Dopamine (DA) responses are synonymous with the ‘reward prediction error’ of reinforcement learning (RL), and are thought to update neural estimates of expected value. A recent study by Dabney et al. enriches this picture, demonstrating that DA neurons track variability in rewards, providing a readout of risk in the brain. Read Full Article (External Site) […]
Published on May 16, 2020
Our aim is to propose an efficient algorithm for enhancing the contrast of dark images based on the principle of stochastic resonance in a global feedback spiking network of integrate-and-fire neurons. By linear approximation and direct simulation, we disclose the dependence of the peak signal-to-noise ratio on the spiking threshold and the feedback coupling strength. […]
Published on May 15, 2020
Human arm movements are highly stereotypical under a large variety of experimental conditions. This is striking due to the high redundancy of the human musculoskeletal system, which in principle allows many possible trajectories toward a goal. Many researchers hypothesize that through evolution, learning, and adaption, the human system has developed optimal control strategies to select […]
Published on May 15, 2020