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Synthetic sounds, tone-beeps, vowels or syllables are typically used in the assessment of attention to auditory stimuli because they evoke a set of well-known event-related potentials, whose characteristics can be statistically contrasted. Such approach rules out the use of stimuli with non-predictable response, such as human speech. In this study we present a procedure based on the robust binary phase-shift keying (BPSK) receiver that permits the real-time detection of selective attention to human speeches in dichotic listening tasks. The goal was achieved by tagging the speeches with two barely-audible tags whose joined EEG response constitutes a reliable BPSK constellation, which can be detected by means of a BPSK receiver. The results confirmed the expected generation of the BPSK constellation by the human auditory system. Also, the bit-error rate and the information transmission rate achieved in the detection of attention fairly followed the expected curves and equations of the standard BPSK receiver. Actually, it was possible to detect attention as well as the estimation a priori of its accuracy based on the signal-to-noise ratio of the BPSK signals. This procedure, which permits the detection of the attention to human speeches, can be of interest for new potential applications, such as brain–computer interfaces, clinical assessment of the attention in real time or for entertainment.

Disorders of consciousness (DOC) are among the major challenges of contemporary medicine, mostly due to the high rates of misdiagnoses in clinical assessment, based on behavioral scales. This turns our attention to potentially objective neuroimaging methods. Paradigms based on electroencephalography (EEG) are most suited for bedside applications, but sensitive to artifacts. These problems are especially pronounced in pediatric patients.

We present the first study on the assessment of pediatric DOC patients by means of command-following procedures and involving long-latency cognitive event-related potentials. To deal with the above mentioned challenges, we construct a specialized signal processing scheme including artifact correction and rejection, parametrization, classification and final assessment of the statistical significance. To compensate for the possible bias of the tests involved in the final diagnosis, we propose the Monte Carlo evaluation of the processing pipeline. To compensate for possible sensory impairments of DOC patients, for each subject we check command-following responses to the stimuli in the major modalities: visual, tactile, and audio (words and sounds).

We test the scheme on 20 healthy volunteers and present results for 15 patients from a hospital for children with severe brain damage, in relation to their behavioral diagnosis on the Coma Recovery Scale-Revised (CRS-R).

EPR and magnetic susceptibility measurements on xMnO·(100-x)[70TeO₂·25B₂O₃·5SrF₂] glasses, within 0.1 ≤ x ≤ 50 mol% were performed. The number of isolated Mn²⁺ ions, participating at the g ≈ 4.3 resonance increases up to 1 mol% MnO and after that decreases to nil for 10 mol% MnO. The number of Mn²⁺ ions participating at the g ≈ 2.0 resonance increases when the MnO content rises. From line-width composition dependence of these glasses, for x > 3 mol%, the manganese ions participate in the superexchange magnetic interaction. Magnetic measurements revealed both Mn²⁺ and Mn³⁺ valence states as simultaneously present in the vitreous matrix and these ions are involved in negative superexchange interactions, being antiferromagnetically coupled.

The present report describes the dynamic foundations of long-standing experimental work in the field of oscillatory dynamics in the human and animal brain. It aims to show the role of multiple oscillations in the integrative brain function, memory, and complex perception by a recently introduced conceptional framework: the super-synergy in the whole brain. Results of recent experiments related to the percept of the grandmother-face support our concept of super-synergy in the whole brain in order to explain manifestation of Gestalts and Memory-Stages. This report may also provide new research avenues in macrodynamics of the brain.

Human performance is strongly influenced by the sequence of events. Decreasing the response-stimulus interval (RSI) between events qualitatively changes these so-called sequential effects. Using event-related brain potentials (ERPs) to detect electrical brain activity related to sequential patterns helps to uncover mechanisms underlying the observed performance data. Using a spatial compatible two-choice task ERPs were recorded from 32 electrode sites and Independent Component Analysis (ICA) applied to separate sequence-sensitive ERP components from two experiments, involving different RSIs. Independent Component Analysis was able to separate temporally and spatially overlapping ERP components. Sensitivity to the sequence of preceding events could be revealed in an early subcomponent of the N100 complex. Moreover, and in line with earlier reports sequential effects were also observed in P300 subcomponents.

