76 research outputs found
Visualization of Multichannel EEG Coherence Networks Based on Community Structure
An electroencephalography (EEG) coherence network is a representation of functional brain connectivity. However, typical visualizations of coherence networks do not allow an easy embedding of spatial information or suffer from visual clutter, especially for multichannel EEG coherence networks. In this paper, a new method for data-driven visualization of multichannel EEG coherence networks is proposed to avoid the drawbacks of conventional methods. This method partitions electrodes into dense groups of spatially connected regions. It not only preserves spatial relationships between regions, but also allows an analysis of the functional connectivity within and between brain regions, which could be used to explore the relationship between functional connectivity and underlying brain structures. In addition, we employ an example to illustrate the difference between the proposed method and two other data-driven methods when applied to coherence networks in older and younger adults who perform a cognitive task. The proposed method can serve as an preprocessing step before a more detailed analysis of EEG coherence networks
Cue avoidance training and inhibitory control training for the reduction of alcohol consumption: a comparison of effectiveness and investigation of their mechanisms of action
Attentional capture by alcohol-related stimuli may be activated involuntarily by top-down search goals
Previous research has found that the attention of social drinkers is preferentially oriented towards alcohol related stimuli (attentional capture). This is argued to play a role in escalating craving for alcohol that can result in hazardous drinking. According to Incentive theories of drug addiction, the stimuli associated with the drug reward acquire learned incentive salience, and grab attention. However, it is not clear whether the mechanism by which this bias is created is a voluntary or an automatic one, although some evidence suggests a stimulus-driven mechanism. Here we test for the first time whether this attentional capture could reflect an involuntary consequence of a goal-driven mechanism. Across three experiments, participants were given search goals to detect either an alcoholic or a non-alcoholic object (target) in a stream of briefly presented objects unrelated to the target. Prior to the target, a task-irrelevant parafoveal distractor appeared. This could either be congruent or incongruent with the current search goal. Applying a meta-analysis, we combined the results across the three experiments and found consistent evidence of goal-driven attentional capture; whereby alcohol distractors impeded target detection when the search goal was for alcohol. By contrast, alcohol distractors did not interfere with target detection while participants were searching for a non-alcoholic category. A separate experiment revealed that the goal-driven capture effect was not found when participants held alcohol features active in memory but did not intentionally search for them. These findings suggest a strong goal-driven account of attentional capture by alcohol cues in social drinkers
Neural dynamics of shooting decisions and the switch from freeze to fight
Real-life shooting decisions typically occur under acute threat and require fast switching between vigilant situational assessment and immediate fight-or-flight actions. Recent studies suggested that freezing facilitates action preparation and decision-making but the neurocognitive mechanisms remain unclear. We applied functional magnetic resonance imaging, posturographic and autonomic measurements while participants performed a shooting task under threat of shock. two independent studies, in unselected civilians (N = 22) and police recruits (N = 54), revealed that preparation for shooting decisions under threat is associated with postural freezing, bradycardia, midbrain activity (including the periaqueductal gray-PAG) and PAG-amygdala connectivity. Crucially, stronger activity in the midbrain/pAG during this preparatory stage of freezing predicted faster subsequent accurate shooting. Finally, the switch from preparation to active shooting was associated with tachycardia, perigenual anterior cingulate cortex (pgACC) activity and pgACC-amygdala connectivity. These findings suggest that threat-anticipatory midbrain activity centred around the PAG supports decision-making by facilitating action preparation and highlight the role of the pgACC when switching from preparation to action. These results translate animal models of the neural switch from freeze-to-action. In addition, they reveal a core neural circuit for shooting performance under threat and provide empirical evidence for the role of defensive reactions such as freezing in subsequent action decision-making
Can Motivation Normalize Working Memory and Task Persistence in Children with Attention-Deficit/Hyperactivity Disorder? The Effects of Money and Computer-Gaming
Visual-spatial Working Memory (WM) is the most impaired executive function in children with Attention-Deficit/Hyperactivity Disorder (ADHD). Some suggest that deficits in executive functioning are caused by motivational deficits. However, there are no studies that investigate the effects of motivation on the visual-spatial WM of children with- and without ADHD. Studies examining this in executive functions other than WM, show inconsistent results. These inconsistencies may be related to differences in the reinforcement used. The effects of different reinforcers on WM performance were investigated in 30 children with ADHD and 31 non-ADHD controls. A visual-spatial WM task was administered in four reinforcement conditions: Feedback-only, 1 euro, 10 euros, and a computer-game version of the task. In the Feedback-only condition, children with ADHD performed worse on the WM measure than controls. Although incentives significantly improved the WM performance of children with ADHD, even the strongest incentives (10 euros and Gaming) were unable to normalize their performance. Feedback-only provided sufficient reinforcement for controls to reach optimal performance, while children with ADHD required extra reinforcement. Only children with ADHD showed a decrease in performance over time. Importantly, the strongest incentives (10 euros and Gaming) normalized persistence of performance in these children, whereas 1 euro had no such effect. Both executive and motivational deficits give rise to visual-spatial WM deficits in ADHD. Problems with task-persistence in ADHD result from motivational deficits. In ADHD-reinforcement studies and clinical practice (e.g., assessment), reinforcement intensity can be a confounding factor and should be taken into account. Gaming can be a cost-effective way to maximize performance in ADHD
Eye-Tracking Based Attention Bias Modification (ET-ABM) Facilitates Disengagement from Negative Stimuli in Dysphoric Individuals
Effectiveness of two web-based cognitive bias modification interventions targeting approach and attentional bias in gambling problems: study protocol for a pilot randomised controlled trial
A incorporação de novas tecnologias nos serviços de saúde: o desafio da análise dos fatores em jogo
A landscape-based cluster analysis using recursive search instead of a threshold parameter.
Cluster-based analysis methods in neuroimaging provide control of whole-brain false positive rates without the need to conservatively correct for the number of voxels and the associated false negative results. The current method defines clusters based purely on shapes in the landscape of activation, instead of requiring the choice of a statistical threshold that may strongly affect results. Statistical significance is determined using permutation testing, combining both size and height of activation. A method is proposed for dealing with relatively small local peaks. Simulations confirm the method controls the false positive rate and correctly identifies regions of activation. The method is also illustrated using real data. •A landscape-based method to define clusters in neuroimaging data avoids the need to pre-specify a threshold to define clusters.•The implementation of the method works as expected, based on simulated and real data.•The recursive method used for defining clusters, the method used for combining clusters, and the definition of the "value" of a cluster may be of interest for future variations
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