Delta Signal Research Articles

Multimodal imaging for the differential diagnosis and efficacy evaluation of intraocular retinoblastoma in children with selective ophthalmic artery infusion.

Retinoblastoma (RB) is the most common malignant tumor in children under the age of 3 years and is associated with a high disability and mortality rate. The aim of this study was, first, to evaluate the clinical efficacy of multimodal imaging in differentially diagnosing RB in children and in predicting the efficacy of selective ophthalmic artery infusion (SOAI) and, second, to identify the factors associated with this efficacy. This study retrospectively collected the data from 256 children with unilateral RB and intraocular involvement, including multimodal imaging magnetic resonance imaging (MRI), computed tomography (CT), and clinical characteristics. Among the cases, 33 with both CT and MRI data available were used to evaluate the diagnostic accuracy in distinguishing RB, with histopathological results serving as the gold standard. Additionally, a retrospective analysis was conducted on the MRI and clinical characteristics of 256 cases of unilateral RB with intraocular involvement before SOAI treatment. The predictive ability of imaging features and clinical characteristics for the treatment efficacy of children was analyzed, and the differences in globe salvage rates and visual preservation based on different tumor stages were evaluated. The diagnostic accuracy of CT imaging for RB was 96.96% while that of MRI was 84.84%, with both showing high consistency with the histopathological results. CT images demonstrated a posterior intraocular mass with a high-density appearance, with spots, patches, or clustered calcifications visible within the tumor. The CT values were mostly above 100 Hounsfield units (HU), and enhanced scanning showed varying degrees of enhancement in noncalcified masses. MRI showed low or moderate signal intensity on T1-weighted images and moderate-to-high signal intensity on T2-weighted images, with significant enhancement after contrast administration. Tumors with more calcifications showed long T1 and short T2 signals. Patients with better prognosis had a higher delta signal increase (ΔSI), a greater distance from the optic disc, smaller tumor diameter, absence of implantation nodules or smaller implantation range, endogenous growth pattern, smaller extent of retinal detachment, absence of clinical high-risk factors, no vitreous hemorrhage, no globe shrinkage, and smaller calcification volume. The distance between the tumor and optic disc, clinical high-risk factors, and tumor growth pattern were found to be independent factors associated with prognosis. The rate of successful globe salvage and visual acuity decreased with increasing tumor stage. CT and MRI are highly valuable for the comprehensive assessment of tumors in pediatric RB. MRI alone can complete a comprehensive assessment of patients with RB and thus allow for the reduction radiation dose in children. Calcification of the tumor is crucial for diagnosis, and imaging findings can serve to inform patient prognosis and treatment planning. The distance between the tumor and optic disc, clinical high-risk factors, and tumor growth pattern are closely related to the prognosis of children.

Microcystins in the benthic food-web of the Sacramento-San Joaquin Delta, California

Harmful cyanobacteria blooms are a growing threat in estuarine waters as upstream blooms are exported into coastal environments. Cyanobacteria can produce potent toxins, one of which—hepatotoxic microcystins (MCs)—can persist and accumulate within the food web. Filter-feeding invertebrates may biomagnify toxins up to 100× ambient concentrations. As such, bivalves can be used as an environmentally relevant and highly sensitive sentinel for MC monitoring. To date there has been little research on cyanotoxin bioaccumulation in estuaries. The Sacramento-San Joaquin Delta (Delta) aquatic food web has undergone a profound change in response to widespread colonization of aquatic invasive species such as Asian clams (Corbicula fluminea) in the freshwater portion of the Delta. These clams are prolific—blanketing areas of the Delta at densities up to 1000 clams/m2 and are directly implicated in the pelagic organism decline of threatened and endangered fishes. We hypothesized that Asian clams accumulate MCs which may act as an additional stressor to the food web and MCs would seasonally be in exceedance of public health advisory levels. MCs accumulation in Delta Asian clams and signal crayfish (Pacifastacus leniusculus) were studied over a two-year period. ELISA and LC-MS analytical methods were used to measure free and protein-bound MCs in clam and crayfish tissues. We describe an improved MC extraction method for use when analyzing these taxa by LC-MS. MCs were found to accumulate in Asian clams across all months and at all study sites, with seasonal maxima occurring during the summer. Although MC concentrations rarely exceeded public health advisory levels, the persistence of MCs year-round still poses a chronic risk to consumers. Crayfish at times also accumulated high concentrations of MCs. Our results highlight the utility of shellfish as sentinel organisms for monitoring in estuarine areas.

