Articles tagged with Neural Networks
Researchers found that brain circuits in 'deep-blind' zebrafish are fully functional and can drive normal visual behavior through direct stimulation. This study challenges the long-held assumption that neural development depends on visual experience.
Researchers found differential activation patterns of the Default Mode Network nodes, with facial movement inducing an inverted positive BOLD pattern in certain areas. Facial recognition and movement uniquely impact brain activity, highlighting their importance in cognitive and social development.
Researchers at Brigham and Women's Hospital have identified a common brain network associated with substance use disorder, regardless of the substance used. The finding could lead to targeted neurostimulation therapies for addiction, such as transcranial magnetic stimulation.
Scientists at the Max Planck Institute present a method for training artificial intelligence using physical processes, reducing energy consumption and computing time. The new approach relies on non-linear processes, such as optics, to mimic the human brain's parallel processing, potentially leading to more efficient neural networks.
Researchers uncover clues about how chemicals released by brain cells regulate our attention span, finding that two neurotransmitters work together in a precise sequence to regulate signal transmission. This discovery could lead to new treatments for neurological conditions associated with concentration difficulties.
Researchers discovered that brain nerve networks are organized into interconnected modules to segregate and integrate inputs, enabling efficient processing. This modular architecture allows the brain to balance local activity with global integration, essential for information representation.
Monash University researchers successfully print 3D nerve networks with living neurons that can transmit and respond to nerve signals. The networks mimic the arrangement of grey matter and white matter in the brain, allowing for significant advancements in studying nerve growth and disease mechanisms.
A new approach for coupling different light modes enables unprecedented data transfer rates in an MDM system. By using a gradient-index metamaterial waveguide, researchers achieved a high coupling coefficient and created a 16-channel MDM communication system with a data transfer rate of 2.162 Tbit/s.
A UMass Amherst neuroscientist is mapping the brain of a sea slug to study how neurons are added to functional neural circuits, shedding light on how this process contributes to neurological conditions. The project aims to provide an unprecedented look at brain development and potentially inform human brain development.
A new study led by Dr. Armen Saghatelyan uncovered the migratory mechanisms of neuronal cells in a neurodevelopmental disorder. The team found that modulating autophagy with FDA-approved drug metformin restored the cells' migratory properties.
Researchers developed a high-performance photonic spiking neural network that surpasses traditional digital systems with its ultrafast performance and low power consumption. The new network achieved excellent classification accuracies of over 94%, outperforming benchmark results with small training sets.
Researchers aim to understand the role of gaze in post-stroke reading impairments and develop an employment-specific assessment tool for individuals with autism. The studies may provide major steps towards finding innovative solutions for individuals affected by neglect dyslexia and autism.
Researchers used a new analytical approach to understand how the brain controls movement and eye stability in zebrafish. By analyzing neuronal activity, they identified two main features that correspond to specific types of movements, including eye rotation and body positioning.
Researchers have identified a conserved brain region in vertebrates essential for initiating forward movement. The mesencephalic locomotor region (MLR) stimulates reticulospinal neurons to control finer details of movement. Mapping this circuit could lead to new treatments for Parkinson's disease.
A paper published in Nature Communications shows that when neurons are given task-related sensory input, they change how they behave and support the critical brain hypothesis theory. The researchers used DishBrain, a collection of 800,000 human neural cells, to demonstrate near-critical network behavior emerges when the neural network ...
Researchers found that insects like American cockroaches use the mushroom body to encode behavioral decision-making based on sensory information. The study challenges the prevailing view of insect cognition, suggesting a more complex brain function than previously thought.
A new study by North Carolina State University found that artificial intelligence performs better when it chooses diversity over lack of diversity. The AI was able to increase its accuracy up to 10 times more than conventional AI in solving complicated problems.
Researchers have developed a novel neural network approach to design brand new proteins with unique arrangements and dynamic functionalities. The method combines attention neural networks with graph neural networks to predict existing protein properties and envision new proteins that nature has not yet devised.
A hybrid system of electronic encoding and diffractive optical decoding transmits optical information with high fidelity through random, unknown diffusers. The system outperforms traditional approaches that only utilize a diffractive optical network or an electronic neural network for optical information transfer.
Researchers use surface normal nonlinear photodetector to improve speed and energy efficiency of diffractive optical neural networks. The new device can perform high-speed image and video processing at the speed of light in an extremely energy efficient manner.
