Articles tagged with Learning Processes
New research identifies Smoothened as a regulator of dopamine-acetylcholine timing, influencing learning, motivation, and behavioral flexibility in adulthood. The study found that animals lacking Smoothened learned motor tasks more quickly but were less sensitive to changes in effort or reward timing.
Researchers propose a temporally developmental continual learning framework inspired by human brain development, enabling cross-domain learning across perception, motor control, and interaction tasks. The approach achieves stable and strong continual learning performance while reducing network size and mitigating catastrophic forgetting.
A new analysis by NYU psychology professor Moira Dillon reveals that humans' ability to think geometrically may originate from shared mental processes with animals, rather than a unique 'math module'. This challenges traditional views on human geometric thinking and suggests that language plays a key role in transforming these processes.
Researchers at Dartmouth College developed a mathematical framework to map students' conceptual knowledge from short multiple-choice quizzes, revealing peaks of mastery and valleys of struggle. The technique could enable personalized learning, AI tutoring systems, and more efficient feedback.
A new study from Dartmouth College finds that social information can significantly impact how people experience negative events, including physical pain and mentally demanding tasks. When others describe an experience as painful, individuals tend to feel it that way, even when the actual experience is low in intensity.
Research shows that expert birders have more compact attention- and perception-related brain areas, linked to accurate bird identification. These structural changes persist in older birders and may benefit cognition as people age.
A new theory asserts that associative learning depends less on repetition and more on time passing between rewards, explaining why students who cram don't perform well. The study's findings could shift the way we look at learning and addiction, potentially speeding up artificial intelligence by borrowing from this new approach.
Researchers found individuals with stronger cue sensitivity tend to have harder time updating beliefs, leading to persistent poor decision-making. This association can lead to biased avoidance or favoritism of cues in people with compulsive disorders, addictions, or anxiety.
Researchers discovered cerebellar signals strengthen visual cues during learning, facilitating precise visuomotor associations. This finding highlights the cerebellum's crucial role in cognitive functions beyond motor control.
Researchers from UC San Francisco have identified the superior temporal gyrus brain region responsible for tracking words in a foreign language. The study shows that this region learns to recognize word boundaries through years of experience, enabling fluent speakers to distinguish individual words.
A University of Georgia study found that students who focus on personal growth and mastering the material tend to use deeper learning strategies and earn better grades. Instructors can help by creating opportunities for self-reflection and problem-solving tasks.
Researchers found that the brain's logical reasoning network was active before learning to code, and continued to engage strongly after acquiring Python skills. This suggests that humans can repurpose cognitive areas involved in reasoning to learn computer programming.
A recent Finnish study found that students' self-efficacy in mathematics is a key factor contributing to their motivation and performance. High self-efficacy predicted better performance, regardless of prior achievement level. In contrast, co-teaching showed no significant benefits on mathematics performance.
A new study combines eye tracking and artificial intelligence to identify key moments in educational videos that matter for learning. The research provides promise for individualized video education, where AI dynamically adjusts the content for a student's understanding.
Researchers at USC Dornsife College of Letters, Arts and Sciences found that empathy can be trained by associating someone's happiness with personal reward. This effect was subtle but meaningful and lasted even when no rewards were involved.
Researchers discovered that sign trackers, which prioritize interacting with cues over waiting for rewards, rely on dopamine in specific brain regions. The study found that inhibiting dopamine prevented rats from learning to sign track, while increasing dopamine did not speed up the process.
Researchers found that positive emotions during learning increase brain activity, which predicts better memory performance. Positive emotions, not neutral or negative ones, play a crucial role in enhancing memory strength.
Mark Ramos developed software to help therapists measure children's skill development in autism therapy, providing a more accurate estimate of mastery. The tool, called MIEBL, employs Bayesian estimates to set performance criteria based on predicted success and observed data.
Researchers discovered a novel connection between the amygdala brain region and social learning in zebra finches. Young birds preferred approaching tutors with longer but less frequent songs, suggesting the amygdala plays a role in socially selective behavior. This finding sheds new light on the neural mechanisms underlying song learning.
Researchers at the University of Tokyo developed a framework to enable decentralized artificial intelligence-based building automation, allowing devices to cooperate directly without central servers. The system learns user preferences over time, adjusting automatically, and provides fine-grained control without programming.
A team of researchers used machine learning to analyze changes in astrocyte cells' structure, shedding light on heroin addiction and relapse. The study, published in Science Advances, found that specific subpopulations of astroglia exhibit more pronounced morphological changes during drug use.