An automated drug dependence detection system based on EEG

ObjectiveSubstance abuse causes damage to the brain structure and function. This research aim is to design an automated drug dependence detection system based on EEG signals in a Multidrug (MD) abuser. MethodsEEG signals were recorded from participants categorized into MD-dependents (n = 10) and Healthy Control (HC) (n = 12). The Recurrence Plot investigates the dynamic characteristics of the EEG signal. The entropy index (ENTR) measured from the Recurrence Quantification Analysis was considered the complexity index of the delta, theta, alpha, beta, gamma, and all-band EEG signals. Statistical analysis was performed by t-test. The support vector machine technique was used for the data classification. ResultsThe results show decreased ENTR indices in the delta, alpha, beta, gamma, and all-band EEG signal and increased theta band in MD abusers compared to the HC group. That indicated the reduction of complexity in the delta, alpha, beta, gamma, and all-band EEG signals in the MD group. Additionally, the SVM classifier distinguished the MD group from the HC group with 90% accuracy, 89.36% sensitivity, 90.7% specificity, and 89.8% F1 score. Conclusions and significanceThe nonlinear analysis of brain data was used to build an automatic diagnostic aid system that could identify HC people apart from those who abuse MD.

Notch signaling sculpts the stem cell niche.

Adult stem cells depend on their niches for regulatory signaling that controls their maintenance, division, and their progeny differentiation. While communication between various types of stem cells and their niches is becoming clearer, the process of stem cell niche establishment is still not very well understood. Model genetic organisms provide simplified systems to address various complex questions, for example, how is a stem cell niche formed? What signaling cascades induce the stem cell niche formation? Are the mechanisms of stem cell niche formation conserved? Notch signaling is an evolutionarily conserved pathway first identified in fruit flies, crucial in fate acquisition and spatiotemporal patterning. While the core logic behind its activity is fairly simple and requires direct cell-cell interaction, it reaches an astonishing complexity and versatility by combining its different modes of action. Subtleties such as equivalency between communicating cells, their physical distance, receptor and ligand processing, and endocytosis can have an effect on the way the events unfold, and this review explores some important general mechanisms of action, later on focusing on its involvement in stem cell niche formation. First, looking at invertebrates, we will examine how Notch signaling induces the formation of germline stem cell niche in male and female Drosophila. In the developing testis, a group of somatic gonadal precursor cells receive Delta signals from the gut, activating Notch signaling and sealing their fate as niche cells even before larval hatching. Meanwhile, the ovarian germline stem cell niche is built later during late larval stages and requires a two-step process that involves terminal filament formation and cap cell specification. Intriguingly, double security mechanisms of Notch signaling activation coordinated by the soma or the germline control both steps to ensure the robustness of niche assembly. Second, in the vast domains of mammalian cellular signaling, there is an emerging picture of Notch being an active player in a variety of tissues in health and disease. Notch involvement has been shown in stem cell niche establishment in multiple organs, including the brain, muscle, and intestine, where the stem cell niches are essential for the maintenance of adult stem cells. But adult stem cells are not the only cells looking for a home. Cancer stem cells use Notch signaling at specific stages to gain an advantage over endogenous tissue and overpower it, at the same time acquiring migratory and invasive abilities to claim new tissues (e.g., bone) as their territory. Moreover, in vitro models such as organoids reveal similar Notch employment when it comes to the developing stem cell niches. Therefore, a better understanding of the processes regulating stem cell niche assembly is key for the fields of stem cell biology and regenerative medicines.

