges and motor outcomes with a kindling process. Wistar rats were subjected to electrical amygdala kindling to induce temporal lobe epilepsy. During the kindling process, different morphologies of afterdischarges (ADs) were found and a recognition method, using template matching techniques combined with morphological comparators, was developed to automatically detect the epileptic patterns. The recognition results were compared to manually labeled results, and 79%-91% sensitivity was found. In addition, the initial ADs (the first 10 s) of different seizure stages were specifically utilized for recognition, and an average of 85% sensitivity was achieved. Our study provides an alternative viewpoint away from frequency analysis and time-frequency analysis to investigate epileptogenesis in an epileptic brain. The recognition method can be utilized as a preliminary inspection tool to identify remarkable changes in a patient's electrophysiological activities for clinical use. Moreover, we demonstrate the feasibility of predicting behavioral seizure stages from the early epileptiform discharges.

Combination of Expert Knowledge and a Genetic Fuzzy Inference System for Automatic Sleep Staging.

OBJECTIVE: In this paper, the genetic fuzzy inference system based on expert knowledge for automatic sleep staging was developed. METHODS: Eight features, including temporal and spectrum analyses of the EEG and EMG signals, were utilized as the input variables. The fuzzy rules and the fuzzy sets were constructed based on expert knowledge and the distributions of feature values at different sleep stages. Three experiments were designed to develop and evaluate the proposed system. PSGs of 32 healthy subjects and 16 subjects with insomnia were included in the experiment to develop and evaluate the proposed method. Finally, a complete sleep scoring system integrating two fuzzy inference models with robust performance on various subject groups is developed. RESULTS: The overall agreement and kappa coefficient of this integrated system applied to PSG data from 8 subjects with good sleep efficiency, 8 subjects with poor sleep efficiency and 8 subjects with insomnia were 86.44 % and 0.81, respectively. CONCLUSION: Due to the high performance of the proposed system, it is expected to integrate the proposed method with various PSG systems for sleep monitoring in clinical or homecare applications in the future. SIGNIFICANCE: An automatic sleep staging system integrating knowledge of the experts in scoring of PSG data and the elasticity of fuzzy systems in reasoning and decision making is proposed and the robustness and clinical applicability of the proposed method is demonstrated on data from healthy subjects and subjects with insomnia.

Using off-the-shelf lossy compression for wireless home sleep staging.

BACKGROUND: Recently, there has been increasing interest in the development of wireless home sleep staging systems that allow the patient to be monitored remotely while remaining in the comfort of their home. However, transmitting large amount of Polysomnography (PSG) data over the Internet is an important issue needed to be considered. In this work, we aim to reduce the amount of PSG data which has to be transmitted or stored, while having as little impact as possible on the information in the signal relevant to classify sleep stages. NEW METHOD: We examine the effects of off-the-shelf lossy compression on an all-night PSG dataset from 20 healthy subjects, in the context of automated sleep staging. The popular compression method Set Partitioning in Hierarchical Trees (SPIHT) was used, and a range of compression levels was selected in order to compress the signals with various degrees of loss. In addition, a rule-based automatic sleep staging method was used to automatically classify the sleep stages. RESULTS: Considering the criteria of clinical usefulness, the experimental results show that the system can achieve more than 60% energy saving with a high accuracy (>84%) in classifying sleep stages by using a lossy compression algorithm like SPIHT. COMPARISON WITH EXISTING METHOD(S): As far as we know, our study is the first that focuses how much loss can be tolerated in compressing complex multi-channel PSG data for sleep analysis. CONCLUSIONS: We demonstrate the feasibility of using lossy SPIHT compression for wireless home sleep staging.

Musicians and non-musicians' different reliance of features in consonance perception: a behavioral and ERP study.

OBJECTIVE: The aim of this study was to compare the different features that musicians and non-musicians rely upon when they discern consonant and dissonant intervals. Previous studies have addressed this issue from the perspective of either the frequency ratio (Western music theory) or the frequency difference (psychoacoustics), but have not considered both features in a single and balanced study. METHODS: Twelve musicians and twelve non-musicians judged musical consonance at various 50-500 Hz intervals, orthogonally selected from across the "pitch interval" and "roughness" spectrum. Both behavioral and event-related potential (ERP) data were collected separately. RESULTS: Behavioral results demonstrated that while musicians relied upon pitch intervals (between perfect fifths and tritones, with 95% accuracy), non-musicians performed around chance. The latter performance could, however, be sub-divided into "rough tritone and non-rough perfect-fifth" (70-80%) and "non-rough tritone and rough perfect-fifth" combinations (25-30%), suggesting non-musicians' reliance on the roughness dimension. ERP components revealed corresponding P2 (200-250 ms) amplitude differences in the Fz and Cz channels for the "tritones vs. perfect fifths" comparison in musicians, and by the "rough vs. non-rough" comparison in the non-musicians. In addition, N1 (∼100 ms) and N2 (300-400 ms) components also revealed difference in Fz, F3, F4, FCz, Cz and CPz electrodes for "tritones vs. perfect fifths" in musicians. In the non-musicians, a stronger negative N2 for rough than for non-rough stimuli was found at F4 and Cz. CONCLUSION: Together, these results suggest that musicians and non-musicians rely upon pitch intervals and sensory roughness, respectively, for consonance/dissonance perception. SIGNIFICANCE: To our knowledge, this is the first study to compare independently across the pitch interval and roughness spectrum. Our results further support the brain plasticity as a result of musical training in consonance perception.