Articles tagged with Neural Modeling
Comprehensive exploration of living organisms, biological systems, and life processes across all scales from molecules to ecosystems. Encompasses cutting-edge research in biology, genetics, molecular biology, ecology, biochemistry, microbiology, botany, zoology, evolutionary biology, genomics, and biotechnology. Investigates cellular mechanisms, organism development, genetic inheritance, biodiversity conservation, metabolic processes, protein synthesis, DNA sequencing, CRISPR gene editing, stem cell research, and the fundamental principles governing all forms of life on Earth.
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Comprehensive investigation of human society, behavior, relationships, and social structures through systematic research and analysis. Encompasses psychology, sociology, anthropology, economics, political science, linguistics, education, demography, communications, and social research methodologies. Examines human cognition, social interactions, cultural phenomena, economic systems, political institutions, language and communication, educational processes, population dynamics, and the complex social, cultural, economic, and political forces shaping human societies, communities, and civilizations throughout history and across the contemporary world.
Fundamental study of the non-living natural world, matter, energy, and physical phenomena governing the universe. Encompasses physics, chemistry, earth sciences, atmospheric sciences, oceanography, materials science, and the investigation of physical laws, chemical reactions, geological processes, climate systems, and planetary dynamics. Explores everything from subatomic particles and quantum mechanics to planetary systems and cosmic phenomena, including energy transformations, molecular interactions, elemental properties, weather patterns, tectonic activity, and the fundamental forces and principles underlying the physical nature of reality.
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Study of the practice, culture, infrastructure, and social dimensions of science itself. Addresses how science is conducted, organized, communicated, and integrated into society. Encompasses research funding mechanisms, scientific publishing systems, peer review processes, academic ethics, science policy, research institutions, scientific collaboration networks, science education, career development, research programs, scientific methods, science communication, and the sociology of scientific discovery. Examines the human, institutional, and cultural aspects of scientific enterprise, knowledge production, and the translation of research into societal benefit.
Comprehensive study of the universe beyond Earth, encompassing celestial objects, cosmic phenomena, and space exploration. Includes astronomy, astrophysics, planetary science, cosmology, space physics, astrobiology, and space technology. Investigates stars, galaxies, planets, moons, asteroids, comets, black holes, nebulae, exoplanets, dark matter, dark energy, cosmic microwave background, stellar evolution, planetary formation, space weather, solar system dynamics, the search for extraterrestrial life, and humanity's efforts to explore, understand, and unlock the mysteries of the cosmos through observation, theory, and space missions.
Comprehensive examination of tools, techniques, methodologies, and approaches used across scientific disciplines to conduct research, collect data, and analyze results. Encompasses experimental procedures, analytical methods, measurement techniques, instrumentation, imaging technologies, spectroscopic methods, laboratory protocols, observational studies, statistical analysis, computational methods, data visualization, quality control, and methodological innovations. Addresses the practical techniques and theoretical frameworks enabling scientists to investigate phenomena, test hypotheses, gather evidence, ensure reproducibility, and generate reliable knowledge through systematic, rigorous investigation across all areas of scientific inquiry.
Study of abstract structures, patterns, quantities, relationships, and logical reasoning through pure and applied mathematical disciplines. Encompasses algebra, calculus, geometry, topology, number theory, analysis, discrete mathematics, mathematical logic, set theory, probability, statistics, and computational mathematics. Investigates mathematical structures, theorems, proofs, algorithms, functions, equations, and the rigorous logical frameworks underlying quantitative reasoning. Provides the foundational language and tools for all scientific fields, enabling precise description of natural phenomena, modeling of complex systems, and the development of technologies across physics, engineering, computer science, economics, and all quantitative sciences.
A tiny worm called C. elegans is enabling scientists to explore the emerging theory that Parkinson’s disease starts in the gut, where a sticky protein causes neurons to die. The worms have a digestive tract and neurotransmitters similar to humans, making them a great model for studying cognitive problems associated with Parkinson's.
Researchers are developing a deep learning model to predict where waste is accumulating in cities and how often public bins should be cleared. This can help councils optimise their waste management services, schedule bin clearances and relocate rarely used bins.
A new study by NYU researchers found that infants excel at spotting motivations driving human actions, while state-of-the-art AI models struggle. By comparing infant and machine intelligence on a series of tasks, the researchers shed light on the limitations of current AI systems.