Bipolar disorder traits: An electroencephalogram systematic review

Bipolar disorder (BD) is a serious mental disorder that globally affected 40 million people in 2019. According to the National Alliance on Mental Illness (NAMI), the present state of scientific knowledge only permits psychiatrists to diagnose BD using subjective and imprecise questionnaires. Therefore, developing a diagnostic tool with objective and precise biomarkers should be a major focus of research in this field. Among the potential biomarkers for BD, electroencephalogram (EEG)-based signatures of BD are considered to be the most optimal marker due to their strong links with behavioural symptoms and also their non-invasiveness. The goal of this review is to give a detailed summary of current techniques for investigating the traces of BD through EEG abnormalities. In this review, 13 studies from databases such as ScienceDirect and PubMed seeking to utilize EEG characteristics to diagnose BD were selected. The search keywords were “EEG in BD diagnosis”, “EEG microstates in BD”, and “EEG features for BD patients”. The publication date was set from 2007 to 2021. From these studies, we synthesize the effects of BD on each EEG feature, as well as detail the pros and cons when using each feature as a biomarker for BD. Results showed that EEG microstates demonstrate their potential among the seven EEG properties discussed in this article, as shown by several studies. By definition, EEG microstates are a dynamic representation of the spatial distribution of the scalp's electric potential as it varies over time. Specifically, four microstate classes recorded in different brain regions are classified into A (right-frontal left-posterior), B (left-frontal right-posterior), C (midline frontal-occipital), and D (midline frontal topographies). Greater presence of microstate class B in BD patients during task-free resting states are a distinctive characteristic of BD patients from which BD can be differentiated from other psychiatric illnesses. Besides microstates, EEG resting states are also considered to have a bright future in BD diagnosis. Specifically, by investigating brain frequency bands, researchers have discovered that BD patients exhibit abnormal delta and alpha signals as compared to healthy controls (HCs). The abnormalities of microstate B in EEG microstate characteristics would be the most promising biomarker for detecting BD. In addition, anomalies in delta and alpha signals during resting EEG states are possible BD diagnostic indicators.

Fringe-positive Golgi outposts unite temporal Furin 2 convertase activity and spatial Delta signal to promote dendritic branch retraction.

Golgi outposts (GOPs) in dendrites are known for their role in promoting branch extension, but whether GOPs have other functions is unclear. We found that terminal branches of Drosophila class IV dendritic arborization (C4da) neurons actively grow during the early third-instar (E3) larval stage but retract in the late third (L3) stage. Interestingly, the Fringe (Fng) glycosyltransferase localizes increasingly at GOPs in distal dendritic regionsthrough the E3 to the L3 stage. Expression of the endopeptidase Furin 2 (Fur2), which proteolyzes and inactivates Fng, decreases from E3 to L3 in C4da neurons, thereby increasing Fng-positive GOPs indendrites.The epidermal Delta ligand and neuronal Notch receptor, the substrate for Fng-mediated O-glycosylation, also negatively regulate dendrite growth. Fng inhibits actin dynamics in dendrites, linking dendritic branch retraction to suppression of the C4da-mediated thermal nociception response in late larval stages. Thus, Fng-positive GOPs function in dendrite retraction, which would add another function to the repertoire of GOPs in dendrite arborization.

Time-frequency dynamics of error monitoring in childhood: AnEEG study.