We present a systematic and straightforward approach to the problem of single-trial classification of event-related potentials (ERP) in EEG. Instead of using a generic classifier off-the-shelf, like a neural network or support vector machine, our classifier design is guided by prior knowledge about the problem and statistical properties found in the data. In particular, we exploit the well-known fact that event-related drifts in EEG potentials, albeit hard to detect in a single trial, can well be observed if averaged over a sufficiently large number of trials. We propose to use the average signal and its variance as a generative model for each event class and use Bayes' decision rule for the classification of new and unlabeled data. The method is successfully applied to a data set from the NIPS*2001 Brain–Computer Interface post-workshop competition. Our result turned out to be competitive with the best result of the competition.

The purpose of this paper is to improve the financial management efficiency of large enterprises and enhance the overall operation vitality of enterprises. First, the connotation and characteristics of enterprise resource planning (ERP) are analyzed, and the financial ERP system is established. Then, the relevant dynamic models of nonlinear systems are classified and their characteristics are analyzed. Moreover, the system model of enterprise financial risk management is constructed based on the key success factors of project implementation risk and control flow chart of project life cycle. Finally, based on MATLAB software, $Z$ large enterprise is taken as an example to evaluate the implementation effect of analytical hierarchy process (AHP) algorithm and back propagation neural network (BPNN) algorithm in ERP system. The results reveal that compared with 2019, the capital concentration in 2020 increases by 8%, the operating cost decreases by 23.6%, and the expense reimbursement process time decreases from 60–80 days to about 6 days. The expected output and assessment result of AHP are 6.912 and 6.823, respectively, and the error between them is 0.0196. The expected output and assessment result of BPNN are 6.798 and 6.675, respectively, and the error between them is 0.0121. The error value of BPNN in ERP implementation effect assessment is less than that of AHP, which indicates that the assessment effect of BPNN is better than that of AHP.

A framework for investigating information processing in cortico-thalamocortical (cortico-TC) networks is presented, that in part can be used to model and interpret individual changes in electroencephalographic spectra and event-related potentials such as those from the Brain Resource International Database. Scientific work covering neurophysiology, TC firing modes, and TC models are explored in the framework to explain how the brain might process complex information in a multistage process. It is proposed that the thalamus and the cortico-TC system have unique ionic properties and transmission delays (in humans), which are suited to the function of taking "snapshots" or samples of complex environmental stimuli, rather than continuous data streams. This leads to careful and sequential coordination of stimulus and response processes, and increases the probability of information transfer and the resulting information complexity in higher cortical regions. Given the scope of this framework, the multidimensional and standardized Brain Resource International Database provides a pertinent set of measures for both testing hypotheses generated from the model, and for fitting the model to experimental data to investigate mechanisms underlying information processing.

The effects of methylphenidate (MPH) on 32 healthy human male volunteers (aged 18 to 25 years, mean age = 22.26) were examined using a within-subject design. Each participant attended six testing periods, held once per week. Within each testing period, three repeat testing sessions were undertaken: pre-medication, on-medication and two hours post-medication. In these sessions, dose was manipulated (placebo, 5 mg, 15 mg or 45 mg) according a double-blind placebo design. In this report, we focus on behavioral, autonomic arousal (heart rate, skin conductance) and psychophysiological (ERP) data acquired during the working memory task. We found increased autonomic arousal (heart rate, skin conductance and blood pressure) with MPH. A linear reduction in reaction time, omission errors and target P3 latency, and a corresponding increase in background P3 amplitude was observed with increased MPH dose. The relationship between these measures supported an increase in performance and underlying brain function with MPH. To our knowledge, this is the first paper to use behavioral, arousal and electrophysiological measures in an integrative approach to study the effects of MPH on healthy adults.

