Articles tagged with Computational Neuroscience
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.
Researchers have linked specific neurons to a type of somatosensation, opening the door for a better understanding of our sense of touch. The study found that these neurons respond uniquely to certain tactile stimuli and receive direct synaptic input from other brain regions.
Researchers have developed a new method to analyze electrical activity in the brain, enabling better diagnosis and treatment of brain illnesses. The technique can help identify impending seizures and paralysis, allowing for more effective interventions.
Scientists at LMU Munich developed a mathematical model that accurately mimics human sound recognition, showing the brain compares stored and perceived sounds efficiently. The new library-based model predicts the flow of information from cerebrum to thalamus, enabling highly efficient real-time implementation.
A walking robot, RunBot, has been engineered to mimic human gait and adapt to different environments, including mountainous terrain. The robot's ability to learn from trial and error allows it to adjust its gait in response to visual input, ensuring stability and balance on slopes.
Researchers developed a new approach to interpreting brain electroencephalograms that provides an unprecedented view of thought in action. The technique uses Independent Component Analysis to separate signals from different areas of the brain, enabling detailed insights into neural dynamics.
A Princeton scientist created a computer model of a mouse brain that can recognize spoken words, challenging conventional views on sensory perception. The model uses sensitive timing of electrical signals to perform calculations, potentially leading to faster and more sophisticated brain functions.