Neural dynamics underlying the acquisition of distinct auditory category structures.

Despite the multidimensional and temporally fleeting nature of auditory signals we quickly learn to assign novel sounds to behaviorally relevant categories. The neural systems underlying the learning and representation of novel auditory categories are far from understood. Current models argue for a rigid specialization of hierarchically organized core regions that are fine-tuned to extracting and mapping relevant auditory dimensions to meaningful categories.

The impact of training methodology and representation on rule-based categorization: An fMRI study.

Hélie, Shamloo, & Ell (2017) showed that regular classification learning instructions (A/B) promote between-category knowledge in rule-based categorization whereas conceptual learning instructions (YES/NO) promote learning within-category knowledge with the same categories. Here we explore how these tasks affect brain activity using fMRI. Participants learned two sets of two categories.

Learning and generalization of within-category representations in a rule-based category structure.

The task requirements during the course of category learning are critical for promoting within-category representations (e.g., correlational structure of the categories).

The impact of training methodology and category structure on the formation of new categories from existing knowledge.

Categorization decisions are made thousands of times every day, and a typical adult knows tens of thousands of categories. It is thus relatively rare that adults learn new categories without somehow reorganizing pre-existing knowledge. Yet, most perceptual categorization research has investigated the ability to learn new categories without considering they relation to existing knowledge.

Restoring Speech Following Total Removal of the Larynx.

By speech articulator movement and training a transformation to audio we can restore the power of speech to someone who has lost their larynx. We sense changes in magnetic field caused by movements of small magnets attached to the lips and tongue. The sensor transformation uses recurrent neural networks.