Neuropsychological effects of the CSMD1 genome‐wide associated schizophrenia risk variant rs10503253

The single‐nucleotide polymorphism (SNP) rs10503253, located within the CUB and Sushi multiple domains‐1 (CSMD1) gene on 8p23.2, was recently identified as genome‐wide significant for schizophrenia (SZ), but is of unknown function. We investigated the neurocognitive effects of this CSMD1 variant in vivo in patients and healthy participants using behavioral and imaging measures of brain structure and function. We compared carriers and non‐carriers of the risk ‘A’ allele on measures of neuropsychological performance typically impaired in SZ (general cognitive ability, episodic and working memory and attentional control) in independent samples of Irish patients (n = 387) and controls (n = 171) and German patients (205) and controls (n = 533). Across these groups, the risk ‘A’ allele at CSMD1 was associated with deleterious effects across a number of neurocognitive phenotypes. Specifically, the risk allele was associated with poorer performance on neuropsychological measures of general cognitive ability and memory function but not attentional control. These effects, while significant, were subtle, and varied between samples. Consistent with previous evidence suggesting that CSMD1 may be involved in brain mechanisms related to memory and learning, these data appear to reflect the deleterious effects of the identified ‘A’ risk allele on neurocognitive function, possibly as part of the mechanism by which CSMD1 is associated with SZ risk.     

Su-30飞行员在模拟飞行任务中的眼动指标分析

目的：获取战斗机飞行员在模拟飞行任务中的注意力分配情况和工作负荷的变化,为以后的飞行训练提供技术指导。方法：让十八名SU-30飞行员在模拟飞行器上完成爬升和翻转任务,同时使用眼动仪记录下飞行员的眼动数据,将数据源划分为外景、地平仪、高度表、速度表和综合电子屏显五个区域,并对这五个区域的眼动的数据进行分析对比。结果：在两种任务下,飞行员均在在座舱仪表分配更多的注视点和注视时间;在翻转任务中,飞行员在各个兴趣区的瞳孔直径都小于爬升任务中的直径;扫视幅度随着任务难度的加大而减小。结论：眼动技术可以作为测量飞行员注意力分配的有效方法;不同的任务下飞行员有不同的注意力分配模式,飞行员注意力主要集中在座舱仪表内;翻转任务比爬升任务在仪表上分配了更多的注意力,获取飞行员的注意力分配模式可以为飞行学员训练提供参考。     

THE EFFECT OF 40 HOURS OF CONSTANT WAKEFULNESS ON NUMBER COMPARISON PERFORMANCE

We investigated the effects of sleep loss and circadian rhythm on number comparison performance. Magnitude comparison of single-digits is robustly characterized by a distance effect: Close numbers (e.g., 5 versus 6) produce longer reaction times than numbers further apart (e.g., 2 versus 8). This distance effect is assumed to reflect the difficulty of a comparison process based on an analogous representation of general magnitude. Twelve male participants were required to stay awake for 40?h in a quasi-constant-routine protocol. Response speed and accuracy deteriorated between 00:00 and 06:00?h but recovered afterwards during the next day, indicating a circadian rhythm of elementary cognitive function (i.e., attention and speed of mental processing). The symbolic distance effect, however, did not increase during the nighttime, indicating that neither cumulative sleep loss nor the circadian clock prolongs numerical comparison processes. The present findings provide first evidence for a relative insensitivity of symbolic magnitude processing against the temporal variation in energy state. (Author correspondence: michael.steinborn@uni-tuebingen.de)     

