The relationship between short-term memory capacity and EEG power spectral density

Multiplying memory span by mental speed, we obtain the information entropy of short-term memory capacity, which is rate-limiting for cognitive functions and corresponds with EEG power spectral density. The number of EEG harmonics (n = 1, 2,, 9) is identical with memory span, and the eigenvalues of the EEG impulse response are represented by the zero-crossings up to the convolved fundamental, the P300. In analogy to quantum mechanics the brain seems to be an ideal detector simply measuring the energy of wave forms. No matter what the stimulus is and how the brain behaves, the metric of signal and memory can always be understood as a superposition of n states of different energy and their eigenvalues.     

Effects of voluntary control of the functional state on the organization of cortical processes during mnemenic activity in schoolchildren aged nine to ten years

In schoolchildren aged nine to ten years, the analysis of EEG indices (spectral power density, the function of coherence in the α band) of different cortex regions in four experimental situations—quiet wakefulness, mnemenic activity, relaxation, and mnemenic activity in the postrelaxation period—was performed. In the mnemenic activity situations, a task for determining the short-term auditory-speech memory span was used. A positive effect of relaxation on the efficiency of mnemenic activity expressed in an increase in the short-term memory span was found. Comparison of groups formed according to the increase in the memory span showed differences in the dynamics of coherence indices. Only in children with a pronounced postrelaxation increase in the memory span in the situation of mnemenic activity was an increase in coherence in the high-frequency subrange of the α band of the EEG detected, whose functional significance is related to selective inhibition.     

Computational Immunology Meets Bioinformatics: The Use of Prediction Tools for Molecular Binding in the Simulation of the Immune System

We present a new approach to the study of the immune system that combines techniques of systems biology with information provided by data-driven prediction methods. To this end, we have extended an agent-based simulator of the immune response, C-ImmSim, such that it represents pathogens, as well as lymphocytes receptors, by means of their amino acid sequences and makes use of bioinformatics methods for T and B cell epitope prediction. This is a key step for the simulation of the immune response, because it determines immunogenicity. The binding of the epitope, which is the immunogenic part of an invading pathogen, together with activation and cooperation from T helper cells, is required to trigger an immune response in the affected host. To determine a pathogen''s epitopes, we use existing prediction methods. In addition, we propose a novel method, which uses Miyazawa and Jernigan protein–protein potential measurements, for assessing molecular binding in the context of immune complexes. We benchmark the resulting model by simulating a classical immunization experiment that reproduces the development of immune memory. We also investigate the role of major histocompatibility complex (MHC) haplotype heterozygosity and homozygosity with respect to the influenza virus and show that there is an advantage to heterozygosity. Finally, we investigate the emergence of one or more dominating clones of lymphocytes in the situation of chronic exposure to the same immunogenic molecule and show that high affinity clones proliferate more than any other. These results show that the simulator produces dynamics that are stable and consistent with basic immunological knowledge. We believe that the combination of genomic information and simulation of the dynamics of the immune system, in one single tool, can offer new perspectives for a better understanding of the immune system.     

Principal Components of Electroencephalographic Spectrum as Markers of Opponent Processes Underlying Ultradian Sleep Cycles

Sleep-wake regulation involves reciprocal interactions between sleep- and wake-promoting processes that inhibit one another. To uncover the signatures of the opponent processes underlying ultradian sleep cycles, principal component analysis was performed on the sets of 16 single-Hz log-transformed electroencephalographic (EEG) power densities (1–16?Hz frequency range). Data were collected during unrestricted night sleep followed by 9 20-min naps (14 women aged 17–55 yrs) and during 12 20-min naps after either restriction or deprivation of sleep (9 males and 9 males, respectively, aged 18–22 yrs). It was found that any subset of power spectra could be reduced to the invariant four–principal component structure. The time courses of scores on these four components might be interpreted as the spectral EEG markers of the kinetics of two pairs of opponent chronoregulatory processes. In a sequence of ultradian sleep cycles, the 1st and 2nd components represent the alternations between competing drives for sleep and wakefulness, respectively, whereas the 3rd and 4th components reflect the alternations between light and deep sleep, respectively. The results suggest that principal component structuring of EEG spectrum can be employed for derivation of the parameters of the quantitative models conceptualizing the three major aspects of sleep-wake regulation—homeostatic, circadian, and ultradian processes. (Author correspondence: putilov@ngs.ru)     

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.

