Cognitive Processing最新文献

Cognitive disabilities significantly impact individuals' ability to navigate daily life, creating challenges in communication, memory, and task performance. This research proposes an AI-enhanced framework integrating neural network technologies and advanced natural language processing algorithms to support individuals with cognitive disabilities. The framework aims to enhance language understanding, memory retention, and overall task efficiency. Its validity is demonstrated through experiments and performance analysis using real-world datasets, showing marked improvements in language comprehension, memory recall, and task execution. Key factors influencing the model's effectiveness include the severity of cognitive impairments, individual cognitive profiles, and the adaptability of AI algorithms. The transformative potential of AI-driven interventions is highlighted, offering personalized, scalable solutions to meet diverse needs. This study contributes to ongoing discussions on leveraging technology to promote independence, inclusion, and quality of life for individuals with cognitive disabilities, laying the groundwork for future advancements in cognitive augmentation and assistive technologies.

Forgiveness is crucial for emotional wellbeing and good mental health. It is therefore important to understand what cognitive processes may promote forgiveness to achieve optimal outcomes for individuals. There is some evidence to suggest that core self-evaluation (CSE) is related to how forgiving an individual may be. However, these studies have shown that this influence may be mediated by other cognitive processes. To date, the combined role of anger rumination and mindfulness as potential mediators has not been considered. This is despite recognized associations with constructs that underly CSE. To address this gap in knowledge, this study aimed to explore the relationship between CSE and forgiveness; considering whether this relationship is mediated by mindfulness and anger rumination. A further contribution to knowledge was that these relationships were considered across the three subtypes of forgiveness: self, others, and situation. A total of 490 participants (54% men; 45% women; 1% non-binary; average age = 43.7 years; SD = 17.7) provided complete responses to an online questionnaire measuring CSE, forgiveness, mindfulness, and anger rumination. The results demonstrated that CSE was positively related to forgiveness and mindfulness and negatively related to anger rumination. Mediation analysis demonstrated that some of the influence of CSE on forgiveness was through mindfulness and anger rumination. These results indicate that people with higher levels of CSE tend to have a greater degree of mindfulness, are less likely to engage in anger rumination, and are subsequently more likely to be forgiving. These findings provide further insight into the beliefs and processes that contribute to an individual's willingness to forgive. It also suggests that interventions targeting CSE, mindfulness, and anger rumination can help with the promotion of forgiveness.

Cognitive sex differences are shaped by hormone effects on brain development, organisation, structure, function, and ageing. In human speech and language, sex differences and hormone effects are typically studied in the form of performance-based differences (via measures of central tendency) with little attention given to underlying cognitive strategy. This study presents data from 126 healthy adults, aged 20-79 years, from three studies of letter based verbal fluency. Comparisons were conducted based on sex, menstrual cycle phase, and menopause stage to examine total words produced, plus switching and clustering strategy use. The investigation probed differences in performance, underlying cognitive strategies, and correlations between performance and strategy. For performance, there were no statistically significant sex or menopause group differences in total words, number of switches and cluster size. Menstrual cycle differences were significant for switches and cluster size, but not total words. However, there were large effect sizes for correlations between total word performance and strategy measures in some groups; these correlations formed patterns which differed as a function of sex, menstrual cycle phase, and menopausal stage. Words produced were highly correlated with switching in younger women at higher hormone menstrual cycle phases. Correlations between total words and both strategies were moderate and equivalent in older premenopausal and perimenopausal women. Postmenopausal women showed a pattern of higher correlation between total words and cluster size which was observed in younger women at the lower hormone cycle phase, and men. This study illustrates the impact of hormones and sex differences on strategy use in verbal fluency-underscoring the value of comparisons in strategy use between women at different reproductive life stages.

In spatial cognition, we conventionally draw a typological distinction between mental rotation (intrinsic, object movement) versus perspective taking (extrinsic, self movement). This paper re-examines a previous finding which could indicate that fundamentally different cognitive processes are reflected in these tasks. Specifically, performance as a function of rotation magnitude is a linear profile for mental rotation but a notched profile for perspective taking. Experiment 1 conceptually replicates this, finding a task by rotation magnitude interaction with more participants, more trials, and updated statistical controls. Experiment 2 extends the previous analysis to verify that the two performance profiles are genuinely different shapes rather than different effect sizes. Together these help confirm that mental rotation and perspective taking reflect fundamentally different cognitive processes, thus justifying their central focus in the typology of spatial cognition.

The human brain operates as a complex network, and understanding its functional connectivity is a core challenge in neuroscience. Functional near-infrared spectroscopy (fNIRS) offers a non-invasive, portable method for studying brain activity and connectivity, providing valuable insights into the brain's network dynamics. In this study, we used fNIRS to examine the functional connectivity of the human brain during the Dual n-back task, a cognitive challenge that varies in memory load (0-back, 1-back, and 2-back). Data were collected from 24 channels in the frontal cortex and pre-processed with discrete wavelet transform. Functional connectivity matrices for each task level were calculated using correlation analysis, and graph theory metrics such as clustering coefficient and local and global efficiency were assessed. Statistical comparisons (t-tests and ANOVA) revealed significant differences in these metrics across memory load levels, with higher memory loads leading to altered brain connectivity patterns (p < 0.05 for clustering coefficient and local efficiency, p < 0.04 for global efficiency). These findings suggest that as cognitive demand increases, the functional connectivity of the brain's frontal network changes, reflecting the dynamic nature of brain activity during complex tasks. This research highlights the potential of fNIRS for exploring brain network functions and has broader implications for understanding cognitive processes and developing neurocognitive diagnostics and interventions.