Sleep,Sleepiness, Fatigue,and Performance of 12-Hour-Shift Nurses

Nurses working 12-h shifts complain of fatigue and insufficient/poor-quality sleep. Objectively measured sleep times have not been often reported. This study describes sleep, sleepiness, fatigue, and neurobehavioral performance over three consecutive 12-h (day and night) shifts for hospital registered nurses. Sleep (actigraphy), sleepiness (Karolinska Sleepiness Scale [KSS]), and vigilance (Performance Vigilance Task [PVT]), were measured serially in 80 registered nurses (RNs). Occupational fatigue (Occupational Fatigue Exhaustion Recovery Scale [OFER]) was assessed at baseline. Sleep was short (mean 5.5?h) between shifts, with little difference between day shift (5.7?h) and night shift (5.4?h). Sleepiness scores were low overall (3 on a 1–9 scale, with higher score indicating greater sleepiness), with 45% of nurses having high level of sleepiness (score ?>?7) on at least one shift. Nurses were progressively sleepier each shift, and night nurses were sleepier toward the end of the shift compared to the beginning. There was extensive caffeine use, presumably to preserve or improve alertness. Fatigue was high in one-third of nurses, with intershift fatigue (not feeling recovered from previous shift at the start of the next shift) being most prominent. There were no statistically significant differences in mean reaction time between day/night shift, consecutive work shift, and time into shift. Lapsing was traitlike, with rare (39% of sample), moderate (53%), and frequent (8%) lapsers. Nurses accrue a considerable sleep debt while working successive 12-h shifts with accompanying fatigue and sleepiness. Certain nurses appear more vulnerable to sleep loss than others, as measured by attention lapses. (Author correspondence: jgeiger@son.umaryland.edu)     

A randomized trial of cognitive rehabilitation in cancer survivors

Aims

The second most frequently reported post-treatment symptom in cancer survivors are concerns about impaired cognition. Despite numerous studies demonstrating significant impairments in a portion of survivors, information on effective treatments remains an emerging area of research. This study examined the effectiveness of a group-based cognitive rehabilitation intervention in cancer survivors.

Main methods

This study was a randomized, controlled study of a 7-week cognitive rehabilitation intervention delivered in group format. Participants were evaluated with subjective symptom questionnaires and objective neurocognitive tests prior to and following treatment.

Key findings

Twenty-eight participants (mean age 58 years) with a median of 3 years (± 6 years) post-primary/adjuvant treatment and various cancer sites (breast, bladder, prostate, colon, uterine) completed the study. Compared to baseline, the treatment group demonstrated improvements in symptoms of perceived cognitive impairments (p < .01), cognitive abilities (p < .01) and overall quality of life with regard to cognitive symptoms (p < .01) as measured by the FACT-Cog. The treatment group also improved on objective measures of attention (p < .05) and a trend toward improvement on verbal memory. Significant improvement was not observed on all cognitive tests.

Significance

A group based cognitive rehabilitation intervention in cancer survivors was effective for improving attention abilities and overall quality of life related to cognition. Results suggest that group based cognitive rehabilitation may be an effective intervention for treating cognitive dysfunction in cancer patients and should be further studied in a larger trial with an active control condition.     

Attentional bias in the radial and vertical dimensions of space

Under visual guidance, healthy subjects usually misbisect radial lines farther than, and vertical lines above the true center. It was suggested that radial and vertical misbisection depended on the presence of an attentional bias toward far/upper space. The aim of the present study was to investigate whether such attentional bias depends on a single mechanism or on separate mechanisms. Ninety participants were asked to bisect lines radially and vertically oriented. The results confirmed the presence of a consistent bisection bias farther than (radial lines), and above (vertical lines) the true center. Furthermore, there was a significant correlation between radial and vertical bisection errors. These findings suggest that a single neural mechanism is involved in producing the attentional bias toward far/upper space.     

A robust deep attention dense convolutional neural network for plant leaf disease identification and classification from smart phone captured real world images

