Event
Ph.D. Defense: Joshua P. Kulasingham
Thursday, October 28, 2021
9:30 a.m.
1146 A. V. Williams Building
Maria Hoo
301 405 3681
mch@umd.edu
ANNOUNCEMENT: Ph.D. Defense
Name: Joshua P. Kulasingham
Committee:
Prof. Jonathan Z. Simon, Chair
Prof. Shihab Shamma
Prof. Steve Marcus
Prof. Behtash Babadi
Prof. Ellen Lau, Dean’s representative
Date/Time: Thursday, October 28, 2021 at 9.30 am
Location: 1146 A. V. Williams Building
Title: Time-Locked Cortical Processing of Speech in Complex Environments
Abstract:
Our ability to communicate using speech depends on complex, rapid processing mechanisms in the human brain. These cortical processes make it possible for us to easily understand one another even in noisy environments. Measurements of neural activity have found that cortical responses time-lock to the acoustic and linguistic features of speech. Investigating the neural mechanisms that underlie this ability could lead to a better understanding of human cognition, language comprehension, and hearing and speech impairments.
We use Magnetoencephalography (MEG), which non-invasively measures the magnetic fields that arise from neural activity, to further explore these time-locked cortical processes. One method for detecting this activity is the Temporal Response Function (TRF), which models the impulse response of the neural system to continuous stimuli. Prior work has found that TRFs reflect several stages of speech processing in the cortex. Accordingly, we use TRFs to investigate cortical processing of both low-level acoustic and high-level linguistic features of continuous speech.
First, we find that cortical responses time-lock at high gamma frequencies (~100 Hz) to the acoustic envelope modulations of the low pitch segments of speech. Older and younger listeners show similar high gamma responses, even though slow envelope TRFs show age-related differences. Next, we utilize frequency domain analysis, TRFs and linear decoders to investigate cortical processing of high-level structures such as sentences and equations. We find that the cortical networks involved in arithmetic processing dissociate from those underlying language processing, although both involve several overlapping areas. These processes are more separable when subjects selectively attend to one speaker over another distracting speaker. Finally, we compare both conventional and novel TRF algorithms in terms of their ability to estimate TRF components, which may provide robust measures for analyzing group and task differences in auditory and speech processing. Overall, this work provides insights into several stages of time-locked cortical processing of speech and highlights the use of TRFs for investigating neural responses to continuous speech in complex environments.