     

IL-15 activates telomerase and minimizes telomere loss and may preserve the replicative life span of memory CD8+ T cells in vitro

The preservation of the replicative life span of memory CD8(+) T cells is vital for long-term immune protection. Although IL-15 plays a key role in the homeostasis of memory CD8(+) T cells, it is unknown whether IL-15 regulates the replicative life span of memory CD8(+) T cells. In this study, we report an analysis of telomerase expression and telomere length in human memory phenotype CD8(+) T cells maintained by IL-15 in vitro. We demonstrate that IL-15 is capable of activating telomerase in memory CD8(+) T cells via Jak3 and PI3K signaling pathways. Furthermore, IL-15 induces a sustained level of telomerase activity over long periods of time, and in turn minimizes telomere loss in memory CD8(+) T cells after substantial cell divisions. These findings suggest that IL-15 activates stable telomerase expression and compensates telomere loss in memory phenotype CD8(+) T cells, and that telomerase may play an important role in memory CD8(+) T cell homeostasis.     

Circadian rhythm parameters of endocrine functions in elderly subjects during the seventh to the ninth decade of life

The circadian rhythm of 17 endocrine parameters (ACTH, aldosterone, cortisol, C-peptide, DHEA-S, FSH, growth hormone, insulin, LH, 17-OH progesterone, prolactin, testosterone, total T3, total T4 and TSH and estradiol and progesterone in women only) were studied in 63 clinically apparently healthy men (124 profiles) and 86 women (154 profiles) during the 7th to 9th decade of life. The subjects lived under very uniform conditions in a home for the aged with their daily schedule standardized by institutional routine with rest at night on the average from 21:30 to 06:30 local time and 3 daily meals at 08:30, 13:00 and 18:30. Blood was drawn over a 24-h span at 4-h intervals. Circadian periodicity was ascertained and the rhythm parameters quantified by cosinor analysis. In clinically healthy elderly subjects, circadian periodicity persisted in most parameters studied well into the 9th decade of life. The timing of the circadian rhythm was comparable between subjects in their 7th decade and 9th decade of life with the exception of cortisol and DHEA-S, which showed a phase advance with advancing age. A decrease in circadian amplitude is limited during this part of the human life span to only a few of the functions investigated and with the exception of prolactin in the women, a decrease in amplitude did accompany a decrease in MESOR.     

A new 2-D graphical representation of DNA sequences and their numerical characterization

We consider a novel 2-D graphical representation of DNA sequences according to chemical structures of bases, reflecting distribution of bases with different chemical structure, preserving information on sequential adjacency of bases, and allowing numerical characterization. The representation avoids loss of information accompanying alternative 2-D representations in which the curve standing for DNA overlaps and intersects itself. Based on this representation we present a numerical characterization approach by the leading eigenvalues of the matrices associated with the DNA sequences. The utility of the approach is illustrated on the coding sequences of the first exon of human beta-globin gene.     

Stability of cluster solutions in a cooperative consumer chain model

We study a cooperative consumer chain model which consists of one producer and two consumers. It is an extension of the Schnakenberg model suggested in Gierer and Meinhardt [Kybernetik (Berlin), 12:30–39, 1972] and Schnakenberg (J Theor Biol, 81:389–400, 1979) for which there is only one producer and one consumer. In this consumer chain model there is a middle component which plays a hybrid role: it acts both as consumer and as producer. It is assumed that the producer diffuses much faster than the first consumer and the first consumer much faster than the second consumer. The system also serves as a model for a sequence of irreversible autocatalytic reactions in a container which is in contact with a well-stirred reservoir. In the small diffusion limit we construct cluster solutions in an interval which have the following properties: The spatial profile of the third component is a spike. The profile for the middle component is that of two partial spikes connected by a thin transition layer. The first component in leading order is given by a Green’s function. In this profile multiple scales are involved: The spikes for the middle component are on the small scale, the spike for the third on the very small scale, the width of the transition layer for the middle component is between the small and the very small scale. The first component acts on the large scale. To the best of our knowledge, this type of spiky pattern has never before been studied rigorously. It is shown that, if the feedrates are small enough, there exist two such patterns which differ by their amplitudes.We also study the stability properties of these cluster solutions. We use a rigorous analysis to investigate the linearized operator around cluster solutions which is based on nonlocal eigenvalue problems and rigorous asymptotic analysis. The following result is established: If the time-relaxation constants are small enough, one cluster solution is stable and the other one is unstable. The instability arises through large eigenvalues of order $O(1)$ . Further, there are small eigenvalues of order $o(1)$ which do not cause any instabilities. Our approach requires some new ideas: (i) The analysis of the large eigenvalues of order $O(1)$ leads to a novel system of nonlocal eigenvalue problems with inhomogeneous Robin boundary conditions whose stability properties have been investigated rigorously. (ii) The analysis of the small eigenvalues of order $o(1)$ needs a careful study of the interaction of two small length scales and is based on a suitable inner/outer expansion with rigorous error analysis. It is found that the order of these small eigenvalues is given by the smallest diffusion constant ${\epsilon }_2^2$ .     

