Electrophysiological correlates of listening effort: neurodynamical modeling and measurement

An increased listing effort represents a major problem in humans with hearing impairment. Neurodiagnostic methods for an objective listening effort estimation might support hearing instrument fitting procedures. However the cognitive neurodynamics of listening effort is far from being understood and its neural correlates have not been identified yet. In this paper we analyze the cognitive neurodynamics of listening effort by using methods of forward neurophysical modeling and time-scale electroencephalographic neurodiagnostics. In particular, we present a forward neurophysical model for auditory late responses (ALRs) as large-scale listening effort correlates. Here endogenously driven top–down projections related to listening effort are mapped to corticothalamic feedback pathways which were analyzed for the selective attention neurodynamics before. We show that this model represents well the time-scale phase stability analysis of experimental electroencephalographic data from auditory discrimination paradigms. It is concluded that the proposed neurophysical and neuropsychological framework is appropriate for the analysis of listening effort and might help to develop objective electroencephalographic methods for its estimation in future.     

EEG correlates of social creativity

EEG correlates of social creativity defined as ability to originally and flexibly interpret social significant situations were studied. It was found that the alpha2 and gamma2 rhythms are specific bands which make it possible to tell the difference between social creativity and control task. Solving socially significant problems in experimental conditions is accompanied by an increase in the power of the delta and gamma2 bands and desynchronization in the alpha2 band less pronounced in divergent tasks than during the interpretation of convergent visual stimuli.     

Force and EMG correlates of constant effort contractions

The relation between the force exerted by the left arm and the electromyographic (EMG) activity of the brachial biceps and triceps muscles was examined during constant effort contractions maintained for 120 s. The initial force levels were set at 35%, 50% and 65% of each subject's maximal strength, but thereafter no feedback was provided. In contrast to previous results it was found that the direction of the change in force and EMG during constant effort contractions was dependent on the level of force initially exerted. During the lowest initial force contraction the force remained constant, while for the other two force levels there was an exponential decline in the force exerted. These changes in force during the three contractions were well described by an exponential equation with two free parameters. The EMG also varied as a function of initial force. For the higher two forces the amplitude of the EMG fluctuated during the first 40 s but thereafter remained constant, while it increased steadily during the lowest initial force contraction. These results suggest that depending upon the initial level of exertion either peripheral sensory cues relating to the actual force exerted, or centrally-generated signals reflecting the magnitude of the descending motor command may be used by subjects to maintain a constant level of muscular effort.     

Automatic detection of epileptic EEG signals using higher order cumulant features

The unpredictability of the occurrence of epileptic seizures makes it difficult to detect and treat this condition effectively. An automatic system that characterizes epileptic activities in EEG signals would allow patients or the people near them to take appropriate precautions, would allow clinicians to better manage the condition, and could provide more insight into these phenomena thereby revealing important clinical information. Various methods have been proposed to detect epileptic activity in EEG recordings. Because of the nonlinear and dynamic nature of EEG signals, the use of nonlinear Higher Order Spectra (HOS) features is a seemingly promising approach. This paper presents the methodology employed to extract HOS features (specifically, cumulants) from normal, interictal, and epileptic EEG segments and to use significant features in classifiers for the detection of these three classes. In this work, 300 sets of EEG data belonging to the three classes were used for feature extraction and classifier development and evaluation. The results show that the HOS based measures have unique ranges for the different classes with high confidence level (p-value < 0.0001). On evaluating several classifiers with the significant features, it was observed that the Support Vector Machine (SVM) presented a high detection accuracy of 98.5% thereby establishing the possibility of effective EEG segment classification using the proposed technique.     

Spectral analysis of the human EEG while listening to music

EEG was recorded from 16 electrodes (International 10-20 System) in 14 healthy volunteers aged from 18 to 45 in the state of rest and during listening to music (popular classical symphonic pieces). The EEG spectral analysis was carried out. Presentation of musical pieces increased the EEG spectral power in the alpha-range in the parietal and occipital areas of both hemispheres. During repeated listening of the same musical fragment there was a tendency for attenuation of these changes. A significant decrease in the peak frequency of the alpha-band was found in the process of listening. The spectral values did not significantly differ between the left and right hemispheres. The findings suggest a decrease in the level of CNS activation under the influence of music.     

Individual-typologic features of EEG structure

EEG monopolarly recorded in points F3, F4, O1, O2 of 20 healthy subjects in six states (quiet wakefulness with open or closed eyes, spontaneous button pressings in arbitrary moments of time, listening to clicks, reaction to clicks by pressing the button at random or at equal intervals between stimuli), were processed by means of the computer program transforming the raw EEG tracings to a sequence of stationary segments. The accumulated segments were divided into classes of "similar" ones by a two-stage procedure of cluster analysis. In each lead six types of segments were identified forming populations of structural units of an individual human EEG. Four types were recorded all over the brain: their spectra were of a great resemblance in different brain areas. The EEG of each individual was characterized by a certain combination of segment types which practically did not change by their quality in different states of the subject.     

