Articles tagged with Neural Networks
Researchers at PNNL create a uniform two-dimensional layer of silk protein fragments on graphene, enabling the design and fabrication of silk-based electronics. This biocompatible system has potential applications in wearable and implantable health sensors, as well as computing neural networks.
A Concordia-led team developed a framework that enables crowdsourced deep reinforcement learning as a service, using blockchain technology. This allows smaller organizations to access complex AI tasks previously out of reach, reducing costs and risk.
A study at the University of Bonn has revealed that fly larvae have special sensors triggered by swallowing, releasing serotonin to continue eating. This control circuit may also exist in humans and could help understand eating disorders such as anorexia or binge eating.
Researchers at Peking University developed a dual-IMC scheme to accelerate machine learning and improve energy efficiency. The new computing scheme stores both neural network weights and inputs in memory, reducing data movement and power consumption.
A new study using advanced MRI techniques has discovered a functional backbone formed by robust, delay-free interactions that serve as the core of communication in the brain. Weaker connections amplify the system's potential functional states, providing flexibility.
A deep-learning algorithm developed by astronomer David Harvey can untangle the complex signals of self-interacting dark matter and AGN feedback in galaxy cluster images. The Inception model achieved an accuracy of 80% under ideal conditions, showcasing its potential for analyzing vast amounts of space data.
A novel approach to overcome limitations of traditional methods, NeuPh uses local conditional neural fields to reconstruct high-resolution phase information from low-resolution measurements. It provides robust resolution enhancement and outperforms existing models in accuracy.
A new study reveals that more than half of strokes causing ataxia are located outside the cerebellum but affect a specific brain network. This discovery changes our understanding of ataxia's neural mechanisms and may lead to safer treatments for patients.
A new 'deep scanning' approach reveals that individuals with depression have a larger salience network in the frontal cortex and striatum, increasing their risk for depression. This finding suggests that people may be pre-wired for depression if they have this brain feature in childhood.
Researchers at the University of Birmingham have discovered that male fruit flies ignore physical threats as they pursue a female fly, driven by the neurotransmitter dopamine. As courtship advances, dopamine levels increase, blocking sensory pathways and reducing the ability to respond to threats.
Researchers used neural networks to solve fundamental equations in complex molecular systems, achieving promising results in simulating excited states of molecules. This breakthrough could lead to practical uses in materials science and chemical synthesis.
Researchers developed a new technique to study charge density waves in materials, revealing two previously unobserved ways electricity can manipulate their state. The method allows for the observation of nanoscale lengths and nanosecond speeds, with potential applications in energy-efficient microelectronics.
Researchers used advanced imaging techniques to create detailed maps of mouse brains, identifying areas vulnerable to blood vessel degeneration. These changes can lead to cognitive decline and neurodegenerative disorders like Alzheimer's disease.
A novel, fast and high-quality neural text-to-speech model was successfully developed using a Transformer encoder + ConvNeXt decoder and MS-FC-HiFi-GAN. The model can synthesize one second of speech at high speed in just 0.1 seconds using a single CPU core, achieving eight times faster synthesis than conventional methods.
A new study finds that psilocybin temporarily desynchronizes the default mode network in the brain, creating a psychedelic experience. The study provides a neurobiological explanation for the drug's effects and lays groundwork for its potential use as a therapy for mental illnesses.
Researchers have developed Nano-MIND technology, which uses magnetism to selectively activate specific deep brain neural circuits, modulating complex brain functions such as cognition and emotion. The technology has been successfully tested in animals, demonstrating its potential to regulate feeding behaviors and maternal instincts.
Scientists from HZDR, TU Chemnitz, TU Dresden, and Forschungszentrum Jülich have demonstrated the storage of entire bit sequences in cylindrical domains. The team's findings could lead to novel types of data storage and sensors, including magnetic variants of neural networks.
Researchers found that small regions of the brain can momentarily 'flicker' awake while the rest of the brain remains asleep, and vice versa from wake to sleep. This challenges traditional understanding of sleep and wake patterns, which have been defined by slow, long-lasting waves.
Researchers discovered that propofol, a commonly used anesthesia drug, induces unconsciousness by causing the brain to become increasingly unstable. This instability leads to chaotic brain activity, resulting in loss of consciousness. The study's findings could help develop better tools for monitoring patients during general anesthesia.
A study published in Nature Medicine found that off-the-shelf wearable trackers can monitor the response to two treatments for atrial fibrillation and heart failure. The devices provided clinically useful information similar to in-person hospital assessments, with a neural network helping to analyze missing data.
Researchers at Max Planck Institute propose a new method for implementing neural networks with optical systems, which could lead to faster and more energy-efficient alternatives. The approach allows for parallel computations in high speeds limited by the speed of light, and can be applied to various physically different systems.
A recent study found that the cerebellum plays a crucial role in regulating thirst, with the hormone asprosin activating Purkinje neurons to enhance water intake. This discovery has significant implications for managing thirst disorders such as polydipsia and hypodipsia, for which current treatments are scarce.
Researchers developed Boundary Integrated Neural Networks (BINNs) for precise acoustic field analysis in unbounded domains. BINNs offer improved precision, efficiency, and reduced computational costs compared to traditional methods.
Researchers create an analog system that can learn complex tasks like XOR relationships and nonlinear regression, using local learning rules without centralized processor. The system is fast, low-power, and scalable, offering a unique opportunity for studying emergent learning.
Researchers at the University of Houston have introduced a new method for sleep stage classification that can be performed at home and uses only two leads. This approach achieves expert-level agreement with the gold-standard polysomnography without expensive equipment, paving the way for more accessible and cost-effective sleep studies.
Researchers create detailed wiring diagram of motor circuits in fruit flies, revealing complex nerve coordination for leg and wing movements. The study advances understanding of how the central nervous system coordinates individual muscles for various behaviors.
Scientists at the University of Washington and Harvard Medical School have discovered the neural circuits that coordinate leg and wing movements in fruit flies. The study uses X-ray holographic nanotomography to map motor neurons controlling legs and wings, revealing pre-motor neurons coordinating motor neuron function.
Scientists at Kyushu University created QDyeFinder, an AI pipeline that untangles the dense neuronal networks in the brain. The system uses a super-multicolor labeling protocol to tag neurons and then automatically identifies their structure by matching similar color combinations.
Researchers investigated the efficiency of modern neural network-based generative models, comparing them to traditional sampling techniques. The study found that modern diffusion-based methods may face challenges due to a first-order phase transition, but also exhibit superior efficiency in certain cases.
A new model developed by Flatiron Institute researchers proposes that individual neurons exert more control over their surroundings, which could be replicated in artificial neural networks. This updated model treats neurons as tiny 'controllers' and may lead to better AI performance and efficiency.
A new tool, BioemuS, enables real-time emulation and hybridization of biological systems using biomimetic Spiking Neural Networks, addressing limitations of current pharmacological treatments. The system, developed through international collaboration, prioritizes cost efficiency and accessibility for closed-loop applications.
Researchers at Delft University of Technology use drone racing to test neural-network-based AI control systems planned for next-generation space missions. The goal is to achieve optimal onboard operations by continuously replanning trajectories, reducing resource consumption and boosting mission autonomy.
Researchers have developed a new photonic chip that can process, transmit and reconstruct images in nanoseconds, eliminating optical-electronic conversions. This technology holds promise for revolutionizing edge intelligence in machine vision applications.
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 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.
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.
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.
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.
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...
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.