Articles tagged with Observational Learning
Researchers found that male mice become aggressive after witnessing familiar peers attack intruders, not strangers. The study suggests that familiarity with attackers may be a risk factor for violent behavior in males.
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.
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.
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.
Researchers at Concordia University have developed a new approach to identifying fake news on social media using the SmoothDetector model. The model integrates probabilistic algorithms with deep neural networks to capture uncertainties and patterns in multimodal data, providing more nuanced judgments of authenticity.
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.
Researchers have identified distinct protein degradation patterns in key brain regions for individuals who witnessed trauma, differing from those who experienced it firsthand. Sex-specific differences also emerge, with implications for targeted treatments and a better understanding of PTSD development.
A research team at Kumamoto University developed a deep learning-based method for analyzing the cytoskeleton more accurately and efficiently than ever before. This technique enabled more reliable measurements of cytoskeleton density, which is critical for understanding cellular structure and function.
A new self-assessment questionnaire has been developed to evaluate the progress of novice nurses during on-the-job training. The Modeling Scale for Novice Nurses assesses four subscales and 21 Likert scale questions to understand the nurses' behavior and growth, enabling senior nurses to provide targeted support.
Researchers developed a portable system using AI to spot cognitive impairment by measuring subtle differences in motor function. The device accurately identified 83% of participants with mild cognitive impairment (MCI), offering potential for early intervention and improved outcomes.
A study led by Dr. Rodrigo Quian Quiroga has confirmed that individual neurons represent concepts learned in any context, enabling abstract relationships and human intelligence. This finding contradicts previous research on animals, where memories were thought to be stored in different groups of neurons.
The article presents guidelines for designing consent materials and procedures for autistic adults and people with intellectual disability, highlighting the importance of multiple modes to deliver content. These guidelines aim to improve accessibility and respectfulness in research with individuals on the autism spectrum.
Researchers argue that a new definition is needed to accurately describe dyslexia and provide specific support. The new definition retains the idea of difficulties with reading and spelling relative to age, ability, or educational expectations.
Researchers found that capuchin monkeys in Brazil's Serra da Capivara National Park learn from each other's actions and that social tolerance is crucial for this process. The study showed that partners in collective activities, such as searching for parasites and playing games, are more likely to learn new skills from their companions.
Parrots display automatic imitation of intransitive (goal-less) actions, a phenomenon previously documented only in humans. The study also suggests the presence of a mirror-neuron system in parrots, akin to that found in humans.
Researchers use real-time neuroimaging and neurofeedback to modify brain activity patterns, enabling faster learning and treatment of psychiatric disorders. The study demonstrates the ability to inscribe new patterns into the brain without physical manipulation.
A new study at Durham University found that social tolerance enables social learning in wild bearded capuchin monkeys, leading to the transmission of skills and traditions. The research showed that individuals with strong social tolerance were more likely to learn from others and share information about solving complex tasks.
A WVU research partnership with the DEA aims to improve fast and accurate identification of psychoactive substances like fentanyl. The Expert Algorithm for Substance Identification (EASI) will enable labs using different instruments to share data on chemical profiles, helping to identify drugs like fentanyl.
The new system uses AI technology combined with Earth observation data to detect risks of events that might trigger forced displacement, delivering timely alerts ahead of emergencies. It will help humanitarian actors plan and respond more effectively, minimizing response times and avoiding duplication of efforts.
A study found that stereotactic radiosurgery (SRS) achieved high rates of tumor control for patients with Koos grade I vestibular schwannomas. The procedure also reduced the risk of cranial dysfunction, tinnitus, and vestibular dysfunction compared to observation alone.
Devin Harris and his team have developed an augmented reality app, STRUCT-AR, that allows students to 'stress test' virtual bridges, beams, frames, and trusses. The app, which is set to be tested this spring, aims to improve students' understanding of structural behavior by providing a more interactive and immersive learning experience.
A global research team, led by Indiana University's Linda Smith, will investigate how shape perception influences language acquisition in children with typical and atypical developmental trajectories. The project aims to develop a cross-disciplinary theory of the dynamic interaction between language and cognitive systems.
