Linking metaphor comprehension with analogical reasoning: Evidence from typical development and autism spectrum disorder

We examined the relationship between metaphor comprehension and verbal analogical reasoning in young adults who were either typically developing (TD) or diagnosed with Autism Spectrum Disorder (ASD). The ASD sample was highly educated and high in verbal ability, and closely matched to a subset of TD participants on age, gender, educational background, and verbal ability. Additional TD participants with a broader range of abilities were also tested. Each participant solved sets of verbal analogies and metaphors in verification formats, allowing measurement of both accuracy and reaction times. Measures of individual differences in vocabulary, verbal working memory, and autistic traits were also obtained. Accuracy for both the verbal analogy and the metaphor task was very similar across the ASD and matched TD groups. However, reaction times on both tasks were longer for the ASD group. Additionally, stronger correlations between verbal analogical reasoning and working memory capacity in the ASD group indicated that processing verbal analogies was more effortful for them. In the case of both groups, accuracy on the metaphor and analogy tasks was correlated. A mediation analysis revealed that after controlling for working memory capacity, the inter-task correlation could be accounted for by the mediating variable of vocabulary knowledge, suggesting that the primary common mechanisms linking the two tasks involve language skills.     

Relationships Among Sleep Disturbance,Reward System Functioning,Anhedonia, and Depressive Symptoms

Recent models propose reward system dysfunction as a key mediator of the relationship between sleep and depression and anhedonia. This study explored interrelationships among sleep disturbance, depressive symptoms, anhedonia, and reward responsiveness. Two-hundred and sixty undergraduate students completed questionnaires and a daily diary paradigm assessing sleep, reward responsiveness, depression, anhedonia, and positive affect over 1 week. Baseline sleep disturbance was associated with depressive symptoms, anhedonia, and reward responsiveness. Daily diary sleep parameters showed differential associations with anticipatory versus consummatory reward responsiveness and positive affect. Poorer sleep quality, shorter sleep duration, and longer awakening after sleep onset predicted blunted anticipatory and consummatory reward responsiveness, while increased sleep onset latency and lower sleep efficiency predicted only decreased consummatory reward responsiveness. All sleep indices, except sleep onset latency, were associated with positive affect. Findings demonstrate unique associations between disparate sleep disturbance and reward responsiveness elements, highlighting new treatment mechanisms for anhedonia and depression.     

眼睛区域构型信息与特征信息的跨维共变增益效应及其加工特异性

面孔知觉可能在区域尺度上发生多维信息整合, 但迄今无特异性实验证据。本研究在两个实验中操纵面孔眼睛区域或嘴巴区域的单维构型或特征信息, 测量人们觉察单维变化或跨维共变的敏感度, 以此检测面孔区域尺度上的多维信息整合有何现象与规律, 进而揭示面孔知觉的多维信息整合机制。实验获得3个发现：(1)正立面孔眼睛区域的信息变化觉察呈现出“跨维共变增益效应”, 跨维信息共变觉察的敏感度显著高于任意一种单维信息变化觉察的敏感度; (2)“跨维共变增益效应”只在正立面孔的眼睛区域出现, 在倒置面孔的眼睛区域、正立面孔的嘴巴区域或倒置面孔的嘴巴区域都没有出现, 因此具有面孔区域特异性和面孔朝向特异性; (3)就单维信息变化觉察而言, 眼睛区域的敏感度不会受到面孔倒置的损伤, 但是嘴巴区域的敏感度会受到面孔倒置的显著损伤。综合可知, 面孔知觉确实会发生区域尺度上的信息整合, 它不是普遍性的信息量效应, 而是特异性的眼睛效应(只发生在正立面孔的眼睛区域)。这是面孔整体加工(face holistic processing)在单维信息分辨和多维信息整合之间建立联系的必经环节。这提示我们对全脸多维信息知觉整合的理解需要从传统的面孔整体加工假设升级到以眼睛为中心的层级化多维信息整合算法(a hierarchical algorithm for multi-dimensional information integration)。     

目光注视线索对客体注意的影响及作用机制

目光注视在人类社交以及捕获和维持注意方面发挥重要作用。但是, 目光注视如何与客体交互以引导注意分配至今尚不明确。因此, 本研究采用双框线索范式, 以具有两种注视方向(直视或回避)的面孔或实物作为客体, 通过操纵线索到目标间的SOA来考察目光注视对客体注意的影响及作用机制。实验1发现, 目光注视对客体效应的影响只出现在300 ms SOA时; 进一步分析发现, 客体效应的差异来自于直视条件下被试对无效相同客体位置上的目标比回避条件下反应更快。这表明与回避目光相比, 直视更能捕获我们的注意, 从而产生更大的客体效应。实验2将面孔对比度反转, 排除了低水平物理特征对实验1结果的影响。实验3使用两种注视方向的眼睛叠加杯子作为客体, 以探究目光注视效应是否能扩展到其他客体中, 结果与实验1相同。本研究结果表明, 目光注视能够与客体交互共同引导注意分配, 直视更能捕获注意, 但受SOA的影响, 上述结果支持了感觉增强理论。     

