A smarter brain is associated with stronger neural interaction in healthy young females: A resting EEG coherence study

General intelligence, the g factor, is a major issue in psychology and neuroscience. However, the neural mechanism of the g factor is still not clear. It is suggested that the g factor should be non-modular (a property across the brain) and show good colinearity with various cognitive tests. This study examines the hypothesis that functional connectivity may be a good candidate for the g factor. We recorded resting state eyes-closed EEG signals in 184 healthy young females. Coherence values of 38 selected channel pairs across delta, theta, alpha, beta and gamma frequencies were correlated with six intelligence quotient (IQ) subtests, including symbol search, block design, object assembly, digit span, similarity and arithmetic. A three-stage analytic flow was constructed to delineate common (g factor) and unique neural components of intelligence. It is noticed that the coherence pattern demonstrates good correlation with five of the IQ subtests (except symbol search) and non-modularity in the brain. Our commonality analyses support connectivity strength in the brain as a good indicator of the g factor. For the digit span and arithmetic tests, the uniqueness analyses provide left-lateralized topography relevant to the operation of working memory. Performance on the arithmetic test is further correlated with strengths at left temporo-parietal and bilateral temporal connections. All the significant correlations are positive, indicating that the stronger the connectivity strengths, the higher the intelligence. Our analyses conclude that a smarter brain is associated with stronger interaction in the central nervous system. The implication and why the symbol search does not show parallel results are discussed.     

Functional cortical connectivity analysis of mental fatigue unmasks hemispheric asymmetry and changes in small-world networks

Changes in functional connectivity across mental states can provide richer information about human cognition than simpler univariate approaches. Here, we applied a graph theoretical approach to analyze such changes in the lower alpha (8–10 Hz) band of EEG data from 26 subjects undergoing a mentally-demanding test of sustained attention: the Psychomotor Vigilance Test. Behavior and connectivity maps were compared between the first and last 5 min of the task. Reaction times were significantly slower in the final minutes of the task, showing a clear time-on-task effect. A significant increase was observed in weighted characteristic path length, a measure of the efficiency of information transfer within the cortical network. This increase was correlated with reaction time change. Functional connectivity patterns were also estimated on the cortical surface via source localization of cortical activities in 26 predefined regions of interest. Increased characteristic path length was revealed, providing further support for the presence of a reshaped global topology in cortical connectivity networks under fatigue state. Additional analysis showed an asymmetrical pattern of connectivity (right > left) in fronto-parietal regions associated with sustained attention, supporting the right-lateralization of this function. Interestingly, in the fatigue state, significance decreases were observed in left, but not right fronto-parietal connectivity. Our results indicate that functional network organization can change over relatively short time scales with mental fatigue, and that decreased connectivity has a meaningful relationship with individual difference in behavior and performance.     

Musical experts recruit action-related neural structures in harmonic anomaly detection: Evidence for embodied cognition in expertise

Humans are extremely good at detecting anomalies in sensory input. For example, while listening to a piece of Western-style music, an anomalous key change or an out-of-key pitch is readily apparent, even to the non-musician. In this paper we investigate differences between musical experts and non-experts during musical anomaly detection. Specifically, we analyzed the electroencephalograms (EEG) of five expert cello players and five non-musicians while they listened to excerpts of J.S. Bach’s Prelude from Cello Suite No. 1. All subjects were familiar with the piece, though experts also had extensive experience playing the piece. Subjects were told that anomalous musical events (AMEs) could occur at random within the excerpts of the piece and were told to report the number of AMEs after each excerpt. Furthermore, subjects were instructed to remain still while listening to the excerpts and their lack of movement was verified via visual and EEG monitoring. Experts had significantly better behavioral performance (i.e. correctly reporting AME counts) than non-experts, though both groups had mean accuracies greater than 80%. These group differences were also reflected in the EEG correlates of key-change detection post-stimulus, with experts showing more significant, greater magnitude, longer periods of, and earlier peaks in condition-discriminating EEG activity than novices. Using the timing of the maximum discriminating neural correlates, we performed source reconstruction and compared significant differences between cellists and non-musicians. We found significant differences that included a slightly right lateralized motor and frontal source distribution. The right lateralized motor activation is consistent with the cortical representation of the left hand – i.e. the hand a cellist would use, while playing, to generate the anomalous key-changes. In general, these results suggest that sensory anomalies detected by experts may in fact be partially a result of an embodied cognition, with a model of the action for generating the anomaly playing a role in its detection.     