A study published in Communications Psychology reveals how the brain forms a sense of agency when learning new motor skills. Researchers used a data glove to control a cursor on screen, finding that motor exploration plays a crucial role in developing self-agency.
A new study offers fresh perspective on how education systems can adapt to the challenges and opportunities of artificial intelligence. The study proposes a spatiotemporal framework for transforming education, including innovative strategies such as self-directed learning, student-centered pedagogy, and personalized assessments.
A new study published in Scientific Reports reveals that audio quality severely affects dogs' ability to recognize and respond to recorded words. Dogs excelled at responding to direct human speech, but struggled with AIC buttons, which lost frequencies necessary for conveying human speech.
A study by Emory University researchers has found that spiritual health practitioners' personal experiences with psychedelics drive their careers in the emerging field of psychedelic-assisted therapy. The study introduced a novel training approach, emphasizing self-literacy and reflective learning to balance personal experience with cl...
A new curriculum framework helps train future family physicians to integrate AI into their practice, addressing a critical gap in medical training. The AIFM-ed framework provides a structured road map for medical educators to bridge the AI gap, ensuring that future doctors are clinically competent and technologically fluent.
Researchers introduced an innovative ML model for classifying faults in SRF cavities, utilizing historical data and expert insights to enhance operational stability. The system achieved high accuracy and efficiency, facilitating long-term trend analysis and proactive maintenance strategies.
Research reveals two parallel processes during post-learning sleep: reactivation of initial learning experience and emergence of new neurons encoding future memories. This study highlights the critical role of sleep in maintaining cognitive function and overall well-being.
The CoVaRR-Net network successfully bridged critical research and public health gaps exposed by the COVID-19 pandemic through interdisciplinary collaboration and innovative approaches like wastewater surveillance. Its achievements include 139 peer-reviewed publications, evidence-based public health decisions, and a global leader in ear...
Schmid's contributions have helped computers recognize complex objects, understand video analysis, and process realistic settings. Her leadership has built active research communities, mentoring and supervising peers across the field of computer vision.
Machine learning (ML) techniques can identify materials with high synthesis feasibility and suggest suitable experimental conditions. Computational models derived from thermodynamics and kinetics enhance predictive performance and interpretability of ML models, optimizing experimental design and increasing synthesis efficiency.
A team of researchers developed Lp-Convolution, a novel method that uses multivariate p-generalized normal distribution to reshape CNN filters dynamically. This breakthrough improves the accuracy and efficiency of image recognition systems while reducing computational burden.
Researchers developed an IEAC framework combining robust security with high-capacity transmission performance, achieving a record 1 Tb/s secure transmission over 1,200 km of optical fibre. The system eliminates the trade-off between security and speed by integrating encryption into the communication process.
A new study from the University of Kansas explores the role of working memory in word problem-solving for students with and without math difficulties. Researchers found that using interventions to improve working memory can benefit students who struggle with math, reducing cognitive load and improving word problem-solving ability.
Researchers at the University of California San Diego have made a groundbreaking discovery about how our brains learn new information. Using sophisticated imaging techniques, they found that individual neurons follow multiple rules during learning, rather than one set of uniform rules as previously thought. This new understanding has s...
The ELion Intelligent Chinese Composition Tutoring System uses LLMs to evaluate student essays across four dimensions, providing detailed assessments and personalized feedback. The system has been instrumental in addressing teachers' excessive grading workloads and has facilitated the analysis of nearly 50,000 compositions.
The human brain can learn to suppress early visual processing of distracting stimuli, such as roadside billboards, after repeated exposure. This learned suppression enhances attention to relevant stimuli and improves performance in tasks that involve frequent distractions.
A study published in JNeurosci found that brain activity associated with social coordination during dance is linked to specific movement patterns, particularly bouncing or flexing of the knees. This discovery sheds light on how the brain supports socially engaging activities while integrating dynamic sensory information.
Researchers from East China Normal University developed an AI-driven system to analyze classroom videos, revealing teacher-centered instruction prevails in primary and secondary schools. The study also found that older students engage less in critical discussions and more in structured questions.
Petra Anders receives the Communicator Award for her commitment to communication that opens dialogue with diverse groups and promotes reading and language skills. Her multimodal approach incorporates images, films, and poetry slams to give students a voice, sparking discussions on education issues.
