Articles tagged with Computational Neuroscience
A new tool called Facemap uses deep neural networks to relate mouse facial movements to neural activity in the brain. This allows researchers to track and quantify movements and correlate them with brain activity, bringing them one step closer to understanding how the brain uses persistent, widespread signals.
Research suggests that consciousness requires synchronized communication across cortical regions; propofol general anesthesia cancels sensory processing by cutting it off. Neural activity in higher-level processing and cognitive regions fails to propagate during anesthesia.
Researchers are combining biology, physics, computer science, and engineering to design electric circuits that mimic the brain's adaptive behavior. The goal is to create a more efficient AI application that can learn from history and adapt without significant energy consumption.
Researchers at King's College London are studying the effects of maternal prenatal exposure to COVID-19 infection on children's brain development. The six-year study will explore how the maternal immune system affects fetal brain development and identify potential impacts on childhood outcomes.
Researchers found that deep neural networks often respond the same way to images with no resemblance to the target, generating unnatural signals. The models develop unique invariances that are different from human perceptual systems, causing them to perceive pairs of stimuli as similar despite their differences.
Fruit flies use a unique toggle-switch in their brains to switch between solo and mating songs, exchanging information through dialogue. Researchers decoded the tiny brains' behavior using neural imaging and AI, providing insights into complex brain decision-making.
Researchers have found that neural activity in the brain changes between sensing a stimulus and taking action, regardless of the context. This discovery has implications for understanding executive functions and potentially aiding in the development of autonomous vehicle systems.
Researchers have created the first-ever map of a single animal's early visual system, reconstructing it from the eyes to neurons in a tiny parasitic wasp. The study reveals complex behaviors such as flight in an insect with just 8,600 cells compared to the human brain's 171 billion.
In a new study, researchers deciphered mice's behavior during reward-based learning tasks, finding they persistently blend multiple strategies. The findings suggest mice do not fully adopt optimal approaches, and their ability to shift between strategies is crucial for understanding their decision-making process.
The Fralin Biomedical Research Institute at VTC will accelerate health sciences research with a focus on cancer and brain disorders. The institute will recruit 14 researchers and support six major projects.
A team of scientists has developed a rigorous accounting of the neurons in the tiny brain of a humble C. elegans worm, mapping out how its brain cells encode essential behaviors such as movement and feeding. The atlas reveals the underlying logic of how the worm's brain produces a sophisticated repertoire of behaviors, even as environm...
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.
A study published in Neuron found that a structure in rat brains called the periaqueductal gray is essential for play and laughter. The researchers used tickling to simulate playful environments and measured brain activity, finding strong neural responses to both tickling and playing.
Researchers found that nearly all Purkinje cells in the human cerebellum have multiple primary dendrites, which contradicts the traditional understanding of a one-to-one relationship between climbing fibers and Purkinje cells. This discovery was made possible by analyzing thousands of cells from both human and mouse tissue using immuno...
Researchers created a simplified mathematical analysis to visualize neuron activities in daily experiences, employing state-space analysis. This technique allows for visualization of neuronal activity using general statistical software, revealing changes in brain activity over short time periods.
Human metacognitive behavior is distinct from AI's reward-punishment system, with humans adjusting memory retention in response to gain and learning speed in response to loss. This asymmetric property may provide insights into the neural mechanisms underlying human metacognition.
A recent study published in Nature Neuroscience clarifies the connection between autism and the microbiome, identifying autism-specific metabolic pathways associated with particular human gut microbes. The analysis, which harmonized dozens of previously published datasets, reveals a common microbial signature distinguishing autistic fr...
Researchers mapped receptor densities across the cortex, identifying two main arrangements that align with functional systems. The findings provide insights into how the brain adapts to a changing world, with potential applications for computational models and neuroscientific research.
Researchers at MIT have designed a computational model that can predict other people's emotions, including joy, gratitude, and regret. The model uses insights into human intuition, incorporating factors such as desires, expectations, and observation of actions to make predictions.
Researchers at the University of Rochester Medical Center found that predicting movement is crucial for eye-and-hand coordination. The study used high-speed cameras and AI methods to analyze primate behavior and developed a detailed model of vision-guided reaching behavior.