Learning to control brain activity: a review of the production and control of EEG components for driving brain-computer interface (BCI) systems

Brain-computer interface (BCI) technology relies on the ability of individuals to voluntarily and reliably produce changes in their electroencephalographic (EEG) activity. The present paper reviews research on cognitive tasks and other methods of generating and controlling specific changes in EEG activity that can be used to drive BCI systems. To date, motor imagery has been the most commonly used task. This paper explores the possibility that other cognitive tasks, including those used in imaging studies, may prove to be more effective. Other factors which influence performance are also considered in relation to selection of tasks, as well as training of subjects.     

EEG相干分析在语言理解研究中的应用

EEG相干反映了EEG信号在各个脑区之间的信息传递,可以揭示各种认知加工过程中不同功能网络的协同工作方式。首先介绍了这一方法的基本原理,然后从词语和句子两个水平上阐述了EEG相干分析在语言理解研究中的应用。在词语水平上涉及一般认知加工过程、语法加工和语义加工三个方面;在句子水平上,从句子的语义整合角度进行了介绍。最后指出了这一方法的优缺点,并对今后的研究方向进行了展望     

Shedding light on words and sentences: near-infrared spectroscopy in language research

Investigating the neuronal network underlying language processing may contribute to a better understanding of how the brain masters this complex cognitive function with surprising ease and how language is acquired at a fast pace in infancy. Modern neuroimaging methods permit to visualize the evolvement and the function of the language network. The present paper focuses on a specific methodology, functional near-infrared spectroscopy (fNIRS), providing an overview over studies on auditory language processing and acquisition. The methodology detects oxygenation changes elicited by functional activation of the cerebral cortex. The main advantages for research on auditory language processing and its development during infancy are an undemanding application, the lack of instrumental noise, and its potential to simultaneously register electrophysiological responses. Also it constitutes an innovative approach for studying developmental issues in infants and children. The review will focus on studies on word and sentence processing including research in infants and adults.     

L’influence longitudinale de la justice organisationnelle sur le bien-être psychologique au travail : quels types de justice sont déterminants ?

Regarding the relationship between perceived organizational justice and psychological well-being at work, few studies compare the influence of the four organizational justice facets, and even fewer do so longitudinally. The objective of this study is to evaluate the longitudinal relationships between these facets and psychological well-being at work. Social exchange theory suggests that distributive, interpersonal, and informational justices are better predictors of well-being than procedural justice. A sample of 192 Canadian workers from a diversity of occupations completed two self-reported questionnaires at a six-month interval. Results support the importance of rewards allocation (distributive justice) and information given on this allocation (informational justice) to promote workers’ well-being.     

Learning by looking: Infants' social looking behavior across the transition from crawling to walking

This study investigated how infants gather information about their environment through looking and how that changes with increases in motor skills. In Experiment 1, 9.5- and 14-month-olds participated in a 10-min free play session with both a stranger and ambiguous toys present. There was a significant developmental progression from passive to active social engagement, as evidenced by younger infants watching others communicate more and older infants making more bids for social interaction. Experiment 2 examined longitudinally the impact of age and walking onset on this progression. The transition to independent walking marked significant changes in how often infants watched others communicate and made active bids for social interaction. Results suggest that infants transition from passive observers as crawlers to active participants in their social environment with the onset of walking.