Error monitoring allows individuals to monitor and adapt their behavior by detecting errors. Error monitoring is thought to develop throughout childhood and adolescence. However, most of this evidence comes from studies in late childhood and adolescence utilizing event-related potentials (ERPs). The current study utilizes time-frequency (TF) and connectivity analyses to provide a comprehensive examination of age-related changes in error-monitoring processes across early childhood (N=326; 50.9% females; 4-9years). ERP analyses indicated the presence of the error-related negativity (ERN) and error positivity (Pe) across all ages. Results showed no error-specific age-related changes in the ERN and the Pe. However, TF analyses suggested error-related frontocentral responses in delta and theta signal strength (power), delta consistency (intertrial phase synchrony), and delta synchrony (interchannel phase synchrony) between frontrocentral and frontolateral clusters-all of which increased with age. Additionally, the current study examines the reliability and effect size estimates of the ERP and TF measures. For most measures, more trials were needed to achieve acceptable reliability than what is commonly used in the psychophysiological literature. Resources to facilitate the measurement and reporting of reliability are provided. Overall, findings highlight the utility of TF analyses and provide useful information for future studies examining the development of error monitoring.

Patient-specific method of sleep electroencephalography using wavelet packet transform and Bi-LSTM for epileptic seizure prediction

Epileptic seizures during sleep increase the probability of complications and sudden death in patients. Effective epileptic seizure prediction in sleep can assist doctors (patients) in administering (receiving) effective treatments to reduce the abovementioned probability. Most existing prediction methods do not consider electroencephalogram (EEG) features during sleep, leading to low accuracies in predicting seizures during sleep. Furthermore, traditional machine-learning based approaches might be susceptible to a high false alarm rate. In this paper, a novel patient-specific method based on deep learning and sleep scalp EEG is proposed to predict epileptic seizures. Raw EEG data are preprocessed to remove noise and reduce the complexity. Wavelet energy is used to reveal the features of the EEG signals in the time–frequency domain as the input of the classification phase. Bi-directional long short-term memory (Bi-LSTM) networks are applied to excavate the most discriminative features to obtain classification results combined with leave-one-out cross-validation method. Subsequently, a two-step post-processing process optimises the prediction results. Based on four patients reasonably selected from the CHB-MIT scalp database, our experiments with various frequency band constraints demonstrate that the delta and gamma-band signals are important factors affecting seizure prediction performance. The classification performance of Bi-LSTM in our method with an accuracy of 99.47%, a sensitivity of 99.34%, and a specificity of 99.60%, is higher than that achieved with other neural networks. Additionally, compared with the existing methods for seizure prediction during sleep, the proposed method has a better prediction performance.

Abstract P730: MCA Stroke Chronically Disrupts Hippocampal Activity and Cortico-Hippocampal Communication

Introduction: Cognition and memory deficits are common sequelae following middle cerebral artery (MCA) stroke, one of the most common strokes in humans. However MCA stroke does not compromise the structural integrity of the hippocampus, which is highly involved in memory function, because the MCA does not supply blood flow to the hippocampus. We previously reported on the acute effect of MCA stroke, where we observed increased hippocampal activity and cortico-hippocampal communication. Here we investigate chronic changes to local oscillations and cortico-hippocampal communication following MCA occlusion in rats two weeks and one month following stroke. Hypothesis: Cortical stroke affects remote brain regions, disrupting hippocampal function and cortico-hippocampal communication. Methods: We subjected male rats (n=28) to distal MCA occlusion compared to controls (n=19). We recorded local field potentials simultaneously from cortex and hippocampus two weeks and one month following stroke using 16-site linear electrode arrays under urethane anesthesia. We analyzed signal power, brain state, CFC, and sharp wave SPW-Rs to assess hippocampal function and cortico-hippocampal communication. Results: Our results show disruptions to local oscillations; lowered delta (1-3 Hz) signal power in the cortex and hippocampus, increased signal power in gamma (30-60 Hz) and high gamma (60-200 Hz) in cortex and hippocampus. Theta/delta brain state is disrupted, and SPW-Rs increase in power at two weeks, before returning to baseline levels at one month. Communication is also disrupted; Theta-gamma coupling, a measure of information being communicated between regions, breaks down after stroke. Conclusions: These results suggest that chronic stroke causes significant changes to hippocampal function, which can be characterized by these electrophysiological biomarkers, establishing putative targets for targeted stimulation therapies.

