Previous studies have found that individuals with dyslexia perform poorly in paired associate learning (PAL) tasks, which were explained by a deficit in cross-modal association or verbal demand in alphabetic language. However, the nature of PAL defic...
Brief post-learning wakeful resting periods and local sleep mechanisms have been proposed to support offline memory consolidation processes. Mind-wandering (MW), thought to reflect the occurrence or need for local sleep, has been linked to momentary...
This study investigated the effects of collagen hydrolysates (CH) on language cognitive function and brain structure. In this open-label study, 5 g CH was administered once a day for 4 weeks to 30 healthy participants aged 49–63 years. The prim...
Background/Objectives: This study aimed to explore whether perioperative changes in cognitive function following carotid artery revascularization, including carotid endarterectomy (CEA) and carotid artery stenting (CAS), are associated with subsequen...
Previous studies have found a benefit of closed-loop transcranial alternating current stimulation (CL-tACS) matched to ongoing slow-wave oscillations (SWO) during sleep on memory consolidation for words in a paired associates task (PAT). Here, we exa...
Mental imagery is used extensively in the sporting domain. It is used for performance-enhancement purposes, arousal regulation, affective and cognitive modification, and rehabilitation purposes. The purpose of this experiment was to evaluate whether...
Eidetic memory has been reported in children and in patients with synesthesia but is otherwise thought to be a rare phenomenon. Presented herein is a patient with right-sided language dominance, as proven via multiple functional imaging and neuropsyc...
Background: Episodic memory (EM) is particularly sensitive to pathological conditions and aging. In a neurocognitive context, the paired-associate learning (PAL) paradigm, which requires participants to learn and recall associations between stimuli,...
Cognitive bias tests are frequently used to assess affective state in nonhumans. We adapted the ambiguous-cue paradigm to assess affective states and to compare learning of reward associations in two distantly related species, an American black bear...
Making judgments of learning (JOLs) while studying is a useful tool for students to evaluate the status of their learning. Additionally, in associative learning contexts, JOLs can directly benefit learning when the to-be-learned information is relate...
Understanding how bodily signals shape emotional cognition across adulthood is critical for explaining age-related changes in emotional learning and memory. This study investigated age-related differences in interoceptive sensitivity and emotional as...
Identifying novel indications for approved drugs can accelerate drug development and reduce research costs. Most previous studies used shallow models for prioritizing the potential drug-related diseases and failed to deeply integrate the paths betwee...
Recently, graph neural networks (GNN), due to their compelling representation learning ability, have been exploited to deal with emotion-cause pair extraction (ECPE). However, current GNN-based ECPE methods mostly concentrate on modeling the local de...
21 June 2021
This study focused on the associative learning of new word forms in the first language and haptic stimuli. In this study, healthy Japanese participants performed three-step tasks. First, participants made nine subjective evaluations of haptic stimuli...
It is well known that the unusual expression of long non-coding RNAs (lncRNAs) is closely related to the physiological and pathological processes of diseases. Therefore, inferring the potential lncRNA–disease associations are helpful for unders...
Predicting novel uses for drugs using their chemical, pharmacological, and indication information contributes to minimizing costs and development periods. Most previous prediction methods focused on integrating the similarity and association informat...
Associative learning is a fundamental neural mechanism in human memory and cognition. It has attracted considerable attention in neuromorphic system design owing to its multimodal integration, fault tolerance, and energy efficiency. However, prior st...
24 October 2022
The COVID-19 pandemic has led to severe consequences for people’s mental health. The pandemic has also influenced our language use, shaping our word formation habits. The overuse of new metaphorical meanings has received particular attention fr...
Network alignment (NA) offers a comprehensive way to build associations between different networks by identifying shared nodes. While the majority of current NA methods rely on the topological consistency assumption, which posits that shared nodes ac...
Enhancer-promoter interactions (EPIs) are crucial for transcriptional regulation. Mapping such interactions proves useful for understanding disease regulations and discovering risk genes in genome-wide association studies. Some previous studies showe...
As modern technology enables instant access to virtually limitless information, students may perceive memorization of information as lacking in practical importance. The current study investigated the relationship between attitudes toward remembering...
MicroRNAs (miRNAs) play a crucial role in gene regulation and are strongly linked to various diseases, including cancer. This study presents AEmiGAP, an advanced deep learning model that integrates autoencoders with long short-term memory (LSTM) netw...
One of the main goals of human genetics is to understand the connections between genomic variation and the predisposition to develop a complex disorder. These disease–variant associations are usually studied in a single independent manner, disr...
Although associative interference has traditionally been attributed to retrieval competition, emerging evidence suggests that interference may also arise from encoding-based representational processes. The present study examined whether retroactive i...
Background: Bilingual children are frequently exposed to accented speech, yet it remains unclear how accent familiarity affects their ability to learn new words. This study examined Spanish–English bilingual children’s (n = 46) novel word...