Researchers at Gladstone Institutes found that ApoE4 from neurons plays a critical role in Alzheimer's disease, contrary to previous focus on glial cells. The study shows that deleting ApoE4 from neurons reduces brain changes resembling Alzheimer's disease, offering new possibilities for treatment.
Researchers developed a testing model to understand cognitive challenges of superior semicircular canal dehiscence (SSCD), a rare condition causing sound-induced dizziness and hearing abnormalities. The Mongolian gerbil model shows promise for accelerating recovery with reversible diagnostic findings characteristic of patients with SSCD.
Researchers at the University of Virginia Health System have identified a vital contributor to hyperactive immune responses and neuroinflammation in multiple sclerosis. Blocking this regulator alleviated harmful inflammation in lab mice, suggesting a potential therapeutic target for new treatments.
The new Cell Atlas updates reveal that 20% of all neurons in the mouse brain are inhibitory, with detailed information on morphological and electrophysiological properties. The atlas combines various datasets to create a coherent framework for simulating neural circuits.
A new technique maps the effects of fire-induced permafrost thaw in Alaska, revealing widespread topographic change and vegetation shifts. The study used a machine learning-based approach to quantify thaw settlement across 3 million acres of land, with results showing a significant loss of evergreen forest and shrubland encroachment.
Researchers employed computer vision to extract social behaviors and linked them to brain synchronization patterns in a novel approach. During cooperative play, brain synchronization was strongest when participants shared gaze, while individual play showed increased within-brain synchronization.
Researchers at MIT developed a technique to improve machine-learning models' reliability without requiring additional data or extensive computing resources. The method uses a simpler companion model to estimate uncertainty, enabling more effective uncertainty quantification.
A team of researchers developed a model-free approach using deep reinforcement learning to optimize estimation of multiple parameters in quantum sensors. The protocol achieved significantly better estimations compared to nonadaptive strategies, demonstrating enhanced performance in resource-limited regimes.
A UCF cancer researcher is studying the molecular causes of Alzheimer's disease by examining a protein deficiency in the brain. His research may lead to new targets for therapy and earlier diagnosis. The study focuses on KLF8, a protein important for brain function that has been recorded as deficient in patients with Alzheimer's.
Researchers developed a neural network model that uses terahertz time-domain spectroscopy data to predict burn healing outcomes with high accuracy. The new approach improves upon existing methods by reducing training data requirements, making it more practical for processing large clinical trials.
Researchers at the University of Essex have developed a new technique that uses non-invasive brain wave monitoring to accurately identify the music someone is listening to. The method has been successfully tested on a dataset of simple piano music and shows promise for decoding language signals from the brain in the future.
Researchers have developed a machine learning model that can predict the word about to be uttered by a subject based on their neural activity. The model achieved 55% accuracy using six channels of data and 70% accuracy using eight channels, comparable to other studies requiring electrodes over the entire cortical surface.
Researchers have discovered a unique, fast synapse in the inner ear that processes signals faster than any other in the human body. This breakthrough could lead to improved treatments for vertigo and balance disorders affecting millions of Americans over 40.
Researchers at Kyoto University found that a poor, low-yeast diet causes fruit flies' larvae to grow dendrites in an unexpected way. The hyperarborization phenotype is triggered by a simultaneous deficiency in vitamins, metal ions, and cholesterol, which increases the production of Wingless signaling molecules from body wall muscle.
A new study finds that autonomous vehicles could consume enough energy to generate significant greenhouse gas emissions, highlighting the need for rapid advancements in hardware efficiency. To mitigate this, researchers recommend more efficient autonomous vehicles with smaller carbon footprints.
Researchers found that dendritic cells in meninges produce mediators causing pain hypersensitivity after nerve injury. The kynurenine pathway, primarily driven by IDO1, is involved in pain production.
Scientists at Georgia Institute of Technology investigate how cats maintain balance while studying human spinal cord injury treatment.
A new AI model developed at USC accurately captures cognitive decline linked to neurodegenerative diseases like Alzheimer's much earlier than previous methods. The model analyzes MRI brain scans and detects subtle brain anatomy markers that correlate with cognitive decline, offering an unprecedented glimpse into human cognition.