Hydrophobic development and mechanical properties of cellulose substrates supercritically impregnated with food-grade waxes

Supercritical impregnation may be used to impart specific functional properties into porous substrates such as wood, textiles, or paper. In the current study, food-grade beeswax (BW), carnauba wax (CW) and vegetable wax (VW) were impregnated into paper substrates to improve their hydrophobicity and mechanical strength. The contact angle of impregnated and annealed samples was approximately 110–120° when annealed at 140 °C, and 130° when annealed at 160 °C. SEM analyses revealed that dual micro- and nano-scale roughness was generated in impregnated paper substrates that also underwent annealing. FTIR analysis showed evidence of H-bonding between the waxes and cellulose, but this was more dominant with BW/CW compared with VW due to the different chemical structures of the waxes. Annealed samples showed lower intensity FTIR peaks, tentatively confirming a phase transition of the waxes as a result of the annealing. A reduced tan delta signal up to the secondary alpha transition temperature for paper was observed with BW/CW impregnated samples, indicating the formation of additional chemical bonds between cellulose and wax. Compared with untreated paper substrates, the sharp decrease in storage modulus during degradation occurred at temperatures up to 10 °C higher for wax-impregnated papers, and up to 40 °C lower for baseline papers impregnated and annealed without wax. It is believed that the H-bonds between the waxes and cellulose were able to withstand higher temperatures in the degradation region, thus offsetting the effects of sample preparation.

Brainwave entrainment through external sensory stimulus: a therapy for insomnia

Objective: To use Brainwave Entrainment through External sensory stimulus to treat Insomnia. Background: Insomnia is a condition that makes disorderness in the sleep. It plays a significant role in normal, pathological and psychiatric subjects. Most of the times, inducing sleep either through hypnotics or through sedative medicines are commonly adopted for treating sleeplessness. Brainwave Entrainment is an alternative procedure that modulates neural activities by synchronizing brainwave frequency with that of stimuli (Shusheng et al., 2016). Design/Methods: In this work audio, visual and haptic stimuli are used to improve overall sleep quality for insomnia subjects. Two audio signals at different frequencies were given to left and right ears. The results in binaural beat signal in delta band. Visual input is also given to two eyes through eye-mask to block the entry of external light. Automated system is developed to give pressure at HT-7 with time and pressure control. This therapy is self-administered by the TEST Group (who are diagnosed for insomnia) for a brief period on regular pace. Brain signals are acquired before and after therapy to understand the influence of AVE. Subjects who are not into insomnia (CONTROLs) are also studied for sleep pattern to make baseline comparison. Results: By analyzing power spectrum of these signals, results demonstrate that average delta signal power increases by 10% becoming at par with the CONTROLs. The test responses are also statistically analyzed using Cohen’s d value. The obtained results demonstrate impact of this therapy as significant changes in quality of sleep. Also, insomnia subjects who are not into oral medicine shows better response, in the sense their rhythmic changes became almost similar to that of CONTROLs with marked increase in REM state duration, reaching 20% of full sleep time, a normally recommended value. Conclusions: Brainwave entertainment through external sensory stimulus is very beneficial to treat insomnia soon after the diagnosis. Disclosure: Dr. Srinivasan has nothing to disclose. Dr. E has nothing to disclose. Dr. Venkatesan has nothing to disclose. Dr. R has nothing to disclose.

Shifts in Phytoplankton Community Structure Across an Anticyclonic Eddy Revealed From High Spectral Resolution Lidar Scattering Measurements

