Proficient brain for optimal performance: the MAP model perspective

Background. The main goal of the present study was to explore theta and alpha event-related desynchronization/synchronization (ERD/ERS) activity during shooting performance. We adopted the idiosyncratic framework of the multi-action plan (MAP) model to investigate different processing modes underpinning four types of performance. In particular, we were interested in examining the neural activity associated with optimal-automated (Type 1) and optimal-controlled (Type 2) performances. Methods. Ten elite shooters (6 male and 4 female) with extensive international experience participated in the study. ERD/ERS analysis was used to investigate cortical dynamics during performance. A 4 × 3 (performance types × time) repeated measures analysis of variance was performed to test the differences among the four types of performance during the three seconds preceding the shots for theta, low alpha, and high alpha frequency bands. The dependent variables were the ERD/ERS percentages in each frequency band (i.e., theta, low alpha, high alpha) for each electrode site across the scalp. This analysis was conducted on 120 shots for each participant in three different frequency bands and the individual data were then averaged. Results. We found ERS to be mainly associated with optimal-automatic performance, in agreement with the “neural efficiency hypothesis.” We also observed more ERD as related to optimal-controlled performance in conditions of “neural adaptability” and proficient use of cortical resources. Discussion. These findings are congruent with the MAP conceptualization of four performance states, in which unique psychophysiological states underlie distinct performance-related experiences. From an applied point of view, our findings suggest that the MAP model can be used as a framework to develop performance enhancement strategies based on cognitive and neurofeedback technique

Changes in brain electrical activity during extended continuous word recognition

Twenty healthy subjects (10 men, 10 women) participated in an EEG study with an extended continuous recognition memory task, in which each of 30 words was randomly shown 10 times and subjects were required to make old vs. new decisions. Both event-related brain potentials (ERPs) and induced band power (IBP) were investigated. We hypothesized that repeated presentations affect recollection rather than familiarity. For the 300- to 500-ms time window, an 'old/new' ERP effect was found for the first vs. second word presentations. The correct recognition of an 'old' word was associated with a more positive waveform than the correct identification of a new word. The old/new effect was most pronounced at and around the midline parietal electrode position. For the 500- to 800-ms time window, a linear repetition effect was found for multiple word repetitions. Correct recognition after an increasing number of repetitions was associated with increasing positivity. The multiple repetitions effect was most pronounced at the midline central (Cz) and fronto-central (FCz) electrode positions and reflects a graded recollection process: the stronger the memory trace grows, the more positive the ERP in the 500- to 800-ms time window. The ERP results support a dual-processing model, with familiarity being discernable from a more graded recollection state that depends on memory strengths. For IBP, we found 'old/new' effects for the lower-2 alpha, theta, and delta bands, with higher bandpower during 'old' words. The lower-2 alpha 'old/new' effect most probably reflects attentional processes, whereas the theta and delta effects reflect encoding and retrieval processes. Upon repeated word presentations, the magnitude of induced delta power in the 375- to 750-ms time window diminished linearly. Correlation analysis suggests that decreased delta power is moderately associated with faster decision speed and higher accurac

Specific heat and thermal conductivity in the vortex state of the two-gap superconductor MgB_2

The specific heat coefficient gamma_s(H) and the electronic thermal conductivity kappa_{es}(H) are calculated for Abrikosov's vortex lattice by taking into account the effects of supercurrent flow and Andreev scattering. First we solve the gap equation for the entire range of magnetic fields. We take into account vertex corrections due to impurity scattering calculated in the Born approximation. The function gamma_s(H)/gamma_n increases from zero and becomes approximately linear above H/H_{c2} \sim 0.1. The dependence on impurity scattering is substantially reduced by the vertex corrections. The upward curvature of kappa_{es}(H)/kappa_{en}, which is caused by decreasing Andreev scattering for increasing field, is reduced for increasing impurity scattering. We also calculate the temperature dependence of the scattering rates 1/tau_{ps}(H) of a phonon and 1/tau_{es}(H) of a quasiparticle due to quasiparticle and phonon scattering, respectively. At low temperatures the ratio tau_{pn}/tau_{ps}(H) increases rapidly to one as H tends to H_{c2} which yields a rapid drop in the phononic thermal conductivity kappa_{ph}. Our results are in qualitative agreement with the experiments on the two-gap superconductor MgB_2.Comment: 12 pages, 5 figures, additions to figures 1, 2, and 3. Accepted by Phys. Rev.

A common short-term memory retrieval rate may describe many cognitive procedures

We examine the relationship between response speed and the number of items in short-term memory (STM) in four different paradigms and find evidence for a similar high-speed processing rate of about 25–30 items per second (∼35–40 ms/item). We propose that the similarity of the processing rates across paradigms reflects the operation of a very basic covert memory process, high-speed retrieval, that is involved in both the search for information in STM and the reactivation or refreshing of information that keeps it in STM. We link this process to a specific pattern of rhythmic, repetitive neural activity in the brain (gamma oscillations). This proposal generates ideas for research and calls for an integrative approach that combines neuroscientific measures with behavioral cognitive techniques

