# Functional organization of the superior temporal gyrus for speech perception

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2021 · $608,474

## Abstract

PROJECT SUMMARY
The basic mechanisms underlying comprehension of spoken language are unknown. We do not understand,
for example, how the human brain extracts the most fundamental linguistic elements (consonants and vowels)
from a complex and highly variable acoustic signal. An investigation of the cortical representation of speech
sounds can likely shed light on this fundamental question. Previous research has implicated the superior
temporal cortex in the processing of speech sounds. However, how the cortex actually represents (i.e.
encodes) phonemes is undetermined. The recording of neural activity directly from the cortical surface is a
promising approach since it can provide both high spatial and temporal resolution. Here, I propose to examine
the mechanisms of phonetic encoding by utilizing neurophysiological recordings obtained during neurosurgical
procedures. High-density electrode arrays, advanced signal processing, and direct electrocortical stimulation
will be utilized to unravel both local population encoding of speech sounds in the lateral temporal cortex as well
as global processing across multiple sensory and cognitive areas.

## Key facts

- **NIH application ID:** 10224725
- **Project number:** 5R01DC012379-10
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Edward Chang
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $608,474
- **Award type:** 5
- **Project period:** 2012-04-01 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10224725

## Citation

> US National Institutes of Health, RePORTER application 10224725, Functional organization of the superior temporal gyrus for speech perception (5R01DC012379-10). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10224725. Licensed CC0.

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