The article discusses the use of Rapamycin in the context of Pascal's Wager, a philosophical framework used to justify beliefs. ChatGPT's generative pre-trained transformer model provides an exhaustive research perspective on the pros and cons of taking Rapamycin for anti-aging purposes.
A UCI-led study reveals that outbred Chilean degu rodents exhibit robust neurodegenerative features, including hippocampal neuronal loss and altered parvalbumin staining, resembling human Alzheimer's Disease. This provides a practical model for studying sporadic AD.
A review of over 100 scientific articles suggests that the safety of antidepressants during pregnancy is endorsed by science, but their effects on fetal neurodevelopment are poorly understood. Brazilian researchers propose using lab-grown mini-brains to investigate this impact and identify potential alterations.
A new report by The Hastings Center recommends clearer ethics guidelines and enhanced oversight for human-animal chimera research, which raises questions about animal welfare and moral status. The report also highlights the potential benefits of this research, including better disease models and organ transplantation.
Researchers at MIT and Harvard University have developed a new optogenetics-based tool to manipulate neuron excitability using light. By altering the electrical capacitance of cell membranes, they can change how strongly neurons respond to electrical input, with potential applications in learning, aging, and brain disorders.
Researchers discovered that krill oil protects dopaminergic neurons from age-related degeneration through temporal transcriptome rewiring and suppression of several hallmarks of aging. Krill oil increases neuronal resilience, promoting anti-oxidative stress and anti-inflammation, and abrogating multiple aging hallmarks.
Researchers create a new type of organic material that learns from its past behavior and emulates synaptic behaviour, enabling 'brain-like computing' networks. This breakthrough opens up opportunities in sustainable and green chemistry, energy, environment, and health.
A Rutgers-led study found that a gene mutation associated with autism causes an overstimulation of brain cells, disrupting the normal information flow. The researchers used human stem cells and transplanting them into mouse brains to understand how the mutation affects brain development.
A novel multi-modal image retrieval system, DenseBert4Ret, has been developed by researchers from Gwangju Institute of Science and Technology (GIST) using deep learning algorithms. The system outperforms state-of-the-art models in retrieving images based on both image and text features.
Researchers propose a new network approach to understand brain function, suggesting that connections between brain regions are key to cognitive tasks. This new view also sheds light on individual variability and can be applied to predict symptoms in patients with brain lesions.
Researchers trained a mouse brain model to solve visual tasks, achieving superior robustness and performance compared to traditional neural networks. The model's unique coding properties enable it to cope with errors and unexpected input, making it a promising tool for advances in neuromorphic computing.
Researchers at MIT have developed a machine-learning model that captures how sounds propagate through spaces, allowing for accurate visual renderings of rooms. This technique has potential applications in virtual and augmented reality, as well as improving AI agents' understanding of their environment.
A new computational model based on fruit fly brain data may help explain how humans process memories and experiences. The model suggests that living organisms, including humans, use a similar '1-2-3-many' count sketch to track encounters with familiar sights and smells.
Researchers at MIT have developed a new method that uses optics to accelerate machine-learning computations on low-power devices. By encoding model components onto light waves, data can be transmitted rapidly and computations performed quickly, leading to over a hundredfold improvement in energy efficiency.
Conscious perception of sound generates specific neuronal assemblies in the brain, differing from spontaneous brain activity. Under anesthesia, similar assemblies are present but lack sound-specificity, highlighting the importance of cortical creativity in sensory processing.
Researchers at the University of Oxford discovered that goldfish can accurately estimate distances by processing visual cues. The study found that goldfish use 'optic flow' to estimate distance, unlike terrestrial animals which rely on changes in angle between their eye and surrounding objects.
A team of Illinois Tech researchers used machine learning to estimate the age and gender of individual users with high accuracy, raising questions about data security and privacy. The study highlights the need for better regulations and best practices to protect personal information from being misused.
Researchers developed a new technique that enables on-device training using less than a quarter of a megabyte of memory, reducing the need for powerful computers and central servers. This approach preserves privacy by keeping data on the device, making deep learning more accessible for low-power edge devices.
Researchers from Xi'an Jiaotong-Liverpool University found that brain stimulation combined with a nose spray containing nanoparticles can improve recovery after ischemic stroke. The treatment increased cognitive and motor functions, and weighed more quickly than those treated with TMS alone.
A new research model allows scientists to study hereditary spastic paraplegias (HSPs) and test potential therapeutics. HSPs cause increased muscle tone in infants and young children, leading to wheelchair-bound individuals who lose motor function.
A new study proposes reducing toxic proteins in the blood as a potential therapy for Alzheimer's disease. By doing so, it aims to improve memory and learning capacity, as well as correct cognitive impairments. The next step is to test this treatment at a clinical level.
A new neurocomputational model introduces a three-level information processing framework to understand brain development and cognition. The model focuses on Hebbian learning and reinforcement learning, highlighting two fundamental mechanisms for multilevel cognitive ability development in biological neural networks.
Researchers at Emory University used machine learning and fMRI to analyze a dog's brain activity while watching videos. The results show that dogs are more attuned to actions in their environment than to who or what is performing the action. This study offers proof of concept for decoding canine visual perception.
A team of researchers from Japan successfully reconstructed common brain input signals from the firing rates of neurons using a method called superposed recurrence plot. This breakthrough has significant implications for artificial intelligence, neuroscience, and potential treatments for mental health disorders.
Researchers from Singapore University of Technology and Design (SUTD) have developed a new Brain-Inspired Replay model that enables continual learning in edge computing systems without storing data. This approach achieves state-of-the-art accuracy and high energy efficiency, overcoming the stability-plasticity issue in traditional models.
A study from MIT neuroscientists has identified a population of neurons in the visual cortex that respond to images of food. The researchers found four previously known populations and a fifth, more surprising population that appears to be selective for food images. This finding may reflect the special importance of food in human culture.
Researchers at Cedars-Sinai created complex computer models of individual brain cells using artificial intelligence. These models capture the electrical signals that neurons fire to communicate with each other, allowing researchers to replicate brain activity at the single-cell level.
Researchers found that the brain's cortex uses principles of calculus to implement a 'stop' signal, allowing for quick and precise decision-making in goal-directed behaviors. The study reveals how the brain integrates learned rules with sensory information to guide actions.
Researchers developed a novel convolutional neural network for facial expression recognition, outperforming conventional models while being computationally less expensive. The new model achieved an accuracy of 72.4% using only 58,000 parameters.
A new neurobiological model provides a unified framework for understanding various forms of creativity, including abstract thinking, improvisation, and divergent problem-solving. The model suggests that different brain areas are activated depending on the type of creativity, with dopamine playing a crucial role in controlling and optim...
A team from Nagoya University created an artificial neural network model that performed the delayed matching-to-sample task and analyzed its behavior. The model was able to evolve to exhibit human-like metamemory, adapting to its environment by learning and evolving. This breakthrough aims to create machines with memories like humans.
Researchers at Sainsbury Wellcome Centre found that mice can choose the best escape route after only 10 minutes of exploration, without needing to experience threat. The study suggests that mice use innate heuristics and natural exploration to learn this information.
Researchers have successfully processed sequences with a large neural network while consuming significantly less energy on neuromorphic hardware. This breakthrough showcases the potential of neuromorphic technology to improve the energy efficiency of AI workloads.
Researchers at EPFL's School of Life Sciences create a digital twin of Drosophila called NeuroMechFly, which uses biomechanical modeling and machine learning to simulate the fly's movements. The model is validated through experiments that demonstrate its accuracy in replicating real animal behaviors.
Researchers developed a deep learning-based model to predict drug-drug interactions using gene expression data. The DeSIDE-DDI model can identify potentially dangerous pairs and act as a drug safety monitoring system, helping establish the correct usage of drugs in the development phase.
Researchers developed a machine-learning method that allows robots to pick up and place never-before-seen objects in random poses, requiring only 10 human demonstrations. The system uses a neural network specifically designed to reconstruct 3D shapes, enabling the robot to generalize to new object orientations.
Researchers at Salk Institute discover that brain parses information through interactions of waves of neural activity, changing how data is processed and affecting attention and focus.
The VIGICOVID system uses deep neural architectures to answer natural language questions about COVID-19 and SARS-CoV-2. Researchers have developed a prototype that provides good results and can be easily scaled up for marketability.
Researchers at Kaunas University of Technology improved an algorithm to detect Alzheimer's disease from MRI images, achieving over 98% accuracy. The new model uses a modified neural network and adapts to variations in data, such as differences in hospital equipment and patient positions.