Kelsey Mankel

Predicting Speech in Noise Perception using Measures of Neural Entrainment

The paper uses neural entrainment measures from EEG data to predict speech-in-noise perception performance in a cohort of healthy listeners.

Chirped Speech (Cheech) Enables Rapid Assessment of Multi-Level Auditory Evoked Potentials During Speech-in-Noise Recognition

This study evaluates a chirped-speech stimulus (Cheech) to assess auditory evoked potentials during speech-in-noise recognition, showing it preserves intelligibility while enabling robust neural recordings.

Auditory brainstem responses to speech-in-noise reflect selective attention, comprehension, and subjective listening effort

This study investigates how auditory brainstem responses to speech-in-noise reflect selective attention, comprehension, and listening effort using a novel stimulus.

Comparison of a Novel Real-World Speech in Noise Auditory Attention Task to Standard Clinical Audiological Metrics

The paper evaluates how age, pure tone audiometry, and cognitive ability predict speech perception in noise using a novel auditory attention task.

Neural microstates underlying categorical speech perception using Bayesian nonparametrics

The paper uses Bayesian nonparametrics and machine learning to analyze neural microstates during speech perception, finding that specific microstates and brain regions predict speech categorization accuracy and perceptual gradiency.

Individual Differences in Cognition and Perception Predict Neural Processing of Speech in Noise for Audiometrically Normal Listeners.

The paper investigates how individual cognitive and perceptual differences predict neural speech processing in noise using EEG and cognitive tasks.

Functional plasticity coupled with structural predispositions in auditory cortex shape successful music category learning

This study shows that successful learning of nonspeech sound categories involves both short-term neural efficiency gains and preexisting structural differences in auditory cortex.

Single-trial neural dynamics influence auditory category learning

This study uses computational modeling to show that single-trial neural dynamics, specifically smaller P2 amplitudes, predict successful auditory category learning in nonmusicians.