Uncovering the overlapping community structure of complex networks in nature and society

Many complex systems in nature and society can be described in terms of networks capturing the intricate web of connections among the units they are made of. A key question is how to interpret the global organization of such networks as the coexistence of their structural subunits (communities) associated with more highly interconnected parts. Identifying these a priori unknown building blocks (such as functionally related proteins, industrial sectors and groups of people) is crucial to the understanding of the structural and functional properties of networks. The existing deterministic methods used for large networks find separated communities, whereas most of the actual networks are made of highly overlapping cohesive groups of nodes. Here we introduce an approach to analysing the main statistical features of the interwoven sets of overlapping communities that makes a step towards uncovering the modular structure of complex systems. After defining a set of new characteristic quantities for the statistics of communities, we apply an efficient technique for exploring overlapping communities on a large scale. We find that overlaps are significant, and the distributions we introduce reveal universal features of networks. Our studies of collaboration, word-association and protein interaction graphs show that the web of communities has non-trivial correlations and specific scaling properties.Comment: The free academic research software, CFinder, used for the publication is available at the website of the publication: http://angel.elte.hu/clusterin

ERP evidence suggests executive dysfunction in ecstasy polydrug users

Background: Deficits in executive functions such as access to semantic/long-term memory have been shown in ecstasy users in previous research. Equally, there have been many reports of equivocal findings in this area. The current study sought to further investigate behavioural and electro-physiological measures of this executive function in ecstasy users. Method: Twenty ecstasy–polydrug users, 20 non-ecstasy–polydrug users and 20 drug-naïve controls were recruited. Participants completed background questionnaires about their drug use, sleep quality, fluid intelligence and mood state. Each individual also completed a semantic retrieval task whilst 64 channel Electroencephalography (EEG) measures were recorded. Results: Analysis of Variance (ANOVA) revealed no between-group differences in behavioural performance on the task. Mixed ANOVA on event-related potential (ERP) components P2, N2 and P3 revealed significant between-group differences in the N2 component. Subsequent exploratory univariate ANOVAs on the N2 component revealed marginally significant between-group differences, generally showing greater negativity at occipito-parietal electrodes in ecstasy users compared to drug-naïve controls. Despite absence of behavioural differences, differences in N2 magnitude are evidence of abnormal executive functioning in ecstasy–polydrug users

Multitask training promotes automaticity of a fundamental laparoscopic skill without compromising the rate of skill learning.

A defining characteristic of expertise is automated performance of skills, which frees attentional capacity to better cope with some common intraoperative stressors. There is a paucity of research on how best to foster automated performance by surgical trainees. This study examined the use of a multitask training approach to promote automated, robust laparoscopic skills.Eighty-one medical students completed training of a fundamental laparoscopic task in either a traditional single-task training condition or a novel multitask training condition. Following training, participants' laparoscopic performance was tested in a retention test, two stress transfer tests (distraction and time pressure) and a secondary task test, which was included to evaluate automaticity of performance. The laparoscopic task was also performed as part of a formal clinical examination (OSCE).The training groups did not differ in the number of trials required to reach task proficiency (p = .72), retention of skill (ps > .45), or performance in the clinical examination (p = .14); however, the groups did differ with respect to the secondary task (p = .016). The movement efficiency (number of hand movements) of single-task trainees, but not multitask trainees, was negatively affected during the secondary task test. The two stress transfer tests had no discernable impact on the performance of either training group.Multitask training was not detrimental to the rate of learning of a fundamental laparoscopic skill and added value by providing resilience in the face of a secondary task load, indicative of skill automaticity. Further work is needed to determine the extent of the clinical utility afforded by multitask training

Learned Value Magnifies Salience-Based Attentional Capture

Visual attention is captured by physically salient stimuli (termed salience-based attentional capture), and by otherwise task-irrelevant stimuli that contain goal-related features (termed contingent attentional capture). Recently, we reported that physically nonsalient stimuli associated with value through reward learning also capture attention involuntarily (Anderson, Laurent, & Yantis, PNAS, 2011). Although it is known that physical salience and goal-relatedness both influence attentional priority, it is unknown whether or how attentional capture by a salient stimulus is modulated by its associated value. Here we show that a physically salient, task-irrelevant distractor previously associated with a large reward slows visual search more than an equally salient distractor previously associated with a smaller reward. This magnification of salience-based attentional capture by learned value extinguishes over several hundred trials. These findings reveal a broad influence of learned value on involuntary attentional capture