Bio-inspired cognitive architecture of episodic memory

Memory and learning are essential functions in human beings as they allow us to acquire and store in the brain representations of thoughts, experiences, and behaviors, which are required for problem-solving in our daily life and mainly for survival. Episodic memory is a type of memory that provides the ability to re-experience events in one’s life, and it is associated with their conscious recollection. Since episodic memory can represent our experiences about the environment, similar to a mental journey, it is desired in systems that attempt to create human-like behavior. Currently, the main problem is that state of the art proposals do not consider neuroscientific evidence like memory dynamics for forgetting or bottom-up inputs, and most of them do not consider episodic memory as a different memory but as part of general declarative memory. We consider these omissions to limit the generation of human-like behavior. In this work, we propose a bio-inspired cognitive architecture of episodic memory. Neuroscientific evidence provides us with the brain structures associated with this type of memory, the connections, and the operations these areas perform. We hypothesize that virtual entities endowed with our episodic memory cognitive architecture will plan and make decisions in a more human-like fashion. To test the capabilities of the proposal, we endowed a virtual creature with a distributed and concurrent implementation of our architecture, and it was given two tasks. The first task validated the functions of the memory independently, and in the second task, the creature used episodic memory to solve a planning problem. From the results of these experiments, we validate our proposal and show that it is possible to create a system that behaves as the human brain does.     

Bio-inspired computational object classification model for object recognition

Human beings can effortlessly perceive stimuli through their sensory systems to learn, understand, recognize and act on our environment or context. Over the years, efforts have been made to enable cybernetic entities to be close to performing human perception tasks; and in general, to bring artificial intelligence closer to human intelligence.Neuroscience and other cognitive sciences provide evidence and explanations of the functioning of certain aspects of visual perception in the human brain. Visual perception is a complex process, and its has been divided into several parts. Object classification is one of those parts; it is necessary for carrying out the declarative interpretation of the environment. This article deals with the object classification problem.In this article, we propose a computational model of visual classification of objects based on neuroscience, it consists of two modular systems: a visual processing system, in charge of the extraction of characteristics; and a perception sub-system, which performs the classification of objects based on the features extracted by the visual processing system.With the results obtained, a set of aspects are analyzed using similarity and dissimilarity matrices. Also based on the neuroscientific evidence and the results obtained from this research, some aspects are suggested for consideration to improve the work in the future and bring us closer to performing the task of visual classification as humans do.     

基于过程数据的问题解决能力测量及数据分析方法

问题解决能力是指在没有明显解决方法的情况下个体从事认知加工以理解和解决问题情境的能力。对问题解决能力的测量需要借助相对更复杂、更真实、具有可交互性的问题情境来诱导问题解决行为的呈现。使用虚拟测评抓取问题解决的过程数据并分析其中所蕴含的潜在信息是当前心理计量学中测量问题解决能力的新趋势。首先, 回顾问题解决能力测量方式的发展：从纸笔测验到虚拟测评。然后, 总结对比两类过程数据的分析方法：统计建模法和数据挖掘法。最后, 从非认知因素的影响、多模态数据的利用、问题解决能力发展的测量、其他高阶思维能力的测量和问题解决能力概念及结构的界定五个方面展望未来可能的研究方向。     

Computational modeling of organisational learning by self-modeling networks

Within organisational learning literature, mental models are considered a vehicle for both individual learning and organizational learning. By learning individual mental models (and making them explicit), a basis for formation of shared mental models for the level of the organization is created, which after its formation can then be adopted by individuals. This provides mechanisms for organizational learning. These mechanisms have been used as a basis for an adaptive computational network model. The model is illustrated by a not too complex but realistic case study.     

The role of mental rotation in TetrisTM gameplay: An ACT-R computational cognitive model

The mental rotation ability is an essential spatial reasoning skill in human cognition and has proven to be an essential predictor of mathematical and STEM skills, critical and computational thinking. Despite its importance, little is known about when and how mental rotation processes are activated in games explicitly targeting spatial reasoning tasks. In particular, the relationship between spatial abilities and Tetris^TM has been analysed several times in the literature. However, these analyses have shown contrasting results between the effectiveness of Tetris-based training activities to improve mental rotation skills. In this work, we studied whether, and under what conditions, such ability is used in the Tetris^TM game by explicitly modelling mental rotation via an ACT-R based cognitive model controlling a virtual agent. The obtained results show meaningful insights into the activation of mental rotation during game dynamics. The study suggests the necessity to adapt game dynamics in order to force the activation of this process and, therefore, can be of inspiration to design learning activities based on Tetris^TM or re-design the game itself to improve its educational effectiveness.     

Sleep interventions for performance,mood and sleep outcomes in athletes: A systematic review and meta-analysis

Sleep is fundamental to sports performance and other health outcomes such as mental wellbeing. This systematic review explored the effects of sleep interventions implemented among athletes on performance, sleep, and mood outcomes. Five databases were searched, returning 5996 records for screening. Of these, 27 articles met the inclusion criteria (16 controlled deigns, 11 uncontrolled; athletes n = 617; male n = 432, female n = 93, non-binary/other n = 0 or not reported n = 92). Narrative synthesis of all studies based on intervention type suggested that sleep hygiene, assisted sleep, and sleep extension interventions may be associated with improved sleep, performance, and mood outcomes. Twelve controlled trials were eligible for quantitative meta-analysis, investigating the effect of sleep interventions on athlete sleep, performance, and negative affect, compared to controls post-intervention. Utilizing random-effects meta-analyses, sleep interventions improved subjective sleep quality (g = 0.62, 95% CI [0.21, 1.02]), reduced sleepiness (g = 0.81, 95% CI [0.32, 1.30]) and decreased negative affect (g = 0.63, 95% CI [0.27, 0.98]), but did not appear to influence subjective sleep duration. No effects were identified for objective sleep measures (e.g., actigraphy), or aerobic/anaerobic performance indices. While sleep interventions may offer some benefit to athletes, caution is warranted given limitations of the extant research relating to small, non-representative studies with methodological concerns.