Stimulus discrimination

…across trials that allow for reliable stimulus discrimination. Under this perspective, any response variability appears detrimental to sensory systems as it severely limits stimulus discriminability. Here, we propose a beneficial role of response variability: to facilitate faster learning in feedforward-recurrent networks through a self-stabilizing feedback mechanism. We explore this hypothesis in the framework of learning novel stimulus representations in pre-structured recurren

Magnitude estimation and stimulus discrimination tasks are affected by perceptual biases that cause the stimulus parameter to be perceived as shifted toward the mean of its distribution. These biases have been extensively studied in psychophysics and, more recently and to a lesser extent, with neural activity recordings. New computational techniques allow us to train spiking recurrent neural networks on the tasks used in the experiments. This provides us with another valuable tool with which to investigate the network mechanisms responsible for the biases and how behavior could be modeled. As

…higher-order visual areas and measured stimulus discrimination thresholds of 0.35 degrees and 0.37 degrees respectively in an orientation decoding task. These neural thresholds were almost 100 times smaller than the behavioral discrimination thresholds reported