# Intracranial Electrophysiology & Anatomical Connectivity of Voice-Selective Auditory Cortex

> **NIH NIH F30** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2024 · $51,320

## Abstract

ABTRACT:
The ability to recognize voice is an intricate feat of human audition. For the listener, the brain is able to
seamlessly extract complex linguistic and non-linguistic cues from highly variable vocal acoustic input.
Neuroimaging studies have proposed specialized regions of auditory cortex dedicated to voice perception,
including superior temporal gyrus (STG) and superior temporal sulcus (STS), referred to as “temporal voice
areas”. Functional neuroimaging studies also demonstrate these areas respond most strongly to vocalizations
of the same-species compared to other primate vocalizations and natural sounds, further suggesting
specialization of auditory cortex for vocal acoustic stimuli. It remains unknown if these regions demonstrate
true selectivity for voice, or more generally function to process the spectrotemporal features of complex
auditory stimuli, such as voice. The voice perception network has been partially described by neuroimaging
studies and suggests temporal voice areas exhibit connectivity to inferior frontal gyrus and precentral gyrus,
however these studies are limited in their ability to characterize voice areas at physiologic timescales and have
largely focused on characterizing frontotemporal white matter pathways underlying speech perception and
production. The proposed research aims to characterize local electrophysiologic responses to voice in
temporal voice areas and will describe the frontotemporal structural connectivity of the voice
perception network. I will leverage intracranial electroencephalography (iEEG) from neural populations
across human auditory cortex in 15 patient-participants undergoing epilepsy surgery evaluation to examine the
neural representation of voice. Neural recordings will be acquired while participants listen to a published Voice
Localizer stimulus set optimized for iEEG research, as well as an engineered acoustic stimulus set from
modulated noise that mimick the spectrotemporal features of voice and other natural sounds, called Gaussian
Sound Patterns (GSPs). Frontotemporal connectivity of voice-selective auditory cortex will be examined across
patients using clinically-acquired diffusion tensor imaging (DTI) in all patients with Voice Localizer recruited to
date (n=11) and included in this proposal (n=15). Connectivity analyses will reveal regions of frontal cortex
demonstrating connectivity to neuronal populations along STG and STS with the greatest voice-selective
responses. Together this proposal will leverage a multimodal dataset that marries local cortical iEEG
recordings at physiologic timescales and DTI structural connectivity analysis to critically examine voice
selective auditory cortex.

## Key facts

- **NIH application ID:** 10847388
- **Project number:** 5F30DC021342-02
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Jasmine Leah Hect
- **Activity code:** F30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $51,320
- **Award type:** 5
- **Project period:** 2023-07-01 → 2027-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10847388

## Citation

> US National Institutes of Health, RePORTER application 10847388, Intracranial Electrophysiology & Anatomical Connectivity of Voice-Selective Auditory Cortex (5F30DC021342-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10847388. Licensed CC0.

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