A study found that dogs are more sensitive to speech directed at them than adult-directed speech, with a greater response to female voices. The researchers measured dog brain activity via fMRI and found that the sensitivity was affected by voice pitch and variation.
A recent study published in Neuron reveals that Noelin proteins play a crucial role in learning and memory formation in the mammalian brain. The study found that these proteins act as 'universal anchors' controlling the distribution and dynamics of AMPA receptors, which are essential for synaptic plasticity.
Researchers propose a new approach to reconfigurable diffractive neural networks using metasurfaces, enabling flexible AI computing for various tasks. The proposed pluggable diffractive neural networks demonstrate high classification accuracy and efficiency, with potential applications in real-time object detection and intelligent opti...
Researchers propose a hypothesis that astrocytes, non-neuronal cells in the brain, can perform core computation as transformers, providing insights into human brain function and machine learning success. This discovery could spark future neuroscience research and help explain transformer performance across complex tasks.
Researchers discovered intricate neural connections in Octopus vulgaris, a model organism for studying memory acquisition networks. The findings challenge traditional models of neural network functionality, revealing an evolutionary adaptation that underlies the octopus's unique cognitive prowess.
Researchers found that children with autism and macrocephaly exhibit excessive growth of excitatory neurons, while others show a deficit. The study's findings could help doctors diagnose autism and identify potential treatments for specific cases.
Researchers found an abnormal imbalance of excitatory cortical neurons in people with autism spectrum disorder, depending on their head size. The study used human 'mini-brain' models called organoids to recreate the brain development alteration that occurred in patients during fetal development.
A recent study at the University of Helsinki found that speech production and singing are supported by the same neural network in the brain, challenging previous notions about their separate functions. The left hemisphere plays a crucial role in both abilities, particularly in terms of singing.
Researchers at Beth Israel Deaconess Medical Center discovered a non-ectodermal and mesodermal origin for large numbers of enteric neurons born after birth. This finding overturns decades of scientific dogma and offers hope for disease-modifying cures to aging patients.
Neuroscientists at Penn Medicine identified a brain mechanism that enables focus despite visual distractions. By analyzing neuron activity in animal models, they discovered 'beta bursts' in the lateral prefrontal cortex, which suppress distracting stimuli and direct attention towards tasks.
Researchers aim to create machine learning tools that can analyze and quantify shape information from images, enabling more accurate diagnoses and improving patient care. A new family of deep neural networks, called DSNNs, will be developed to tackle AI's blind spot in image analysis.
Researchers used a mathematical theory called the free energy principle to predict how real neural networks learn and organize themselves. The study successfully mimicked this process in rat embryo neurons grown in a culture dish, demonstrating the principle's guiding force behind biological neural network learning.
A KAIST research team has identified excessive astrocyte-mediated synapse removal as the cause of mental diseases induced by childhood abuse trauma. This mechanism is linked to stress hormones and can lead to abnormal neural networks and complex behavioral abnormalities.
A study led by Dr. Roy Sillitoe discovered the cerebellum as a source of generalized convulsive seizures, implicating alterations in midbrain neurons and a reciprocal cortico-thalamic loop. The research found that 80% of VPM neurons contribute to seizures, with cerebellar circuits driving seizure activity.
Researchers at Weill Cornell Medicine developed a non-opioid designer molecule to calm hyperactive pain-sensing neurons, showing promising results in preclinical studies. The novel drug effectively reversed neuropathic pain signs without cardiac side effects or sedation.
A breakthrough in photonic memory has been achieved, enabling fast volatile modulation and nonvolatile weight storage for rapid training of optical neural networks. The 5-bit photonic memory utilizes a low-loss PCM antimonite to achieve rapid response times and energy-efficient processing.
A new complex-domain neural network enhances large-scale coherent imaging by exploiting latent coupling information between amplitude and phase components. The technique reduces exposure time and data volume significantly while maintaining high-quality reconstructions.
Researchers propose a new mathematical neural network theory that consolidates memories to the neocortex if they improve generalization. This view contradicts the classical understanding of systems consolidation, which assumes all memories move from the hippocampus to the neocortex over time.
Researchers have made breakthroughs in two areas of computing: improving current semiconductor technology and developing new neuromorphic devices that think like the human brain. These advancements aim to increase efficiency, power, and processing capabilities for future technological leaps.
A Nagoya University research team discovered two distinct thermosensory pathways in the brain that transmit temperature information to different areas of the forebrain. Blocking one pathway was found to impair a rat's ability to avoid heat, while blocking another impaired its ability to avoid cold.