A new reinforcement learning framework, AVATARS, uses diverse sensor streams to track whales and predict their surface locations. The framework aims to minimize missed encounters and improve data collection for Project CETI.
A study found that people's choices between safe and risky options are influenced by their perception of an observer's opinion. After initial biases, participants learned to correctly predict their partners' choices and adjusted their behavior accordingly.
A recent study published in Cell reveals that nearly one in six disease-causing mutations leads to proteins mislocalizing within the cell. The research team developed a high-throughput imaging platform to assess protein location and found that breakdowns in protein stability are a major driver of misplaced proteins.
New research from Binghamton University reveals that Mexican jumping bean larvae respond differently to various lighting conditions, with red light stimulating the most vigorous jumps. However, damage to their 'bean' hosts hinders their ability to jump away from stressors.
Researchers at Tampere University have observed hidden deformations in complex light fields for the first time. These deformations carry significant information about the object, such as its material properties. The study has implications for measuring material properties with structured waves and will inspire new optical technologies.
Pretend play is associated with enhanced cognitive abilities like executive function, language, and perspective-taking. Research suggests that play-based preschool curricula offer more significant long-term advantages in academic performance and students' attitudes towards school.
Researchers at UNIL find that observing others cope with trauma increases resilience and prevents pathological states. Serotonin release in the habenula brain structure is identified as the key mechanism, offering new perspectives for understanding depression and treatment.
Researchers led by Daniela Vallentin successfully rewired zebra finches' brains using optogenetics, expanding their vocal repertoire. The findings have implications for human aging and potential therapies for neurodegenerative diseases and learning impairments.
A study published in Neuron reveals that neurons are wired to connect seemingly unrelated concepts, enhancing the brain's ability to predict what we see based on past experiences. Visual experience influences the organisation of feedback projections, which store information about the world.
The study reveals that eye-tracking technology can help identify difficulties in mathematical problem-solving, allowing teachers to suggest effective teaching methods. By analyzing data on student gaze patterns and attention shifts, educators can personalize the learning process and improve academic achievements.
A study found that 'floating duck syndrome', where individuals present themselves as effortlessly high-achieving, leads to underinvestment of effort towards goals and spreading oneself too thinly. This phenomenon is exacerbated by social media platforms and institutional public relations, causing individuals to invest too much total ef...
Researchers developed a deep learning-based model to estimate rainfall intensity from surveillance audio, achieving a root mean absolute error of 0.88 mm h-1 and a coefficient of correlation of 0.765. This approach offers a new method for high-resolution hydrological sensing, contributing to environmental resilience and urban sensing.
A study published in PNAS found that infants less than a year old can combine novel words describing quantities with familiar words to understand phrases. This ability helps them interpret language input and learn about the world, laying the foundation for human creativity.
Researchers at Universiteit van Amsterdam found that observing prejudiced individuals interact with group members can lead to the formation of similar prejudices. Observers often go on to act with prejudice without realizing they've been influenced, misperceiving worse behavior from group members who interacted with a prejudiced actor.
Researchers used AI to analyze over 16,000 butterfly images, finding both males and females contribute to diversity among species. The study resolves a century-old debate between Charles Darwin and Alfred Russel Wallace on the role of natural selection in female evolution.
A study by Pusan National University researchers found that repeated item development training enhances faculty members' accuracy in predicting and adjusting item difficulty levels, leading to better educational outcomes. The training improved the quality of MCQ assessments in medical education.
Researchers have found that cognitive maps stored in the hippocampus and entorhinal cortex are activated when navigating through space physically or mentally. The study used animal models to demonstrate that these mental maps can be created and used during purely mental run-throughs, even without physical movement.
Researchers confirmed that elephant calls contained a name-like component identifying the intended recipient through machine learning analysis. Elephants responded affirmatively to calls addressed to them and less so to those meant for others, suggesting an ability to learn and use arbitrary vocal labels like humans.
A novel approach to training AI systems uses information about spatial position to identify objects and navigate surroundings, inspired by children's visual development. The method improves contrastive learning models' effectiveness by incorporating simulated spatial context information, outperforming base models in various tasks.
Research suggests that preverbal infants who struggle with sequence understanding are more likely to experience social communication difficulties later in childhood. Visual statistical learning is identified as a key predictor of autistic-related traits and behaviors.
