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Han Gyol Yi
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Han Gyol Yi

Postdoctoral Scholar

Chang Lab, University of California, San Francisco

I study how the brain processes speech sounds.

Currently, I am using electrocorticography (ECoG) to directly measure neural dynamics of learning-induced changes from the surface of the human auditory cortex.

Previously, I have used a combination of functional and structural neuroimaging methods (fMRI; DTI) as well as electroencephalography (EEG) to examine neural correlates of individual variability in non-native speech sound learning.

Education

  • PhD in Communication Sciences & Disorders, 2017

    The University of Texas at Austin

  • MA in Communication Sciences & Disorders, 2013

    The University of Texas at Austin

  • BSc in Communication Sciences & Disorders, 2010

    Northwestern University

Featured Publications

Please see CV for a full list of publications (2010-2020)

Han Gyol Yi*, Matthew K. Leonard*, Edward F. Chang
June 2019 Neuron, 102(6)

The Encoding of Speech Sounds in the Superior Temporal Gyrus

The human superior temporal gyrus (STG) encodes phonological features relevant for speech perception. We describe how direct human neurophysiology has revealed the local and context-dependent nature of STG representations and propose a theory for temporal binding in speech.
PDF DOI
Gangyi Feng*, Han Gyol Yi*, Bharath Chandrasekaran
December 2018 Cerebral Cortex, bhy289

The role of the human auditory corticostriatal network in speech learning

Using fMRI and DTI, we show a critical role for the auditory corticostriatal circuitry in mediating the acquisition of new speech categories.
PDF DOI
Han Gyol Yi, Zilong Xie, Rachel Reetzke, Alexandros G. Dimakis, Bharath Chandrasekaran
April 2017 Brain and Behavior, 7(6)

Vowel decoding from single-trial speech-evoked electrophysiological responses: A feature-based machine learning approach

We use a machine-learning approach to decode speech tokens from scalp-recorded electrophysiological responses on a single-trial basis.
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