A University of Ottawa study reveals that a diverse brain's ecosystem is key to maintaining normal function while responding to changes. This concept is inspired by Charles Darwin's idea that biodiversity is crucial for survival, suggesting cell-to-cell diversity helps prevent failures in brain circuits.
New research shows that electric fields drive neural activity and coordinate memory across two key brain regions. The findings could lead to improved brain-controlled prosthetics for people with paralysis.
Researchers at EPFL have found a way to teach quantum computers to learn and process information using principles inspired by quantum mechanics. By training quantum neural networks (QNNs) on a few simple examples called 'product states', the computer can effectively grasp complex dynamics of entangled quantum systems.
Researchers use photonics to accelerate convolutional neural networks by harnessing light's unique properties, reducing power consumption and increasing efficiency. This approach enables real-time image processing and scalable solutions for complex images.
The study reveals five distinct brain types, each suited for its purpose, from a jellyfish's diffuse neural network to the human brain's reflective capabilities. Researchers suggest that autonomous machines can learn from coordination in bees, rapid thinking in birds, and single-mindedness in worms.
A team of researchers from Kyoto University and international institutions has developed a mathematical solution to the temporal asymmetry of nonequilibrium disordered Ising networks. This breakthrough offers insights into the behavior of biological systems, machine learning, and AI tools.
Researchers develop an ionic device utilizing redox reactions to achieve a high number of reservoir states, enabling efficient complex nonlinear operations. The device demonstrated remarkable performance in solving second-order nonlinear dynamic equations and predicting future values with low mean square prediction error.
Researchers found that neural networks grown in a dish can predict future stimulus events, with higher prediction efficiencies in focally stimulated networks. Focal electrical stimulation induced long-term memory traces and reduced dependence on short-term memory.
Scientists at Karolinska Institutet have identified a group of nerve cells involved in creating negative emotional states and chronic stress. The neurons, which are sensitive to oestrogen levels, were mapped using advanced techniques such as Patch-seq, Neuropixels, and optogenetics.
BioAutoMATED is an all-in-one AutoML platform designed for biologists, enabling easy analysis and interpretation of biological sequences. The platform uses three existing AutoML tools to generate models that can predict biological functions from sequence information.
The proposed multi-scale facial video pulse extraction network uses separable spatiotemporal convolution and dimension separable attention to extract pulse signals from facial videos. This approach yields better results than single-scale methods, especially when fusing multiple scales.
The study reveals that spontaneous waves of neurotransmitter glutamate facilitate dendrite pruning, while a unique protection/punishment machinery strengthens certain connections and eliminates others. Proper pruning is critical for neural development, with insufficient or excessive connections linked to neurophysiological disorders.
Researchers at Mainz University and Berlin found a previously unknown function of electrical synapses in the insect neural network, governing wing movement and generating consistent flight power. The discovery reveals new concepts of information processing by the central nervous system.
Scientists using popular computational tools to interpret AI predictions are picking up too much 'noise' when analyzing DNA. Researchers have found a way to fix this by applying a new line of code, leading to more reliable explanations and potentially unlocking the next breakthrough in health and medicine.
Researchers trained a robotic chef to watch and learn from cooking videos, enabling it to identify ingredients and actions. The robot recognized 93% of the correct recipe from 16 videos, including variations and new recipes, showcasing its potential for automated food production and cost-effective deployment.
A unique microcircuit in fruit flies' visual system transforms a single type of neuronal input to compute direction selectivity, with no inhibitory neurons present. The discovery reveals a striking example of the multilayered mechanisms of inhibition and excitation in the brain.
A deep learning-based framework called EMGSense enables accurate wearable EMG device usage through AI self-training techniques. It achieves average accuracy of 91.9% in gesture recognition and 81.2% in activity recognition, outperforming state-of-the-art approaches.
A study by Florida Atlantic University and CINVESTAV found that long-term running maintains the connectivity of adult-born hippocampal neurons, which contribute to memory function during aging. Exercise may prevent or delay age-related memory decline by increasing the survival and modifying the network of these neurons.
Research suggests that brain's electrical activity tunes sub-cellular components to optimize network stability and efficiency. This 'Cytoelectric Coupling' hypothesis proposes that electric fields influence neurons' physical configuration to fine-tune information processing.
Researchers developed a new sensor array that mimics the red, green and blue photoreceptors in human eyes, producing high-quality images through a neural network-based algorithm. The device has the potential to revolutionize camera technology by increasing spatial resolution and reducing power consumption.