Topic: auditory categorization

In perceptual judgments, sensory information is typically combined with contextual information which can determine the prior statistics. In a previously developed 2AFC auditory categorization task in which the stimulus sequence included two different statistical contexts, rats can capitalize on the context information but only in after-correct trials; in after-error trials, they consistently deviate from optimal behavior by waiving the accumulated context evidence (Hermoso-Mendizabal et al. 2020). Recently, it has been shown that Recurrent Neural Networks (RNNs) pre-trained in a naturalistic t

Auditory categorization is a crucial aspect of everyday communication, but we lack a clear understanding of the computations performed by the brain to define boundaries between groups of natural sounds. While modern machine-learning-based classifiers perform as well as humans in categorizing sounds, they can rely on idiosyncratic acoustic cues that diverge from biologically relevant cues. We hypothesized that, since auditory cortical neurons show robust category selectivity, training a classifier with an auditory cortical front end should more accurately reflect biological categorization. To t

Previous work has suggested that our perception of time is plastic and dependent on the distance of the stimulus to our body. For example, Annelli et al (2015) showed that stimuli presented in peri-personal and far space are judged differently and that this distance-effect on time perception can be shaped by training participants with a tool that effectively extends the reachable space. We here aimed to replicate and extend these results using a paradigm in which we tested time perception at multiple distances from the body prior to and following active tool-use training. In two experiments, w