A new approach uses neural networks to automatically determine polynomial coefficients for digital pre-distortion (DPD) in RF-PAs, reducing hardware complexity and power efficiency. This method can correct non-linearities and support emerging standards without extensive real-time processing.
Astronomers have discovered an enormous circular radio feature around a galaxy, dubbed the Cloverleaf, which was created by clashing groups of galaxies. The XMM-Newton satellite has detected X-ray emission associated with this structure for the first time, revealing clues about its formation and the merger process.
Researchers have developed a new open-source algorithm called Conditional Variational Diffusion Model (CVDM) that improves the quality of images by reconstructing them from randomness. The CVDM is computationally less expensive than established diffusion models and can be easily adapted for various applications.
A new AI model, called Lars, can accurately detect signs of lymph node cancer in 90% of cases, reducing workload for radiologists and increasing access to healthcare. The model was developed using a large dataset of over 17,000 images from 5,000 patients and is based on deep learning technology.
Researchers found that bumblebees can learn multi-step tasks through social interaction, even when struggling individually. The study revealed that bees could acquire complex behaviors beyond their individual cognitive capabilities, challenging the traditional view of human exclusivity in social learning.
A study published in Nature tracked neural activity of freely moving macaques using wireless eye tracking and neural monitoring. The research found that the visual cortex plays an active role in social behavior by providing signals to the prefrontal cortex, enabling the decision to cooperate.
A new study confirms that the predominant outcome of non-fatal pediatric drowning is locked-in syndrome. Researchers found that 60% of children who survived drowning events were classified as locked in, with cognitive and sensory networks preserved in their brains.
Researchers extend spatially incoherent diffractive networks to perform complex-valued linear transformations with negligible error, opening up new applications in fields like autonomous vehicles. This breakthrough enables the encryption and decryption of complex-valued images using spatially incoherent diffractive networks.
A study by Norwegian University of Science and Technology found that using podcasts and compulsory attendance in small seminar groups increased student engagement and confidence. The changes led to a 36% increase in successful exam completion compared to the previous year.
Researchers at Tokyo Metropolitan University found that visual-motor illusion (VMI) can improve motor performance and early-stage motor learning. Volunteers who used VMI showed greater improvements in task completion and persisted changes in brain activity, suggesting a potential new treatment strategy for hemiplegic stroke patients.
Researchers used machine learning and mobile mapping systems to analyze the town of Sabbioneta's streets and pavements, identifying accessible trajectories and paths for citizens with motor disabilities. The study demonstrated the effectiveness of AI in assessing physical accessibility in historic urban contexts.
A new deep learning-based detection system has been developed by INU researchers to improve the detection capabilities of autonomous vehicles. The system, aided by IoT technology, generates bounding boxes and confidence scores for visible obstacles using point cloud data and RGB images as input.
A study at Uppsala University found that infant face preference is influenced by genes and linked to later language development. The researchers analyzed over 500 infant twins and found that individual infants' preferences for faces could be largely explained by their genetics.
Scientists have developed an AI system that accurately maps the surface area and outline of giant icebergs in one-hundredth of a second. This technology surpasses manual interpretation methods, which can take several minutes to delineate an iceberg's outline, and offers insights into their impact on the polar environment.
Researchers found self-supervised models generate activity patterns similar to mammalian brains, suggesting an organizing principle. The models learn representations of the physical world to make accurate predictions, potentially unlocking human-labeled data limitations.
A study shows pigeons tackle complex problems using associative learning and error correction, similar to AI models. Researchers used an AI model to replicate the pigeons' behavior, finding strong evidence for the similarities between pigeon and AI learning mechanisms.
Researchers at Gwangju Institute of Science and Technology (GIST) have developed a deep learning-based biosensing platform called DeepGT, which can accurately quantify nanoscale bioparticles, including viruses. The platform harnesses the advantages of Gires-Tournois biosensors and AI to refine visual artifacts and extract relevant info...
Researchers discovered protein p53's role in regulating sociability, repetitive behavior, and hippocampus-related learning and memory in mice. Lowering p53 levels led to changes in gene expressions related to behavior, while elevated p53 levels were linked to positive learning outcomes.