Changes in airborne high spectral resolution lidar (HSRL) measurements of scattering, depolarization, and attenuation coincided with a shift in phytoplankton community composition across an anticyclonic eddy in the North Atlantic. We normalized the total depolarization ratio (delta) by the particulate backscattering coefficient (b(b)(p)) to account for the covariance in delta and b(b)(p) that has been attributed to multiple scattering. A 15% increase in delta/b(b)(p) inside the eddy coincided with decreased phytoplankton biomass and a shift to smaller and more elongated phytoplankton cells. Taxonomic changes (reduced dinoflagellate relative abundance inside the eddy) were also observed. The delta signal is thus potentially most sensitive to changes in phytoplankton shape because neither the observed change in the particle size distribution (PSD) nor refractive index (assuming average refractive indices) are consistent with previous theoretical modeling results. We additionally calculated chlorophyll-a (Chl) concentrations from measurements of the diffuse light attenuation coefficient (K-d) and divided by b(b)(p) to evaluate another optical metric of phytoplankton community composition (Chl:b(bp)), which decreased by more than a factor of two inside the eddy. This case study demonstrates that the HSRL is able to detect changes in phytoplankton community composition. High spectral resolution lidar measurements reveal complex structures in both the vertical and horizontal distribution of phytoplankton in the mixed layer providing a valuable new tool to support other remote sensing techniques for studying mixed layer dynamics. Our results identify fronts at the periphery of mesoscale eddies as locations of abrupt changes in near-surface optical properties.

Spectral Graph Based Vertex-Frequency Wiener Filtering for Image and Graph Signal Denoising

In this article, we propose and develop a spectral graph based vertex varying Wiener filtering framework in the joint vertex-frequency domain for denoising of graph signals defined on weighted, undirected and connected graphs. To this end, we first extend the Zadeh time-frequency filter concept to graph signals and obtain vertex-frequency transfer function of the proposed Wiener filter by transforming its vertex varying impulse response that minimizes the mean square error between original and recovered signals. To facilitate the derived Wiener filter, we present a detailed derivation of a recently proposed graph Rihaczek vertex-frequency signal distribution (GRD) so as to match the structure of the proposed graph Zadeh filter, based on a graph translation operator defined by generalized convolution with a delta signal. We express the filter transfer function in terms of this graph transform of the original, noiseless signal. The form of the obtained Wiener filter is, interestingly, different than those of time-frequency Wiener filters prevalent in the classical signal processing. We also investigate the invertibility of the employed GRD. Assuming that the original graph signal of interest can be viewed as deterministic, we propose two algorithms to implement the proposed vertex-frequency Wiener filter from a single realization of a noisy, input signal. We derive mean and variance of the GRD of the noisy signal, since they are required in one of these algorithms. We apply proposed Wiener filter algorithms to denoise a standard set of images and three irregularly structured graph signals, and demonstrate their competitiveness with compared high performance denoising methods.

Longitudinal quantitative electroencephalographic study in mono-hemispheric stroke patients.

The identification of individual factors modulating clinical recovery after a stroke is fundamental to personalize the therapeutic intervention to enhance the final clinical outcome. In this framework, electrophysiological factors are promising since are more directly related to neuroplasticity, which supports recovery in stroke patients, than neurovascular factors. In this retrospective observational study, we investigated brain neuronal activity assessed via spectral features and Higuchi’s fractal dimension (HFD) of electroencephalographic signals in acute phase (2–10 days from symptom onset, T0) and sub-acute phase (2.5 months, T1) in 24 patients affected by unilateral middle cerebral artery stroke. Longitudinal assessment of the clinical deficits was performed using the National Institutes of Health Stroke Scale (NIHSS), together with the effective recovery calculated as the ratio between difference of NIHSS at T0 and T1 over the NIHSS value at T0. We observed that delta and alpha band electroencephalographic signal power changed between the two phases in both the hemispheres ipsilateral (ILH) and contralateral (CHL) to the lesion. Moreover, at T0, bilateral higher delta band power correlated with worse clinical conditions (Spearman’s rs = 0.460, P = 0.027 for ILH and rs = 0.508, P = 0.013 for CLH), whereas at T1 this occurred only for delta power in ILH (rs = 0.411, P = 0.046) and not for CHL. Inter-hemispheric difference (ILH vs. CLH) of alpha power in patients was lower at T0 than at T1 (P = 0.020). HFD at T0 was lower than at T1 (P = 0.005), and at both phases, ILH HFD was lower than CLH HFD (P = 0.020). These data suggest that inter-hemispheric low band asymmetry and fractal dimension changes from the acute to the sub-acute phase are sensitive to neuroplasticity processes which subtend clinical recovery. The study protocol was approved by the Bioethical Committee of Ospedale San Giovanni Calibita Fatebenefretelli (No. 40/2011) on July 14, 2011.

