Functional magnetic resonance imaging data for the neural dynamics underlying the acquisition of distinct auditory categories

How people learn and represent auditory categories in the brain is a fundamental question in auditory neuroscience. Answering this question could provide insights into our un-derstanding of the neurobiology of speech learning and per-ception. However, the neural mechanisms underlying audi -tory category learning are far from understood. We have re-vealed that the neural representations of auditory categories emerge during category training, and the type of category structures drives the emerging dynamics of the representa-tions [1] . The dataset introduced here was derived from [1] , where we collected to examine the neural dynamics underly-ing the acquisition of two distinct category structures: rule-based (RB) and information-integration (II) categories. Partic-ipants were trained to categorize these auditory categories with trial-by-trial corrective feedback. The functional mag-netic resonance imaging (fMRI) technique was used to assess the neural dynamics related to the category learning pro -cess. Sixty adult Mandarin native speakers were recruited for the fMRI experiment. They were assigned to either the RB (n = 30, 19 females) or II (n = 30, 22 females) learning task. Each task consisted of six training blocks where each consist-ing of 40 trials. Spatiotemporal multivariate representational similarity analysis has been used to examine the emerging patterns of neural representations during learning [1] . This open-access dataset could potentially be reused to investigate a range of neural mechanisms (e.g., functional network orga-nizations underlying learning of different structures of cat-egories and neuromarkers associated with individual behav-ioral learning success) involved in auditory category learning. (c) 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ )