# Shared and specific mechanisms of auditory and visual category learning

> **NIH NIH F32** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2020 · $64,554

## Abstract

PROJECT SUMMARY/ABSTRACT
The ability to learn new perceptual categories enables some of the most complex human behaviors, from speech
perception to visual object recognition. Current understanding of the mechanisms involved in perceptual category
learning relies on the fundamental assumption that the processes underlying such learning are shared across
the senses. However, the vast majority of this work has focused on the visual modality. As a consequence, the
research regarding how humans learn to group complex auditory information into categories has relied greatly
on conclusions from the research in the visual domain without testing this critical assumption. However, recent
evidence from the attention literature suggests that even seemingly domain-general cognitive processes, such
as working memory, are accomplished via sensory-biased regions in frontal cortex. The current investigation will
directly compare the computational and neural mechanisms supporting auditory and visual category learning by
training the same individuals on categories in both modalities while in an fMRI scanner. Aim #1 of this
investigation will identify the shared and sensory-biased circuits supporting feedback processing during auditory
and visual category learning. If the neural circuits supporting perceptual category learning are shared across the
modalities, it is expected that similar regions will be recruited to a similar extent during feedback processing. If
instead, the neural circuits are distinct for particular modalities, it is expected that sensory-biased regions will
emerge as supporting category learning for auditory and visual modalities. Aim #2 will utilize advanced machine
learning techniques (multivariate pattern classification and representational similarity analyses) to characterize
the emergence of category-level neural representations over the course of learning. Aim #3 will identify the
functional and structural connectivity of the circuits as they contribute to perceptual category learning. The
proposed research will directly test the fundamental assumption about the nature of this complex problem that
affects everyday behaviors. This research has the potential to impact understanding of cases where modality-
specific learning abilities might be impaired, such as phonetic learning and language-related impairments in
dyslexia, autism, and specific language impairment. The proposed research will provide the training foundation
to support the PI’s long-term objective of developing theories of perceptual category learning that are constrained
by neurobiology and behavior and will specify the behavioral, computational, and neural mechanisms of such
learning. This project presents the opportunity to directly test a critical assumption underlying understanding of
perceptual category learning. The proposed research will take place in an exceptional training environment and
the PI will be mentored by a team of knowledgeable and accomplished scientists. T...

## Key facts

- **NIH application ID:** 10064815
- **Project number:** 1F32DC018979-01
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Casey L Roark
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $64,554
- **Award type:** 1
- **Project period:** 2020-05-01 → 2022-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10064815

## Citation

> US National Institutes of Health, RePORTER application 10064815, Shared and specific mechanisms of auditory and visual category learning (1F32DC018979-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10064815. Licensed CC0.

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