Researchers at Sainsbury Wellcome Centre found that instinctual exploratory runs enable mice to learn a map of the world efficiently. The study demonstrates how biological brains can learn faster and more efficiently than AI agents by focusing on salient objects.
A groundbreaking study published in Nature Neuroscience shows that monkeys can think deeply about problems, consider multiple factors, and find optimal outcomes. This discovery challenges traditional views on animal intelligence and highlights the complexity of monkey cognition.
The Human Brain Project has achieved significant scientific breakthroughs, including world-leading 3D brain atlases and personalized medicine based on computational modeling. The project's legacy will leave a lasting impact on the research community.
Researchers have developed a multidisciplinary approach using a new microscope, artificial intelligence algorithm, and voltage indicators to better measure brain activity. The technique enables the imaging of up to 100 neurons at a time, far surpassing previous limits.
Dr. Nico Spiller to develop new analysis methods using machine learning to analyze complex brain data related to memory, decision making, and movement. The fellowship aims to provide insights into neurodegenerative diseases such as Alzheimer's and Parkinson's disease.
Neuroscientists have uncovered a brain circuit that enables mice to rapidly escape to shelter when faced with a threat. The retrosplenial cortex and superior colliculus form a circuit that encodes the direction to a shelter, allowing mice to accurately orient and escape.
Researchers propose that delayed recoveries in COVID-19 patients may be due to a protective response from their brains, similar to those seen in animals exposed to extreme conditions. This theory could lead to new approaches for ICU sedation and recovery from disorders of consciousness.
The Keck School of Medicine's Stevens INI has received a nearly $2 million grant to upgrade its storage system, increasing its capacity to handle vast amounts of brain imaging data. This will enable the lab to maximize scientific productivity and fulfill its promise to collaborate with researchers globally.
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 theory developed by a collaboration between a former cosmologist and a computational neuroscientist has identified essential connections between brain cells. The theory, published in Physical Review Research, uses geometric framework to predict structure from function in neural networks.
A new GPU-based machine learning algorithm, ReAL-LiFE, can rapidly analyze large amounts of data from diffusion Magnetic Resonance Imaging (dMRI) scans of the human brain. This allows for faster analysis and prediction of brain connectivity, enabling better understanding of brain-behaviour relationships at scale.
Researchers found that two types of computer models, deep neural networks and the Basel Face Model, are surprisingly accurate at replicating human facial similarity judgments. These models were tested on a dataset of realistic computer-generated faces and ranked by students in terms of similarity.
Researchers from the University of Tsukuba develop a model that combines multiple theories to simulate motor learning in humans. The study found that larger amounts of motor exploration aid in learning sensitivity derivatives and transforming errors into motor corrections.
A new AI system uses artificial neural networks to recognize objects more accurately and stably, despite changing visual inputs. The system mimics human eye movements to improve machine vision capabilities, reducing errors in self-driving cars and other applications.
Researchers found that walking enhances performance on cognitive tasks in 14 participants by increasing frontal brain function, while 12 others showed no improvement. This discovery highlights the flexibility of a healthy brain and has implications for understanding aging and neurological disorders.
Researchers at the Sainsbury Wellcome Centre discovered that brain area communication is dynamic and changes over rapid timespans, with influences varying on a fast timescale. This finding suggests that cortical areas may control different aspects of processing in downstream regions over very short time spans.
A new circuit model provides an explanation for how deep brain stimulation (DBS) relieves Parkinson's disease motor symptoms by interrupting a vicious cycle between the subthalamic nucleus and the striatum. The model suggests that DBS restores a balance with other rhythm frequencies, enabling better movement control.
A new study by MIT scientists reveals that propofol anesthesia significantly alters the state of brain waves, with lower frequency delta waves dominating. Higher frequency beta waves decrease in structure and power, with their traveling nature disrupted by the surging delta waves. The findings suggest a profound impact on consciousness.
A study by Tokyo University of Science researchers has demonstrated that a computationally-light model can simulate complex brain cell responses, including periodic and quasi-periodic responses. The Izhikevich neuron model was found to be capable of reproducing both types of responses at lower computational cost.
Scientists at Johannes Gutenberg University discovered that fruit fly eyes can distinguish six types of global motion patterns generated by self-motion. The T4/T5 cell subtypes directly represent complex motion cues rather than uniform directions, matching the fly's actual behavior closely.
Scientists have developed a new technology to decode brain activity and infer the meaning of a person's mental picture. The study used electrocorticogram to detect patterns in brain activity while patients imagined different images, revealing distinct representations for each concept. This breakthrough could lead to the development of ...
Professor Alexander Ecker is awarded a Starting Grant to develop machine-learning methods to describe neurons' shape and function, leveraging a large dataset from the US Brain Initiative. The research aims to uncover how a neuron's shape relates to its role in sensory information processing.
Researchers have published an extensive 7T fMRI dataset to study how humans perceive and interpret naturalistic photographs. The Natural Scenes Dataset provides a massive scale of brain data for training complex deep-learning models that predict brain activity.
Carlos Ponce is studying the parts of the visual system that analyze shapes, using macaque monkeys as a model. He combines computational models with electrophysiology experiments to understand how neurons process visual information.
A study published in eLife found that rats exhibit efficient coding processes for visual stimuli, similar to those observed in humans. This suggests a universal principle in vision, where the brain adapts to its environment by specializing in the recognition of informative signals, thereby conserving computational resources and energy.
Astrocytes play a crucial role in self-repairing the brain and may hold the key to creating energy-efficient artificial intelligence. By emulating astrocyte functions in hardware devices, researchers aim to reduce power consumption and increase fault resilience.
A new study reveals that high-performing AI next-word prediction models resemble the function of language-processing centers in the human brain. The models' activity patterns closely match those seen in the brain during language tasks, suggesting a potential connection between AI and human language processing.
The Human Brain Project unveiled its 8th annual Summit with presentations of new scientific insights and technologies. The project has developed a powerful new infrastructure called EBRAINS, which will serve generations of brain scientists.
Researchers from Cold Spring Harbor Laboratory have published a comprehensive census of cell types in the primary motor cortex of human, mouse, and monkey brains. This milestone could lead to breakthroughs in studying and treating conditions like schizophrenia, depression, Alzheimer's, and traumatic brain injuries.
Researchers used fractal analysis to study brain network patterns while listening to a story. The results show that complex thoughts are reflected in high-order dynamic correlations in neural activity patterns.
Researchers at Osaka University used machine learning to analyze locomotion data from diverse species, revealing common features associated with dopamine deficiency. The study found that worms, mice, and humans exhibit similar movement disorders when lacking dopamine, despite their evolutionary differences.
A team of researchers found that when people use mental abstractions, the brain area that signals valuable information becomes highly active. This discovery could lead to new advances in basic research, education, rehabilitation, and artificial intelligence.
Emery N. Brown, a neuroscientist and practicing anesthesiologist, has won the SfN's Swartz Prize for his contributions to neural signal processing, anesthetic mechanisms, and statistical methods. His research advances neuroscientific understanding of how anesthetics affect the brain, improving patient care.
The Alfred P. Sloan Foundation has selected 126 U.S. and Canadian researchers as the recipients of the 2019 Sloan Research Fellowships. These fellowships recognize early-career scholars whose achievements mark them as among the most promising researchers in their fields.
The study combines synfire communication, coherence and resonance to provide insight into how messages are exchanged between brain areas. The researchers found that oscillations play a significant role in determining whether communication can take place.
Kenneth Miller received the 2018 Swartz Prize in Theoretical and Computational Neuroscience for his contributions to modeling cerebral cortex function. His research has led to a reliable model of synaptic plasticity, confirmed by experimental data.
Researchers developed high-speed computational software 'Parallel STEPS' to model neuronal interactions and functions. The new approach achieved significantly improved performance, enabling faster simulation of complex models and revealing new insights into individual neuron behavior.
Researchers propose a mathematical theory explaining grid cell activity, enabling precise representation of spatial position and direction. The framework combines population-vector decoding with grid scale progression to maximize spatial resolution.
Terrence Sejnowski receives the Swartz Prize for his significant cumulative contribution to theoretical models and computational methods in neuroscience. He has made major research discoveries, including learning models for birdsong and neuroeconomics.
A new study by neuroscientists at the Bernstein Center Munich found that previous experience plays a significant role in shaping our perceptions of physical quantities. The researchers developed a Bayesian model that integrates two classic theories and explains how prior knowledge affects judgment, leading to systematic estimation biases.