scholarly journals Dynamics of cerebral responses to sustained attention performance during one night of sleep deprivation

2017 ◽  
Vol 27 (2) ◽  
pp. 184-196 ◽  
Author(s):  
Yuanqiang Zhu ◽  
Yibin Xi ◽  
Ningbo Fei ◽  
Yuchen Liu ◽  
Xinxin Zhang ◽  
...  
Keyword(s):  
Sleep Deprivation ◽  
Sustained Attention ◽  
Attention Performance

scholarly journals Sleep Deprivation and Sustained Attention Performance: Integrating Mathematical and Cognitive Modeling

2009 ◽  
Vol 33 (5) ◽  
pp. 880-910 ◽  
Author(s):  
Glenn Gunzelmann ◽  
Joshua B. Gross ◽  
Kevin A. Gluck ◽  
David F. Dinges
Keyword(s):  
Sleep Deprivation ◽  
Sustained Attention ◽  
Cognitive Modeling ◽  
Attention Performance

scholarly journals Sustained Attention Performance during Sleep Deprivation Associates with Instability in Behavior and Physiologic Measures at Baseline

SLEEP ◽  
2014 ◽  
Vol 37 (1) ◽  
pp. 27-39 ◽  
Author(s):  
Eric Chern-Pin Chua ◽  
Sing-Chen Yeo ◽  
Ivan Tian-Guang Lee ◽  
Luuan-Chin Tan ◽  
Pauline Lau ◽  
...  
Keyword(s):  
Sleep Deprivation ◽  
Sustained Attention ◽  
Attention Performance

Sustained attention performance during sleep deprivation and following nap: associated with trait-like vulnerability

2019 ◽  
Vol 64 ◽  
pp. S181-S182
Author(s):  
Y.J. Jung ◽  
J. Lee ◽  
T.J. Lee ◽  
S.Y. Ryu ◽  
S.B. Lee ◽  
...  
Keyword(s):  
Sleep Deprivation ◽  
Sustained Attention ◽  
Attention Performance

scholarly journals 0308 DRD2 C957T Genotype Influences Vigilant Attention Performance Impairment During Total Sleep Deprivation

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A116-A116
Author(s):  
R A Muck ◽  
L Skeiky ◽  
M A Schmidt ◽  
B C Satterfield ◽  
J P Wisor ◽  
...  
Keyword(s):  
Sleep Deprivation ◽  
Analysis Of Covariance ◽  
Genotype Distribution ◽  
Total Sleep Deprivation ◽  
Psychomotor Vigilance Test ◽  
Time In Bed ◽  
Dat1 Gene ◽  
Performance Impairment ◽  
Attention Performance ◽  
Time Awake

Abstract Introduction There are substantial, phenotypical individual differences in the adverse impact of total sleep deprivation (TSD) on vigilant attention performance. Dopaminergic genotypes have been found to contribute to these phenotypical differences. Here we investigated the association between a single nucleotide polymorphism (SNP) of the dopamine receptor D2 (DRD2) gene, C957T (rs6277), on vigilant attention performance measured with the psychomotor vigilance test (PVT) in a laboratory TSD study. Methods N=46 healthy adults (ages 26.0±5.3y; 25 females) completed a 4-day in-laboratory study with a baseline day (10h time in bed: 22:00-08:00), a 38h TSD period, and a recovery day (10h time in bed: 22:00-08:00). DNA isolated from whole blood was assayed for DRD2 C957T genotype using real-time polymerase chain reaction. PVT performance was measured during TSD at 2-4h intervals, and analyzed for genotype using mixed-effects analysis of covariance of lapses of attention (RTs>500ms). Results The genotype distribution in this sample - 28.3% C/C, 50.0% C/T, 21.7% T/T - was found to be in Hardy-Weinberg Equilibrium (X21=0.0008, p=0.98). As expected, there was a significant effect of time awake on PVT performance (F14,602=26.67, p<0.001). There was a significant main effect of DRD2 genotype (F2,602=3.24, p=0.040) and a significant interaction of time awake by DRD2 genotype (F28,602=1.96, p=0.003). Subjects homozygous for the T allele showed greater impairment during extended wakefulness than carriers of the C allele. Genotype explained 7.6% of the variance in the PVT data observed during the 38h TSD period. Conclusion Subjects homozygous for the T allele of DRD2 C957T were considerably more vulnerable to TSD-induced PVT performance impairment than carriers of the C allele. A recent study showed that DRD2 C957T influences PVT performance in interaction with a SNP of the DAT1 gene. Here, DRD2 genotype was by itself also associated with PVT performance impairment during TSD. Support CDMRP awards W81XWH-16-1-0319 and W81XWH-18-1-0100.

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 ◽  
...  
Keyword(s):  
Sustained Attention ◽  
Interactive Effects ◽  
Facial Emotion ◽  
Attention Performance

scholarly journals Interpersonal early-life trauma alters amygdala connectivity and sustained attention performance

2017 ◽  
Vol 7 (5) ◽  
pp. e00684 ◽  
Author(s):  
Francesca C. Fortenbaugh ◽  
Vincent Corbo ◽  
Victoria Poole ◽  
Regina McGlinchey ◽  
William Milberg ◽  
...  
Keyword(s):  
Sustained Attention ◽  
Early Life ◽  
Early Life Trauma ◽  
Attention Performance

scholarly journals Overlapping attentional networks yield divergent behavioral predictions across tasks: Neuromarkers for diffuse and focused attention?

2019 ◽  
Author(s):  
Esther X.W. Wu ◽  
Gwenisha J. Liaw ◽  
Rui Zhe Goh ◽  
Tiffany T.Y. Chia ◽  
Alisia M.J. Chee ◽  
...  
Keyword(s):  
Attentional Blink ◽  
Sustained Attention ◽  
Attention Networks ◽  
Domain Specific ◽  
Performance Predictions ◽  
Connectivity Patterns ◽  
Reading Recall ◽  
The Common ◽  
Attention Performance ◽  
Behavioral Predictions

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.

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