METHODS: We collected and analyzed functional near-infrared spectroscopy data of 38 participants while performing the revised lateralized attention network tast.
RESULTS: Elite players were significantly faster than novices (p = .005), and the experts' overall accuracy rate (ACC) was higher than that of novices (p = .001). The effect of the executive network on reaction time was higher in novices than in elite players (p = .008) and experts (p = .004). The effect of the executive network on the ACC was lower in elite players than in experts (p = .009) and novices (p = .010). Finally, elite player had higher flanker conflict effects on RT (p = .005) under the invalid cue condition. the effect of the alertness network and orientation on the ACC was lower in elite players than in novices (p = .000) and experts (p = .022). Changes in the blood oxygen level-dependent signal related to the flanker effect were significantly different in the right dorsolateral prefrontal cortex (F=3.980, p = .028) and right inferior frontal gyrus (F=3.703, p = .035) among the three groups. Elit players showed more efficient executive control (reduced conflict effect on ACC) (p = .006)in the RH.The changes related to the effect of blood oxygen level on orienting were significantly different in the right frontal eye fields (F=3.883, p = .030) among the three groups, Accompanied by significant activation of the right dorsolateral prefrontal cortex(p = .026).
CONCLUSION: Our findings provide partial evidence of the superior cognitive performance and high neural efficiency of elite ice hockey players during cognitive tasks. These results demonstrate the right hemisphere superiority for executive control.We also found that specific brain activation in hockey players does not show a clear and linear relationship with skill level.
PATIENTS AND METHODS: The brain activities of healthy young and older adults were recorded using electroencephalography (EEG).
RESULTS: Elderly participants spent significantly more time completing the task than young participants. During eye-hand coordination in elderly groups, beta power decreased significantly in the central midline and parietal brain regions. The data suggest that healthy elderly subjects had intact cognitive performance, but relatively poor eye-hand coordination associated with loss of beta brain oscillation in the central midline and parietal cortex and reduced ability to attentional movement.
CONCLUSION: Beta frequency in the parietal brain sites may contribute to attentional movement. This could be an important method for monitoring cognitive brain function changes as the brain ages.
METHODS: A subcohort of 201 children with behavioural outcome measures was identified within a longitudinal, Australian birth-cohort study. The faecal microbiota were analysed at 1, 6, and 12 months of age. Behavioural outcomes were measured at 2 years of age.
FINDINGS: In an unselected birth cohort, we found a clear association between decreased normalised abundance of Prevotella in faecal samples collected at 12 months of age and increased behavioural problems at 2 years, in particular Internalizing Problem scores. This association appeared independent of multiple potentially confounding variables, including maternal mental health. Recent exposure to antibiotics was the best predictor of decreased Prevotella.
INTERPRETATION: Our findings demonstrate a strong association between the composition of the gut microbiota in infancy and subsequent behavioural outcomes; and support the importance of responsible use of antibiotics during early life.
FUNDING: This study was funded by the National Health and Medical Research Council of Australia (1082307, 1147980, 1129813), The Murdoch Children's Research Institute, Barwon Health, Deakin University, Perpetual Trustees, and The Shepherd Foundation. The funders had no involvement in the data collection, analysis or interpretation, trial design, recruitment or any other aspect pertinent to the study.
METHOD: For this purpose, we employ fractal theory and analyze the variations of fractal dimension of GSR and EEG signals when subjects are exposed to different olfactory stimuli in the form of pleasant odors.
RESULTS: Based on the obtained results, the complexity of GSR signal changes with the complexity of EEG signal in case of different stimuli, where by increasing the molecular complexity of olfactory stimuli, the complexity of EEG and GSR signals increases. The results of statistical analysis showed the significant effect of stimulation on variations of complexity of GSR signal. In addition, based on effect size analysis, fourth odor with greatest molecular complexity had the greatest effect on variations of complexity of EEG and GSR signals.
CONCLUSION: Therefore, it can be said that human skin reaction changes with the variations in the activity of human brain. The result of analysis in this research can be further used to make a model between the activities of human skin and brain that will enable us to predict skin reaction to different stimuli.
METHODS: Such activity is recorded through various neuroimaging techniques like fMRI, EEG, MEG etc. EEG signals based localization is termed as EEG source localization. The source localization problem is defined by two complementary problems; the forward problem and the inverse problem. The forward problem involves the modeling how the electromagnetic sources cause measurement in sensor space, while the inverse problem refers to the estimation of the sources (causes) from observed data (consequences). Usually, this inverse problem is ill-posed. In other words, there are many solutions to the inverse problem that explains the same data. This ill-posed problem can be finessed by using prior information within a Bayesian framework. This research work discusses source reconstruction for EEG data using a Bayesian framework. In particular, MSP, LORETA and MNE are compared.
RESULTS: The results are compared in terms of variational free energy approximation to model evidence and in terms of variance accounted for in the sensor space. The results are taken for real time EEG data and synthetically generated EEG data at an SNR level of 10dB.
CONCLUSION: In brief, it was seen that MSP has the highest evidence and lowest localization error when compared to classical models. Furthermore, the plausibility and consistency of the source reconstruction speaks to the ability of MSP technique to localize active brain sources.