The influence of cognitive components such as attention and consciousness, perception and emotion, memory and mental patterns, language and meaning, problem-solving and creativity, decision-making and reasoning, and intelligence can be identified and tracked across many phenomena. Innovation is also effective as a consequence of the dynamic movement of these components. In the analysis of innovative movements, issues have been highlighted that have not been addressed by the rational and logical attitude of the technological approach, and in some cases, these issues are in direct opposition to the resulting rationalism from this attitude. To decipher these propositions, it is necessary to investigate the effects of cognitive components on innovative processes and then analyze the scope of these effects. The influence of creativity on innovative factors has been mentioned among the cognitive components, but the role of components such as perception, emotion, and meaning, which are introduced as stimuli for the initiation of an innovative movement, has been discussed less. Most products have an acceptable level of technology in their function, but they have deficiencies in the cognitive dimension. In fact, cognitive components can be considered a competitive advantage for firms.

Neuroscience research to decode cognitive and emotional processes has been widely embraced in education. The development of methodologies, case studies, and new technologies have advanced our understanding of students' complex thinking. Despite these advancements, long-term analysis at the convergence of neurosciences, education, and complex thinking remains limited. To address this gap, we conducted a bibliometric review using the prism method, spanning from 1960 to 2023 to map research trends, thematic evolutions, and future challenges. Our analysis of 3792 Scopus-indexed studies using advanced data visualization techniques yielded the following findings: (1) a predominant focus on critical thinking, with creativity driving innovative approaches that enhance problem-solving; (2) growing integration of neurotechnologies-such as EEG and neuroimaging-to assess and optimize cognitive engagement in educational settings; (3) an increasing emphasis on metacognition, highlighting its role as a reflective thinking strategy that fosters cogntive control and higher-order thinking; and (4) emerging research on executive functions, particularly their role in fostering decision-making and cognitive flexibility in learning environments. These findings contribute to the understanding of cognitive processes and inform practical applications in education, including the design of personalized learning strategies, real-time cognitive assessment tools, and neurotechnology-supported pedagogical models. The study advocates an interdisciplinary approach, integrating neuroscientific insights into complex thinking to enhance cognitive processing within STEAM education.

Political leaders are often regarded as the most qualified individuals to address modern societal challenges, owing to the knowledge they acquire through their experience in dealing with complex issues, governance and management, and working towards making impactful decisions. To understand the influence of prior knowledge on decision-making, we conducted a comparative analysis of complex decision-making performance in a politically themed computer-simulated microworld involving incumbent elected officials and a general population sample, each contrasted with a random-response baseline produced with randomly generated decisions. Participants were tasked to govern a country for re-election while maintaining financial stability. The pattern of results suggests that decision-making faces a 'wall of complexity' whether one is an elected official or a citizen. Although elected officials generally reported having greater political knowledge, their performance was still relatively poor. The elected officials and general population subgroups performed at the same level and only slightly better than chance. Addressing the societal challenges of our time requires elected officials to possess more than domain-specific prior knowledge.

Flexibly using memories to guide planning behavior is critical for typical functioning, yet little is known of how this ability emerges and the mechanisms supporting performance. The current study examined children's ability to generalize during memory-guided planning in a sample of 76 preschoolers (24 2-year-olds, M = 32.21 months, SD = 2.21, 12 girls; 27 3-year-olds, M = 41.37 months, SD = 3.50, 17 girls; and 25 4-year-olds, M = 54.64 months, SD = 3.29, 6 girls). Results suggested that 3 and 4-year-olds can flexibly apply a memory from one context to another, while 2-year-olds struggle to generalize. Further, individual differences in inhibitory control predicted performance during memory-guided planning, providing a potential mechanism supporting its early development.

This research aimed to translate and assess the psychometric characteristics of the abbreviated Self-Reported Olfactory Functioning and Olfaction-Related Quality of Life (ASOF) among Iranian Farsi-speaking individuals. This tool development study, initiated after receiving authorization from the original questionnaire's corresponding author, involved the translation of the ASOF questionnaire using the forward-backward method, in line with the World Health Organization's standards. The research was conducted quantitatively, incorporating minor modifications in the Farsi version of the questionnaire items to ensure cultural relevance. The validity of the questionnaire, including face, content, and structural aspects, was evaluated. The internal consistency was measured using Cronbach's alpha. Acceptable levels were observed in the item impact score, content validity index, and content validity ratio across all questionnaire items based on data from 30 healthy participants. The Cronbach's alpha coefficients for self-reported olfactory function and olfactory quality of life assessment were 0.906 and 0.943, respectively, falling within a permissible range. Confirmatory factor analysis supported the three-factor structure of the ASOF questionnaire, as evidenced by standard factor loadings and goodness of fit indices, using a sample of 120 patients. The study concludes that the Farsi version of the ASOF questionnaire is a reliable and valid tool. It can effectively be used to assess a broad spectrum of olfactory disorders and olfaction-related quality of life in Farsi-speaking populations.