The Influence of Noise in the Neurofeedback Training Sessions in Student Athletes.

Considering that athletes constantly practice and compete in noisy environments, the aim was to investigate if performing neurofeedback training in these conditions would yield better results in performance than in silent ones. A total of forty-five student athletes aged from 18 to 35 years old and divided equally into three groups participated in the experiment (mean ± SD for age: 22.02 ± 3.05 years). The total neurofeedback session time for each subject was 300 min and were performed twice a week. The environment in which the neurofeedback sessions were conducted did not seem to have a significant impact on the training's success in terms of alpha relative amplitude changes (0.04 ± 0.08 for silent room versus 0.07 ± 0.28 for noisy room, p = 0.740). However, the group exposed to intermittent noise appears to have favourable results in all performance assessments (p = 0.005 for working memory and p = 0.003 for reaction time). The results of the study suggested that performing neurofeedback training in an environment with intermittent noise can be interesting to athletes. Nevertheless, it is imperative to perform a replicated crossover design.

The Influence of an Alpha Band Neurofeedback Training in Heart Rate Variability in Athletes.

Neurofeedback training is a technique which has seen a widespread use in clinical applications, but has only given its first steps in the sport environment. Therefore, there is still little information about the effects that this technique might have on parameters, which are relevant for athletes' health and performance, such as heart rate variability, which has been linked to physiological recovery. In the sport domain, no studies have tried to understand the effects of neurofeedback training on heart rate variability, even though some studies have compared the effects of doing neurofeedback or heart rate biofeedback training on performance. The main goal of the present study was to understand if alpha-band neurofeedback training could lead to increases in heart rate variability. 30 male student-athletes, divided into two groups, (21.2 ± 2.62 year 2/week protocol and 22.6 ± 1.1 year 3/week protocol) participated in the study, of which three subjects were excluded. Both groups performed a pre-test, a trial session and 12 neurofeedback sessions, which consisted of 25 trials of 60 s of a neurofeedback task, with 5 s rest in-between trials. The total neurofeedback session time for each subject was 300 min in both groups. Throughout the experiment, electroencephalography and heart rate variability signals were recorded. Only the three sessions/week group revealed significant improvements in mean heart rate variability at the end of the 12 neurofeedback sessions (p = 0.05); however, significant interaction was not found when compared with both groups. It is possible to conclude that neurofeedback training of individual alpha band may induce changes in heart rate variability in physically active athletes.

Generative Art with Swarm Landscapes.

We present a generative swarm art project that creates 3D animations by running a Particle Swarm Optimization algorithm over synthetic landscapes produced by an objective function. Different kinds of functions are explored, including mathematical expressions, Perlin noise-based terrain, and several image-based procedures. A method for displaying the particle swarm exploring the search space in aesthetically pleasing ways is described. Several experiments are detailed and analyzed and a number of interesting visual artifacts are highlighted.

Neurofeedback Training for Cognitive and Motor Function Rehabilitation in Chronic Stroke: Two Case Reports.

Stroke is a debilitating neurological condition which usually results in the abnormal electrical brain activity and the impairment of sensation, motor, or cognition functions. In this context, neurofeedback training, i.e., a non-invasive and relatively low cost technique that contributes to neuroplasticity and behavioral performance, might be promising for stroke rehabilitation. We intended to explore neurofeedback training on a 63-year-old male patient and a 77-year-old female patient with chronic stroke. Both of them had suffered from an ischemic stroke for rather long period (more than 3 years) and could not gain further improvement by traditional therapy. The neurofeedback training was designed to enhance alpha activity by 15 sessions distributed over 2 months, for the purpose of overall cognitive improvement and hopefully also motor function improvement for the female patient. We found that the two patients showed alpha enhancement during NFT compared to eyes open baseline within most sessions. Furthermore, both patients reduced their anxiety and depression level. The male patient showed an evolution in speech pattern in terms of naming, sentences completion and verbal fluency, while the female patient improved functionality of the march. These results suggested that alpha neurofeedback training could provide a spectrum of improvements, providing new hope for chronic stroke patients who could not gain further improvements through traditional therapies.

Steady state particle swarm.

This paper investigates the performance and scalability of a new update strategy for the particle swarm optimization (PSO) algorithm. The strategy is inspired by the Bak-Sneppen model of co-evolution between interacting species, which is basically a network of fitness values (representing species) that change over time according to a simple rule: the least fit species and its neighbors are iteratively replaced with random values. Following these guidelines, a steady state and dynamic update strategy for PSO algorithms is proposed: only the least fit particle and its neighbors are updated and evaluated in each time-step; the remaining particles maintain the same position and fitness, unless they meet the update criterion. The steady state PSO was tested on a set of unimodal, multimodal, noisy and rotated benchmark functions, significantly improving the quality of results and convergence speed of the standard PSOs and more sophisticated PSOs with dynamic parameters and neighborhood. A sensitivity analysis of the parameters confirms the performance enhancement with different parameter settings and scalability tests show that the algorithm behavior is consistent throughout a substantial range of solution vector dimensions.

The Dark Proteome Database.

BACKGROUND: Recently we surveyed the dark-proteome, i.e., regions of proteins never observed by experimental structure determination and inaccessible to homology modelling. Surprisingly, we found that most of the dark proteome could not be accounted for by conventional explanations (e.g., intrinsic disorder, transmembrane domains, and compositional bias), and that nearly half of the dark proteome comprised dark proteins, in which the entire sequence lacked similarity to any known structure. In this paper we will present the Dark Proteome Database (DPD) and associated web services that provide access to updated information about the dark proteome. RESULTS: We assembled DPD from several external web resources (primarily Aquaria and Swiss-Prot) and stored it in a relational database currently containing ~10 million entries and occupying ~2 GBytes of disk space. This database comprises two key tables: one giving information on the 'darkness' of each protein, and a second table that breaks each protein into dark and non-dark regions. In addition, a second version of the database is created using also information from the Protein Model Portal (PMP) to determine darkness. To provide access to DPD, a web server has been implemented giving access to all underlying data, as well as providing access to functional analyses derived from these data. CONCLUSIONS: Availability of this database and its web service will help focus future structural and computational biology efforts to study the dark proteome, thus providing a basis for understanding a wide variety of biological functions that currently remain unknown. AVAILABILITY AND IMPLEMENTATION: DPD is available at http://darkproteome.ws. The complete database is also available upon request. Data use is permitted via the Creative Commons Attribution-NonCommercial International license (http://creativecommons.org/licenses/by-nc/4.0/).

Resting and Initial Beta Amplitudes Predict Learning Ability in Beta/Theta Ratio Neurofeedback Training in Healthy Young Adults.

Neurofeedback (NF) training has been proved beneficial in cognitive and behavioral performance improvement in healthy individuals. Unfortunately, the NF learning ability shows large individual difference and in a number of NF studies there are even some non-learners who cannot successfully self-regulate their brain activity by NF. This study aimed to find out the neurophysiological predictor of the learning ability in up-regulating beta-1 (15-18 Hz)/theta (4-7 Hz) ratio (BTR) training in healthy young adults. Eighteen volunteers finished five training sessions in successive 5 days. We found that low beta (12-15 Hz) amplitude in a 1-min eyes-open resting baseline measured before training and the beta-1 amplitude in the first training block with 4.5-min duration could predict the BTR learning ability across sessions. The results provide a low cost, convenient and easy way to predict the learning ability in up-regulating BTR training, and would be helpful in avoiding potential frustration and adjusting training protocol for the participants with poor learning ability.

Dynamic peripheral visual performance relates to alpha activity in soccer players.

Many studies have demonstrated the relationship between the alpha activity and the central visual ability, in which the visual ability is usually assessed through static stimuli. Besides static circumstance, however in the real environment there are often dynamic changes and the peripheral visual ability in a dynamic environment (i.e., dynamic peripheral visual ability) is important for all people. So far, no work has reported whether there is a relationship between the dynamic peripheral visual ability and the alpha activity. Thus, the objective of this study was to investigate their relationship. Sixty-two soccer players performed a newly designed peripheral vision task in which the visual stimuli were dynamic, while their EEG signals were recorded from Cz, O1, and O2 locations. The relationship between the dynamic peripheral visual performance and the alpha activity was examined by the percentage-bend correlation test. The results indicated no significant correlation between the dynamic peripheral visual performance and the alpha amplitudes in the eyes-open and eyes-closed resting condition. However, it was not the case for the alpha activity during the peripheral vision task: the dynamic peripheral visual performance showed significant positive inter-individual correlations with the amplitudes in the alpha band (8-12 Hz) and the individual alpha band (IAB) during the peripheral vision task. A potential application of this finding is to improve the dynamic peripheral visual performance by up-regulating alpha activity using neuromodulation techniques.

KANTS: a stigmergic ant algorithm for cluster analysis and swarm art.