The current study aimed to investigate whether children and adolescents diagnosed with Attention Deficit/Hyperactivity Disorder Predominantly Inattentive (AD/HD-in; Child n = 24, Adolescent n = 33) and Combined (AD/HD-com; Child n = 30, Adolescent n = 42) subtypes were more distractible than controls (Child n = 54; Adolescents n = 75), by assessing event-related potential (ERP), performance and peripheral arousal measures. All AD/HD groups displayed smaller amplitudes and/or shorter latencies of the P3a ERP component — thought to reflect involuntary attention switching — following task-deviant novel stimuli (checkerboard patterns) embedded in a Working Memory (WM) task. The P3a results suggested that both AD/HD-in and AD/HD-com subtypes ineffectively evaluate deviant stimuli and are hence more "distractible". These abnormalities were most pronounced over the central areas. AD/HD groups did not display any abnormalities in averaged heart rate over the WM task, a measure of peripheral arousal. They did display abnormalities in performance measures from the task, but these were unrelated to P3a abnormalities. AD/HD groups also displayed a number of deficits on Switching of Attention and Verbal Memory tasks, however, the pattern of abnormality mostly reflected general cognitive deficits rather than resulting from distraction.

Aims: Following an integrative neuroscience perspective, we propose that cognitive and emotional functions are integrally linked, and that genetic polymorphisms which impact upon neural processes may have complementary effects on these functions. The brain-derived neurotrophic factor (BDNF) 66Met allele may contribute to both cognitive and emotional aspects of the depression phenotype.

Methods: In 374 nonclinical subjects, BDNF genotype differences in task-related ERPs, emotion, memory, and EEG cortical arousal were examined.

Results: Using path modeling, higher negative affect in Met homozygotes was predicted by slow-wave EEG via the mediating effects of neuroticism. Both negative affect and working memory deficits were predicted by disturbances in emotion- and cognitive-related ERPs. This model held across groups with varying levels of depressed mood.

Discussion: Since impairments in emotion and working memory are core features of major depression, the BDNF Met allele may contribute to vulnerability for this disorder. An integrative approach in which genotypes are considered in combination with brain function and behavioral measures may be important in identifying profile markers of depression.

Integrative Significance: This study directly demonstrates that cognitive and emotional neural networks are not parallel independent systems, but rather highly integrated with effects on both cognitive performance and emotional behavior.

The aim of this study was to extend our understanding of the "asynchrony" phenomenon by examining the existence of several additional differences in brain activity. The differences which were investigated were the difference between the left and right hemisphere processing, the anterior and posterior areas processing and the differences between the different stages of information processing. These differences could account as an additional explanation for word decoding failure among individuals with dyslexia. The research utilized behavioral and electrophysiological (ERP - Event Related Potentials) measures in skilled and dyslexic university students. The subjects performed a lexical decision task presented in the visual and auditory modalities. The dyslexics exhibited a larger processing time interval between the activation of the P2 and P3 components, between the left and right hemisphere and between posterior and anterior regions of the cortex. Disharmony of the dyslexic brain is suggested as a possible explanation for the dyslexia phenomenon.

Purpose: This paper investigates and compares challenges and success factors within different supply chain ERPs used globally across humanitarian and private organizations in Africa, Asia, Canada, Australia, Europe, and the Americas. Eighteen challenges and 27 success factors were selected from literature published between 2015 and 2020 to determine whether they are equally relevant globally in the private and humanitarian sectors.

Design/methodology/approach: The research utilized an anonymous online questionnaire advertised on different social media websites and completed by 50 humanitarian supply chain professionals and 53 private sector professionals worldwide. The collected data was analyzed using a descriptive statistic–crosstabulation analysis to show the differences or similarities in supply chain professionals’ opinions from humanitarian and private organizations. Additionally, the hypotheses were tested by using the Mann–Whitney Test.

