Articles tagged with Neural Networks
Scientists at Virginia Tech have discovered that controlling the precise timing of electrical pulses can rebalance synaptic connections between nerve cells, selectively up- or down-regulating those connections. This finding suggests potential avenues for more effective treatment strategies for mild traumatic brain injuries.
Researchers developed a reliable iris recognition method by applying statistical limits to the spatial domain zero crossing technique, reducing errors to 0.022%. The algorithm uses a neural network to recognize unique features of each person's iris, achieving over 99.78% accuracy.
Researchers discovered that command-like DNs in fruit flies recruit additional networks of neurons to orchestrate complex behaviors. The study shows that these networks work together to produce coordinated actions, transforming the way we understand brain signals and behavior.
A new study found that internet addiction in adolescents can lead to changes in the brain's neural networks, resulting in addictive behaviors and tendencies. The study, published in PLOS Mental Health, reviewed 12 articles involving 237 young people aged 10-19 with a formal diagnosis of internet addiction.
A team of researchers discovered a group of neurons in the brain associated with compulsive eating and food craving. The discovery found that activation of these cells triggered vigorous foraging behavior in mice, even when they were already full.
A groundbreaking study introduces a method for sorting vector structured beams with spin-multiplexed diffractive metasurfaces, promising significant advancements in optical communication and quantum computing. This technology enables precise control over complex light beams, opening new avenues for scientific exploration.
Researchers have developed a system combining bio-inspired cameras with AI to quickly detect obstacles around cars, using less computational power. The hybrid system detects objects up to one hundred times faster than current systems while reducing data transmission and processing needs.
Researchers developed a novel light-sensitive drug that enhances extracellular adenosine activity, inducing sleep artificially without genetic modification. The drug overcomes issues with conventional photosensitive drugs, showcasing optochemistry's potential in targeting A2A receptors and regulating brain function.
Researchers have developed a method to detect microplastics in marine and freshwater environments using porous metal substrates and machine learning. The system can identify six types of microplastics with high accuracy, offering a cost-effective solution for environmental monitoring.
Researchers at University of California - San Francisco discovered a new type of neuron that guides the formation of intricate 3D lattices of blood vessels in the retina. These perivascular neurons produce PIEZO2 protein to sense nearby cells and direct the lattice's growth.
A new study found significant differences in brain development between autistic boys and girls, with autistic females showing a thicker cortex at age 3 and faster cortical thinning into middle childhood. The findings highlight the need for longitudinal studies that include both sexes to better understand sex-specific changes in autism.
A new study uses computational modeling to understand how ketamine affects individual neurons, leading to changes in brain network function. The model predicts that ketamine can disinhibit network activity by shutting down certain inhibitory interneurons.
Researchers at the University of Minnesota have found that the cortex can transform unorganized inputs into highly organized patterns of activity, demonstrating self-organization. This process occurs entirely within the cortex itself, indicating that the brain is able to organize its own function during development.
A newly discovered connection between two brain regions may help regulate how much we eat, according to a Northwestern University study. The weaker the connection between these regions, the higher a person's BMI, suggesting that individuals with weak brain circuits may overeat even when full.
A new approach uses artificial intelligence to turn low-quality images into high-quality ones, enhancing the image quality of metalens cameras. This technology could make these cameras viable for intricate microscopy applications and mobile devices.
Researchers at Delft University of Technology developed a drone that flies autonomously using neuromorphic image processing and control based on the workings of animal brains. The drone's deep neural network processes data up to 64 times faster and consumes three times less energy than when running on a GPU.
A new soft multi-electrode system for electroretinography has been developed to overcome the limitations of traditional devices. The system uses a commercially available soft disposable contact lens with gold mesh electrodes, allowing for simultaneous measurement of electrical potentials from different regions of the retina. This innov...
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.
The new approach combines central pattern generators (CPGs) with deep reinforcement learning (DRL), generating human-like movements for walking, running, and adapting to frequencies where motion data is absent. This breakthrough sets a new benchmark in robotics, offering unprecedented environmental adaptation capability.
The study suggests that memory plays a pivotal role in shaping consciousness, contrasting the idea that computer-based Information Theory provides a sufficient framework for understanding neural memory. The researchers propose a novel perspective that memory underpins consciousness, introducing the concept of a "brain cloud" to illustr...
Researchers at UCLA Health discovered a novel, energy-efficient mechanism of working memory that reduces metabolic cost even during sleep. The discovery is published in Nature Communications and may provide an early diagnostic for Alzheimer's disease and related dementia.
Macquarie University researchers debunked a 75-year-old theory about sound localization, revealing that humans use a simpler neural network. This finding could unlock next-generation hearing devices and improve smart devices' ability to understand speech in noisy environments.
A study by Washington State University found ChatGPT's generative AI system provided inconsistent heart risk assessments for patients with chest pain. The AI failed to match traditional methods used by physicians and returned different results for the same patient data, highlighting its limitations in high-stakes clinical situations.
Researchers have developed a magnetic coil array called MagPatch that can stimulate individual neurons with precision. The device uses soft magnetic materials to boost the magnetic field, reducing the need for high current levels.
Researchers at U of T have mapped the movement of proteins encoded by the yeast genome throughout its cell cycle, identifying patterns of emergence and disappearance or movement to specific areas. The study provides a unique dataset that offers a genome-scale view of molecular changes during cell division.
A new neural network-based system called BONES improves video streaming quality by up to 13% while reducing download size, according to NJIT researcher Jacob Chakareski. The system uses a mathematical function to optimize data transmission and can be applied to various platforms, including popular video conferencing services.
Researchers at the University of Basel discovered a molecular pathway that helps balance neural excitation and inhibition in the brain. This balance is crucial for preventing neurodevelopmental disorders like epilepsy, and understanding this process may lead to new treatments.
A study by Charité – Universitätsmedizin Berlin found that human neurons communicate in a feed-forward manner, unlike mice where signals flow in loops. This discovery could further the development of artificial neural networks, leading to more efficient and cost-effective AI models.
This study introduces selective sampling with the Gromov–Hausdorff metric to improve dense-shape correspondence. It proposes a novel method that filters out unsatisfactory features during training and testing, improving alignment accuracy and reducing computation time.
A research team has successfully created a new dimension in photonic machine learning by incorporating sound waves, enabling the creation of reconfigurable neuromorphic building blocks. This innovation has the potential to revolutionize computing tasks by providing high-speed and large-capacity solutions.
The Digitally programmable Over-brain Therapeutic (DOT) device, the size of a pea, activates the motor cortex, allowing patients to move their hands. The technology offers greater patient autonomy and accessibility than current neurostimulation-based therapies.
Researchers found proteasomes in neurons near the skin that convey sensory signals from the central nervous system. The protein grinds down proteins and helps differentiate between pain and itch sensation.
Researchers at The University of Tokyo successfully connected lab-grown brain-mimicking tissue using axonal bundles, mimicking natural brain connections. This breakthrough enables the study of complex brain networks and their role in various neurological and psychiatric conditions.
Researchers focused on measuring information transfer in biological neurons, simulated neurons, and electronic neuromorphic systems. The team demonstrated that it is possible to transform biological circuits into electronic circuits while maintaining the amount of information transferred.
Researchers at University of Cologne's CECAD Cluster of Excellence discovered that mitochondrial fusion boosts new neuron plasticity. The study found that as new neurons mature, their mitochondria fuse to acquire elongated shapes, sustaining synaptic plasticity and refining brain circuits.
A new study identifies multiple emotion regulation systems in the human brain, providing targets for therapy. The research reveals that regions in the anterior prefrontal cortex and higher-level cortical hierarchies are involved in emotion regulation.
Researchers discovered a class of cerebellar inputs, called climbing fibres, are essential for associative learning to occur. These
A new type of optical neural network has been developed, exhibiting a quantum speedup similar to quantum neural networks. The network uses classical optical correlations as a carrier of information, allowing for efficient processing and convergence speed.
Researchers used intracortical recordings to study the neural mechanisms behind exogenous attention, identifying three cortical networks activated in sequence as attention was captured by visual stimuli. The findings suggest a continuum of activity in the cortex, with attention emerging as a bridge between perception and action.
A new study has identified the likely origin of tone deafness in the brain, finding that strokes causing amusia affect the right hemisphere and a specific region called the superior temporal gyrus. This discovery highlights the differences between processing music and language in the brain, with implications for diagnosis and treatment.
Researchers developed a new model that highlights the crucial role of interactions among neighboring contact sites of nerve cells for brain plasticity. Synaptic plasticity, the brain's method for learning, is shaped by the strength and stability of neuronal connections, which are influenced by both excitatory and inhibitory synapses.