Plant diseases cause significant food loss and hence economic loss around the globe. Therefore, automatic plant disease identification is a primary task to take proper medications for controlling the spread of the diseases. Large variety of plants species and their dissimilar phytopathological symptoms call for the implementation of supervised machine learning techniques for efficient and reliable disease identification and classification. With the development of deep learning strategies, convolutional neural network (CNN) has paved its way for classification of multiple plant diseases by extracting rich features. However, several characteristics of the input images especially captured in real world environment, viz. complex or indistinguishable background, presence of multiple leaves with the diseased leaf, small lesion area, solemnly affect the robustness and accuracy of the CNN modules. Available strategies usually applied standard CNN architectures on the images captured in the laboratory environment and very few have considered practical in-field leaf images for their studies. However, those studies are limited with very limited number of plant species. Therefore, there is need of a robust CNN module which can successfully recognize and classify the dissimilar leaf health conditions of non-identical plants from the in-field RGB images. To achieve the above goal, an attention dense learning (ADL) mechanism is proposed in this article by merging mixed sigmoid attention learning with the basic dense learning process of deep CNN. The basic dense learning process derives new features at higher layer considering all lower layer features and that provides fast and efficient training process. Further, the attention learning process amplifies the learning ability of the dense block by discriminating the meaningful lesion portions of the images from the background areas. Other than adding an extra layer for attention learning, in the proposed ADL block the output features from higher layer dense learning are used as an attention mask to the lower layers. For an effective and fast classification process, five ADL blocks are stacked to build a new CNN architecture named DADCNN-5 for obtaining classification robustness and higher testing accuracy. Initially, the proposed DADCNN-5 module is applied on publicly available extended PlantVillage dataset to classify 38 different health conditions of 14 plant species from 54,305 images. Classification accuracy of 99.93% proves that the proposed CNN module can be used for successful leaf disease identification. Further, the efficacy of the DADCNN-5 model is checked after performing stringent experiments on a new real world plant leaf database, created by the authors. The new leaf database contains 10,851 real-world RGB leaf images of 17 plant species for classifying their 44 distinguished health conditions. Experimental outcomes reveal that the proposed DADCNN-5 outperforms the existing machine learning and standard CNN architectures, and achieved 97.33% accuracy. The obtained sensitivity, specificity and false positive rate values are 96.57%, 99.94% and 0.063% respectively. The module takes approximately 3235 min for training process and achieves 99.86% of training accuracy. Visualization of Class activation mapping (CAM) depicts that DADCNN-5 is able to learn distinguishable features from semantically important regions (i.e. lesion regions) on the leaves. Further, the robustness of the DADCNN-5 is established after experimenting with augmented and noise contaminated images of the practical database.     

Gender difference in N170 elicited under oddball task

Background

Some studies have reported gender differences in N170, a face-selective event-related potential (ERP) component. This study investigated gender differences in N170 elicited under oddball paradigm in order to clarify the effect of task demand on gender differences in early facial processing.

Findings

Twelve males and 10 females discriminated targets (emotional faces) from non-targets (emotionally neutral faces) under an oddball paradigm, pressing a button as quickly as possible in response to the target. Clear N170 was elicited in response to target and non-target stimuli in both males and females. However, females showed more negative amplitude of N170 in response to target compared with non-target, while males did not show different N170 responses between target and non-target.

Conclusions

The present results suggest that females have a characteristic of allocating attention at an early stage when responding to faces actively (target) compared to viewing faces passively (non-target). This supports previous findings suggesting that task demand is an important factor in gender differences in N170.     

Inhibition in Adults with Attention Deficit/Hyperactivity Disorder: Event-Related Potentials in the Stop Task

The core deficit in Attention Deficit/Hyperactivity Disorder (ADHD) may be a deficiency in executive functions, particularly the processes that are associated with the inhibition of predominant responses. To test this notion in the adult population, healthy undergraduate volunteers and students with ADHD symptoms performed a visual Stop Signal Task (Logan et al. J Exp Psychol: Hum Percept Perform 10:276–291, 1984) while Event-Related brain Potentials were recorded. The two groups did not differ on behavioral measures of performance, but there was a significant difference in the N2–P3 component. These results underline the robustness of an N2–P3 difference between healthy adults and people with ADHD symptoms that have persisted into young adulthood.     

Some conceptual problems with the classical theory of behaviour

Behaviour is usually assumed to depend on the reach of a critical intensity--termed reactivity threshold--by its motivation. This view represents a simple, predictive theoretical framework in ethology and animal psychology. However, it is here argued that only the influence of an isolated motivation on behaviour can be explained that way; that such a view fails to account for behaviour when several motivations are jointly activated. Upon analysis, the classical theory of behaviour (CTB) proves to be under-specified and thus leads to three conceptual problems that make it logically inconsistent for the study of multiple motivations. A revision of the CTB, called anticipatory dynamics model (ADM), is then developed in order to bring a theoretical solution to these conceptual problems. The ADM hypothesizes that an organism's motivational interactions are due to the limitation of the organism's attentional resources.