Interactive effects of background facial emotion stimulus and target salience on sustained attention performance in schizophrenia

2012 ◽  
Vol 135 (1-3) ◽  
pp. 90-94 ◽  
Author(s):  
Sung-Hyouk Park ◽  
Jin-Chan Noh ◽  
Jin Hun Kim ◽  
Jaewon Lee ◽  
Jin Young Park ◽  
...  
2017 ◽  
Vol 27 (2) ◽  
pp. 184-196 ◽  
Author(s):  
Yuanqiang Zhu ◽  
Yibin Xi ◽  
Ningbo Fei ◽  
Yuchen Liu ◽  
Xinxin Zhang ◽  
...  

2017 ◽  
Vol 7 (5) ◽  
pp. e00684 ◽  
Author(s):  
Francesca C. Fortenbaugh ◽  
Vincent Corbo ◽  
Victoria Poole ◽  
Regina McGlinchey ◽  
William Milberg ◽  
...  

2019 ◽  
Author(s):  
Esther X.W. Wu ◽  
Gwenisha J. Liaw ◽  
Rui Zhe Goh ◽  
Tiffany T.Y. Chia ◽  
Alisia M.J. Chee ◽  
...  

AbstractAttention is a critical cognitive function, allowing humans to select, enhance, and sustain focus on information of behavioral relevance. Attention contains dissociable neural and psychological components. Nevertheless, some brain networks support multiple attentional functions. Connectome-based Predictive Models (CPM), which associate individual differences in task performance with functional connectivity patterns, provide a compelling example. A sustained attention network model (saCPM) successfully predicted performance for selective attention, inhibitory control, and reading recall tasks. Here we constructed a visual attentional blink (VAB) model (vabCPM), comparing its performance predictions and network edges associated with successful and unsuccessful behavior to the saCPM’s. In the VAB, attention devoted to a target often causes a subsequent item to be missed. Although frequently attributed to attentional limitations, VAB deficits may attenuate when participants are distracted or deploy attention diffusely. Participants (n=73; 24 males) underwent fMRI while performing the VAB task and while resting. Outside the scanner, they completed other cognitive tasks over several days. A vabCPM constructed from these data successfully predicted VAB performance. Strikingly, the network edges that predicted better VAB performance (positive edges) predicted worse selective and sustained attention performance, and vice versa. Predictions from the saCPM mirrored these results, with the network’s negative edges predicting better VAB performance. Furthermore, the vabCPM’s positive edges significantly overlapped with the saCPM’s negative edges, and vice versa. We conclude that these partially overlapping networks each have general attentional functions. They may indicate an individual’s propensity to diffusely deploy attention, predicting better performance for some tasks and worse for others.Significance statementA longstanding question in psychology and neuroscience is whether we have general capacities or domain-specific ones. For such general capacities, what is the common function? Here we addressed these questions using the attentional blink (AB) task and neuroimaging. Individuals searched for two items in a stream of distracting items; the second item was often missed when it closely followed the first. How often the second item was missed varied across individuals, which was reflected in attention networks. Curiously, the networks’ pattern of function that was good for the AB was bad for other tasks, and vice versa. We propose that these networks may represent not a general attentional ability, but rather the tendency to attend in a less focused manner.


2017 ◽  
Vol 56 (6) ◽  
pp. 991-1001 ◽  
Author(s):  
Stefania Coelli ◽  
Riccardo Barbieri ◽  
Gianluigi Reni ◽  
Claudio Zucca ◽  
Anna Maria Bianchi

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