Findings: Findings revealed that all the examined success factors were supported except one, which was similar in both sectors. However, the challenges during the implementation of ERPs differ in these two sectors — with four success factors not supported in the humanitarian sector and nine not supported challenges in the private sector.

Originality: This study’s significance is that, as per the researchers’ knowledge, such a comparative study was never done before, and it will allow both sectors’ professionals to understand all the elements mentioned above better and integrate them while implementing supply chain ERPs.

Access control plays an important role in ERP system. Conventional ways of access control are access control list, access control matrix, and capability listing, which have a rigid security mechanism and lead to poor performance. The paper addresses a RBAC-based user authorization mechanism, which has a layered architecture, including database layer, authorization information layer, authentication layer, and presentation layer. Based on RBAC, security issues are considered at each layer, so that it offers better flexibility and scalability. MVC, middleware techniques are taken to build this security mechanism. According to the hierarchy, it presents the design and implementation of each layer. The system security is enhanced significantly by means of the mechanism.

An intelligent method based on wavelet neural network for evaluating effectiveness of ERP application is presented. Following the minimum mean-square error principle, the scale and delay parameters of wavelet functions and weight of neural network are solved by using of conjugate gradient algorithm. Furthermore, a diagnostic algorithm for evaluating ERP effectiveness based on a wavelet neural network is given with example so as to provide a quantitative method for rapid evaluation of ERP effectiveness.

There has been considerable recent interest in the identification of neural correlates of the Attentional Blink (AB), and the development of neurally explicit computational models. A prominent example is the Simultaneous Type Serial Token (ST²) model, which suggests that when the visual system detects a task-relevant item, a spatially specific Transient Attentional Enhancement (TAE), called the blaster, is triggered. This paper reports on our investigations into EEG activity during the AB, and a hypothesized correlation between the blaster and the N2pc ERP component. Specifically, we demonstrate that the temporal firing pattern of the blaster in the model matches the N2pc component in human ERP recordings, for targets that are seen and missed inside and outside the attentional blink window. Such a correlation between a computational account of the AB and ERP data provides useful insights into the processes underlying selectivity in temporal attention.

Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive method of altering patterns of brain activity. rTMS has been applied to a wide variety of psychiatric and neurological conditions and is generally regarded as safe and has no lasting side effects. Within the context of autism spectrum disorders (ASD), rTMS has a unique application as a treatment modality. Recent evidence suggests the symptoms of ASD may be related to increased cortical excitability and, specifically, an increased ratio of cortical excitation to inhibition accompanied by deficiencies in long-range cortical connectivity. Locally over-connected neural networks may explain the superior ability of autistic children in isolated tasks (e.g., visual discrimination) while, at the same time, deficiencies in long-range connectivity may explain other features of the disorder (e.g., lack of social reciprocity). An increased ratio of cortical excitation to inhibition and higher-than-normal cortical “noise” may also explain the strong aversive reactions to auditory, tactile, and visual stimuli frequently recorded in autistic individuals as well as a higher incidence of epilepsy. Using specific parameters of stimulation, rTMS has been shown to increase cortical inhibition by selectively activating cortical inhibitory neurons. In a number of investigations, our group evaluated the effects of rTMS on indices of selective attention and executive functioning, as well as measures of social awareness, hyperactivity, irritability, and repetitive/stereotyped behavior. Subjects with ASD were assessed at baseline and following rTMS with electroencephalographic (EEG) and event-related potential (ERP) measures of selective attention and executive functioning. Subjects were also assessed for ASD symptomatology using neuropsychological questionnaires. Following rTMS, subjects showed significant improvement in EEG and ERP measures of selective attention and executive functioning, and also showed significant improvement in measures of irritability and repetitive/stereotyped behavior. Our preliminary findings in three experimental studies using 6-, 12-, and 18 session-long rTMS courses in children with autism indicate that rTMS has the potential to become an important therapeutic tool in research and treatment, and may play an important role in improving the quality of life for many individuals with ASD. Further research directions are proposed.