IMP regulates Kuzbanian to control the timing of Notch signalling in Drosophila follicle cells.

ABSTRACTThe timing of Drosophila egg chamber development is controlled by a germline Delta signal that activates Notch in the follicle cells to induce them to cease proliferation and differentiate. Here, we report that follicle cells lacking the RNA-binding protein IMP go through one extra division owing to a delay in the Delta-dependent S2 cleavage of Notch. The timing of Notch activation has previously been shown to be controlled by cis-inhibition by Delta in the follicle cells, which is relieved when the miRNA pathway represses Delta expression. imp mutants are epistatic to Delta mutants and give an additive phenotype with belle and Dicer-1 mutants, indicating that IMP functions independently of both cis-inhibition and the miRNA pathway. We find that the imp phenotype is rescued by overexpression of Kuzbanian, the metalloprotease that mediates the Notch S2 cleavage. Furthermore, Kuzbanian is not enriched at the apical membrane in imp mutants, accumulating instead in late endosomes. Thus, IMP regulates Notch signalling by controlling the localisation of Kuzbanian to the apical domain, where Notch cleavage occurs, revealing a novel regulatory step in the Notch pathway.

MindID

Person identification technology recognizes individuals by exploiting their unique, measurable physiological and behavioral characteristics. However, the state-of-the-art person identification systems have been shown to be vulnerable, e.g., anti-surveillance prosthetic masks can thwart face recognition, contact lenses can trick iris recognition, vocoder can compromise voice identification and fingerprint films can deceive fingerprint sensors. EEG (Electroencephalography)-based identification, which utilizes the user's brainwave signals for identification and offers a more resilient solution, has recently drawn a lot of attention. However, the state-of-the-art systems cannot achieve similar accuracy as the aforementioned methods. We propose MindID, an EEG-based biometric identification approach, with the aim of achieving high accuracy and robust performance. At first, the EEG data patterns are analyzed and the results show that the Delta pattern contains the most distinctive information for user identification. Next, the decomposed Delta signals are fed into an attention-based Encoder-Decoder RNNs (Recurrent Neural Networks) structure which assigns varying attention weights to different EEG channels based on their importance. The discriminative representations learned from the attention-based RNN are used to identify the user through a boosting classifier. The proposed approach is evaluated over 3 datasets (two local and one public). One local dataset (EID-M) is used for performance assessment and the results illustrate that our model achieves an accuracy of 0.982 and significantly outperforms the state-of-the-art and relevant baselines. The second local dataset (EID-S) and a public dataset (EEG-S) are utilized to demonstrate the robustness and adaptability, respectively. The results indicate that the proposed approach has the potential to be widely deployed in practical settings.