Abnormal miRNA functions are widely involved in many diseases recorded in the database of experimentally supported human miRNA-disease associations (HMDD). Some of the associations are complicated: There can be up to five heterogeneous association ty...
The AI-driven applications and large data generated by IoT devices connected to large-scale utility infrastructures pose significant operational challenges, including increased latency, communication overhead, and computational imbalances. Addressing...
Aberrant expressions of long non-coding RNAs (lncRNAs) are often associated with diseases and identification of disease-related lncRNAs is helpful for elucidating complex pathogenesis. Recent methods for predicting associations between lncRNAs and di...
Identifying new disease indications for existing drugs can help facilitate drug development and reduce development cost. The previous drug–disease association prediction methods focused on data about drugs and diseases from multiple sources. Ho...
Assessing preferences for heating, ventilation, and air conditioning (HVAC) sounds is important for improving comfort in living spaces. Recently, preference assessments using neurophysiological measurements have gained attention. However, association...
Pre-commercial virtual fence (VF) neckbands (eShepherd®, Agersens, Melbourne, Vic, Australia) can contain cows within a designated area without the need for physical fencing, through associative learning of a paired audio tone and electrical puls...
The standard matrix factorization methods for recommender systems suffer from data sparsity and cold-start problems. Thus, in real-world scenarios where items are commonly associated with textual data such as reviews, it becomes necessary to build a...
Context-aware international event forecasting must preserve context-specific evidence while drawing on related interactions across semantic boundaries. We propose the hierarchical adaptive fusion and separation network (HA-AFSNet), which learns this...
This magnetoencephalography (MEG) study investigated evoked ON and OFF responses to ramped and damped sounds in normal-hearing human adults. Two pairs of stimuli that differed in spectral complexity were used in a passive listening task; each pair co...
Making judgments of learning (JOLs) while studying related word pairs can enhance performance on tests that rely on cue-target associations (e.g., cued recall) compared to studying alone. One possible explanation for this positive JOL reactivity effe...
The adoption of provincial carbon-trading market-construction policies in China expanded rapidly before a five-year hiatus in new qualifying policies. This study examines how industrial-structure and GDP-feasibility learning cues relate to diffusion...
Artificial intelligence (AI) is reshaping occupational tasks and skill requirements, creating a human resource management (HRM) challenge around how future employees develop readiness for responsible AI-enabled work. This study examines relationships...
Targeted memory reactivation (TMR) and transcranial direct current stimulation (tDCS) can enhance memory consolidation. It is currently unknown whether TMR reinforced by simultaneous tDCS has superior efficacy. In this study, we investigated the comp...
Background: Robotic systems have the potential to significantly enhance the accuracy and outcomes of spinal surgery. Adopting this new technology requires an examination of its learning curve and influencing factors. This study analyzes the learning...
In this study, we investigated the associations between implicit associative learning with the cortisol and salivary alpha-amylase (sAA) stress response to an acute stressor as well as their associations with attention. Eighty one healthy adults (25...
Sleep supports brain development and adaptability, yet its relationship with cognitive performance in farm animals remains unclear. This study examined the association between a behavioral indicator of rapid eye movement (REM) sleep, the REM sleep-li...
In this work, we develop a pipeline that associates Persistence Diagrams to digital data via the most appropriate filtration for the type of data considered. Using a grid search approach, this pipeline determines optimal representation methods and pa...
Assessing chart understanding requires distinguishing responses to local visual evidence from associations with a chart’s overall shape. We present Martingale Doppelgänger-Eval, an interventional audit framework that connects executable ed...
The use of intelligent systems in clinical diagnostics has evolved, integrating statistical learning and knowledge-based representation models. Two recent works propose the identification of risk factors for the diagnosis of obstructive sleep apnea (...
MicroRNAs (miRNAs) are small RNA molecules consisting of approximately 22 nucleotides; they regulate gene expression and are employed in the development of therapeutics for intractable diseases. Predicting the association between miRNAs and genes is...
Peptidylarginine deiminase 4 (PAD4) is an increasingly prominent therapeutic target in oncology, inflammatory disease, and neutrophil extracellular trap (NET)-associated pathologies, yet public bioactivity data for PAD4 inhibitors remain fragmented a...
Background: MicroRNAs (miRNAs) regulate biological processes and are associated with human diseases. Computational prediction can prioritize candidate associations for experimental investigation, but many existing methods emphasize nonlinear represen...
Molecular-scale understanding of rheological properties of small-molecular liquids and polymers is critical to optimizing their performance in practical applications such as lubrication and hydraulic fracking. We combine nonequilibrium molecular dyna...
Researchers in social semiotics have shown students’ emotions to be associated with their positioning, an association which contributes to students’ cognitive processes and, therefore, to their learning. Nevertheless, this association between emotion...
With the rapid developments of hyperspectral imaging, the cost of collecting hyperspectral data has been lower, while the demand for reliable and detailed hyperspectral annotations has been much more substantial. However, limited by the difficulties...
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