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Movement-related beta event-related synchronization (ERS) has been linked to motor control and learning, showing potential as a therapeutic target for those with movement deficits, such as stroke survivors. However…
Human perception of polarised light, known as Haidingerâs brushes, is linked to macular health but is typically too faint for reliable clinical use. Structured light can enhance these entoptic patterns, but the…
Early diagnosis of Parkinson’s disease (PD) is challenging due to the difficulty in identification of various early motor signs. We aimed to develop and validate a highly efficient detection model for early-stage PD…
The cerebral cortex is highly sensitive to oxygen availability and thus serves as an ideal model for studying neural adaptation to hypoxia. Here, we integrated long-read (Oxford Nanopore) and short-read (Illumina)…
Parkinsonâs disease (PD) is characterized by degeneration of dopaminergic neurons in the substantia nigra pars compacta, but the molecular events preceding neuronal loss remain unclear. Here, we combine spatial…
Artificial intelligence systems are becoming more intelligent, but at a very high cost in terms of energy consumption and training requirements. By contrast, our brains only require 20âW of energy, they learn online…
Stroke is a common disease with an extremely high disability rate. In addition to conventional training, environmental stimulation training is also an effective approach. However, its neuropsychological basis remains…
Robotic systems can enhance the amount and repeatability of physical guided motor training. Yet their real-world adoption is limited, partly due to non-intuitive trainer/therapist-trainee/patient interactions. To address…
Manual annotation of spike-wave discharges (SWDs), the electrographic hallmark of absence seizures, is labor-intensive for long-term electroencephalography (EEG) monitoring studies. While machine learning approaches show…
Drug addiction is marked by drug-biased salience attribution and prefrontal cortex (PFC) dysfunction. As drug-associated cues acquire incentive properties and underpin drug craving, seeking, and relapse, diminishing…
The network organization of the human brain dynamically reconfigures in response to changing environmental demands, an adaptive process that may be disrupted in a symptom-relevant manner across psychiatric illnesses…
The primary visual cortex (V1) encodes multidimensional representations of ongoing movements, raising the question of how these signals are organized and interact with sensory representations within the same population…
With artificial-intelligence tools speeding up and taking on ever more steps in science, Nature canvassed opinions on tasks that readers would rather keep for themselves. Here is a snapshot of the responses. As a student…
Reward responsiveness plays an important role in promoting health and well-being in youth. Understanding associations between early experiences and variation in the typical developmental trajectory of reward…
Public health policy and clinical guidelines worldwide have stressed the importance of exercise for health and well-being. However, an increasing evidence-base shows that personality traits can impact individual…
Adolescence is a period of rapid neurobiological and behavioural change, yet how brain maturation deviations relate to psychopathology remains unclear. Here, we show, using data from the Adolescent Brain Cognitive…
Repeatedly processing an object leads to subsequent behavioral improvements in its identification and reductions in associated neural activity, a form of neural processing efficiency that multiple theoretical models have…
Deceptive actions such as head fakes are a hallmark of interactive sports, yet it is not well understood how decisions and whole-body responses to head fakes unfold over time. In the present study, participants viewed…
Despite broad scientific consensus, a large proportion of the UK population remain unconvinced of the reality of anthropogenic climate change. Segmentation research has increased understanding of attitudes towards…
Social capital (SC) is a key determinant of well-being and social participation, yet the magnitude of its individual differences and their neurobiological bases remain poorly understood. Here we showed that social…
Are public sector workers more honest? Although an important question in public administration and the policy sciences, empirical results have been inconclusive. Current studies have largely relied on indirect methods…
Mental health issues, especially depressive symptoms, among young adults represent a public health challenge. Conventional psychological assessment tools have limited sensitivity and specificity for identifying…
The development of young childrenâs emotional competence not only affects their current mental health and well-being but also has a profound impact on their future socialization, learning ability, and overall quality…
Despite the growing importance of open and online higher education in widening access, student attrition remains a major concern. This study seeks to provide a large-scale descriptive analysis of student attrition in an…
Workâfamily conflict is a prevalent issue among parents of preschool children, and prolonged exposure to such conflict can significantly impact the social adjustment of preschool children. In this study, we conducted a…
Mental health applications (MHAs) hold promise for expanding access to care, yet user satisfaction varies across cultural contexts. Drawing on value co-creation theory, this study integrates developer and user…
This study examines how video duration—specifically short-form (under 1 min) versus long-form (over 10 min)—affects learner engagement and sentiment in YouTube-based educational content. Drawing on 623 videos retrieved…
The development of AI technology has enabled algorithms to gradually take on some of the management tasks previously completed by human managers in organizations, such as task allocation, performance review, employee…
Deep interaction is closely linked to learning quality in blended learning, yet its mechanisms remain unclear. While cognitive interaction has been widely studied, group dynamics are increasingly seen as an important…
Large Language Models (LLMs) are increasingly being applied to time-series forecasting, giving rise to a class of models referred to as time-series LLMs. While these models achieve competitive predictive accuracy, their…
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