MIT researchers have found that a computational model of the ventral stream, which processes object recognition, also performs well on spatial tasks such as determining an object's location and orientation. This challenges the dominant perspective that the ventral stream is optimized for object recognition.
A new hardware platform for AI accelerators capable of handling significant workloads with reduced energy requirement has been developed. The platform leverages III-V compound semiconductors to create photonic integrated circuits, which operate at the speed of light with minimal energy loss.
Thoracic surgeons can rely on DeepSeek's accurate diagnoses, precise surgical planning, and early warning systems to enhance patient care. However, challenges persist, such as limited dataset availability and high economic burdens, which must be addressed for seamless integration of AI in thoracic surgery.
Eight hospitals, including Oklahoma Children’s Hospital, receive funding to refine discharge processes for mothers and babies with neonatal abstinence syndrome. The program aims to provide continuity of care through prenatally-based education and post-discharge support.
A new study published in Annals of Internal Medicine found that AI diagnostic and treatment recommendations were more accurate than those made by physicians in a virtual urgent care setting. In 77% of cases, AI recommendations were rated as optimal, compared to 67% for physicians' decisions.
A new study published in Brain Medicine found that administering Osanetant shortly after a traumatic event significantly dampens fear expression in female mice. This suggests that targeting fear memory at its roots may be an effective intervention to reduce PTSD-like behaviors.
Virginia Tech aims to establish a hydrogen innovation hub using natural gas conversion technology, producing cleaner and more economically viable products. The project's goal is to reduce methane and carbon dioxide emissions by transforming potent greenhouse gases into less harmful high-value products.
A new web platform, AutoSolvateWeb, developed at Emory University enables chemists of all levels to configure and execute complex quantum mechanical simulations through chatting. The free platform uses cloud infrastructure and automates software processes on the backend.
New research identifies specific populations of neurons in the amygdala that play a key role in regulating nutritional needs and turning them into action. The study reveals distinct groups of neurons responding to thirst and hunger, guided by molecular cues.
Researchers developed a machine learning-powered fluid simulation model that significantly reduces computation time without compromising accuracy. The new surrogate model maintains the same level of accuracy as traditional particle-based simulations while reducing computation time from approximately 45 minutes to just three minutes.
A study explores how large language models (LLMs) can transform teaching by generating customized educational materials, assessing student progress, and providing targeted feedback. LLMs excel at automating routine tasks, reducing teachers' workload and enabling them to focus on mentoring students.
Rachid Guerraoui has made groundbreaking contributions to distributed computing, shaping the landscape of concurrent environments. He also promotes computer science education in Africa, fostering academic excellence through initiatives like the Excellence in Africa program.
Researchers found that local release of dopamine triggers plasticity mechanisms, enabling motor learning by storing new skills for future use. Blocking dopamine results in complete learning cessation.
Researchers have developed a new way to map how individual connections between neurons change across the entire brain during learning. The method, DELTA, provides a brain-wide map of how individual synaptic proteins change over time, allowing scientists to understand how synaptic connections change and pinpoint areas of the brain impor...
A research team has uncovered a fundamental brain circuit that distinguishes between direct and vicarious fear, with the locus coeruleus playing a crucial role in processing fear. The study reveals a lateralized LC-NAergic system that separates personal from socially learned fear, shedding light on empathy and social learning.
Three UVA Engineering faculty members, Scott T. Acton, Gustavo Kunde Rohde and Shannon Barker, have been named to the 2025 class of the American Institute for Medical and Biological Engineering (AIMBE) College of Fellows. They are recognized for their contributions to biomedical engineering research, innovation, teaching and leadership.
Göttingen research team develops infomorphic neurons that learn independently and self-organize among neighboring neurons. This allows the smallest unit in the network to control its own learning, enabling novel machine learning approaches and a deeper understanding of brain function.
A new study from Duke University reveals that dopamine levels in the brains of baby birds increase with every effort they make while practicing their songs, regardless of success. This discovery has implications for understanding human learning and neurological disorders.
The grant aims to develop an electrochemical system capable of recovering uranium from wastewater, improving ecosystem health and addressing uranium security. The project will focus on designing electrode materials for efficient uranium extraction and minimizing toxic waste.
Researchers at ISTA discovered that neural activity patterns during sleep reflect recently learned spatial memories and transform into those seen later upon awakening. This 'representational drift' phenomenon optimizes memory representations for long-term storage, allowing the brain to free up resources for new memories.