Theoretical analysis on relationship between the neural activity and the EEG

Firstly, a collective oscillation mode of the neural activity is derived from the neural network system by using the multicompartment equation and the projection operator technique. This technique takes into account higher order interactions among neurons. The solution of the equation gives a chain structure with an infinite number of circuit loops in which each of them is only composed of four neurons. The obtained eigenvalues are quite similar to the spectrum of frequencies of the EEG. Secondly, the time-dependent behavior of the observed EEG is simulated by starting from the elementary process of action potential trains of neurons, which includes the effect of the collective oscillation mode mentioned above. This gives a comprehensive derivation of the EEG from the neural activity of action potentials. The simulation assumes that information of the action potential trains can be transmitted to the EEG through the intermediate states of the postsynaptic potential trains and the slow waves. The paper reports that a slightly modulated activity of a relatively small amount of neurons can cause a strong influence on the shape of the global EEG and that the calculated results reproduce the characteristic features of the EEG in a rat such as the theta rhythm, the spindle wave and the arousal wave.     

Comparison of the effects of the subjective complexity and verbal creativity on EEG spectral power parameters

The EEG recording was made when the subjects performed tasks that involved overcoming the stereotype (creative) and retrieving information from memory (noncreative) with the usual and complicated presentation of the initial material (incomplete proverbs and sayings without concluding words). The subjective complexity of the task performance under different conditions was assessed. The EEG power from 19 EEG derivations was compared in the β₂ and γ frequency bands. The creative task performance was associated with a marked increase in the EEG power; significantly more complicated noncreative tasks were not accompanied by marked changes in the EEG power in these bands.     

An improved alignment-free model for dna sequence similarity metric

Background

DNA Clustering is an important technology to automatically find the inherent relationships on a large scale of DNA sequences. But the DNA clustering quality can still be improved greatly. The DNA sequences similarity metric is one of the key points of clustering. The alignment-free methodology is a very popular way to calculate DNA sequence similarity. It normally converts a sequence into a feature space based on words’ probability distribution rather than directly matches strings. Existing alignment-free models, e.g. k-tuple, merely employ word frequency information and ignore many types of useful information contained in the DNA sequence, such as classifications of nucleotide bases, position and the like. It is believed that the better data mining results can be achieved with compounded information. Therefore, we present a new alignment-free model that employs compounded information to improve the DNA clustering quality.

Results

This paper proposes a Category-Position-Frequency (CPF) model, which utilizes the word frequency, position and classification information of nucleotide bases from DNA sequences. The CPF model converts a DNA sequence into three sequences according to the categories of nucleotide bases, and then yields a 12-dimension feature vector. The feature values are computed by an entropy based model that takes both local word frequency and position information into account. We conduct DNA clustering experiments on several datasets and compare with some mainstream alignment-free models for evaluation, including k-tuple, DMk, TSM, AMI and CV. The experiments show that CPF model is superior to other models in terms of the clustering results and optimal settings.

Conclusions

The following conclusions can be drawn from the experiments. (1) The hybrid information model is better than the model based on word frequency only. (2) For DNA sequences no more than 5000 characters, the preferred size of sliding windows for CPF is two which provides a great advantage to promote system performance. (3) The CPF model is able to obtain an efficient stable performance and broad generalization.     

Local Properties of Vigilance States: EMD Analysis of EEG Signals during Sleep-Waking States of Freely Moving Rats

Understanding the inherent dynamics of the EEG associated to sleep-waking can provide insights into its basic neural regulation. By characterizing the local properties of the EEG using power spectrum, empirical mode decomposition (EMD) and Hilbert-spectral analysis, we can examine the dynamics over a range of time-scales. We analyzed rat EEG during wake, NREMS and REMS using these methods. The average instantaneous phase, power spectral density (PSD) of intrinsic mode functions (IMFs) and the energy content in various frequency bands show characteristic changes in each of the vigilance states. The 2nd and 7th IMFs show changes in PSD for wake and REMS, suggesting that those modes may carry wake- and REMS-associated cognitive, conscious and behavior-specific information of an individual even though the EEG may appear similar. The energy content in θ₂ (6Hz-9Hz) band of the 1st IMF for REMS is larger than that of wake. The decrease in the phase function of IMFs from wake to REMS to NREMS indicates decrease of the mean frequency in these states, respectively. The rate of information processing in waking state is more in the time scale described by the first three IMFs than in REMS state. However, for IMF5-IMF7, the rate is more for REMS than that for wake. We obtained Hilbert-Huang spectral entropy, which is a suitable measure of information processing in each of these state-specific EEG. It is possible to evaluate the complex dynamics of the EEG in each of the vigilance states by applying measures based on EMD and Hilbert-transform. Our results suggest that the EMD based nonlinear measures of the EEG can provide useful estimates of the information possessed by various oscillations associated with the vigilance states. Further, the EMD-based spectral measures may have implications in understanding anatamo-physiological correlates of sleep-waking behavior and clinical diagnosis of sleep-pathology.     

A Psychometric Measure of Working Memory Capacity for Configured Body Movement

Working memory (WM) models have traditionally assumed at least two domain-specific storage systems for verbal and visuo-spatial information. We review data that suggest the existence of an additional slave system devoted to the temporary storage of body movements, and present a novel instrument for its assessment: the movement span task. The movement span task assesses individuals'' ability to remember and reproduce meaningless configurations of the body. During the encoding phase of a trial, participants watch short videos of meaningless movements presented in sets varying in size from one to five items. Immediately after encoding, they are prompted to reenact as many items as possible. The movement span task was administered to 90 participants along with standard tests of verbal WM, visuo-spatial WM, and a gesture classification test in which participants judged whether a speaker''s gestures were congruent or incongruent with his accompanying speech. Performance on the gesture classification task was not related to standard measures of verbal or visuo-spatial working memory capacity, but was predicted by scores on the movement span task. Results suggest the movement span task can serve as an assessment of individual differences in WM capacity for body-centric information.     

The age-related features of influence biofeedback training on efficiency of functional state voluntary regulation in young schoolchildren

The aim of the study was to assess an impact of biofeedback training (5 sessions) onto the voluntary regulation of the brain functional state (relaxation) in two groups of children of 7-8 and 9-10 years old. EEG alpha-band spectral coherence and skin resistance were measured during pre-relaxation, relaxation and post-relaxation phases before and after training. Short-term memory test was used to evaluate behavioral changes in functional state regulation before and after training. The group of children of 9-10 y.o. was the only group that showed any significant relaxation-related changes of spectral coherence in alpha-band after training. Besides, that group showed a significant post-relaxation improvement in short-term memory volume. We found a number of individual psychophysiological indices that influenced an efficiency of the biofeedback training.     

A novel approach to the detection of genomic approximate tandem repeats in the Levenshtein metric.

An efficient algorithm for detecting approximate tandem repeats in genomic sequences is presented. The algorithm is based on innovative statistical criteria to detect candidate regions which may include tandem repeats; these regions are subsequently verified by alignments based on dynamic programming. No prior information about the period size or pattern is needed. Also, the algorithm is virtually capable of detecting repeats with any period. An implementation of the algorithm is compared with the two state-of-the-art tandem repeats detection tools to demonstrate its effectiveness both on natural and synthetic data. The algorithm is available at www.cs.brown.edu/people/domanic/tandem/.     

Deployment of Spatial Attention towards Locations in Memory Representations. An EEG Study

Recalling information from visual short-term memory (VSTM) involves the same neural mechanisms as attending to an actually perceived scene. In particular, retrieval from VSTM has been associated with orienting of visual attention towards a location within a spatially-organized memory representation. However, an open question concerns whether spatial attention is also recruited during VSTM retrieval even when performing the task does not require access to spatial coordinates of items in the memorized scene. The present study combined a visual search task with a modified, delayed central probe protocol, together with EEG analysis, to answer this question. We found a temporal contralateral negativity (TCN) elicited by a centrally presented go-signal which was spatially uninformative and featurally unrelated to the search target and informed participants only about a response key that they had to press to indicate a prepared target-present vs. -absent decision. This lateralization during VSTM retrieval (TCN) provides strong evidence of a shift of attention towards the target location in the memory representation, which occurred despite the fact that the present task required no spatial (or featural) information from the search to be encoded, maintained, and retrieved to produce the correct response and that the go-signal did not itself specify any information relating to the location and defining feature of the target.