Waveguide model of the hearing aid earmold system

Background

Epstein-Barr virus (EBV) is associated to the etio-pathogenesis of an increasing number of tumors. Detection of EBV in pathology samples is relevant since its high prevalence in some cancers makes the virus a promising target of specific therapies. RNA in situ hybridization (RISH) is the standard diagnostic procedure, while polymerase chain reaction (PCR)-based methods are used for strain (EBV type-1 or 2) distinction. We performed a systematic comparison between RISH and PCR for EBV detection, in a group of childhood B-cell Non-Hodgkin lymphomas (NHL), aiming to validate PCR as a first, rapid method for the diagnosis of EBV-associated B-cell NHL.

Methods

EBV infection was investigated in formalin fixed paraffin-embedded tumor samples of 41 children with B-cell NHL, including 35 Burkitt's lymphoma (BL), from Rio de Janeiro, Brazil, by in situ hybridization of EBV-encoded small RNA (EBER-RISH) and PCR assays based on EBNA2 amplification.

Results

EBV genomes were detected in 68% of all NHL. Type 1 and 2 accounted for 80% and 20% of EBV infection, respectively. PCR and RISH were highly concordant (95%), as well as single- and nested-PCR results, allowing the use of a single PCR round for diagnostic purposes. PCR assays showed a sensitivity and specificity of 96% and 100%, respectively, with a detection level of 1 EBV genome in 5,000–10,000 EBV-negative cells, excluding the possibility of detecting low-number EBV-bearing memory cells.

Conclusion

We describe adequate PCR conditions with similar sensitivity and reliability to RISH, to be used for EBV diagnostic screening in high grade B-NHL, in "at risk" geographic regions.     

Classification of voice disorder in children with cochlear implantation and hearing aid using multiple classifier fusion

Background  

Speech production and speech phonetic features gradually improve in children by obtaining audio feedback after cochlear implantation or using hearing aids. The aim of this study was to develop and evaluate automated classification of voice disorder in children with cochlear implantation and hearing aids.     

Deconstructing insight: EEG correlates of insightful problem solving

Background

Cognitive insight phenomenon lies at the core of numerous discoveries. Behavioral research indicates four salient features of insightful problem solving: (i) mental impasse, followed by (ii) restructuring of the problem representation, which leads to (iii) a deeper understanding of the problem, and finally culminates in (iv) an “Aha!” feeling of suddenness and obviousness of the solution. However, until now no efforts have been made to investigate the neural mechanisms of these constituent features of insight in a unified framework.

Methodology/Principal Findings

In an electroencephalographic study using verbal remote associate problems, we identified neural correlates of these four features of insightful problem solving. Hints were provided for unsolved problems or after mental impasse. Subjective ratings of the restructuring process and the feeling of suddenness were obtained on trial-by-trial basis. A negative correlation was found between these two ratings indicating that sudden insightful solutions, where restructuring is a key feature, involve automatic, subconscious recombination of information. Electroencephalogram signals were analyzed in the space×time×frequency domain with a nonparametric cluster randomization test. First, we found strong gamma band responses at parieto-occipital regions which we interpreted as (i) an adjustment of selective attention (leading to a mental impasse or to a correct solution depending on the gamma band power level) and (ii) encoding and retrieval processes for the emergence of spontaneous new solutions. Secondly, we observed an increased upper alpha band response in right temporal regions (suggesting active suppression of weakly activated solution relevant information) for initially unsuccessful trials that after hint presentation led to a correct solution. Finally, for trials with high restructuring, decreased alpha power (suggesting greater cortical excitation) was observed in right prefrontal area.

Conclusions/Significance

Our results provide a first account of cognitive insight by dissociating its constituent components and potential neural correlates.     

EEG correlates of attentional load during multiple object tracking

While human subjects tracked a subset of ten identical, randomly-moving objects, event-related potentials (ERPs) were evoked at parieto-occipital sites by task-irrelevant flashes that were superimposed on either tracked (Target) or non-tracked (Distractor) objects. With ERPs as markers of attention, we investigated how allocation of attention varied with tracking load, that is, with the number of objects that were tracked. Flashes on Target discs elicited stronger ERPs than did flashes on Distractor discs; ERP amplitude (0-250 ms) decreased monotonically as load increased from two to three to four (of ten) discs. Amplitude decreased more rapidly for Target discs than Distractor discs. As a result, with increasing tracking loads, the difference between ERPs to Targets and Distractors diminished. This change in ERP amplitudes with load accords well with behavioral performance, suggesting that successful tracking depends upon the relationship between the neural signals associated with attended and non-attended objects.     

EEG correlates of geno-phenotypical features of the brain development in children of the native and newcomers' population of the Russian North-East

Traditional and original methods of EEG analysis were used to study the brain electrical activity maturation in 156 children and adolescents from 7 to 17 years old who represented the native (Koryaks and Evenks) and newcomers' populations living in severe climatic and geographic conditions of the Russian North-East. New data revealing age-, sex- and ethnic-related features in quantitative EEG parameters are presented. Markers are obtained that characterize alterations in the structure of interaction between different EEG rhythms. The results demonstrate age-dependent transformation of this structure separated in time for both different cortical areas and different EEG frequency bands. These alterations show time lag from 2 to 3 years in children of native population compared to the newcomers. The revealed differences are assumed to reflect geno-phenotypical features of morpho-functional CNS development in children of the native and newcomers' population that depend on strong adaptation tension for extreme environmental conditions.