KANTS is a swarm intelligence clustering algorithm inspired by the behavior of social insects. It uses stigmergy as a strategy for clustering large datasets and, as a result, displays a typical behavior of complex systems: self-organization and global patterns emerging from the local interaction of simple units. This paper introduces a simplified version of KANTS and describes recent experiments with the algorithm in the context of a contemporary artistic and scientific trend called swarm art, a type of generative art in which swarm intelligence systems are used to create artwork or ornamental objects. KANTS is used here for generating color drawings from the input data that represent real-world phenomena, such as electroencephalogram sleep data. However, the main proposal of this paper is an art project based on well-known abstract paintings, from which the chromatic values are extracted and used as input. Colors and shapes are therefore reorganized by KANTS, which generates its own interpretation of the original artworks. The project won the 2012 Evolutionary Art, Design, and Creativity Competition.

Sleepwalking, a disorder of NREM sleep instability.

BACKGROUND AND PURPOSE: Thirty-two chronic sleepwalkers who were part of a larger, previously reported sleepwalking group all achieved control of sleepwalking after undergoing treatment for an associated sleep disorder. In the current study, all records were blindly scored to perform a cyclic alternating pattern (CAP) analysis. PATIENTS AND METHODS: Thirty-two young adult chronic sleepwalkers had polysomnography (PSG) on initial nights without sleepwalking events, as did age-matched normal controls and patients with mild sleep-disordered breathing (SDB). More than 90% of these patients with mild SDB had upper airway resistance syndrome (UARS). Ten randomly selected PSGs for sleepwalkers and matched controls also had quantitative electroencephalographic (EEG) analysis using Fast Fourier Transformation (FFT) with determination of delta power for each non-rapid eye movement (NREM)-REM sleep cycle. RESULTS: Compared to normal controls, an investigation of CAP in sleepwalkers demonstrated the presence of an abnormal CAP rate with a decrease in phase A1 and an increase in phases A2 and A3 on non-sleepwalking nights. The results of CAP analysis in sleepwalkers were similar to those obtained in age-matched UARS patients. Furthermore, the analysis of the first four NREM-REM sleep cycles reconfirmed the presence of an important decrease in delta power in sleep cycles 1 and 2 during a non-sleepwalking night in sleepwalkers compared to normal controls. CONCLUSIONS: The presence of both 'hypersynchronous slow delta' and 'burst of delta waves' have been reported in sleepwalkers, but their significance is controversial. These EEG patterns are similar to phase A1 (and possibly A2) of the CAP. Proper analysis of the sleep EEG of sleepwalkers should integrate CAP analysis. Sleepwalkers on a non-sleepwalking night present instability of NREM sleep, as demonstrated by this analysis. This instability is similar to the one noted in UARS patients. Subtle sleep disorders associated with chronic sleepwalking constitute the unstable NREM sleep background on which sleepwalking events occur. A subtle associated sleep disorder should be systematically searched for and treated in the presence of sleepwalking with abnormal CAP.

The intranuclear mobility of messenger RNA binding proteins is ATP dependent and temperature sensitive.

After being released from transcription sites, messenger ribonucleoprotein particles (mRNPs) must reach the nuclear pore complexes in order to be translocated to the cytoplasm. Whether the intranuclear movement of mRNPs results largely from Brownian motion or involves molecular motors remains unknown. Here we have used quantitative photobleaching techniques to monitor the intranuclear mobility of protein components of mRNPs tagged with GFP. The results show that the diffusion coefficients of the poly(A)-binding protein II (PABP2) and the export factor TAP are significantly reduced when these proteins are bound to mRNP complexes, as compared with nonbound proteins. The data further show that the mobility of wild-type PABP2 and TAP, but not of a point mutant variant of PABP2 that fails to bind to RNA, is significantly reduced when cells are ATP depleted or incubated at 22 degrees C. Energy depletion has only minor effects on the intranuclear mobility of a 2,000-kD dextran (which corresponds approximately in size to 40S mRNP particles), suggesting that the reduced mobility of PABP2 and TAP is not caused by a general alteration of the nuclear environment. Taken together, the data suggest that the mobility of mRNPs in the living cell nucleus involves a combination of passive diffusion and ATP-dependent processes.

Multi-centre comparison of five eye movement detection algorithms.

Although various investigators have suggested algorithms for the automatic detection of eye movements during sleep, objective comparisons of the proposed methods have previously been difficult due to different recording arrangements of different investigators. In this study the results of five eye movement detection algorithms applied to the same data were compared to visually scored data. The percentages of true and false detections are given for various threshold levels in rapid and slow eye movement detections. The methods gave best results when they were used with the same electrode montage they were designed for but the performance decreased when other montages were used. Subtracting the cross-talk of EEG delta activity improved the correctness of eye movement detections.