A Mayo Clinic study found that microglia shield neurons from the aftereffects of anesthesia, enhancing and boosting neuronal activity to awaken the brain. This discovery could lead to new treatments for post-anesthesia delirium and hyperactivity.
A new study uses machine learning to classify fossils of extinct pollen with high accuracy, leveraging morphological features and phylogenetic data. The model successfully placed nearly all specimens within Podocarpus based on their shape and form.
Researchers have made significant breakthroughs by harnessing AI in metamaterials research, leading to faster device development and more precise data analysis. This convergence of AI and metaphotonics has the potential to transform various domains, including diagnosis, environmental monitoring, and security.
Researchers developed a new open-source system to interface with living neurons, offering enhanced control and precision in measuring neural processes. The system boasts over 500 electrodes, allowing for more data collection and customization, while being 10 times cheaper than commercial systems.
Researchers at EPFL have successfully connected two artificial synapses using ions to process data, paving the way for brain-inspired computing. The device stores information in a readily accessible way, reducing energy costs and mimicking the brain's own processing mechanism.
Researchers at the University of California - San Diego developed a mathematical formula that reveals how neural networks learn to detect relevant patterns in data. The Average Gradient Outer Product (AGOP) formula helps interpret which features the network is using to make predictions, improving the accuracy and reliability of AI syst...
Researchers from Tokyo University of Science developed a flexible paper-based sensor that operates like the human brain, enabling low-power and efficient health monitoring. The device can distinguish 4-bit input optical pulses and generate currents in response to time-series optical input, with rapid response times.
A team at Zhejiang University has developed a self-driving cloaked unmanned drone with an intelligent aeroamphibious invisibility cloak, capable of manipulating electromagnetic scattering in real-time across dynamic environments. The cloak integrates perception, decision-making, and execution functionalities using spatiotemporal modula...
A new computational model uses neural network architecture to generate accurate predictions of airflow while reducing computational cost. It can capture most of the original physics in a flow prediction with relatively little processing complexity.
Researchers have developed a non-crossing quantile regression neural network (NCQRNN) model to enhance the statistical reliability of weather forecasts. The NCQRNN model preserves the rank order of output nodes, ensuring lower quantiles stay smaller than higher ones, boosting accuracy and improving forecast interpretability.
A new method called NIRE enables large-scale and long-term observation of neuronal structures and activities in awake mice. The method uses fluoropolymer nanosheets covered with light-curable resin to create larger cranial windows, allowing for high-resolution imaging with sub-micrometer resolution.
The new AI model uses a visual map to explain each diagnosis, helping doctors follow its line of reasoning and check for accuracy. The tool aims to catch diseases in their earliest stages, making it easier on doctors and patients alike.
UCLA Health researchers found a group of astrocytes in the central striatum regulate neurotransmitter communication and gate perseverative behavior. The discovery may lead to potential therapies for disorders like autism, OCD, and Tourette syndrome.
Dr. Ryyna Ethell's lab at UC Riverside has been awarded a $2.4 million NIH grant to investigate the role of astrocytes in inhibitory synapse development and their connection to neurodevelopmental disorders like ADHD and autism.
A new AI model developed by MIT researchers breaks down complex warehouse navigation into smaller chunks, identifying optimal areas for decongesting robots. The technique improves efficiency by nearly four times, opening up potential applications in other complex planning tasks.
A team of researchers used deep brain stimulation to localize disrupted neural pathways in patients with Parkinson's disease, dystonia, OCD, and Tourette's syndrome. The study identified specific brain circuits associated with each disorder, revealing overlapping malfunctions that suggest a complex network of brain dysfunctions.
Researchers developed artificial neural networks using silicon microresonators, offering a promising platform for efficient AI systems. The devices mimic biological neurons' nonlinear behavior, enabling precise control of light properties.
A new mouse study has uncovered the neural connections that help shape decisions, finding sequential groups of neurons activated and suppressed to reinforce a choice. The research combines structural, functional, and behavioral analyses to explore how neuron-to-neuron connections support decision-making in the brain.
Researchers at the University of Pennsylvania have developed a new silicon-photonic chip that can perform vector-matrix multiplication using light waves, allowing for accelerated AI computing. The chip's design has privacy advantages, as sensitive information can be processed simultaneously without being stored in memory.