Modality effects in implicit artificial grammar learning: An EEG study

Recently, it has been proposed that sequence learning engages a combination of modality-specific operating networks and modality-independent computational principles. In the present study, we compared the behavioural and EEG outcomes of implicit artificial grammar learning in the visual vs. auditory modality. We controlled for the influence of surface characteristics of sequences (Associative Chunk Strength), thus focusing on the strictly structural aspects of sequence learning, and we adapted the paradigms to compensate for known frailties of the visual modality compared to audition (temporal presentation, fast presentation rate). The behavioural outcomes were similar across modalities. Favouring the idea of modality-specificity, ERPs in response to grammar violations differed in topography and latency (earlier and more anterior component in the visual modality), and ERPs in response to surface features emerged only in the auditory modality. In favour of modality-independence, we observed three common functional properties in the late ERPs of the two grammars: both were free of interactions between structural and surface influences, both were more extended in a grammaticality classification test than in a preference classification test, and both correlated positively and strongly with theta event-related-synchronization during baseline testing. Our findings support the idea of modality-specificity combined with modality-independence, and suggest that memory for visual vs. auditory sequences may largely contribute to cross-modal differences. (C) 2018 Elsevier B.V. All rights reserved.Max Planck Institute for Psycholinguistics; Donders Institute for Brain, Cognition and Behaviour; Fundacao para a Ciencia e Tecnologia [PTDC/PSI-PC0/110734/2009, UID/BIM/04773/2013, CBMR 1334, PEst-OE/EQB/1A0023/2013, UM/PSI/00050/2013

Spherical harmonic decomposition applied to spatial-temporal analysis of human high-density EEG

We demonstrate an application of spherical harmonic decomposition to analysis of the human electroencephalogram (EEG). We implement two methods and discuss issues specific to analysis of hemispherical, irregularly sampled data. Performance of the methods and spatial sampling requirements are quantified using simulated data. The analysis is applied to experimental EEG data, confirming earlier reports of an approximate frequency-wavenumber relationship in some bands.Comment: 12 pages, 8 figures, submitted to Phys. Rev. E, uses APS RevTeX style

Ultrasonic attenuation in magnetic fields for superconducting states with line nodes in Sr2RuO4

We calculate the ultrasonic attenuation in magnetic fields for superconducting states with line nodes vertical or horizontal relative to the RuO_2 planes. This theory, which is valid for fields near Hc2 and not too low temperatures, takes into account the effects of supercurrent flow and Andreev scattering by the Abrikosov vortex lattice. For rotating in-plane field H(theta) the attenuation alpha(theta)exhibits variations of fourfold symmetry in the rotation angle theta. In the case of vertical nodes, the transverse T100 sound mode yields the weakest(linear)H and T dependence of alpha, while the longitudinal L100 mode yields a stronger (quadratic) H and T dependence. This is in strong contrast to the case of horizontal line nodes where alpha is the same for the T100 and L100 modes (apart from a shift of pi/4 in field direction) and is roughly a quadratic function of H and T. Thus we conclude that measurements of alpha in in-plane magnetic fields for different in-plane sound modes may be an important tool for probing the nodal structure of the gap in Sr_2RuO_4.Comment: 5 pages, 6 figures, replaced in non-preprint form, to appear in Phys. Rev.

Detection of emotions in Parkinson's disease using higher order spectral features from brain's electrical activity

Non-motor symptoms in Parkinson's disease (PD) involving cognition and emotion have been progressively receiving more attention in recent times. Electroencephalogram (EEG) signals, being an activity of central nervous system, can reflect the underlying true emotional state of a person. This paper presents a computational framework for classifying PD patients compared to healthy controls (HC) using emotional information from the brain's electrical activity

Influence of Fermi surface topology on the quasiparticle spectrum in the vortex state

We study the influence of Fermi surface topology on the quasiparticle density of states in the vortex state of type II superconductors. We observe that the field dependence and the shape of the momentum and spatially averaged density of states is affected significantly by the topology of the Fermi surface. We show that this behavior can be understood in terms of characteristic Fermi surface functions and that an important role is played by the number of points on the Fermi surface at which the Fermi velocity is directed parallel to the magnetic field. A critical comparison is made with a broadened BCS type density of states, that has been used frequently in analysis of tunneling data. We suggest a new formula as a replacement for the broadened BCS model for the special case of a cylindrical Fermi surface. We apply our results to the two gap superconductor MgB$_2$ and show that in this particular case the field dependence of the partial densities of states of the two gaps behaves very differently due to the different topologies of the corresponding Fermi surfaces, in qualitative agreement with recent tunneling experiments.Comment: 12 pages 12 figure

Alpha-band rhythms in visual task performance: phase-locking by rhythmic sensory stimulation

Oscillations are an important aspect of neuronal activity. Interestingly, oscillatory patterns are also observed in behaviour, such as in visual performance measures after the presentation of a brief sensory event in the visual or another modality. These oscillations in visual performance cycle at the typical frequencies of brain rhythms, suggesting that perception may be closely linked to brain oscillations. We here investigated this link for a prominent rhythm of the visual system (the alpha-rhythm, 8-12 Hz) by applying rhythmic visual stimulation at alpha-frequency (10.6 Hz), known to lead to a resonance response in visual areas, and testing its effects on subsequent visual target discrimination. Our data show that rhythmic visual stimulation at 10.6 Hz: 1) has specific behavioral consequences, relative to stimulation at control frequencies (3.9 Hz, 7.1 Hz, 14.2 Hz), and 2) leads to alpha-band oscillations in visual performance measures, that 3) correlate in precise frequency across individuals with resting alpha-rhythms recorded over parieto-occipital areas. The most parsimonious explanation for these three findings is entrainment (phase-locking) of ongoing perceptually relevant alpha-band brain oscillations by rhythmic sensory events. These findings are in line with occipital alpha-oscillations underlying periodicity in visual performance, and suggest that rhythmic stimulation at frequencies of intrinsic brain-rhythms can be used to reveal influences of these rhythms on task performance to study their functional roles