COMPARISON OF EEG POWER ANALYSIS FOR THE DIAGNOSIS OF DEMENTIA

The number of dementia patients is increasing according to population aging. Diagnosing dementia is important for proper treatment. We make an effort to find more convenient methodology to analysis EEG. We inspect whether we can get meaningful results with a single electrode. The concept of relative power with/without delta waves, which are distorted largely due to dementia patients' moving or eye blinking was adopted for this study. Relative power analysis was expected to minimize the amplitude differences between subjects. Seven subjects participated in the study: 3 patients with diagnosed alzheimer dementia (AD) and 4 for the normal healthy control. EEG was recorded from one frontal scalp electrode (Fp1) and 2 reference electrodes (earlobes) in accordance with the international 10/20 system. While EEG signals were recorded, participants took a rest with eyes closed. EEGs were sampled at 256Hz. EEG power bands were divided into 5 waves based on frequency: Delta(0∼4Hz), Theta(4∼8Hz), Alpha(8∼13Hz), Beta(13∼30Hz), Gamma(30∼50Hz). Absolute power is the sum of each EEG power wave. Relative power was calculated as the absolute power of each wave divided by the sum of absolute power of all waves. Relative power without delta was calculated as the absolute power of each wave divided by the sum of absolute power of the rest waves excepting for delta. Alpha wave showed the striking results among all waves. Alpha absolute power in AD decreased compared to control group. (Figure 1.A) The relative power and the relative power without delta waves in AD decreased compared to the control group (Figure 1.B, C), which has shown similiar to other studies. The alpha power's gap between AD patients and controls showed the clear distinction in the relative power without delta. The most effective result was obtained from relative power without delta. Variance of delta had most influence on the result. Even though obtaining EEG was difficult due to delta signal, we showed the possibility that dementia could be diagnosed by measuring EEG signals, especially using relative power of brain waves without delta. This study was supported by 2016 Fund of Chungnam National University. Power value of waves, p-value - *:p<0.05, **:p<0.01.

Wavelet coherence analysis of cerebral oxygenation signals measured by near-infrared spectroscopy in sailors: an exploratory, experimental study

ObjectiveThe objective of this study was to assess the effects of long-term offshore work on cerebral oxygenation oscillations in sailors based on the wavelet phase coherence (WPCO) of near-infrared spectroscopy...

Optical encryption with protection against Dirac delta and plain signal attacks.

This Letter proposes an optical encryption technique that disguises the information with modular arithmetic concepts and time-varying noise components that are unknown to the receiver. Optical encryption systems that use these techniques produce a nondeterministic system response, as well as noise like image data that can easily be generated with ordinary spatial light modulators. The principle of this technique is demonstrated for the double random phase encoding (DRPE) method. The conventional DRPE method has major vulnerabilities for Dirac signal and plain signal attacks, making them impractical for secure encryption. It is shown that the proposed encryption technique provides a robustness against these types of attacks, allowing optical DRPE to be employed in secure encryptions. Moreover, applications of this Letter are not limited to DRPE alone but can also be adopted by other optical encryption techniques such as fractional Fourier transform and Fresnel-transform-based techniques.

Opioid hedonic hotspot in nucleus accumbens shell: mu, delta, and kappa maps for enhancement of sweetness "liking" and "wanting".

A specialized cubic-millimeter hotspot in the rostrodorsal quadrant of medial shell in nucleus accumbens (NAc) of rats may mediate opioid enhancement of gustatory hedonic impact or "liking". Here, we selectively stimulated the three major subtypes of opioid receptors via agonist microinjections [mu (DAMGO), delta (DPDPE), or kappa (U50488H)] and constructed anatomical maps for functional localizations of consequent changes in hedonic "liking" (assessed by affective orofacial reactions to sucrose taste) versus "wanting" (assessed by changes in food intake). Results indicated that the NAc rostrodorsal quadrant contains a shared opioid hedonic hotspot that similarly mediates enhancements of sucrose "liking" for mu, delta, and kappa stimulations. Within the rostrodorsal hotspot boundaries each type of stimulation generated at least a doubling or higher enhancement of hedonic reactions, with comparable intensities for all three types of opioid stimulation. By contrast, a negative hedonic coldspot was mapped in the caudal half of medial shell, where all three types of opioid stimulation suppressed "liking" reactions to approximately one-half normal levels. Different anatomical patterns were produced for stimulation of food "wanting", reflected in food intake. Altogether, these results indicate that the rostrodorsal hotspot in medial shell is unique for generating opioid-induced hedonic enhancement, and add delta and kappa signals to mu as hedonic generators within the hotspot. Also, the identification of a separable NAc caudal coldspot for hedonic suppression, and separate NAc opioid mechanisms for controlling food "liking" versus "wanting" further highlights NAc anatomical heterogeneity and localizations of function within subregions of medial shell.